Review of Business and Economics Studies, Vol. 3, Number 1, 2015 by Review of Business and Economics Studies (ROBES)

ISSN 2308-944X

Review of Business and Economics Studies Volume 3, Number 1, 2015 Political Economy of Olympic Games Rustem Nureev, Evgeny Markin The Phenomenon of National Development Bank: Theoretical Foundation and Effectiveness Elizaveta Selyavina Monetary Policy in Russia: Recent Challenges and Changes in Unstable Economic Conditions Natalia Giblova Market Concentration and Competition in Vietnamese Banking Sector Le Hai Trung Remittances and Economic Growth in Vietnam: An ARDL Bounds Testing Approach Dang The Tung Corporate Insurance in the Russian Electric Power Industry Nadezda Kirillova, Victoria Bazhenova

Financial University

Moscow

Review of Business and Economics Studies EDITOR-IN-CHIEF Prof. Alexander Ilyinsky Dean, International Finance Faculty, Financial University, Moscow, Russia ailyinsky@fa.ru EXECUTIVE EDITOR Dr. Alexander Kaffka EDITORIAL BOARD Dr. Mark Aleksanyan Adam Smith Business School, The Business School, University of Glasgow, UK Prof. Edoardo Croci Research Director, IEFE Centre for Research on Energy and Environmental Economics and Policy, Università Bocconi, Italy Prof. Moorad Choudhry Dept.of Mathematical Sciences, Brunel University, UK Prof. David Dickinson Department of Economics, Birmingham Business School, University of Birmingham, UK Prof. Chien-Te Fan Institute of Law for Science and Technology, National Tsing Hua University, Taiwan Prof. Wing M. Fok Director, Asia Business Studies, College of Business, Loyola University New Orleans, USA Prof. Konstantin P. Gluschenko Faculty of Economics, Novosibirsk State University, Russia Prof. George E. Halkos Associate Editor in Environment and Development Economics, Cambridge University Press; Director of Operations Research Laboratory, University of Thessaly, Greece Dr. Christopher A. Hartwell President, CASE - Center for Social and Economic Research, Warsaw, Poland Prof. S. Jaimungal Associate Chair of Graduate Studies, Dept. Statistical Sciences & Mathematical Finance Program, University of Toronto, Canada Prof. Bartlomiej Kaminski University of Maryland, USA;

Rzeszow University of Information Technology and Management, Poland

Prof. Dmitry Sorokin Deputy Rector for Research, Financial University, Russia

Prof. Vladimir Kvint Chair of Financial Strategy, Moscow School of Economics, Moscow State University, Russia

Prof. Robert L. Tang Vice Chancellor for Academic, De La Salle College of Saint Benilde, Manila, The Philippines

Prof. Alexander Melnikov Department of Mathematical and Statistical Sciences, University of Alberta, Canada

Dr. Dimitrios Tsomocos Saïd Business School, Fellow in Management, University of Oxford; Senior Research Associate, Financial Markets Group, London School of Economics, UK

Prof. George Kleiner Deputy Director, Central Economics and Mathematics Institute, Russian Academy Prof. Sun Xiaoqin Dean, Graduate School of Business, of Sciences, Russia Guangdong University of Foreign Studies, China Prof. Kwok Kwong Director, Asian Pacific Business Institute, California State University, Los Angeles, USA Prof. Dimitrios Mavrakis Director, Energy Policy and Development Centre, National and Kapodistrian University of Athens, Greece Prof. Steve McGuire Director, Entrepreneurship Institute, California State University, Los Angeles, USA Prof. Rustem Nureev Head of the Department of Economic Theory, Financial University, Russia Dr. Oleg V. Pavlov Associate Professor of Economics and System Dynamics, Department of Social Science and Policy Studies, Worcester Polytechnic Institute, USA Prof. Boris Porfiriev Deputy Director, Institute of Economic Forecasting, Russian Academy of Sciences, Russia Prof. Svetlozar T. Rachev Professor of Finance, College of Business, Stony Brook University, USA Prof. Boris Rubtsov Chair of Financial Markets and Financial Engineering, Financial University, Russia Dr. Minghao Shen Dean, Center for Cantonese Merchants Research, Guangdong University of Foreign Studies, China

REVIEW OF BUSINESS AND ECONOMICS STUDIES (ROBES) is the quarterly peerreviewed scholarly journal published by the Financial University under the Government of Russian Federation, Moscow. Journal’s mission is to provide scientific perspective on wide range of topical economic and business subjects. CONTACT INFORMATION Financial University Leningradskiy Av. 51 Building 3, 125993 Moscow Russian Federation Telephone: +7(499) 943-95-23 Website: www.robes.fa.ru AUTHOR INQUIRIES Inquiries relating to the submission of articles can be sent by electronic mail to robes@fa.ru. COPYRIGHT AND PHOTOCOPYING © 2015 Review of Business and Economics Studies. All rights reserved. No part of this publication may be reproduced, stored or transmitted in any form or by any means without the prior permission in writing from the copyright holder. Single photocopies of articles may be made for personal use as allowed by national copyright laws. ISSN 2308-944X

Вестник исследований бизнеса и экономики ГЛАВНЫЙ РЕДАКТОР А.И. Ильинский, профессор, декан Международного финансового факультета Финансового университета ВЫПУСКАЮЩИЙ РЕДАКТОР А.В. Каффка РЕДАКЦИОННЫЙ СОВЕТ М. М. Алексанян, профессор Бизнесшколы им. Адама Смита, Университет Глазго (Великобритания)

Д. Мавракис, профессор, директор Центра политики и развития энергетики Национального университета Афин (Греция) С. Макгвайр, профессор, директор Института предпринимательства Университета штата Калифорния, Лос-Анджелес (США)

А. Мельников, профессор Департамента математических и статистических исследований Университета провинции Альберта К. Вонг, профессор, директор Института азиатско-тихоокеанского бизнеса (Канада) Университета штата Калифорния, Лос-Анджелес (США) Р. М. Нуреев, профессор, заведующий кафедрой “Экономическая К. П. Глущенко, профессор экономи- теория” Финансового университета ческого факультета Новосибирского госуниверситета О. В. Павлов, профессор Департамента политологии и политических исследований С. Джеимангал, профессор Департамента статистики и математичеВорчестерского политехнического ских финансов Университета Торонто института (США) (Канада) Б. Н. Порфирьев, профессор, Д. Дикинсон, профессор Департамен- член-корреспондент РАН, заме та экономики Бирмингемской бизнес- ститель директора Института школы, Бирмингемский университет народнохозяйственного прогнози (Великобритания) рования РАН Б. Каминский, профессор, Мэрилендский университет (США); Университет информационных технологий и менеджмента в Жешове (Польша) В. Л. Квинт, заведующий кафедрой финансовой стратегии Московской школы экономики МГУ, профессор Школы бизнеса Лассальского университета (США) Г. Б. Клейнер, профессор, член-корреспондент РАН, заместитель директора Центрального экономико-математического института РАН Э. Крочи, профессор, директор по научной работе Центра исследований в области энергетики и экономики окружающей среды Университета Боккони (Италия)

С. Рачев, профессор Бизнес-кол леджа Университета Стони Брук (США) Б. Б. Рубцов, профессор, заведующий кафедрой “Финансовые рынки и финансовый инжиниринг” Финансового университета Д. Е. Сорокин, профессор, членкорреспондент РАН, проректор Финансового университета по научной работе Р. Тан, профессор, проректор Колледжа Де Ла Саль Св. Бенильды (Филиппины) Д. Тсомокос, Оксфордский университет, старший научный сотрудник Лондонской школы экономики (Великобритания)

Ч. Т. Фан, профессор, Институт права в области науки и технологии, национальный университет Цин Хуа (Тайвань) В. Фок, профессор, директор по исследованиям азиатского бизнеса Бизнес-колледжа Университета Лойола (США) Д. Е. Халкос, профессор, Университет Фессалии (Греция) К. А. Хартвелл, президент Центра социальных и экономических исследований CASE (Польша) М. Чудри, профессор, Университет Брунеля (Великобритания) Сун Цяокин, профессор, декан Выс шей школы бизнеса Гуандунского университета зарубежных исследований (КНР) М. Шен, декан Центра кантонских рыночных исследований Гуандунского университета (КНР) Издательство Финансового университета 125993, Москва, ГСП-3, Ленинградский проспект, 51, корп. 3, к. 104. Тел. 8 (499) 943-95-23. Интернет: www.robes.fa.ru. Журнал “Review of Business and Economics Studies” (“Вестник исследований бизнеса и экономики”) зарегистрирован в Федеральной службе по надзору в сфере связи, информационных технологий и массовых коммуникаций 9 июля 2013 г. Свидетельство о регистрации ПИ № ФС77-54658. Подписано в печать: 20.04.2015. Формат 60 × 84 1/8. Заказ № 330 от 20.04.2015. Отпечатано в ООП Издательства Финуниверситета (Ленинградский проспект, д. 49). 16+

Review of Business and Economics Studies Volume 3, Number 1, 2015

CONTENTS

Political Economy of Olympic Games Rustem Nureev, Evgeny Markin ��5 The Phenomenon of National Development Bank: Theoretical Foundation and Effectiveness Elizaveta Selyavina �� 34 Monetary Policy in Russia: Recent Challenges and Changes in Unstable Economic Conditions Natalia Giblova �� 57 Market Concentration and Competition in Vietnamese Banking Sector Le Hai Trung �� 67 Remittances and Economic Growth in Vietnam: An ARDL Bounds Testing Approach Dang The Tung �� 80 Corporate Insurance in the Russian Electric Power Industry Nadezda Kirillova, Victoria Bazhenova �� 89

Вестник исследований бизнеса и экономики № 1, 2015

CОДЕРЖАНИЕ

Политическая экономия Олимпийских игр Рустем Нуреев, Евгений Маркин ��5 Феномен национального банка развития: теоретические аспекты и эффективность деятельности Елизавета Селявина ��34 Денежно-кредитная политика в России: текущие проблемы и изменения в условиях экономической неопределенности Наталья Гиблова ��57 Рыночная концентрация и конкуренция в банковском секторе Вьетнама Ле Хай Чунг ��67 Влияние денежных переводов на экономический рост во Вьетнаме Данг Зе Тчунг ��80 Корпоративное страхование в российской энергетической промышленности Надежда Кириллова, Виктория Баженова ��89

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Political Economy of Olympic Games* Rustem NUREEV, Doctor of economics, Professor Head of Department of Economic Theory, Financial University; Professor at National Research University — Higher School of Economics, Moscow nureev50@gmail.com Evgeny MARKIN, Ph. D., Senior Lecturer Russian State University of Physical Education, Sport, Youth and Tourism, Moscow ev-markin@yandex.ru Abstract. The purpose of the article is to analyze how IOC voting process modifies the Olympic ideals and sport development in host countries. The authors analyze a representative democracy within the Olympic Movement (the features of the functioning of the IOC, NOCs and other public organizations in the process of Olympic Games preparation). The article discusses the features of the decision making process at different stages of the hosting country selection. Candidature Acceptance Procedure includes 11 indicators. The authors describe these indicators and analyze the importance of each of them for final score. A special attention is paid to the voting procedure in the final part of the decision. The authors investigate the factors contributing to the development of principal-agent problem, logrolling and bureaucracy. Features of voting and logrolling are based on the choice of 2014 Olympic Winter Games capital (Sochi, Russia). Influence of Olympic Games on the host country’s economy is investigated on the base of major macroeconomic factors. Authors show the dependence between chosen model of administration and financing and economy and sport development in SR and LR. The authors draw conclusions on how to improve the constitutional framework for the reduction of the prerequisites for the emergence of informal relations in the decision to host sports mega events. Аннотация. В статье рассматривается прямая и представительная формы демократии и их проявление в Олимпийском движении. Авторы подробно анализируют процесс выбора столицы очередных Олимпийских игр, его слабые стороны. Особое внимание уделено выборам Сочи — столицы зимних Олимпийских игр 2014 года. Авторы дают анализ издержек и выгод на разных этапах олимпийского делового цикла, рассматривают особенности экономической и политической деловой активности и факторов, от которых они зависят. Статья также посвящена анализу влияния Олимпийских игр на экономику страны их проведения. Выделены модели управления и финансирования Олимпийских игр и дан анализ их применения в странах, проводивших Олимпийские игры в 1992–2008 гг. Key words: Olympic Games, decision making process, voting procedure, direct democracy, political business cycle, International Olympic Committee.

1. REVIEW The role of sports mega events in economic and political life of the nations has strongly increased. That is why the investigation of these processes is very important. Economy of physical culture and sports in the history of Russian sports science was studied by the scientists of Russian State University of Physical Training, Sport and Tourism B. S. Kuzmak and R. M. Orlov. Later

this problem was investigated also by V. I. Zholdak and V. E. Levitin. The questions of correlation between productivity and physical education was investigated by V. I. Zholdak. A. M. Alekseev considered the four most important factors determining the cost-effectiveness of sports. Issues of social and economic efficiency are also reflected in the works of S. M. Oksanych, Y. F. Trusov, etc. The most important theoretical aspects of the economy of physical culture and sports in different periods were researched by V. M. Rutgayzer and V. V. Galkin.

* Политическая экономия Олимпийских игр.

Review of Business and Economics Studies

V. I. Koval (1978) has investigated the economic issues of XX Olympic Games in Munich and tried to use this experience for XXII Olympics in Moscow. His work was published in 1978. Foreign publications in sport economy are more diversified. A monographic “Economy of Sport” (by professors Wladimir Andreff and Jean-François Nys) was released in 1986 in Paris and reprinted in 2002. In 2007 Wladimir Andreff and Sandrine Poupaux published the work “The International Dimension of the Sport Economy in Transition Countries”. Interesting aspects of sport influencing on Europe’s economy was described by D. Dimitrov, L. Helmenshtayn, B. Moser, A. Klyaysner and J. Schindler. They analyzed the sport’s impact on the European economy and its influence on Europe’s GDP. In the works of L. Kann and P. Stodohar the interaction of sport and the labor market is described and their influence on each other is examined. Holger Preuss (2000) investigated the economic conditions of Olympic Games hosting. Shank M., I. Blekshow, D. Hogg, S. Brown, W. Sutton, D Duffy, R. Noll and A. Zimbalist paid great attention to sport management and its importance for infrastructure development and new jobs creation. Researches in the field of Olympic Games economy were made by R. Barney, A. Oberger, F. Brunet, O. Shants, R. Mandell, A. Gutman. Public choice questions concerning Olympic Games are still not sufficiently researched. A large quantity of material is contained in the newsletters (so-called Marketing Matters) and official reports of International Olympic Committee. They are published periodically and are the most complete source of information about international Olympic movement activity now.

belongs to Pierre de Coubertin, on whose initiative in June 1894 in Paris was organized the International Athletic Congress, where on June 23, 1894 the International Olympic Committee (IOC) was founded. The need to create the IOC as an organizational and management structure was obvious — without it, all the international Olympic movement was ineffective and unsustainable organization. Only permanent management authority with appropriate financial, organization and human resources was able to solve complex problems of international scope. IOC is nternational non-governmental organization, established as an association with l not-profit status. It recognized by the Swiss Federal Council in accordance with the contract, which came into force on November 1, 2000. Document governing the basic mechanisms of economic management of the modern Olympic Games and the Olympic movement in general is the Olympic Charter. This is a set of fundamental principles of Olympism, rules and byelaws adopted by the International Olympic Committee. The Olympic Charter governs the structure, mechanism of action and processes of the Olympic movement and determines the conditions of the Olympic Games. It performs three main tasks: 1) regulates the basic principles and essential values of Olympism; 2) is a charter of the IOC; 3) defines the basic rights and responsibilities of the three main constituents of the Olympic Movement: the International Olympic Movement, the International Federations and National Olympic Committees and Organizing Committees for the Olympic Games, which must comply with the Olympic Charter. In 1986, the IOC brings together 164 national Olympic Committees (NOC); in 2004 at the Olympic Games in Athens, they became 201. Another important principle of Olympic Movement management is its independence on political influence of individual states and political units. Obviously, if the Olympic institutions will be under someone else’s political influence, they quickly lose their international prestige and global significance. The same can be said about financial independence on any commercial or public organizations. These norms are reflected in the Olympic Charter and allow IOC to maintain its political and commercial independence. IOC is developing special marketing programs to raise money and create a sound financial base for the development of the Olympic movement. A priority for the IOC is to implement programs to broadcast the Olympic Games through telecommunications companies, programs to work with corporate sponsors, minting of commemorative coins and medals, etc.

2. OLYMPIC MOVEMENT: IOC VOTING PROCEDURE MATTER For clear understanding how voting procedure influences the results of decision making process in Olympic movement let’s look at the history and structure of IOC. Central to the international sporting life and a base for the growth in business activity in modern world is the Olympic movement, which is rightfully occupies a leading place among the various social and cultural phenomena, and has a direct impact on the economic development of the Olympic Games host country. The international Olympic movement is a kind of institution, under which the large number of sports federations, national Olympic committees (NOC), sports competitions are held. The first Olympic Games took place in 776 BC in Ancient Greece. The concept of modern Olympism

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

IOC President IOC Board: 4 Vice-Presidents + 10 Members

International Olympic Committee (115 Members)

IOC session Candidates IOC Members

NOC Members

ISF Members

IOC Commission of Sportsmen

Figure 1. IOC organizational structure*. * Created on the base of the data from: www.olympic.org.

Principles listed above were the basis of the practical operation of the IOC in the following areas: • Regular organization of Olympic Games; • Definition of the Games and composition of the participants (in collaboration with sports federations and National Olympic Committee of the Games); • Registration of Olympic records; • Placing orders for the Olympic marketing programs and overseeing their implementation; • Overseeing the distribution of funds among the National Olympic Committees and international sports federations; • Promotion of sports and strengthening of friendship among athletes in the IOC member countries; • Dissemination of ideas of Olympism and healthy lifestyle; • Supporting development centers for sporting events. It should be noted that one of the basic principles by which the IOC in choosing the next capital of the Games is what legacy of the Olympic Games for future generations will be left and what economic and social effect will have the city, region and country of the Games. The total number of IOC should not exceed 115 members, which can only be individuals, representatives of member states of IOC. Composition of the IOC shall be elected at a general meeting, called the session. Sessions are held at intervals not less than once a year. The organizational structure of the IOC is presented in Figure 1. At the IOC session the president and members of the IOC Executive Board are elected. Let’s look at fund-

ing mechanisms of the international Olympic movement and distribution of financial flows. Direct democracy is political system in which every citizen has the right to personally express his/her view and vote on any particular issue. Direct democracy is typical for the assembly of labor collectives of enterprises and institutions,, party meetings and conventions. In a national scale it is the choice of parliament members, or the president conducting nation-wide referendum. Decision-making procedure (the rules) in this situation is the main focus. Direct democracy is not the dominant form in the Olympic movement. It remains as a subordinate element of representative democracy. Majority rule is not a standard in terms of the effectiveness of the decision. Alternatives to majority rule are the two-step rule relative majority, multistep binary voting procedure for approving the ballot, a simple majority of the knock-out and generally exclude the losers on the board. It is obvious that the Olympic movement cannot apply the rule of unanimity in decision-making. This rule applies to the UN Security Council, for example. IOC, of course, tries to take into account the opinion of all the voting for some solutions, but everyone’s opinion into account not his best. That is why every 2 years on the IOC sessions the rule of simple majority of the knockout is using, to select the next Olympic Games host city. A voter in fact cannot select multiple capitals of Games, guided by the idea that a sailing competition, for example, would be better held in Rio-de-Janeiro,

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 1. Relationship between decision making and level of economic development of member countries and their world market power (since 1896). Country

G20

Olympiads

Olympic Winter Games

Total #

GDP per capita (2009)

USA

Yes

45 989

France

Yes

Yes *

41 051

United Kingdom

Yes

35 165

Germany

Yes

Yes *

40 670

Italy

Yes

Yes *

35 084

Canada

Yes

39 599

Japan

Yes

39 738

42 279

45 562

Yes

Australia

Yes

Austria

Yes *

Greece

Yes *

Norway

Yes *

Russia (USSR)

Yes

29 240

79 089

8 684

63 629

2 1

Switzerland

Yes *

Belgium

Yes *

43 671

Brazil

Yes

8 121

Spain

Yes *

31 774

China

Yes

3 744

Mexico

Yes

8 143

Netherlands

Yes*

47 719

Finland

Yes *

44 581

Sweden

Yes *

43 654

4 525

17 078

Yugoslavia (Bosnia & Herzegovina) South Korea

1 Yes

* EU countries represents in G20 as one country (union). Created on the base of: www.gamesbids.com and World Bank.

and athletics — in Moscow. Thus, the choice made in favor of only one candidate. And those of programs that are known to be better with the other candidate, in this case are as “good with a load” (Nureev, 2005). It is important to point out that in the IOC and modern Olympic Movement’s activity the desire to realize the idea of “micro space”, formulated by the American President John Adams in 1780s, can be traced. He believed that parliament should be an accurate portrait of the nation as a whole. In our case we are talking about the Olympic Movement’s governing bodies, which consist of representatives of different nations. Unfortunately, the relationship between decision making and level of economic development of member countries and their political influence is observed. The history of the modern Olympic Games (since 1896) shows that developed countries which now form the so-called G8 or G20 (see Table 1) are most likely to host the Games.

The struggle of countries with weak economies to host the Olympics often finish at the stage of choosing a candidate city. The final choice is made among the developed countries’ representatives. These cities can spend on the Games the necessary funds, which allow to get a profit from the Games in future. Thus, there is a conflict between the ideas and ideals of the Olympic movement and the IOC and their actual deeds. Even the recent decision to hold the 2016 Olympics in Rio de Janeiro, unfortunately, does not give the right to speak about positive trends. Olympic movement has a procedure for selection of the capital of the next Olympic Games. As any other large institution, IOC has its own rules. The choice is made from a limited number of participants, formed by the IOC during the pre-selection. International Olympic Committee has developed a special system of Applicants and Candidate Cities estimation. When the two-phase candidature proce-

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 2. Indicators of Candidature Acceptance Procedure for the Games of XXXI Olympiad in 2016*.

*â&#x20AC;&#x201A;

Games of XXXI Olympiad 2016Â Working Group Report, Lausanne, 2008.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure. 2. Final Result of Working Group Report for estimation of Games of XXXI Olympiad 2016 Applicant Cities. Source: Games of XXXI Olympiad 2016 Working Group Report.

Table 3. Bid Index on the eve of 2014 Winter Olympics final voting. CITY PyeongChang Salzburg Sochi

HIGH 64.99 65.35 63.17

LOW 55.72 60.63 56.71

CHG

LOW 58.78 57.80 59.73 59.20

CHG

+00.09 -01.31 +02.22

INDEX 64.99 62.62 63.17

Source: www.gamesbids.com

Table 4. Bid Index on the eve of 2016 Olympics final voting. CITY Chicago Madrid Rio-de-Janeiro Tokyo

HIGH 61.24 59.50 61.61 61.41

+1.23 0.00

-0.19 -0.18

INDEX 61.24 57.80 61.42 59.02

Source: www.gamesbids.com

dure was introduced, the IOC Executive Board considered that the assessment of Applicant Cities should be supported by decision-making software. “Decision Matrix” was selected from a number of options to assist with the assessment of the 2008 Applicant Cities, based on experience with projects of a similar type. Decision Matrix was formed in 1983 for the purpose of developing decision software catering to large and very specific decision-making processes in organizations. The Decision Matrix software uses graphic user interfaces to display results in an easily interpretable fashion. In consultation with the IOC, Decision Matrix developed the “OlympLogic” decision model — based on an already proven decision model “OptionLogic” — which computes the best option amongst a number of contenders. The OlympLogic program enables the assessment of the Applicant Cities on the basis of a number of IOC specific criteria. Matrix was successfully used by the IOC in the assessment of the 2010, 2012 and 2014 Applicant Cities, as well as in the assessment of the bidding cities for the 2010 Youth Olympic Games.

Candidature Acceptance Procedure includes 11 indicators: 1. Government support, legal issues and public opinion (including compliance with the Olympic Charter and the World Anti-Doping Code); 2. General infrastructure; 3. Sports venues; 4. Olympic Village (s); 5. Environmental conditions and impact; 6. Accommodation; 7. Transport concept; 8. Safety and security; 9. Experience from past sports events; 10. Finance; 11. Overall project and legacy. Each indicator can be in a range between 1 to 10. The acceptable minimum is six. If city receives less than 6 then this indicator is colored in matrix in red color. It is the signal that city is not developed enough. Let’s illustrate this procedure on the example of Games of XXXI Olympiad 2016 (see Table 2). As we can see in Table 2, Prague and Baku do not have enough support according to members of Working Group. All the results are summarized in the final

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 5. Simple Majority With Exclusion (Australian Voting System). a) Group I (4 voters) A C E B D

Group II (6 voters) D C E B A

Group III (7 voters) B E C D A

Group IV (3 voters) C D E B A

Group V (2 voters) E B A C D

When there is no winner by simple majority, alternative that scored least votes is excluded (E – 2). b) Group I (4 voters)

Group II (6 voters)

Group III (7 voters)

Group IV (3 voters)

Group V (2 voters)

A C B D

D C B A

B C D A

C D B A

B A C D

C — 3. Excluded c) Group I (4 voters)

Group II (6 voters) D B A

A B D

Group III (7 voters) B D A

Group IV (3 voters) D B A

Group V (2 voters) B A D

A — 4. Excluded d) Group I (4 voters) B D

Group II (6 voters) D B

Group III (7 voters) B D

Group IV (3 voters) D B

Group V (2 voters) B D

Winner is B — 13 of 22.

decision (Figure 2). As you can see Prague and Baku were not recommended by Working Group. This decision has preliminary status and other cities could also be declined at the last stage. For example, Doha was also declined as a candidate city for the Games of XXXI Olympiad in 2016. This procedure always takes place inside IOC. International sport analytical agencies have their own ratings. They analyze the same indicators and present Bid Indexes. The Bid Indexes of GamesBids Agency on the eve of 2014 and 2016 Olympics final voting are presented in the Tables 3 and 4. Bid Index includes the lowest and highest estimation and the last changes. In Table 3 we can see that Sochi left off PyeongChang but demonstrated the highest level of Bid Index Increase. It became the crucial factor for the win. Rio de Janeiro was the leader on the eve of final voting but there was a small decrease of index. Nevertheless it did not influence the final result, and Rio

de Janeiro was elected as the capital of 2016 Olympics. As noted earlier, IOC members make a decision about Olympic Games next capital using the simple majority rule with a knockout. We shall consider it in detail. In a simple majority of knock-out (the Australian system of voting) wins the candidate who gains a simple majority (see Table 5). However, in the absence of a simple majority at the first stage the candidate with the fewest votes is left. In our example it is E (E - 2). During the multistep voting system, each time a candidate with the fewest votes is eliminated.. In our example it is B (B - 13 out of 22). Olympic Games Capital voting procedure is the following: • More then 100 International Olympic Committee members take part in the voting; • International Olympic Committee members from the countries presented by the candidate cities are not voting;

Review of Business and Economics Studies • International Olympic Committee members representing countries where the Olympic venues are partially situated are not voting; • Candidate city should receive more than 1/2 of all votes; • Olympic Games host city and country are determined at least before 7 years of the Games. The Analysis of Olympic Games selection since 1972 (see Annex 1) shows the following regularity: The majority of the IOC members have an exact scheme of voting before it starting. This scheme is based not only on real IOC Member preferences (Sydney 2000, Nagano 1998, Atlanta 1996). The votes which were given for the first outsider mostly go to the city, which finally wins. But it takes place only if there are no other candidate cities from the same continent or economic area (Sochi 2014, Vancouver 2010). IOC members firstly support the applications from the same home continents (London 2012, Atlanta 1996, Lillehammer 1994, Albertville 1992, Montreal 1976).

3. LOGROLLING AND CORRUPTION The geography of the countries applying for the Olympic Games in recent years has grown significantly: Azerbaijan, Thailand, South Africa, Malaysia (see Figure 3), Poland, Slovakia, Kazakhstan (see Figure 4). Recently, the IOC uses a more rigorous approach for selection of the new Olympic Games capital. This is illustrated in Table 6, which shows that in the last 15 years a large number of applicants were rejected at the first procedure stage and the status of candidate city was given to fewer participants (less than 50%). Previously mentioned examples show that the Olympics enjoy the extremely high popularity, and attract a large number of countries wishing to undertake them. But the number of competing cities to host the Games has been reduced. The main reason for the claims of the leadership in this competition is that the applicant countries expect from the Olympic Games a strong impetus for economic development and social services through their impact on economic growth. Olympic Games bid process includes a very complex and costly procedure for choosing the capital of the next Olympic Games. And as any selection procedure it can be associated with possibilities for manipulation, lobbying, corruption, etc. In 1998–1999 the crisis in the Olympic movement happened. It was linked with the abuses and corruption in the selection of the capital of 2002 Winter Olympics. After that selection procedure of candidate cities and the capital of the Games has changed.

Volume 3, Number 1, 2015

On December 15, 1998 at IOC session in Lausanne, one of IOC members — Marc Hodler (Switzerland) — announced the facts of corruption among fellow Olympians. He said: “5–7% of the 115 IOC members are amenable to bribery.” The IOC set up a commission to investigate this fact. It detected that some IOC members received gifts and cash rewards from the Bid Committee of candidate cities. In the “black list” there were IOC members from Ecuador, Libya, Congo, Netherlands, Finland, Chile, Swaziland, Cameroon, Mauritius, Kenya, Côte d’Ivoire and Russia. The following results were achieved: • 6 Members were temporary excluded from IOC; • 3 Members were completely excluded from IOC; • It was recommended to approve a new selection procedure for 2006 Olympic Games capital; • The rights to host 2000 and 2002 Olympic Games were confirmed to Sydney and Salt Lake City; • IOC members approved Juan Antonio Samaranch as IOC President (86 votes of 90). If a state decides to hold Olympic Games, to achieve this goal it is necessary to do the following: 1) The city receives the status of candidate city (city must receive a positive assessment of the IOC Evaluation Commission, according to the assessment matrix); 2) Majority of IOC members votes for a candidate city in the final vote. Throughout this process there are opportunities for abuse and corruption within the IOC members and officials of the Bid Committee. The first who saw this problem were Frank Daumann and Markus Breuer of Friedrich–Schiller– University, Jena in the paper “The Award of the Olympic Games — Incentives for Corruption in a Multiple Principal-Agent Relationship”. They suggested the following behavior of participants in the process of choosing the capital of Olympic Games: • Abuses are still possible in IOC regardless of the 1999 reform of the Olympic Games selection procedure; • Individual preferences with respect to a particular candidate city prone logrolling process especially in the IOC members from countries traditionally often participating and conducting the Olympic Games (U.S., Canada, France, Japan); • The athletes’ opinion is most often not taken into account. Agent (IOC member) will receive compensation only if the deal goes through. The rate depends on the amount of the transaction (e. g ., a fixed percentage). In this case also may be the likelihood of abuse — double sales of the vote. The IOC member may agree with the different parties to support a par-

Volume 3, Number 1, 2015

18 17

1992-2016

16 15 14

1948-1968

1972-1988 1924-1944

13 12 11 10 9 8 7 6 5

Countries

Dubai

Azerbaijan

Ireland

Czech Republic

Hungary

Netherlands

Australia

South Korea

SAR

Greece

Puerto-Rico

Egypt

Tailand

Malaysia

Great Britain

Cuba

Turkey

Brazil

Argentina

China

Mexico

Japan

Sweden

Yugoslavia

France

Switzerland

USA

Finland

Russia (USSR)

Italy

Canada

Spain

Germany

1 0

Austria

4 3 2

Belgium

Number of Applications

Review of Business and Economics Studies

Figure 3. Number of Candidate Cities to Host The Games of Olympiad (1896–2016) Calculated by authors on the base of www.gamesbids.com, www.olympic.org

1992-2014 1972-1988 1948-1968

Figure 4. Number of Candidate Cities to Host Olympic Winter Games (1924–2014) Calculated by authors on the base of www.gamesbids.com, www.olympic.org

Bolgaria

Georgia

Kazakhstan

South Korea

Bosnia & Herzegovina

Countries

China

Andorra

Japan

Yugoslavia

Sweden

Switzerland

France

Finland

USA

Slovakia

Russia (USSR)

Poland

Norway

Canada

Italy

Spain

Germany

Belgium

1924-1944

Austria

21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

Table 6. Applicant and Candidate cities on the 1992–2018 Olympics. Games of Olympiad

Olympic Winter Games

Years

Number of Applicant Cities

Number of Candidate Cities

% of attrition

Years

Number of Applicant Cities

Number of Candidate Cities

% of attrition

1992

1996

1994

2000

1998

2004

2002

2008

2006

2012

2010

2016

2014

2020

N/A

2018

100

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 7. Number of votes in support of Sochi 2014 Olympic Bid (expert analysis of Russian mass media) Sovetskiy Sport newspaper (2007)

Izvestiya newspaper (2007)

Europe

Asia

America

Africa

Australia & Oceania

TOTAL

Part of World

ticular candidate city and secure income with 100% probability. In fact, he may vote for whom he wants. And in case of lossof one of the candidate cities he says that he voted in support of it and there is no his guilt in losing. In this case, he will receive income from the other (winning) candidate, if pre-entered into an informal agreement with it. The possibility of such behavior is high because everything is regulated by informal relationships and it is impossible to keep track of how 100% of IOC members behave. Sochi 2014 can be analyzed as an example. The final vote of selection of the host city of the XXII Olympic Winter Games in 2014 was attended by 100 members of the IOC: 42 from Europe, 17 from Asia, 18 from America, 19 from Africa and 4 from Oceania. As a result, the Russian resort city in the second round of voting won the bid. It was supported by 51 members of IOC; 47 members voted for Peong-Chang. Some Russian analytical publications independently tried to more specifically define which IOC Members supported Sochi (see Table 7). Analysis shows that Sochi received the greatest support from IOC members from Europe. Australia and Oceania did not support Sochi at all. The most controversial data is on the voting of IOC members from the United States. According to Sovetskiy Sport, Sochi was supported 15 members of the IOC out of 18, while according to Izvestiya — only 3 out of 18. During the Olympic bid top Russian sport and political officials undertook different attempts to get support. Logrolling was non exclusion. Russian sports officials have openly talked in interviews how some votes were got. Ex-President of the Russian Football Union said that his responsibilities included persuasion of “football” IOC members (e. g. Joao Avelange and Zepp Blatter). IOC members at various levels demonstrated the benefits of the application of Sochi 2014. There was a case of logrolling: Sochi received 3 votes of IOC members from Ukraine and Poland in exchange for the Russia’s support to application of these countries to hold European Football Championship in 2012.

4. OLYMPIC POLITICAL BUSINESS CYCLE: THEORY AND PRACTICE In the Olympic business cycle 3 phases can be defined: • Pre-Olympic stage — from the date of filing a formal application from the city and the country to host the Olympic Games till 30 days before the start of the Olympic Games; • Olympic stage — from 30 days before the start of the Olympic Games till 30 days after the official closing ceremony; • Post-Olympic stage — from 30 days after the official closing ceremony till the end of next season (the summer — for the Olympics and the winter — for the Olympic Winter Games) after completion of the Olympic Games. 4.1. OLYMPIC POLITICAL BUSINESS CYCLE: COSTBENEFIT ANALYSIS Cost-benefit analysis allows to define when expenditures are the biggest and when the revenues are the highest. Let’s see on the costs and benefits of Olympic Games organizing committees at different stages of the Olympic business cycle (see Tables 8–11). 4.2. OLYMPIC POLITICAL BUSINESS CYCLE: CORRECTION OF THE WAVE Gross spending related to the 2010 Games and distribution of the investments for the Olympic Games is presented on the Figure 5 and Figure 6. We can see that the biggest part of expenses is required 4–6 years before the Olympics. This fact proves our theory about the costs distribution during the Olympic business cycle. From the other side, as statistics shows (see Figure 6) the largest number of investments is made 3–1 years before the Games. Thus we should correct our model and increase economic activity during the period of 3–1 years before the Games and decrease the political activity during the period of Olympics hosting (see Figure 7). The mechanisms of administration play an important role during the Olympic business cycle, as presented by Nureev R. M. and Markin E. V. (2008). High-quality

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 8. Public and private cost-benefit analysis on pre-Olympic stage (Participation in election procedure). Costs

Benefits

Public

• Olympic bid documentary support • Participation fee • Preparation and organization of activities to popularize the idea of Olympic Games hosting inside the country and abroad • Olympic Games Questionnaire preparing • Applicant City advertising • Infrastructure development and preparation for IOC Commission visit

• Country image increase • Knowledge increase about applicant city abroad

Business

• Participation analysis

• Investment attraction increase

Table 9. Public and private cost-benefit analysis on pre-Olympic stage (Olympic Games Organizing). Costs

Benefits

Public

• Organization costs, — Administrative costs — Opening and closing ceremonies — Olympic touch relay • Technical costs (stadiums, swimming pools, Olympic village, press-center etc.) • Infrastructure development (roads, underground, electronic communications etc.) • Environmental protection

DIRECT • TV rights selling • Sponsors (national and worldwide) • Licensing • Ticketing (partially) • Sales through the Internet • Coins, lottery etc. INDIRECT • Unemployment decrease • Aggregate demand growth • Taxes growth • Business activity growth • Country and city availability growth

Business

• Hotels construction • Tourism infrastructure development in hope for the future benefits

• Investment attraction growth • Advertising of goods and services

Table 10. Public and private cost-benefit analysis on Olympic stage. Costs

Benefits

Public

• Security • Sportsmen accommodation and food • Advertising activities, festivals etc. • Utilities • Subsidies to the factories and companies which are closed for the Games period, traffic jams avoiding and so on.

• Number of tourists increase, • Country image increase, • Ticketing (partially) • Sales through the Internet • GDP and GRP growth • taxes

Business

• General organizational costs • Restrictions for factories and industry companies work

• Country image increase, • Investment attraction increase • Advertising of goods and services • Souvenirs and sport equipment selling • Plastic cards transactions • Hotels filling • Sportsmen and guests expenditures

Table 11. Public and private cost-benefit analysis on post-Olympic stage. Costs

Benefits

Public

Infrastructure and equipment operation costs

Bank interest revenue Assets sales Hosting other mega events

Business

Infrastructure and equipment operation costs

Hosting other mega events Souvenirs and sport equipment sales Tourism

Review of Business and Economics Studies effective management and planning allows to make profitable and successful Olympic Games. Olympic Games hosting gives an impulse to the economy of their countries and achieves two main objectives: profits maximizing and positive externalities maximizing. Private business is more interested in achieving the first objective, state — the second one. All sources of events and infrastructure funding, which come from the state, regional and local (municipal) levels, constitute public financing. All private domestic and foreign expenses are private funding. Value of public and private funding can be divided into 3 basic models of administration and financing, which can be applied to any Olympic Games: • Model of public administration and financing (the share of public participation more than 67%); • Mixed model of administration and financing (the share of public participation from 33% to 67%); • Model of private administration and financing (the share of public participation less than 33%). Figure 8 shows which model of administration and finance was typical for the Olympic Games in 1972–2008. Let us consider which of these models is used in Russia for organization of 2014 Sochi Olympic Games. Usually it is divided in 4 main levels of administration and financing: the government of the Olympic Games host country, the region/district, the city (the capital of the Games) and the private sector. All these levels were involved in Sochi: the President and the Government of Russia, Krasnodar Region Administration, Sochi Administration and private sector (see Figure 9). The Games Organizing Committee is usually

Volume 3, Number 1, 2015

responsible for Games preparation. In Russia it is the “Sochi 2014” Organizing Committee. In Russia a state corporation was founded — SC “OlympStroy”. It is responsible for region infrastructure development (most of which was built from scratch). Analogue of creating state corporations were specially created organizations for the preparation of the Games in Sydney, Athens and Turin, which reported directly to governments. A similar scheme is also used in the organization of the Games of XXX Olympiad in London, where a key role (besides LOCOG) was played by the Olympic Development Agency (ODA). Olympic Winter Games 2014 in Sochi was extremely important for Russia. It gave investment impulse to the development of regional economy, attracted private capital and foreign investments, created high-tech production and environment for economic growth. Games’ cost for Russia was more than 50 bn US dollars. It was the most expensive winter games in the history of Olympic Movement.

5. INFLUENCE OF THE OLYMPIC GAMES ON THE NATIONAL ECONOMY The influence on the Olympics host country economy can be characterized by following factors: 1) production growth (construction, sports paraphernalia, pins, complementary goods, sports equipment, food); 2) employment growth: • temporary: construction workers, the additional hotel and transport service volunteers;

Figure 5. Summary of gross spending related to the 2010 Games. Source: 2010 Winter Olympic and Paralympic Games Report

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 6. Distribution of the investments for the Olympic Games (%). Created by: Preuss (2009)

2 years

5 years

2 years

1 years

Â Figure 7. Political and economic business activity inside the Olympic business cycle (aÂ typical issue). Created by: authors

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Share of public participation (%)

97 USSR/Russia (Moscow, 1980) 95 Canada (Montreal, 1976) China (Beijing, 2008) Germany (Munich, 1972) Greece (Athens, 2004)

84 81

Model of public administration and financing

67% Mixed model of administration and financing South Korea (Seul, 1988)

Spain (Barcelona), 1992) Australia (Sydney, 2000)

38 33% 30

USA (Atlanta, 1996)

Model of private administrat and financing

USA (Los‐Andgeles, 1984)

2 3 5

16 19

33%

62 70 67%

Share of private participation (%)

Figure 8. Administration and financing models of summer Olympic Games in 1972–2008. Created by: Preuss (2000), Koval (1978)

Figure 9. The main levels of administration in organizing 2014 Sochi Olympic Winter Games.

Review of Business and Economics Studies

• constant: the staff and management of hotels, restaurants and technical personnel; 3) the growth of tourism: • turnover of the hotel business; • increasing load of transportation routes (air, railway, bus etc.); 4) the expansion of the banking sector: • lending to the population and small and mediumsized businesses; • exchange transactions (including banking — noncash); 5) value of income tax, sales tax, 6) increase in effective demand, etc. The impact of sport on the GDP can be calculated as the sum of sports sector profit and investment in sports sector in the country. Similar calculation method can be applied to assess the impact of the Olympics for host country’s GDP conduct. We can calculate how domestic investments in the Olympics host country increases the growth of goods or services output. For example, it was estimated that sport has direct impact on the economies of Europe (EU-25) in the amount of 41 billion Euros (0,46% of GDP), with taking into account the multiplier — 45 billion Euro (0,51% of GDPWe now analyze the average number of employees in the economy, conducted the Olympics for the past 20 years (see Table 12). The table shows that employment increased during the Olympic business cycle in each country. This is particularly evident in those countries where data for the full Olympic business cycle is available: Australia (2000) — an increase from 7.8 million to 9.1 million, Japan (1998) — an increase from 62.5 million to 64.5 million, Italy (2006) — an increase from 20.2 million to 22.6 million attendees. And in Japan immediately after the Olympic business cycle in 1999, the number of employed in the economy began to decline. Of course, we must make allowances for the fact that there is population growth in these countries which doesn’t depend on the Games. But, first of all, the growth was not so intensive, and secondly, the population growth within the Olympic business cycle can increase the number of employed people much later. At the same time, the total number of unemployed people in the Olympics host countries decreased within the Olympic business cycle (see Table 13). The data shows that unemployment in Italy during the Italian Olympic business cycle fall down from 2,6 mln. (2000) to 1,8 mln. (2006). The same situation was in Australia where unemployment decreased from 0,75 mln. to 0,67 mln. during 1995–2001. Unemployment growth was fixed only in Japan. It started to increase in 1999 when Japanese Olympic business cycle (1989–1999) finished. The number of unemployed peo-

ple reached 3,1 mln. in 2004 compared to 2,1 mln. in 1995. But this exclusion from our preposition could be explained by the economic crises in Japan at the end of XX century. The crises took place because of the growth of bad debts, delayed structural modernization of Japanese industries and decrease of private sector average demand. Let us draw your attention to the growth of unemployment during this period in other European countries, which didn’t host the Olympics. For example, unemployment in Austria between 2000 and 2005 increased from 139 up to 208 thousand people, in Belgium from 308 up to 380 thousand people (2004), in Hungary from 263 up to 304 thousand people, in Germany from 3 127 up to 4 583 thousand people etc. But there were few countries where unemployment decreased: Finland (from 253 down to 220 thousand people), Lithuania (from 274 down to 133 thousand people)1. The analyzed data also shows that during the Olympic business cycle employment growth is accompanied by the growth of real wage in the economy. As we can see from Table 14 real wage indicator increased. Between 1995 and 2005 Japan, Australia, USA, Greece and Italy were on different stages of Olympic business cycle. Japanese Olympic business cycle took place in 1989–1999, Australian — 1991–2001, USA — 1993–2003, Greece — 1995–2005, Italian — 1997–2007. Compared to 1995 real wage index increased up to 110% in Australia, 114% in USA and down 99% in Japan. Data of the Table 14 also shows that real wage indicator in China and Canada which entered in Olympic business cycles later (in 1999 and 2001) also continued to rise. The dynamics of gross capital assets was always positive, except for Japan (see Table 15). Countries such as Australia and the USA continued to show high growth of capital assets, even after Olympic business cycles in these countries (after 2001 and 2003, respectively). Canada, for which the Olympic business cycle began in 2001, showed very high positive dynamics — 144% in 2001 and 180% in 2005 (compared to 1995). One of the factors, which influences on aggregate production and supply is capital assets. In Table 15 the dynamics of capital assets in 1992–2014 host countries is presented. Figure 10 shows the 20-year dynamics of inflation in countries that have organized the Olympic Games. From 5th to 15th years is the period of Olympic business cycle in particular country. For example, for Spain it is the time period from 1978

Volume 3, Number 1, 2015

Rosstat, 2007.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 12. Olympic business cycle influence on the annual employment in countries which hosted Olympic Games in 1990–2006 (mln.). Host country

Years 1990

1995

2000

2001

2002

2003

2004

2005

2006

France (Albertville 1992)

22,3

22,2

23,3

23,8

23,9

24,6

24,7

n/a

Norway (Lillehammer 1994)

2,0

2,1

2,3

n/a

USA (Atlanta 1996, Salt-Lake-City 2002)

119

125

135

136

138

139

142

n/a

Japan (Nagano 1998)

62,5

64,6

64,5

64,1

63,3

63,2

63,3

63,6

n/a

Australia (Sydney 2000)

7,8

8,2

9,0

9,1

9,2

9,5

9,6

10,0

n/a

Greece (Athens 2004)

n/a

Italy (Turin 2006)

21,5

20,2

21,2

21,6

21,9

22,1

n/a

22,6

n/a

China (Beijing 2008)

639

681

721

730

737

n/a

Source: Rosstat, 2007.

Table 13. Olympic business cycle influence on the annual unemployment in countries which hosted Olympic Games in 1995–2008 (thousand). Host country

Years 1995

2000

2001

2002

2003

2004

2005

2006

2899

2590

2285

2341

2656

2727

n/a

Norway (Lillehammer 1994)

107

106

111

n/a

USA (Atlanta 1996, Salt-Lake-City 2002)

7404

5655

6742

8378

8774

8149

7591

n/a

Japan (Nagano 1998)

2100

3190

3400

3590

3500

3130

2940

n/a

Australia (Sydney 2000)

751

608

667

637

607

571

535

n/a

Greece (Athens 2004)

n/a

2638

2495

2267

2163

2096

n/a

1889

n/a

1402

1084

1164

1272

1289

1234

1173

n/a

France (Albertville 1992)

Italy (Turin 2006) China (Beijing 2008) Canada (Vancouver 2010) Source: Rosstat, 2007.

to 1998 (where 1983–1993 — Olympic business cycle), for Japan — from 1984 to 2004 (where 1983– 1993 — Olympic business cycle) etc. Years 1–5 and 16–20 are given just to understand the overall trend indicator.

Thus we can see that inflation significantly decreased during the Olympic business cycle (see Figure 10). This fact can be explained by the fact that in preparation for the Games the production of goods and services required for their organization drastically increased.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 14. Real wages indicators during Olympic business cycles in countries Which hosted Olympic Games in 1992–2008 (%, 1995=100%). Host country

Years 2000

2001

2002

2003

2004

2005

2006

France (Albertville 1992)

n/a

Norway (Lillehammer 1994)

n/a

USA (Atlanta 1996, Salt-Lake-City 2002)

112

114

n/a

Japan (Nagano 1998)

n/a

Australia (Sydney 2000)

110

n/a

110

n/a

110

n/a

Greece (Athens 2004)

n/a

Italy (Turin 2006)

n/a

China (Beijing 2008)

156

180

207

232

254

n/a

Canada (Vancouver 2010)

106

110

112

113

115

n/a

Source: Rosstat, 2007.

Table 15. Capital investments dynamic during the Olympic business cycles in countries which hosted Olympic Games in 1992–2014 (in constant prices,%, 1995=100%). Host country

Years 2000

2001

2002

2003

2004

2005

2006

France (Albertville 1992)

126

129

127

129

134

138

n/a

Norway (Lillehammer 1994)

131

130

129

140

155

n/a

USA (Atlanta 1996, Salt-Lake-City 2002)

146

144

139

143

152

161

n/a

Japan (Nagano 1998)

n/a

Australia (Sydney 2000)

121

133

152

164

174

189

n/a

Greece (Athens 2004)

n/a

Italy (Turin 2006)

119

122

127

125

127

126

n/a

China (Beijing 2008)

n/a

Canada (Vancouver 2010)

138

144

146

156

168

180

n/a

United Kingdom (London 2012)

135

139

144

153

158

n/a

Russia (Sochi 2014)

79,8

87,9

90,4

103,0

116,0

125,6

n/a

Source: Rosstat, 2007.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 10. Inflation dynamics during the Olympic business cycles in countries hosted Olympic Games in 1988–2006. Created: on the base of World Bank data.

It should be noted that the volume of production (expressed in value added as percent of GDP) reduced during the Olympic business cycles in host countries (see Figure 11). Demand is one of the key macroeconomic factors that affect economic growth. It includes the growth of consumer, investment and government spending and domestic and foreign investments to the economy. Dynamics of households final consumption expenditures in countries that host the Games in 1998–2010 years is shown in Table 16. Let us analyze the dynamics of foreign investments in countries, which organized the Olympiads or Olympic Winter Games from 1988 to 2006 (see Figure 13). For all countries a stable foreign investments took place on the eve of the start of Olympic business cycle. Their level of investments was almost the same — without fluctuations. For most countries (except Norway and Greece) foreign investment fluctuations and its gradual increase coincides with the start of the Olympic business cycle. In the second half of Olympic business cycle very high levels of investment were demonstrated in Australia, Italy and France. These examples suggest that the profitability of the Games largely depends on attracting funding for their private investors: the larger the share of private investments in Games financing, the greater possibility that the Games will pay off. The role of the state here is to create the institutional preconditions for attracting

private business to participate in the Games, as well as in macroeconomic management on various stages of the Olympic business cycle. Conversely, if the government pays more attention to externalities (improving the image of the state, creating the conditions for tourism development, raising the healthy generation) then the Games most often are unprofitable or barely recovered. However, it is important to note that situation could be radically opposite for the country’s economy: the more the state invests in the preparation of the Games (high share of the budget), the more likely that externalities (the main objective of the State) will be maximal, and during the Olympic business cycle and after the Games economic growth and GDP growth rate will be higher (see Figure 15) in comparison with the Olympic business cycles and the period after the elections in countries where funding has prevailed share of private capital (see Figure 14). The Figure 14a shows that Spain’s GDP growth rates (the share of public capital — 38%) were highest in the middle of the Olympic business cycle. After completion of the Olympic business cycle growth again increased, but did not reach the previous level. For Australia (share of public capital — 30%) growth rate during the Olympic business cycle were quite high — an average of 4% (14b). At the end of the Olympic business cycle growth rates have fallen down. This confirms the idea that for the host country the economy is influenced by the Games not so strongly,

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 11. Services dynamics (value added in% of GDP) during the Olympic business cycles in countries hosted Olympic Games in 1988â&#x20AC;&#x201C;2006. Created: on the base of World Bank data.

Figure 12. Rate of production (value added in% of GDP) during the Olympic business cycles in countries hosted Olympic Games in 1988â&#x20AC;&#x201C;2006. Created: on the base of World Bank data.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 16. Expenditures on final household consumption during the Olympic business cycles in countries which hosted Olympic Games in 1992–2010 (in constant prices,%, 1995=100%). Host country

2000

2001

2002

2003

2004

2005

2006

France (Albertville 1992)

114

117

119

122

125

128

130

Norway (Lillehammer 1994)

123

126

130

133

141

145

n/a

USA (Atlanta 1996, Salt-Lake-City 2002)

124

127

131

134

139

144

148

Japan (Nagano 1998)

104

106

107

109

112

n/a

Australia (Sydney 2000)

122

125

130

137

143

147

n/a

Greece (Athens 2004)

114

118

122

127

133

138

n/a

Italy (Turin 2006)

113

114

115

116

117

118

China (Beijing 2008)

n/a

Canada (Vancouver 2010)

119

122

126

130

134

139

145

Source: Rosstat, 2007.

Figure 13. Foreign investments during the Olympic business cycles in countries hosted Olympic Games in 1988–2006 (mln. $). Created: on the base of World Bank data.

and it is usually short-lived when a high share of private capital is taking place. In countries where the share of public capital has prevailed, the situation was different. The break-even point on the Games mostly was not achieved, but their influence for national economy was high and had

a long-term perspective. For example, high rates of Greece’s GDP growth were noted just at the beginning of the Olympic business cycle and continued after its completion. In China, where since the early 90-ies of the XX century the negative dynamics of the annual GDP growth

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 14. Spain’s (a) and Australia’s (b) GDP per capita and GDP growth in dynamics (1980–2006). Created by: World Bank, International Monetary Fund.

was observed, a positive trend of this indicator starts from the beginning of the Olympic business cycle (see Figure 15). It should also be noted that analysis of different models of administration and financing must also take into account the size of the economies themselves. This assumption can be considered by the example of the U.S. economy. Olympic Games of 1984 and 1996 in the United States had no noticeable ef-

fect on the economy in view of the fact that the ratio of the budget of the Games and the U.S. budget was too small. GDP per capita in the United States was growing steadily, but the GDP growth rates ranged (see Figure 16). Thus the effectiveness of the Olympic business cycle can be understood in two ways. On one hand, it is a direct return of costs of Games’ organizing and hosting. These conditions are good especially

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 15. Greeceâ&#x20AC;&#x2122;s (a) and Chinaâ&#x20AC;&#x2122;s (b) GDP per capita and GDP growth in dynamics (1980â&#x20AC;&#x201C;2006). Created by: World Bank, International Monetary Fund.

for private firms. On the other hand, effectiveness means that through the Games the preconditions for long-term and sustainable economic development were created. If the model of private administration and financing were used during the Games organizing the payback on the Games means a success for the organizers and investors. The citizens of the host country, with high probability, slightly feel the economic impact of this case. If the model of

public administration and financing was used then the budget of the Olympic Games for more than 2/3 was financed from public sources. This suggests that the state wants to use the Olympic games mainly as a way to improve infrastructure, to stimulate aggregate demand and improve the quality and living standard of people. Often these efforts cannot be fully reflected in the short run. They tend to have long-term effect.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 16. USA GDP per capita and GDP growth in dynamics (1980–2006). Created by: World Bank, International Monetary Fund.

6. CONCLUSION: THE PROBLEMS OF POLITICAL ECONOMY OF OLYMPIC GAMES DEVELOPMENT IN THE LIGHT OF CONSTITUTIONAL ECONOMY The analysis shows not only the advantages but also disadvantages of the Olympic movement. These deficiencies stem from the fact that the IOC is not always able to ensure efficient allocation and use of public resources. This is primarily due to the following factors: 1. Information asymmetry in decision-making process (the existence of special interest groups, an active lobby, a large bureaucracy). 2. Imperfection of the political process (lobbying, manipulation of votes due to the imperfections of the Rules, logrolling, the search for political rents, political-economic cycle, etc.). 3. Limited control over the bureaucracy. The rapid growth of the IOC apparatus creates new and emerging issues in this area. 4. Failure to fully provide for the IOC and to monitor the immediate and long-term consequences of its decisions. The fact that economic agents alter the meaning and direction taken by the IOC’s shares, leads to consequences, which may be different from the original goals. IOC activities aimed at correcting “failures” of the Olympic movement, in general, are far from perfect level. That is why it is necessary to strictly control the consequences of its activities and to adjust it depending on the socio-economic and political situation. One possible way to solve these problems is to increase the role of the Olympic Charter as social capital. Although

it has long existed, it is necessary to create effective enforcement measures to implement it.

REFERENCES 2010 Winter Olympic and Paralympic Games Report. Alesina A., Roubini N., Cohen G. D. (1997), Political Cycle ad Macroeconomy. Cambridge; L.: MIT Press. Andreff, W. (1986), Economie du sport / Wladimir Andreff, Jean-François Nys. — Paris:. Presses universitaires de France. Athens 2004 Report: Sponsorship Buchanan J. M. (2006), Limits of Liberty. Between Anarchy and Leviathan. 1987. Ch. 7. 2006 Marketing Fact File, IOC report Games of XXXI Olympiad 2016 Working Group Report, Lausanne, 2008 McRay C.D. (1977) A Political Model of the Business Cycle, Journal of Political Economy. Vol. 85. P. 239–263. Nordhaus, W. (1975), The Political Business Cycle, Review of Economic Studies. N42, P. 169–190. Olympic Charter (in force as from 7 July 2007), IOC Preuss, H. (2000), Economics of the Olympic Games. Hosting the Games 1972–2000. Sydney: Walla Walla Press in conjunction with the Centre for Olympic Studies, The University of New South Wales. Preuss, H. (2009), The Olympics. Handbook on the Economics of Sport. Edited by Wladimir Andreff abd Stefan Szymanski. Edward Elgar Publishing, UK, 2009 Fort, R.D. (2005), Sports Economics. — 2nd edition, Pearson Princess Hall. Schwarz E., Hunter J. (2008), Advanced Theory and Practice in Sport Marketing. First Edition. Elsevier Sochi 2014 Candidature File, Sochi, 2006 Sullivan, Arthur; Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River, New Jersey 07458: Pearson Prentice Hall.

Review of Business and Economics Studies

Volume 3, Number 1, 2015 Annex 1.

Olympic Bids Voting Results (1932â&#x20AC;&#x201C;2020) DATE

LOCATION AND SESSION

GAMES

07.09.2013

BuenosAires, Argentina

125 2020

06.07.2011

Durban, South Africa

123 2018

02.10.2009

07.04.2007

07.06.2005

07.02.2003

7/13/2001

Copenhagen, Denmark 121

Guatemala City, Guatemala

Singapore

Prague, Czech Republic

Moscow, Russia

119

117

115

112

2016

2014, Winter

2012

2010, Winter

2008

BID CITY (Winner in BOLD) Tokyo, Japan Istanbul, Turkey Madrid, Spain PyeongChang, South Korea Munich, Germany Annecy, France Rio-de-Janeiro, Brazil Madrid, Spain Tokyo, Japan Chicago, USA Doha, Qatar Prague, Czech Republic Baku (Azer) Sochi, Russia PyeongChang, South Korea Salzburg, Austria Almaty, Kazakhstan Borjomi, Georgia Jaca, Spain Sofia, Bulgaria London, United Kingdom Paris, France Madrid, Spain New York, USA Moscow, Russia Leipzig, Germany Rio de Janeiro, Brazil Istanbul, Turkey Havana, Cuba Vancouver, Canada PyeongChang, South Korea Salzburg, Austria Andorra la Vella, Andorra Berne, Switzerland Harbin, China Jaca, Spain Sarajevo, Bosnia-Herzegovina Beijing, China Candidature File Toronto, Canada Paris, France Istanbul, Turkey Osaka, Japan Bangkok, Thailand Cairo, Egypt Havana, Cuba Kuala Lumpur, Malaysia Seville, Spain

1st 42 26 26 63 25 7 26 28 22 18

2nd 49 45

34 36 25

51 47 -

22 21 20 19 15

27 25 32 16 -

40 51 16

56 53 -

44 20 15 17 6

56 22 18 9 -

46 29 20

Round 3rd 4th 60 36

5th

6th

66 32

39 33 31 -

54 50 -

Review of Business and Economics Studies

6/19/1999

09.05.1997

6/16/1995

9/23/1993

Seoul, South Korea 109

Lausanne, Switzerland

Budapest, Hungary

106

104

Monte-Carlo, Monaco 101

2006, Winter

2004

2002, Winter

2000

6/15/1991

Birmingham, United Kingdom

1998, Winter

9/18/1990

Tokyo, Japan

1996

9/15/1988

Seoul, South Korea

1994, Winter

Turin, Italy Sion, Switzerland Helsinki, Finland Klagenfurt, Austria Poprad-Tatry, Slovakia Zakopane, Poland Athens, Greece Rome, Italy Cape Town, South Africa Stockholm, Sweden Buenos Aires, Argentina Istanbul, Turkey Lille, France Rio de Janeiro, Brazil St. Petersburg, Russia San Juan, Puerto Rico Seville, Spain Salt Lake City, USA Ostersund, Sweden Sion, Switzerland Quebec City, Canada Graz, Austria Jaca, Spain Poprad-Tatry, Slovakia Sochi, Russia Tarvisio, Italy Sydney, Australia Beijing, China Manchester, United Kingdom Berlin, Germany Istanbul, Turkey Nagano, Japan Salt Lake City, USA Ostersund, Sweden Jaca, Spain Aosta, Italy Atlanta, USA Athens, Greece Toronto, Canada Melbourne, Australia Manchester, United Kingdom Belgrade, Yugoslavia Lillehammer, Norway Ostersund, Sweden Anchorage, USA Sofia, Bulgaria

Volume 3, Number 1, 2015 53 36 32 23 16 20 16

62 44

38 28 22 19 -

52 35 20 -

66 41 -

37 40 11 30 27 25 5 26 26 18 16 45 39 -

45 43 36 29 23 34 30 22 -

46 42 51 35 -

54 14 14 7

30 32 11 9 7 21 15 18 19 15 19 23 14 12 11 7 25 19 23 17

30 37 13 9 59

29 20 23 17 21 5 30 33 22 -

Review of Business and Economics Studies

1992

10/16/1986

Lausanne, Switzerland

1992, Winter 1988

9/30/1981

BadenBaden, West Germany

1988, Winter 1984

5/18/1978

Athens, Greece

1984, Winter

10/13/1974

Vienna, Austria

1980 1980, Winter

1976

05.12.1970

Amsterdam, Netherlands

1976, Winter

1972

4/25/1966

Rome, Italy

1972, Winter

1/28/1964

Innsbruck, Austria

1968, Winter

10/18/1963

BadenBaden, West Germany

1968

Volume 3, Number 1, 2015

Barcelona, Spain Paris, France Belgrade, Yugoslavia Brisbane, Australia Birmingham, United Kingdom Amsterdam, Netherlands Albertville, France Sofia, Bulgaria Falun, Sweden Lillehammer, Norway Cortina dâ&#x20AC;&#x2122;Ampezzo, Italy Anchorage, USA Berchtesgaden, West Germany Seoul, South Korea Nagoya, Japan Calgary, Canada Falun, Sweden Cortina dâ&#x20AC;&#x2122;Ampezzo, Italy Los Angeles, USA Sarajevo, Yugoslavia Sapporo, Japan Gothenburg, Sweden Moscow, USSR Los Angeles, USA

29 19 13 11 8 5 19 25 10 10 7 7 6 52 27 35 25 18 31 33 10 39 20

Lake Placid, USA Montreal, Canada Moscow, USSR Los Angeles, USA Denver, USA (Innsbruck Hosted) Sion, Switzerland Tampere, Finland Vancouver-Garibaldi, Canada Munich, Germany Detroit, USA Madrid, Spain Montreal, Canada Sapporo, Japan Banff, Canada Lahti, Finland Salt Lake City, USA Grenoble, France Calgary, Canada Lahti, Finland Sapporo, Japan Oslo, Norway Lake Placid, USA Mexico City, Mexico Detroit, USA Lyon, France Buenos Aires, Argentine

25 28 17 29 18 12 9 29 6 16 6 32 16 7 7 15 12 11 6 4 3 30 14 12 2

37 20 11 9 8 26 25 11 11 6 5 -

47 23 5 10 29 28 11 9 7 -

42 24 11 11 -

41 40

51 25 9 -

48 31 39 36 41 28 29 31 8 31 16 13

39 30 -

18 19 14 -

27 24 -

Review of Business and Economics Studies

1964

5/26/1959

Munich, Germany

6/15/1955

6/16/1955

1964, Winter

1960

Paris, France

1960, Winter

1956

4/28/1949

Rome, Italy

1956, Winter

1952

6/21/1947

Stockholm, Sweden

1952, Winter

Tokyo, Japan Detroit, USA Vienna, Austria Brussels, Belgium Innsbruck, Austria Calgary, Canada Lahti, Finland Rome, Italy Lausanne, Switzerland Brussels, Belgium Budapest, Hungary Detroit, USA Mexico City, Mexico Tokyo, Japan Squaw Valley, USA Innsbruck, Austria St. Moritz, Switzerland Garmisch-Partenkirchen, Germany Karachi, Pakistan Melbourne, Australia Buenos Aires, Argentina Mexico City, Mexico Chicago, USA Detroit, USA Los Angeles, USA Minneapolis, USA Philadelphia, USA San Francisco, USA Montreal, CAN Cortina dâ&#x20AC;&#x2122;Ampezzo, Italy Colorado Springs, USA Lake Placid, USA Montreal, Canada Helsinki, Finland Los Angeles, USA Minneapolis, USA Amsterdam, Netherlands Detroit, USA Chicago, USA Philadelphia, USA Athens, Greece Lausanne, Switzerland Stockholm, Sweden Oslo, Norway Cortina dâ&#x20AC;&#x2122;Ampezzo, Italy Lake Placid, USA

Volume 3, Number 1, 2015 34 10 9 5 49 9 0 15 14 6 8 6 6 4 30 24 3 5 0 14 9 9 1 2 5 1 1 0 0 31 2 1 7 14 4 4 3 2 1 0 0 0 0 18 9 1

26 21 1 11 32 30 18 12 3 4 4 -

15 5 5 3 -

35 24 -

19 13 4 5 -

21 20 -

Review of Business and Economics Studies

Volume 3, Number 1, 2015

London, UK

1948 (London selected without election after end of World War II) -

04.10.1929

Lausanne, Switzerland

Baltimore, USA Lausanne, Switzerland Los Angeles, USA Minneapolis, USA Philadelphia, USA Saint Moritz, Switzerland Lake Placid, USA London, UK

1948, Winter 1944 (Games Cancelled, World War II) Rome, Italy Detroit, USA Lausanne, Switzerland Athens, Greece Budapest, Hungary Helsinki, Finland Montreal, Canada 1944, Winter Cortina dâ&#x20AC;&#x2122;Ampezzo, Italy (Games Cancelled, World War II) Montreal, Canada Oslo, Norway Berlin, Germany Barcelona, Spain Alexandria, Egypt Budapest, Hungary Buenos Aires, Argentina Cologne, Germany Dublin, Ireland Frankfurt, Germany Helsinki, Finland Lausanne, Switzerland Nuremberg, Germany Rio de Janeiro, Brazil 1936, Summer Rome, Italy Garmisch-Partenkirchen, Germany Montreal, Canada 1936, Winter St. Moritz, Switzerland 1932, Summer Los Angeles, USA Lake Placid, USA Montreal, Canada Oslo, Norway Yosemite Valley, CA, USA Lake Tahoe, CA, USA Bear Mountain, NY, USA Duluth, MN, USA Minneapolis, MN, USA 1932, Winter Denver, CO, USA

2 1 0 0 0 0 16

12 2 43 16

Review of Business and Economics Studies

Volume 3, Number 1, 2015

The Phenomenon of National Development Bank: Theoretical Foundation and Effectiveness* Elizaveta SELYAVINA, Ph.D. candidate Financial University, Moscow; London School of Economics and Political Science; Department for Strategic Analysis and Research, Vnesheconombank, Russia selyavinaliza@gmail.com Abstract. Virtually every country has at least one institution regarded as a development bank. However, there is a marked gap in studies of development banks on national scale. Following this demand, the current paper aims to shed light on a phenomenon of national development banks. This article identifies theoretical roots of development bank’s existence and investigates its effectiveness. Based on the substantial amount of data observed we suggest an umbrella definition of a development bank. Further, we suggest relevant taxonomy to avoid potential misleading benchmarks. Descriptive statistics on macro-level of analysis demonstrates idiosyncratic nature of national development banks and its extreme heterogeneity. Constructed empirical model identifies general positive association between development bank’s foundation and national economic growth. Аннотация. Актуальность темы статьи обусловлена объективной необходимостью дальнейшего изучения феномена национального банка развития. В данной работе изучены теоретические аспекты существования банков развития и существующие подходы к оценке их эффективности. Основываясь на проведенном анализе, мы предлагаем «зонтичное» определение национального банка развития, а также подход к классификации банков развития, необходимый для проведения корректного внешнего бенчмаркинга. Представленная автором эмпирическая модель эффективности деятельности национальных банков развития документирует общую позитивную связь между их присутствием и экономическим ростом на национальном уровне. По результатам исследования сформулированы рекомендации по повышению эффективности деятельности национальных банков развития. Key words: Development bank, development theory, political theory, effectiveness, economic growth.

Virtually every country has at least one institution regarded as a development bank (DB). Its potential role in boosting economic growth and complementary domains of development is highlighted by the experts in development economics. At the same time, while the performance of global DBs, such as the World Bank Group’s institutions, European Investment Bank, African DB, Inter-American DB, is discussed in the literature (e. g. Alacevich, 2009; Massa, 2011), there is a marked gap in studies of DBs on national and regional scales. Yet, national DBs seem to perform highly successfully in last decades (Sanderson and Forsythe, 2013; Lazzarini et al., 2011) and therefore become a widely employed tool of policymakers in promotion development. Thus, after the global financial crisis there have been “calls to create a develop-

ment bank even in the United States” (Musacchio and Lazzarini, 2012: 15), while the new DB of BRICS countries1 was established just recently2. However, national DBs’ strategies and operational plans are often not upgraded in line with growth theory evolution, as well as DBs’ management is not aware of challenges, opportunities and progress, experienced by other DBs. In this vein, in the latest survey, experts of the World Bank underline that “despite its size and importance, little is known about DBs”, and acknowledge “an Although the New DB is not national per se, its mandate is grounded on cooperation of national DBs of the BRICS states. 2 The Economist (2014) The BRICS bank: An acronym with capital. Available at http://www.economist.com/news/finance-andeconomics/21607851-setting-up-rivals-imf-and-world-bank-easier-running-them-acronym [Accessed 25 July 2014].

* Феномен национального банка развития: теоретические аспекты и эффективность деятельности.

Review of Business and Economics Studies increasing number of requests for data and new studies about DBs’ (De Luna-Martinez and Vicente, 2012: 2). Following this demand, the current paper aims to shed light on a phenomenon of national DBs and their effectiveness in providing economic growth.

1. T H E O R E T I CA L F O U N DAT I O N Obviously, DBs reflect “their environment and their times” (Diamond, 1957: viii), particularly the fundamental attitude towards government presence in the economy. The latter always determines the rationale behind development banking. In this vein, theoretical roots of DB’s creation as well as of its critique could be found in two competing theories — “development” and “political” theory respectively. The concept of sustainable development and agency theory also provide valuable insights into the question. According to the development view, government’s participation is vital for economic growth, while one of its hybrid forms is DBs’ investments (Musacchio and Lazzarini, 2012). Indeed, economic theory provides a series of reasons that support the continuing need for DBs such as market failures, economies of scale, difference between economic and social benefits and risk aversion of the private sector. Thus, DBs aim at facilitating economic growth by investing in strategic longterm projects and balancing market failures by supporting underserved, infant industries, which often lead to social benefits (Gerschenkron, 1962; Stiglitz, 1994; Andrianova et al., 2009; Levy-Yeyati et al., 2004). In a similar spirit, social view is often identified as a supportive concept to the state presence in the economy (e. g. Körner and Schnabel, 2010). In fact, it seems to be part of the development approach, since lack of the socially desirable investments, in essence, is a market failure. Essential role of DBs is also underlined by proponents of sustainable development concept (e. g . Pezzey, 1992), according to which apart from conventional economic there are also social and environmental pillars of development. This triple bottom line approach highlights distinctive ability of DBs to address the sustainability challenge. Thus, Mazzucato (2013) points out that “wind, solar and biomass technologies have been the largest benefactors of development bank funding in recent years” 3 (ibid.: 139). Indeed, DBs’ contribution to 3 For instance, “approximately $40 billion has been provided be development banks between 2007 and 2010 in support of a variety of renewable energy projects” (Mazzucato, 2013: 139).

Volume 3, Number 1, 2015

“environmental, social, cultural or sport domains” of development (Schmit et al., 2011: 80) leads to the large positive externalities. However, there is an alternative approach — political view (Shleifer and Vishny, 1994; La Porta et al., 2002; Schleifer, 1998), according to which government intervention in the economy seeks political gains “in terms of electoral voting shares, political support” (Körner and Schnabel, 2010: 5) or opportunistic advantages of wealth accumulation, and can produce unintended distortions, limit intermediation, financial innovation and competition (Hart et al., 1997). In addition, “public banks are more prone to bureaucratisation, agency issues and poorer governance than their private counterparts” (Schmit et al., 2011: 33). Therefore, DBs, being one of the government instruments, are supposed to be biased in their investment decisions dictated by redistributive politics, and therefore be both inefficient and ineffective in allocation of resources, sometimes even harmful for economic growth. In this vein, agency theory should be stressed. As Körner and Schnabel (2010: 4) put it, “public banks may suffer from two principal-agent problems: first, between the politician and the bank manager, and second, between society (the taxpayer) and the politician”. While the former type of conflict is accelerated by soft budget constraints and might lead to the misguided and limited managerial incentives to be efficient, the latter is of special interest for the purpose of the current research. Thus, an effective DB allocates resources in consistence with its mission and interests of society (taxpayer), which can be in conflict with political interests and connections leading to the resource misallocation. In essence, this is the point made by the proponents of the political view. Finally, to avoid the binary thinking, in the literature there is an attempt to suggest synergetic and symbiotic forms of market and government coexistence (Stiglitz, 2013), since “the classical paradigms of social and economic development seem to have exhausted themselves” (Morgan, 1997: 491). It might seem that compilation of development and political views in integrated approach is hardly achievable since their different policy implications. However, in practice “in attempting to address the central problem from the perspective of one paradigm, they [government] made the problems under the others worse” (De la Torre and Ize, 2010: 110). From this eclectic perspective, a DB can be justified as an organizational innovation (Kane, 1975), an underestimated vehicle for com-

Figure 1. The taxonomy of DFI with the focus on DBs. Source: Authorâ&#x20AC;&#x2122;s compilation based on data described in the text.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Review of Business and Economics Studies

munication between government and private sector, an effective tool of coordination between topdown and bottom-up approaches of national and regional development. To shed light on this potential provider of development, we design a conceptual taxonomy for development institutions and highlight the role of DBs with its further stratification, which is essential for generating the research population.

directly or, being a second-tier institution, provide target-oriented resources to the first-tier banks. Worth noting, that the rationale behind their establishment also varies: from the post-war economic restructuring via infrastructure investment to financing the most innovative high-risk firms and activities (Bruck, 1998). We think that careful taxonomy of DFI, particularly DBs, is essential for accurate assessment of their effectiveness. Otherwise, benchmarking of different DBs and further generalization of research findings are prone to misleading conclusions.

2. TAXO N O M Y D E S I G N As Diamond (1957: ix) put it, “development banks cannot be fruitfully discussed in isolation from the many other institutions and factors related to economic development”. However, for the best of our knowledge, no studies on development financial institutions (DFI) have brought them together in the conceptual paradigm. Consequently, in the relevant literature one can find controversial treatment of DBs: for instance, World Bank’s economists (De Luna-Martinez and Vicente, 2012: 7) refer to the study on Fannie Mae and Freddie Mac (Acharya, 2011) as an example of DB’s failure. Fragile boundaries between pivotal and complementary DFI lead to the complaints about public ownership structure: “the privatization of profits (for the shareholders and executives) in good times but the socialization of downside risk (for the taxpayer)” (ibid.: 5). However, while this argument is applicable to the complementary DFI such as housing finance providers, it is not consistent with DBs’ fundamental nature, according to which profits go to the special development funds rather than privatized by executives. In this vein, it is essential to distinguish pivotal DFI from complementary ones (Figure 1). At the same time, complementary DFI are present in our taxonomy, since they can provide innovative solutions to development issues. For instance, in case of insurance companies “use of catastrophe insurance might be able to diversify the weather related risk towards other investors and facilitate the interest of commercial banks in lending to farmers” (Rudolph, 2009: 5). Based on empirical observations, we suggest to classify DBs according to their legal status, strategic priorities, scope of mandate, ownership structure and territorial scale. Besides, DBs use dissimilar financial instruments in their operational activities: long-term and short-term loans, syndicated loans, bonds or other securities, stakes (shares, stock), guarantees, public-private partnerships, etc. Technically, a DB may invest in projects

Volume 3, Number 1, 2015

3. W H AT I S A D E V E LO P M E N T B A N K?4 In essence, previous literature on DBs is thin and mostly limited to descriptive reports. To our knowledge, there is no one clear-cut definition of a DB. Thus, the Latin American Association of Development Financial Institutions for the purpose of identification a DB as its member uses the selfdefinition selection principle, since “it is difficult to define whether an institution is a development bank or not” (Levy-Yeyati et al., 2004: 17). Based on the reviewed literature, we suggest the following umbrella definition of a DB (Appendix 1): a financial institution often controlled by the public sector and operated under special legal mandate, offering long-term lending to the bankable economic development projects 5 in line with broadbased development support aimed at achieving socioeconomic goals in a country, region, sector or particular market segment. It should be borne in mind that strategic vision of DBs is to be complementary to private banks meaning not to create market distortions (Rudolph, 2009). In addition, one should be careful in description of DB’s functions. For instance, during recent global financial crisis, most DBs successfully participated in the federal governments’ anti-cyclical efforts (De Luna-Martinez and Vicente, 2012). However, this function is supportive and can be treated just as an additional rationale for DBs’ existence (Levy-Yeyati et al., 2004), since monetary policy is generally the object of central banks’ mandate. As we noticed, in relation to DBs economists determine two main functional directions: investment in long-term costly projects, Thereafter, we mean national DB. Bankable development projects both have a positive development impact (first developmental criteria) and are expected to be fully repaid according to a pre-determined schedule (second banking criteria) (Kane, 1975).

Review of Business and Economics Studies which bring economic growth under condition of underfinance by market, and bridging the gaps of market failures. While the former function is well understandable — “investment is essential to the process of development” (Diamond, 1957: 7), the latter requires additional discussion. De la Torre and Ize (2010) link market failures to several types of frictions. Thus, the asymmetric information and control gap — principal-agent issue — includes market failures of adverse selection of a contract, moral hazard and shirking during the contract implementation and false reporting afterwards, while interaction between the individual and the group may suffer from externalities, free riding and coordination failures. However, mentioned market failures are not idiosyncratic features of market. Instead, in practice it is highly feasible to diagnose them in DB’s activity as well 6. In this vein, Rudolph (2009) finds typical market failures that a DB is supposed to offset in high-risk segment of SME, while Levy-Yeyati et al., (2004: 12) underline “agriculture (plagued by asymmetric information and aggregated shocks), R&D-intensive sectors like the pharmaceutical industry (with a large share of intangible assets and potentially large spillovers), or capital-intensive industries with long start-up periods involving negative cash flow (such as the aerospace industry)”. Therefore, in the discussion of market failures, which a DB is supposed to mitigate, one should think about strategic sectors rather than traditional market failures cited in economic literature. Moreover, in accordance with such approach market failures become dynamic and time- and context-dependent. In addition, if a DB targets non-profitable sector, it becomes “an institution that only leverages the subsidies from the government” (Rudolph, 2009: 6). Since such situation is common for DBs, issue of their effectiveness receives a central place not “to end up with losses and frequent recapitalizations” (ibid.: 6) or, at least, to justify them.

Volume 3, Number 1, 2015

fundamental arguments applied to the effectiveness (and efficiency) of public banks in general and DBs in particular. Based on that, we divide literature related to the DB’s effectiveness into three grand categories. The first strand of the literature fundamentally supports political view in line with its agency theory implications. Generally, scholars create empirical models to compare private banks with public banks, including DBs, and demonstrate that the latter are detrimental to economic growth in terms of growth-promoting ineffectiveness on the macrolevel or their internal inefficiency on the micro-level. Thus, La Porta et al. (2002) in their influential paper run ordinary least squares regressions on a large cross-country sample and find that the share of government ownership of banks in 1970 is negatively correlated with annual growth rate of GDP per capita for 1960 to 1995, controlling for standard determinants of growth. Authors document ineffectiveness of public banks on the macro-level. Following these findings, the World Bank’s economist Hanson (2004) suggests that less growth at the macroeconomic level reflects the lower efficiency of state-owned banks on the micro-level. Indeed, the latter are often characterized by large non-performing loans (Hanson, 2004), overhead costs to bank assets and high spread between the lending and the borrowing rates (La Porta et al., 2002), negative operating income (Dinc, 2005), and low level of financial development (Barth et al., 2000). The main explanations of public banks’ low efficiency are grounded on political considerations. Thus, Dinc (2005) complements findings of La Porta et al. (2002) by examining individual bank data with different ownership structure in 22 emerging countries of the 1990s and providing empirical evidence that government-owned banks increase their lending in election years relative to the private banks. Sapienza (2004) analyses the panel data on credit relations of over than 37 000 Italian firms with state- and privatelyowned banks and finds out that “party affiliation of state-owned banks’ chairpersons does have a 4. E F F E CT I V E N E S S O F D E V E LO P M E N T positive impact on the interest rate discount givB A N K S: D I F F E R E N T A P P ROAC H E S en by state-owned banks in the provinces where Since DB is a state-owned bank, most papers on the associated party is stronger” (ibid.: 24). In a the effectiveness of government presence in the similar spirit, Khawaja and Mian (2005) document banking sector include DBs in the object of re- that in Pakistan politically connected firms get search. We believe that for the purpose of current the preferential corporate lending form the statethesis this approach is relevant due to the same owned banks. In essence, above-discussed papers, directly or indirectly, support political view’s arguments and advocate for the state-owned banks’ 6 The extensive discussion of market failures one can find in Stiglitz (1994). privatization.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 1. DBs sample, by income group and region*. Income group

DBs

Region DBs

High income: non-OECD High income: OECD Low income Lower middle income Upper middle income ∑

9 9 11 29 38 96

East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa North America South Asia Sub-Saharan Africa ∑

22 20 26 4 1 9 14 96

Source: Author’s analysis based on data described in the text. * Classification according to the World Bank.

The second set of studies is more careful in generalizations. Thus, Andrianova et al. (2009) challenge findings of La Porta et al. (2002) by running the same regression but extending the set of conditioning variables to include omitted ones — institutional growth determinants (e. g. Hall and Jones, 1999). At this stage, “the coefficient of government ownership of banks becomes insignificant as soon as one such variable is introduced” (Andrianova et al., 2009: 2). Further, they test crosscountry regression based on more recent datasets and document that during 1995–2007 government ownership of banks has been associated with faster long-run growth. Most importantly, authors pointed out the necessity to interpret such results with caution, since found relationship might be heterogeneous across countries. In this vein, Körner and Schnabel (2010) analyse the nexus between public ownership in the banking sector and economic growth and find heterogeneity pattern: in countries with high level of financial development and high-quality political institutions they document public banks’ positive effects on economic growth. Beck and Levine (2002) in their analysis of cross-country industry-level data for 39 countries also do not find clear-cut support for either development or political views: in their model financial structure does not help to explain “industrial growth patterns or the efficiency of capital allocation” (ibid.: 32). Rather, high level of financial development in line with efficient legal system determines the coherence of investment flows across industries, which is again in support of the heterogeneity hypothesis. The heterogeneous results have been also obtained in the micro-level studies aimed at banking efficiency evaluation. Thus, Micco et al. (2007) analyse bank-level annual financial information for 179 countries during 1995–2002 and conclude that state-owned banks are not necessarily less profitable than private ones: this is the case only in developing countries, while in industrial countries

such correlation is not present. In this vein, Altunbas et al. (2001: 950) estimate relative cost-profit efficiency of German banks with different ownership structure and find that “public and mutual banks have slight cost and profit advantages over their private commercial banking counterparts”. In fact, after considering results of above-discussed papers from the first category of the literature before their concluding generalizations, it becomes evident that they are in line with obtained heterogeneous results for developing and developed countries (e. g. La Porta et al., 2002: 291, Table VIII). In this vein, we find heterogeneous hypothesis to be plausible, since principal-agent problems are significantly limited in the developed countries, “where the politicians’ actions are controlled by the public and their exercise of power is constrained to their political mandate” (Körner and Schnabel, 2010: 5). Taking into account the heterogeneity of DBs, the third stream of the literature investigates their performance and effectiveness by means of case studies on individual DBs, which often represent best practice in development banking. For instance, performance of Canada’s Business DB, Chile’s BancoEstado, South Africa’s DB of Southern Africa, Finland’s Finnvera plc. (Rudolph, 2009), Brazil’s DB BNDES 7 (Lazzarini et al., 2011), and China’s DB (Sanderson and Forsythe, 2013) for different reasons is regarded as effective. Based on good practices, scholars justify DB’s presence and demonstrate its great potential in solving market failures, supporting strategic sectors, and providing economic growth at different scale and scope. According to this approach, above-mentioned issues of public banks’ underperformance can be solved under certain conditions: clearly defined mission (Schmit et al., 2011; Levy-Yeyati et al., 2004), sus7 Interestingly, in case of BNDES Lazzarini et al. (2011) document an increasing lending for politically connected firms. However, they argue that this pattern is not detrimental for the bank’s effectiveness, since these firms bring “good” projects.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 2. Descriptive statistics of efficiency indicators for 88 DBs, 2006–2009. Variable

Obs

Mean

Std. Dev.

Min

Max

ROA06

1.067623

5.279757

-29.31

18.48

ROA07

.9266683

7.360992

-60.09

14.22225

ROA08

1.388473

2.69748

-6.9564

13.56793

ROA09

1.034896

3.12639

-17

ROE06

5.927629

13.35411

-42.35

47.85

ROE07

7.341995

10.06996

-19.9

39.29335

ROE08

5.888734

16.92058

-85.165

50.45663

ROE09

5.464588

16.41031

-65.02

63.45

NPL06

14.43685

24.04769

100

NPL07

13.16465

22.1068

100

NPL08

14.33244

21.8702

NPL09

14.8164

23.79413

120.61

Source: Author’s analysis based on data described in the text.

Figure 2. ROA in DBs and private banks, 2008. Source: Author’s analysis based on IMF data.

tainable self-financed mandate with target sectors, and clear-cut minimum criteria of efficiency, high quality management, sound institutional environment and transparent ownership policy (Scott, 2007). To sum up, there is no a clear-cut DB’s effectiveness valuation system. However, one essential thing to acknowledge is that DBs endeavour to achieve effectiveness rather than efficiency. Effectiveness demonstrates how well a DB fulfils its mandate with less weight to comparison its profits with costs. Interestingly, Levy-Yeyati et al. (2004)

consider a profitable DB as ineffective, since costsaving actions aimed at increasing operational efficiency in some cases reduce long-term development impact of a DB leading to the decreasing of its effectiveness. In a similar spirit, Tirole (1994: 1) points out that “incentives based on measurable goals must be limited to not completely jeopardize the non-measurable dimensions of social welfare”. To address that potential trade-off between internal efficiency and effectiveness, DBs are generally required to support so-called “bankable development projects” and at least to break even, “allow-

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 3. ROE in DBs and private banks, 2008. Source: Author’s analysis based on IMF data.

Figure 4. NPL in DBs and private banks, 2008. Source: Author’s analysis based on IMF data.

ing that bad-debt losses on some projects will be offset by higher returns from others” (Kane, 1975: 18). Yet, “only few institutions […] are in the process of developing a number of indicators/proxies to measure their special contribution dictated by their mandate”, while currently in most cases DB’s effectiveness is measured by comparing its “achievements against predetermined (but arbitrary) targets”(Rudolph, 2009: 20). Such a proxy of effectiveness seems to be questionable, since self-determination of key performance indicators is prone to unfair target setting. In addition, these

indicators do not offer insights whether there is any value added from DB’s existence. Therefore, an empirical examination of national DB’s effectiveness is required.

5. R E S E A RC H D E S I G N First, we analyse the collected quantitative primary and secondary data on more than 90 national DBs by means of descriptive statistics. Further, following the methodology of Wacziarg and Welch (2007) in their study of trade liberalization effect

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 5. Sample means for growth before and after DB' foundation. Source: Author’s analysis based on data described in the text.

on growth, we compare the sample means of economic growth on macro-level for 50 DBs in preand post-DB periods. Data. Our analysis is based on the unique dataset on 96 national DBs of 65 countries (Appendix 2) from different income group and regions (Table 1). The data on 88 DBs is based on the survey conducted by De Luna-Martínez and Vicente (2012) on behalf of the World Bank, results of which was kindly shared with me. In section 6.2 we add in the model additional independently collected data on 8 national DBs. Assumptions. One should notice an assumption that referred to the conceptual framework used in the paper. Thus, GDP, being a quantitative measure, only partly reflects the level of development. As we noticed in section 1, sustainable development concept in line with economic growth incorporates environmental and social outcomes in an integrated system of DBs’ effectiveness, which quantification is a tricky task (Slaper and Hall, 2011). Although we recognize the importance of these perspectives, in the current paper we restrict our discussion of sustainable development concept and focus on analytically rigorous economic growth as a proxy of development. In the following section, we investigate empirically existing approaches to the effectiveness of national DBs.

6. E M P I R I CA L F I N D I N G S O N N AT I O N A L S CA L E 6.1. LOW E F F I C I E N CY O F D E V E LO P M E N T B A N K S: E V I D E N C E? Banking efficiency is measured, among others, by profitability indicators of return on assets (ROA), return on equity (ROE), and non-performing loans (NPL) ratio (e. g. Lin and Zhang, 2009). The descriptive statistics of panel dataset of 88 national DBs (Table 2) shows comparable with private banks average earnings power of DBs (ROA), while ROE and NPL ratio are lower than those of private banks (IMF data)8. These results are consistent with theoretical mission of a DB to trigger socioeconomic development rather than generate profit, as well as with previous empirical studies on dichotomy between public and private banks. However, average results may mask significant deviations of indicators, wherefore we need to look at DBs’ efficiency more specifically. In this vein, we identify countries, for which data on efficiency is available for both national DBs and private banks for the same time period 9 . A brief 8 IMF (2014). Financial Soundness Indicators. Available at http:// elibrary-data.imf.org [Accessed 20 August 2014]. 9 There are several national DBs from India and Germany that participated in the survey: indicators for these two countries are averaged.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 6. DBs’ asset size, 2009. Source: Author’s analysis based on data described in the text.

Figure 7. ROA in Indian national DBs. Source: Author’s analysis based on data described in the text.

snapshot of six countries’ banking sectors demonstrates that DBs’ efficiency is somewhat irrelevant to generalization. It is clear from Figures 2–4 that under similar macroeconomic conditions DBs can be either more or less efficient than national private banking sector. Therefore, our analysis of DBs’ efficiency does not provide evidence on their clear-cut lower efficiency in comparison with private banks. We find lack of any systematic relationship between DBs and private banks to be indicative of the fundamental difference between these financial institutions. Consequently, comparison between

them tends to be misleading. In essence, it seems that DBs to a greater extent are about development, rather than banking. Hence, as discussed above, criterion for their effectiveness evaluation should be linked with its mission of promoting economic growth. 6.2. E F F E CT I V E N E S S AT A G L A N C E In this vein, we aim to identify the changes in national growth rate associated with foundation of a national DB. For that purpose, a panel data is constructed, which shows foundation years for the sample of 50 DBs in line with corresponding national

Review of Business and Economics Studies

GDP growth for 8-year period before and after the year of each DB’s creation 10 (Appendix 3). Further, simple means of growth rates are taken for each year in period T — 8 to T + 8. Figure 5 displays the results. Firstly, before DB’s creation some downward trends are documented. This can be explained by the fact that DBs are often created in time of economic crises or other depressing factors. Secondly and most importantly, one can observe an increase of average growth rate from 3.6 percent in pre-DB period to 4.4 percent in post-DB span. Notice that there results are obtained without controlling for any fixed effects. Evidently, generalization about the factors that may explain this slight increase of growth rates is difficult to draw. Although this exercise sheds some light on the effectiveness of DBs on national scale, the growth difference does not seem to be sustained. In addition, foundation of a DB is often complemented by a set of reforms, which effect on growth is difficult to disentangle. Besides, as we already mentioned, different macroeconomic and institutional environment is likely to cause significant deviations from average DB’s effectiveness.

foundation. However, it seems that such binary judgement overlooks non-linear character of development process. Hence, we find eclectic approach based on synergetic state-market collaboration to be the most fruitful. In this vein, we do not expect markets to promote sustainable development themselves and treat a DB as a by-product of cross-fertilisation between development and political views, which is able to be an effective tool of intelligent government intervention aimed at providing economic growth and mitigating market failures. Further, reflecting diagnosed fundamental heterogeneity of national DBs, we suggest the taxonomy to avoid potential misleading benchmarks. Our analysis puts forward several considerations. • Efficiency evaluation of a DB (financial and operational performance) should be explicitly recognized as a discrete exercise from effectiveness measurement (development impact). • General positive association between DB’s foundation and national economic growth is documented on the sample of 50 DBs. • Descriptive statistics on macro-level of analysis demonstrates idiosyncratic nature of national DBs: substantial variation among national DBs in our sample indicates that effectiveness of a DB is also a diverse category conditioned by individual DB’s and territory-specific characteristics. Therefore, it is essential to allow for the heterogeneity between and within countries. Ex-ante diagnosis of the territorial pattern and specific market gaps is crucial to “understand the main obstacles to productive investment” (Diamond, 1957: 18). A model of national DB therefore is expected to be flexible in order to tailor the specific requirements. Based on that, we think that an increase of DBs’ effectiveness requires improvements in traditional approach to its valuation system, since there are a number of alternative substitutes for the national DB and therefore its foundation has a certain opportunity cost. As we noted above, there is a possibility that economic growth evaluation cannot capture the contribution of a national DB in a development process. In this vein, design of special indicators to quantify environmental and social outcomes might be a gainful recommendation. The experience of global DFI in implementation of costbenefit analysis is likely to be a sound basis for such improvements (e. g. Asian Development Bank, 2013). However, to get a more complete picture a further research on the topic is required. To avoid misleading generalizations and not to conclude with insufficient “one-size-fits-all” recommendations (Barca, 2009), it might be fruitful to con-

6.3. I T’S H E T E RO G E N E I TY, S T U P I D! Difficulties in assignment of national growth purely to the DB’s activity also proved by the findings that DBs is an extremely heterogeneous family. Thus, although DBs are relatively congruent in ownership structure — mostly state-owned, they demonstrate extreme diversity in terms of size, resources of funding, business products provided, strategic sectors and market segments served. For instance, Figure 6 illustrates deviation of assets level from the sample average. Interestingly, many indicators vary significantly even if compared DBs are located in the same country — for instance, Figure 7 highlights heterogeneity of Indian DBs. Further visual elaboration on heterogeneous characteristics of national DBs can be found in Appendix 4.

7. CO N C L U D I N G R E M A R K S A N D PO L I CY R E CO M M E N DAT I O N S To sum up, we demonstrate the existence of reasonable arguments — both pros and cons DB’s Since the World Bank data on annual GDP growth rates is available only for the post-1960 period, the time span is reduced to 8 years before and after DB’s foundation, while research sample of DBs diminishes to 50 DBs, which are founded, consequently, after 1968. 10

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

duct additional qualitative bottom-up analysis of meso-level “untraded interdependencies” (Storper, 1995), putting the region at the centre of development efforts (Morgan, 1997). It might be a valuable contribution to the debate on national DB’s effectiveness.

Hanson, J. (2004). The transformation of State-Owned Banks, in

REFERENCES

Kane, J. (1975). Development Banking. Lexington, United States:

Acharya, V. (2011). Guaranteed to fail Fannie Mae, Freddie Mac,

Khwaja, A. and Mian, A. (2005). Do Lenders Favor Politically Con-

Caprio, G., Fiechter, L., Litan, R., and Pomerleano, M. (eds.) The Future of State-Owned Financial Institutions. Washington, D.C.: Brookings Institution Press. Hart, O., Shleifer, A. and Vishny, R. (1997). The Proper Scope of Government: Theory and Application to Prisons, Quarterly Journal of Economics, 112 (4): 1127–61. Lexington Books.

and the debacle of mortgage finance. Princeton, N.J.; Wood-

nected Firms? Rent Provision in an Emerging Financial Market,

stock: Princeton University Press.

The Quarterly Journal of Economics, (4): 1371–11.

Alacevich, M. (2009). The World Bank’s Early Reflections on De-

Körner, T. and Schnabel, I. (2010) Public Ownership of Banks and

velopment: A Development Institution or a Bank? Review of Po-

Economic Growth — The Role of Heterogeneity. Working Paper

litical Economy, 21 (2): 227–44.

41. Series of the Max Planck Institute for Research on Col-

Altunbas, Y., Evans, L., and Molyneux, P. (2001). Bank ownership and efficiency, Journal of Money, Credit and Banking, 33 (4): 926–54. Andrianova, S., Demetriades, P., and Shortland, A. (2009). Is Government Ownership of Banks Really Harmful to Growth.

lective Goods. La Porta, R., Lopez-de-Silanes, F. and Shleifer, A. (2002). Government Ownership of Banks, The Journal of Finance 57 (1): 265–301. Lazzarini, S., Musacchio, A., Bandeira-De-Mello, R. and Marcon,

CEDI Discussion Paper Series 09–05. Centre for Economic

R. (2011). What do development banks do? Evidence from Brazil,

Development and Institutions (CEDI): Brunel University.

2002–2009. Harvard Business School Working Paper 12–047.

Asian Development Bank (2013). Cost-benefit analysis for de-

Levy-Yeyati, E., Micco, A. and Panizza, U. (2004). Should the

velopment: A practical guide. Mandaluyong City, Philippines:

Government be in the Banking Business? The Role of State-

Asian Development Bank.

Owned and Development Banks, Working Paper 517. Washing-

Barca, F. (2009). An Agenda for a Reformed Cohesion Policy: A Place-Based Approach to Meeting European Union Challenges

ton, DC: Inter-American Development Bank. Lin, X. and Zhang, Y. (2009). Bank ownership reform and bank

and Expectations. Independent report prepared at the request

performance in China, Journal of Banking and Finance, (1): 20–9.

of Danuta Hübner, European Commissioner for Regional Pol-

Massa, I. (2011). Impact of multilateral development finance in-

icy. Brussels: European Commission. Barth, J., Caprio Jr., G. and Levine, R. (2000). Banking systems around the globe: Do regulation and ownership affect performance and stability? Washington, DC: World Bank, Development Research Group, Finance. Beck, T. and Levine, R. (2002). Industry growth and capital allocation: Does having a market- or bank-based system matter? Journal of Financial Economics, 2: 147–80. Bruck, N. (1998). The role of development banks in the TwentyFirst Century, Journal of Emerging Markets 3: 39–67. De La Torre, A. and Ize, A. (2010). Regulatory Reform: Integrating Paradigms, International Finance, (1): 109–39. De Luna-Martínez, J. and Vicente, C.L. (2012). Global Survey of

stitutions on economic growth. London: Overseas Development Institute. Mazzucato, M. (2013). The entrepreneurial state: debunking public vs. private sector myths. London: Anthem Press. Micco, A., Panizza, U. and Yanez, M. (2007). Bank ownership and performance. Does politics matter? Journal of Banking & Finance, 31 (1): 219–41. Morgan, K. (1997). The Learning Region: Institutions, Innovation and Regional Renewal, Regional Studies, 31 (5): 491–503. Morgan, K. (1997). The Learning Region: Institutions, Innovation and Regional Renewal, Regional Studies, 31 (5): 491–503. Musacchio, A. and Lazzarini, S. (2012). Leviathan in Business: Varieties of State Capitalism and their Implications for Eco-

Development Banks, Policy and Research Series 5969. Wash-

nomic Performance. Harvard Business School Working Paper

ington, DC: World Bank.

12–108.

Diamond, W. (1957). Development banks. Baltimore, MD: Johns Hopkins Press.

Pezzey, J. (1992). Sustainable development concepts: An economic analysis. Washington, D.C: World Bank.

Dinc, S. (2005). Politicians and Banks: Political Influences on

Rudolph, H. (2009). State Financial Institutions: Mandates, Gov-

Government-Owned Banks in Emerging Markets, Journal of

ernance, and Beyond, Policy and Research Series 51419. Wash-

Financial Economics, 77: 453–79. Gerschenkron, A. (1962). Economic Backwardness in Historical Perspective. Cambridge, MA: Harvard University Press. Hall, R.E. and Jones, C. (1999). Why Do Some Countries Produce So Much More Output per Worker than Others? Quarterly Journal of Economics, 114 (1): 83–116.

ington, DC: World Bank. Sanderson, H. and Forsythe, M. (2013). China’s Superbank. Debt, Oil and Influence — How China Development Bank is Rewriting the rules of Finance. Singapore: Bloomberg Press. Sapienza, P. (2004). The effects of government ownership on bank lending, Journal of Financial Economics, 72 (2): 357–84.

Review of Business and Economics Studies

Schleifer, A. (1998). State versus Private Ownership, Journal of

Stiglitz, J. (2013). Globalization and the economic role of the

Economic Perspectives, 12 (4): 133–50. Schmit, M., Gheeraert, L., Denuit, T. and Warny, C. (2011). Public Financial Institutions in Europe. Brussels: European Association of Public Banks. Scott, D. (2007). Strengthening the Governance and Performance of State-Owned Financial Institutions. Policy Research Working Paper 4321. Washington, DC: World Bank. Shleifer, A. and Vishny, R. (1994). Politicians and Firms. The Quarterly Journal of Economics, (4): 995–1025. Slaper, T.F. and Hall, T.J. (2011). The Triple Bottom Line: What Is It and How Does It Work? Indiana Business Review, 86 (1): 4–8. Stiglitz, J. (1994). The Role Of The State In Financial Markets, in

Volume 3, Number 1, 2015

state in the new millennium, Industrial and Corporate Change, 12 (1): 3–26. Storper, M. (1995). The Resurgence of Regional Economics, Ten Years Later: the Region as a Nexus of Untraded Interdependencies, European Urban and Regional Studies, 2: 191–221. Tirole, J. (1994). The Internal Organization of Governments, Oxford Economic Papers, 46: 1–29. United Nations (2005). Rethinking the Role of National Development Banks. Background document prepared for the Ad Hoc Expert Group Meeting. New York: United Nations, Department of Economic and Social Affairs. Wacziarg, R. and Welch, K.H. (2007). Trade Liberalization and

Proceedings of the World Bank Annual Conference on Eco-

Growth: New Evidence, The World Bank Economic Review, 22

nomic Development (1993). Washington, DC: The World Bank.

(2): 187–231.

Appendices Appendix 1: Review of “Development Bank” definitions. Development Bank is…

Reference

A financial institution devoted primarily to stimulating the private sector of the economy.

Diamond, 1957: 4

A financial intermediary supplying long-term funds to bankable economic development projects and providing related services.

Kane, 1975: 14

A specialized financial institution with functions and operations that can be defined with regard to its hybrid financial development character. An institutional instrument of public policy whose performance is measured mote in terms of social benefits […]

Bruck, 1998: 62

A financial institution that is primarily concerned with offering long-term capital finance to projects that are deemed to generate positive externalities and hence would be underfinanced by private creditors.

Levy-Yeyati et al., 2004:16

A financial institutions set up to foster economic development, often taking into account objectives of social development and regional integration, mainly by providing long-term financing to, or facilitating the financing of, projects generating positive externalities.

United Nations, 2005:10

A non-monetary financial institution controlled by the public sector that is primarily active in equity participations and bond issue subscriptions and awards long-term loans (that are beyond other financial institutions’ capability or willingness to provide) in a bid to further national and regional development.

Schmit, 2011: 38 (based on the OECD and IMF definition)

A bank or financial institution with at least 30 percent state-owned equity that has been given an explicit legal mandate to reach socioeconomic goals in a region, sector or particular market segment.

De Luna-Martinez and Vicente, 2012: 4

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Appendix 2: List of observed national development banks. Region

Country

East Asia & Pacific

Cambodia

Rural Development Bank

China

China Development Bank

Fiji

Fiji Development Bank

Malaysia

Bank Pembangunan Malaysia Berhad

Malaysia

Bank Perusahaan Kecil & Sederhana Malaysia Berhad

Malaysia

Credit Guarantee Corporation Malaysia Berhad

Malaysia

Sabah Credit Corporation

Micronesia, Fed. Sts.

FSM Development Bank

Mongolia

The Microfinance Development Fund

Palau

National Development Bank of Palau

Philippines

Al-Amanah Islamic Investment Bank of the Philippines

Philippines

Development Bank of the Philippines

Philippines

Philippine Postal Savings Bank, Inc.

Philippines

Philippine Export-Import Credit Agency

Philippines

Land Bank of the Philippines

Samoa

Development Bank of Samoa

Samoa

Samoa Housing Corporation

Thailand

Small and Medium Enterprise Development Bank of Thailand

Tonga

Tonga Development Bank

Vanuatu

Vanuatu Agriculture Development Bank

Vietnam

Vietnam Bank for Social Policies (VBSP)

Bulgaria

Bulgarian Development Bank AD

Croatia

Croatian Bank for Reconstruction and Development (HBOR)

Cyprus

TRNC Development Bank

Finland

Finnvera plc

Germany

Thüringer Aufbaubank (TAB)

Germany

North Rhine-Westphalia (NRW Bank)

Germany

Kreditanstalt für Wiederaufbau (KfW) Development Bank

Hungary

Hungarian Export Import Bank Private Company Limited

Latvia

Mortgage and Land Bank of Latvia

Norway

KBN Kommunalbanken Norway

Poland

Bank Gospodarstwa Krajowego (BGK)

Slovak Republic

Slovak Guarantee and Development Bank

Slovenia

Slovene Export and Development Bank

Turkey

Export Credit Bank of Turkey (Türk Eximbank)

Turkey

T.C. Ziraat Bankası A. Ş.

Turkey

Development Bank of TURKEY

Europe & Central Asia

Name of institution

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Region

Country

Latin America & Caribbean

Antigua and Barbuda

Antigua & Barbuda Development Bank

Bolivia

Banco de Desarrollo Productivo (BDP)

Brazil

Banco Nacional de Desenvolvimento Econômico e Social (BNDES)

Brazil

Banco Da Amazonia (BASA)

Brazil

Banco Do Nordeste DO Brasil

Colombia

Banco De Comercio Exterior de Colombia

Colombia

Fondo Para El Financiamiento del Sector Agropecuario (FINAGRO)

Costa Rica

Banco Nacional de Costa Rica (Bncr)

Curacao

Curacao Development Corporation (Korpodeko)

Dominican Republic

Banco De Reservas De La Republica Dominicana

Ecuador

Banco del Estado (BEDE)

Ecuador

Banco Ecuatoriano de la Vivienda (BEV)

Ecuador

Corporacion Financiera Nacional del Ecuador (CFN)

Guatemala

El Crédito Hipotecario Nacional de Guatemala

Mexico

Banco Nacional de Obras y Servicios Públicos, S.N.C. (BANOBRAS)

Mexico

Nacional Financiera (NAFIN)

Mexico

Financiera Rural

Mexico

Fideicomisos Instituidos en Relación con la Agricultura (FIRA)

Paraguay

Credito Agricola de Habilitacion (CAH)

Paraguay

Agencia Financiera de Desarrollo (AFD)

Paraguay

Banco Nacional de Fomento de Paraguay (BNF)

Peru

Banco Agropecuario (Agrobanco)

Peru

Corporación Financieras de Desarrollo S. A. (Cofide)

Peru

Banco de la Nacion (BN)

Uruguay

Banco de la Republica Oriental del Uruguay (BROU)

Venezuela, RB

Banco de Dearrollo Economico y Social de Venezuela (BANDES)

Egypt, Arab Rep.

Industrial Development and Workers Bank of Egypt

Oman

Export Credit Guarantee Agency of Oman

Canada

Business Development Bank of Canada (BDC)

Bangladesh

Saudi Bangladesh Industrial and Agricultural Investment Co. Ltd.

Bhutan

Bhutan Development Finance Corporation Limited

India

National Bank for Agriculture and Rural Development

India

Export-Import Bank of India (Exim Bank)

India

Small Industries Development Bank of India

Nepal

Nepal Industrial Development Corporation Ltd.

Pakistan

First Credit & Investment Bank Limited

Pakistan

Pak Oman Investment Company Limited

Sri Lanka

DFCC Bank

Middle East & North Africa North America & South Asia

Name of institution

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Region

Country

Name of institution

Sub-Saharan Africa

Angola

BANCO DE POUPANÇA E CRÉDITO S.A.R.L

Congo, Dem. Rep.

FPI — Industrial Promotion Fund

Côte d’Ivoire

Banque de l’Habitat de Côte d’Ivoire (BHCI)

Ghana

National Investment Bank Limited

Kenya

Industrial and Commercial Development Corporation (ICDC)

Kenya

Kenya Tourist Development Corporation (KTDC)

Kenya

IDB Capital Ltd

Nigeria

Nigerian Export-Import Bank (NEXIM)

Rwanda

Rwanda Development Bank (BRD)

South Africa

Development Bank of Southern Africa

Sudan

The Agricultural Bank of Sudan

Tanzania

TANZANIA INVESTMENT BANK LIMITED

Uganda

Uganda Development Bank Limited

Middle East & North Africa

Bahrain

Bahrain Development Bank (BDB)

East Asia & Pacific

Indonesia

Bank Mandiri

Europe & Central Asia

Bulgaria

Bulgarian Development Bank (BDB)

Hungary

Hungarian Development Bank

Kazakhstan

Development Bank of Kazakhstan

Macedonia, FYR

Macedonian Bank for Development Promotion

Middle East & North Africa

United Arab Emirates

Mubadala Development Company

Sub-Saharan Africa

Zimbabwe

Infrastructure Development Bank of Zimbabwe (IDBZ)

Appendix 3: Sample of national development banks. Country

Name of institution

Year of foundation

Angola

BANCO DE POUPANÇA E CRÉDITO S.A.R.L

1991

Bahrain

Bahrain Development Bank (BDB)

1992

Bangladesh

Saudi Bangladesh Industrial and Agricultural Investment Co. Ltd.

1984

Bhutan

Bhutan Development Finance Corporation Limited

1988

Bolivia

Banco de Desarrollo Productivo (BDP)

2007

Bulgaria

Bulgarian Development Bank AD

1999

Bulgaria

Bulgarian Development Bank (BDB)

1999

China

China Development Bank

1994

Colombia

Banco De Comercio Exterior de Colombia

1991

Colombia

Fondo Para El Financiamiento del Sector Agropecuario (FINAGRO)

1990

Congo, Dem. Rep.

FPI — Industrial Promotion Fund

1989

Côte d’Ivoire

Banque de l’Habitat de Côte d’Ivoire (BHCI)

1994

Ecuador

Banco del Estado (BEDE)

1992

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Country

Name of institution

Year of foundation

Egypt, Arab Rep.

Industrial Development and Workers Bank of Egypt

1976

Finland

Finnvera plc

1998

Germany

Thüringer Aufbaubank (TAB)

1992

Germany

North Rhine-Westphalia (NRW Bank)

2004

Hungary

Hungarian Export Import Bank Private Company Limited

1994

Hungary

Hungarian Development Bank

2001

India

National Bank for Agriculture and Rural Development

1982

India

Export-Import Bank of India (Exim Bank)

1982

India

Small Industries Development Bank of India

1990

Indonesia

Bank Mandiri

1998

Kazakhstan

Development Bank of Kazakhstan

2000

Kenya

IDB Capital Ltd

1973

Malaysia

Bank Pembangunan Malaysia Berhad

1973

Malaysia

Credit Guarantee Corporation Malaysia Berhad

1972

Malaysia

Sabah Credit Corporation

1995

Mexico

Financiera Rural

2002

Mongolia

The Microfinance Development Fund

2002

Nigeria

Nigerian Export-Import Bank (NEXIM)

1991

Oman

Export Credit Guarantee Agency of Oman

1991

Pakistan

First Credit & Investment Bank Limited

1989

Pakistan

Pak Oman Investment Company Limited

2001

Paraguay

Agencia Financiera de Desarrollo (AFD)

2005

Peru

Banco Agropecuario (Agrobanco)

2002

Peru

Corporación Financieras de Desarrollo S. A. (Cofide)

1971

Philippines

Al-Amanah Islamic Investment Bank of the Philippines

1973

Philippines

Philippine Postal Savings Bank, Inc.

2006

Philippines

Philippine Export-Import Credit Agency

1977

Republic of Macedonia

Macedonian Bank for Development Promotion

1998

Slovak Republic

Slovak Guarantee and Development Bank

1991

South Africa

Development Bank of Southern Africa

1983

Thailand

Small and Medium Enterprise Development Bank of Thailand

2002

Turkey

Export Credit Bank of Turkey (Türk Eximbank)

1987

Turkey

Development Bank of TURKEY

1975

United Arab Emirates

Mubadala Development Company

2002

Venezuela, RB

Banco de Dearrollo Economico y Social de Venezuela (BANDES)

2001

Vietnam

Vietnam Bank for Social Policies (VBSP)

1996

Zimbabwe

Infrastructure Development Bank of Zimbabwe (IDBZ)

2005

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Appendix 4: Heterogeneity of national development banks in the sample1. The only instance of congruence in the sample – ownership structure, 2009 Source: Author’s analysis based on data described in the text

Equity, US$ million, 2009 Source: Author’s analysis based on data described in the text

Based on the dataset for 88 DBs from Appendix 2.

Review of Business and Economics Studies

Assets, US$ million, 2009 Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Loans, US$ million, 2009 Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Number of branches, 2009 Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Number of subsidiaries, 2009 Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Review of Business and Economics Studies

Staff, 2009 Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Funding options Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Sectoral assignment Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Targeted market segments Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Review of Business and Economics Studies

Lending products Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Products and services provided Source: Authorâ&#x20AC;&#x2122;s analysis based on data described in the text

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Monetary Policy in Russia: Recent Challenges and Changes in Unstable Economic Conditions* Natalia GIBLOVA, Ph.D. Assistant Professor of Banks and Bank Management Department, Financial University, Moscow giblova_natalia@mail.ru Abstract. The purpose of the article is to identify actual condition and recent changes in monetary policy of the Bank of Russia. The article considers the main directions of the monetary policy of the Bank of Russia, especially in correspondence with Russia’s deep political and economic problems. The author underlines negative aspects of the Bank of Russia’s monetary policy that took place in 2014. The attention is focused on consequences of inflation targeting policy influence on the economy, and on the use of monetary control instruments at the level of bank lending, rates of economic growth, etc. The research conducted by the author is based on dynamics of macroeconomic indicators. The author makes the conclusion that there is a change of the Bank of Russia’s monetary policy paradigm, which tends to correspond with the purposes of economic growth. The author also offers possible directions of improving Russia’s monetary policy, including double-purpose, which, in the author’s opinion, is of paramount importance at the present stage of Russia’s economy development under the conditions of economic and political instability, crisis and shocks. Аннотация. Целью проведенного исследования явилось выявление изменений в денежно-кредитном регулировании Банком России, произошедших в последнее время. В статье рассмотрены основные направления денежно-кредитной политики Банка России, проводимой им на современном этапе развития российской экономики, а именно в условиях глубоких экономических и политических проблем. Автором выделены негативные аспекты проводимой в последние годы Банком России политики, акцентировано внимание на последствиях влияния политики по инфляционному таргетированию на состояние российской экономики, исследовано влияние инструментов денежно-кредитного регулирования на уровень банковского кредитования субъектов экономики, темпы экономического роста. По результатам проведенного автором исследования на основании динамики макроэкономических показателей в статье сделан вывод о смене парадигмы денежно-кредитного регулирования, корреспондирующего с целями достижения экономического роста. Автором предложены возможные направления совершенствования денежно-кредитной политики в России, в частности, осуществление бицелевой политики. Key words: Central bank, economic growth, monetary policy, key rate, refinancing system, inflation, bank loan.

1. I N T RO D U CT I O N In this day and age, major economies place special emphasis on monetary policy and its target-oriented constituent (for example, the United States, China, the United Kingdom, Japan, Switzerland, etc.) In view of the pressure on Russian economy, monetary policy may currently become real mean of influencing the rates of economic growth. Monetary policy has been traditionally one of the most important tools of governmental influence on economic life. Issues associated with the

theory and practice of state monetary policy were reflected in works by many authors. Among Russian economists, the following can be mentioned: M. A. Abramova, S. R. Moiseyev, A. V. Ulyukayev, A. J . Simanovsky. In foreign countries, the specific issues of monetary policy were worked out at different times by W. Allen, S. L. Brue, C. R. Mcconnell, F. Mishkin, N. Mogud, S. Rinhart, G. Sather, W. Smith, J. I. Harris, D. L. Hicks, G. Hogarth, J. Schumpeter, etc. Some important aspects of monetary policy, in particular, for example, flexibility in the conditions

* Денежно-кредитная политика в России: текущие проблемы и изменения в условиях экономической неопределенности.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 1. Values of GDP growth and inflation at year-end 2014.

of unstable economy and financial crisis, are underrepresented in the available publications. Despite the analysis of mainly Russian experience in terms of the impact of monetary policy on economic growth, the present research may be interesting for other economies belonging to the group of emerging markets.

2. T H E O R E T I CA L P R I N C I P L E S O F T H E B A N K O F R U S S I A’S M O N E TA RY PO L I CY Economic growth, price stability and high employment rate are usually distinguished as basic and long-run objectives of monetary policy. Unfortunately, despite the critical condition of domestic economy, the main target of Russia’s monetary policy is inflation, so Russia’s monetary policy is still pursued by the Bank of Russia as a tool for restricting rather than facilitating economic growth.1 The steps made by the Bank of Russia during exchange market crisis in November and December of 2014, confirm this point once again. In accordance with the applicable legislation, i. e . the federal law “Main directions of governmental monetary policies for 2015 and for the period of 2016 to 2017”, the main purpose of Russia’s monetary policy consists of “…protecting and ensuring ruble sustainability by reaching and maintaining low inflation rate” It is an interesting fact that in the same document for the last three-year period of 2014 to 2016 the main purpose of monetary policy was “…protecting and ensuring ruble sustainability by maintaining price stability, in particular, for creat1

In general, that corresponds to the Inflation Targeting policy.

ing conditions of balanced and sustainable economic growth…”. Thus, among the variants of target-oriented goals for monetary management, the Bank of Russia chose to maintain price stability, which was called the Inflation Targeting. Moreover, recently the Bank of Russia has excluded economic growth from monetary policy targets. As a result, we can see negative tendency in Central Bank’s understanding of monetary policy.

3. C U R R E N T CO N D I T I O N O F T H E R U S S I A N E CO N O M Y Currently, Russia’s economy is in diseased state. The comparison of rates of economic growth and inflation in a number of countries shows negative tendencies in the development of Russian economy (Fig. 1). The World Bank predicts that GDP growth in Russia will be at the rate of –2.9% at year-end 2015, inflation would be between 13 to 15%. During financial and economic crisis of 2008 to 2010, the drop-down of Russia’s GDP was very noticeable. The dynamics of changes in these indices for the period between 2000 and 2014 shows considerable deviations and sharp drop-downs point at the instability of Russian economy compared to other countries (see Figure 2). Similar situation is observed when analyzing the dynamics of changes in inflation rate for the period under consideration (Fig. 3). The disproportion between the amount of money in Russia and the size of the market still exists and is the factor of inflation. The reasons for

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 2. GDP growth rate for the period between 2000 and 2014.

Figure 3. Inflation rate for the period between 2000 and 2014.

this can be found in the unbalanced money supply, which has been increasing over the past decade due to continuously increasing government spending2 (during the active phase of the crisis in 2008 to 2009, budget expenditures have increased by 23% and 15%, respectively), and export earnings from the sales of resources, along with the reduction of real domestic production (production of consumer goods and import in 2009 have decreased more than 1.5 fold). As a result, the 2â&#x20AC;&#x201A; The increase in government spending in time of crisis in economy on its own is a justified and appropriate measure, provided, however, the funds are directed precisely to economy in order to ensure the normal course of the reproduction process of the real sector of the economy, and to maintain the business activity of economies.

amount of money in circulation has significantly exceeded the need for it in the existing turnover of goods and services. The excess in money supply is distributed unevenly among economic entities. As a result, the real economy industries are experiencing the serious deficiency of resources, along with their general excess in the country, and, with the existing level of interest rate, are not able to act as borrowers. According to the estimates given by a number of economists, stagnation, even recession has already begun in the country. Without doubt, external factors (geopolitical risks)3 make a significant impact 3â&#x20AC;&#x201A;

China successfully coped with economic sanctions applied to it at

Review of Business and Economics Studies

on current situation. However, it is not just them, it is the problems accumulated within the country. The Russian government has been turning a blind eye to these problems a long while, just stating them as facts. The main problem lies in the structural imbalance of Russian economy, its high dependence on energy source exports and, respectively, on currency incomes, and lack of the country’s own internal industries in major sectors. The energy prices that have been increasing over nearly 15 years allowed to successfully finance all expenditures of national budget (over half of which is formed based on oil and gas transfers), to maintain acceptable rates of economic growth, and to increase salaries for the population, despite the fact that the economy was not developing de facto. However, the situation in Russia has changed dramatically. What do we see? • Political and economical sanctions; • High interest rates in the market; • The reduction of oil prices, and other energy resources, subsequently: since the beginning of 2014, oil prices have been decreased by more than 50%; • Ruble devaluation: since the beginning of the year, by over 50%; • Significant capital outflow; • The slowdown of Russian stock market: since the beginning of the year, the RTS-index has decreased by over 40%. The most significant decrease — 40% — occurred in machine-building industry. Performance indices of Russia’s economy are going down: the drop-down of labor productivity index compared to the maximum of 2006 is 4%. As a result: • Increase of inflation; • Decrease in the purchasing power of national currency and at the same time in real disposable money income of citizens; • Growth rate reduction in the economy. According to the estimates of the Ministry of Finance of the Russian Federation, Russia’s losses caused by these factors are more than 300 bln USD. Unless we move away from the dependence on energy source exports and, respectively, on currency incomings, the amounts of which can be significantly influenced by external operators, we will not have a chance for fundamental improvements in Russian economy.

It is necessary to develop internal market, which requires investments. Until recently, such resources have been actively attracted from foreign markets (the consequences of such tactics are described above). Currently, in the changed political and economic situation, resources for financing the investments need to be generated internally within the country, not in external markets. However, due to current monetary policy, finding the opportunity for such financing does not seem possible.

the end of 1990’s. Moreover, since the beginning of 2000-s, growth rates in China have been at the level of 8%.

Volume 3, Number 1, 2015

4. RO L E O F B A N K S I N E N S U R I N G E CO N O M I C G ROWT H The role of banking sector in ensuring economic growth is to transform the temporarily free funds of various economic entities, including shortterm funds, into long-term capital, which in turn is the source of investments in the real sector of economy. At the same time, by loan granting and the possibility to participate in stock market as investors, credit institutions create the channels for floating temporarily free funds to the businesses, which are in need of investments for the purpose of modernization, as well as overcoming the consequences of crisis. Investments are exactly the main driving mechanism of the economy. Thus, the role of banking sector in ensuring economic growth is to accumulate funds from various entities and transform them into investments. Global practice shows that banking sector actively copes with the above role. For example, according to various estimates, the contribution of European banks to economic development is 250 to 500% of GDP. In the source-based structure of investment financing, the share of bank loans in the USA is 32.5%, in China — 15%, in Germany — 41.8%. A reverse trend is typical of Russia (Fig.4). According to the Federal State Statistics Service, Russia’s current investment financing is carried out mainly due to internal sources of business entities and their parent companies — 58%; on bank loans there is only 10%. The ratio of banking sector assets to GDP as of 2015 is 109.4%. It is noteworthy that assets exceed twofold the value of consolidated national budget. Loans (excluding loans granted to financial institutions and population) make 41.6% of GDP. However, only about 3% of credit resources are allocated to investment financing, which is manifold lower than in other countries. Within the structure

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 4. The structure of Russia’s current investment financing in 2014.

Figure 5. Dynamics of the change in interest rates on interbank market (MosPrime Rate), %.

of corporate loans granted by banks, only 1.5% is used in machine-building industry. The share of bank loans to investments in fixed assets of entities makes only 1.5% against GDP. At that, Russia’s GDP value is considerably lower than that of the world’s major economies. During the economic forum held in St. Petersburg in 2014, president Vladimir Putin specified that “…Russia needs real technological revolution…” To implement these large-scale modernization activities, enormous resources are required. In this regard, major hopes are traditionally laid on banking sector and loans. In such circumstances, Russian banking sector has often been criticized for its inability to fulfill its most important purpose — to meet the financial needs of the economy, thus restraining economic growth.

It is important to note that the inflation targeting policy, provided by the Bank of Russia, implies reducing of monetary stock in the economy, and tightening of credit conditions through higher interest rates. Thus, during 2014, key rate in Russia was increased six times from 5.5% to 17%. On December 16, unprecedented rate increase by 6.5% at a time happened. Such serious increase has not happened in Russia since 1998. Despite the fact that such a significant increase in key interest rates was due to the need to stabilize the situation on Russia’s currency market and reduce the speculative appetites of major players, this tool is primarily used for monetary management, and therefore, its influence extends far beyond foreign exchange market. The increase in key interest rates led to the increase in market borrowing rates, first for credit

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 6. Dynamics of the change in loan rates for business, %.

Figure 7. Sales profitability level in key sectors of Russian economy in 2014.

institutions through interbank market (inÂ December, 2014 MosPrime Rate grew to 30% per annum, see Figure 5), as well as deposits, and then, for end consumers including businesses (Fig. 6). The strong relation of interbank and loan rates dynamics to changes in key rate is obvious. The increased borrowing costs will be added to the prime costs of products by manufacturers, and therefore, it will lead to the increase in costs with regard to financial resources, as well as goods and services. At the same time, such panic-like increase in interest rates will lead to increase in inflation expectations. Thus, instead of constraining inflation and stabilizing prices, further ruble devaluation and strengthening of inflation expectations will take place, which will ultimately lead to even more dramatic inflation growth. The second dramatic effect of high market rates is that effective demand is also lacking on the part

of business entities for credit resources necessary to make investments. According to statistics of the Central Bank of Russia the average loan rate for business is between 17 to 20%. In fact, it reaches 25â&#x20AC;&#x201C;30%. With the profitability of sales in general in the Russian economy at the level of 7% such high interest rates are back-breaking and inexpedient (see Fig. 7). Appreciation grown rates and decrease in resources volume have obviously affected the size of lending to the economy. Thus, analyzing the total volume of lending to resident legal entities and individual entrepreneurs (inÂ RUR), including the industries related to manufacturing, descending trend with a negative outlook for further development has been identified (see Figure 8). In these circumstances, due to the lack of any specific measures of government support to subsidize interest rates of investment loans for busi-

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 8. Monthly volume of lending to legal entities and individual entrepreneurs, mln.RUR

ness entities in key sectors of economy, economic growth becomes totally impossible.

5. R E F I N A N C I N G S Y S T E M Apart from direct impact on interest rates on the market (through key interest rate), the Bank of Russia also can actively apply tools for refinancing credit institutions. Refinancing is of dual nature. On the one hand, it is an efficient measure to regulate the liquidity in banking sector, and, on the other hand, it is an effective tool of monetary management. The two key factors influencing the scope of refinancing are as follows: the demand on the part of credit institutions themselves, which may be at the same time artificially limited by high interest rates, and the offering of funds by the Bank of Russia. As a tool of monetary policy, the scope of crediting by the Bank of Russia as to credit institutions is of paramount importance, since the scope of crediting various economic entities by commercial banks depends, to a greater degree, just on this index through banking multiplication. The introduction of money into economic circulation through crediting mechanism contributes to the performance of money-specific functions, the expansion of production and of the ensuring of economic growth. However, in accordance with inflation targeting policy, it is the monetary growth ensured by way of increasing crediting scope that is one of the main inflation factors to fight against.

Taking into consideration that the reduction of the scope of crediting by the Bank of Russia for credit institutions can lead to serious difficulties with liquidity in banking sector and to banking crisis, the Bank of Russia makes an impact on this market by regulating interest rates (see above — increasing key interest rate). In our opinion, this policy, as well as the negative perception of credit in the specified context, cut down its positive role as the source of investments and the catalyst of economic development. Refinancing of credit institutions is mainly performed in two ways — direct lending and repo transactions. Figure 9 shows the dynamics of changes in credit institutions’ indebtedness to the Bank of Russia in repo transactions. The data shows that in 2012 the volume of indebtedness was increasing steadily, despite some fluctuations. This was due to liquidity problems in banking sector, the increasing needs of the banks in cash (as evidenced by the rising trend line). As of December 1, 2014, the volume of credit institutions’ indebtedness to the Bank of Russia in repo transactions has exceeded 3.3 trillion RUR. Similar situation is observed in studying the volume of direct lending to credit institutions by the Bank of Russia (see Fig. 10): significant volumes — 3.1 trillion RUR as of December 01, 2014, and sharp increase in indebtedness since the second half of 2013. However, the existing refinancing volumes are aimed just at ensuring the liquidity of banking sector, and are allocated by banks primarily to cover

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 9. Indebtedness of credit institutions to the Bank of Russia in repo transactions (mln. RUR).

their current liabilities, and do not allow to use the financial resources emissions by national regulabanking multiplier effect in full directing resourc- tors in developed countries is quite interesting. We know a lot about the role of money in the mones for lending to the economy. etary transmission mechanism during periods of quantitative easing. 6. PO S I T I V E T R E N D S Unfortunately, the Bank of Russia has been actDespite the increasing volumes of credits attracted ing in the reverse way. As to refinancing instruby the banks from the Bank of Russia, the indicators ments, short-term and super-short-term instrucharacterizing money supply had the reverse dynam- ments were primary applied. During the post-crisis period, there appeared ics in 2014. According to the Bank of Russia, during the first three quarters of 2014, the money supply a worldwide tendency of attracting the interest of (M2) has decreased by 4%, amounting to 30.3 trillion entities, including commercial banks, to invest in RUR. But in the fourth quarter of 2014 and in the be- internal economy, also known as home bias. For exginning of the year 2015 the trend changed its direc- ample, the standards making financial investments tion. M2 reached its peak in December and amounted abroad less attractive for banks were applied in 32.1 trillion RUR. Once again, it’s worth mentioning Switzerland. In order to provide access for the real sector enthat it is a positive sign because the increase in money supply can lead to increase in amount of banking terprises to bank loans, the Swedish National Bank has introduced the world’s first negative rate on loans in the nearest future (see Fig. 10). The other positive trend is that key rate was re- deposits of commercial banks at the central bank duced two times: from its highest level of 17% to equal to minus 0.25%, and the base repo rate was 15% in February and then to 14% in March. Accord- reduced from 0.5% to 0.25%. This extraordinary ing to Bloomberg forecast to the end of the year measure of the Central Bank of Sweden was aimed at stimulating the real economy crediting by bank2015 Russian key rate may be reduced to 11%. The total increase of amount of net liquidity, ing sector. The British government, together with the Bank given by the Central Bank to banking sector, in January-March, 2015, up to 6 trillion RUR also tells of England, has launched a program of lending to banks at interest rates lower than in the market, us about refusing from hard restrict policy. providing the latter allocate resources for lending to non-financial sectors of the economy, i. e . to 7. G LO B A L P RACT I C E the real sector — Funding for Lending, FLS. This The practice of implementing the policies of long- program was not aimed just at stimulating lendterm money expansion in the economy and long ing, and it consisted of several stages: at the first

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 10. Indebtedness of credit institutions to the Bank of Russia on secured loans (bln. RUR.)

Figure 11. Dynamics of the change in M2.

stage, banks could receive only 5% of the total volume of their loan portfolio, at the second stage, 100% of the newly provided loans to the real sector from the moment of the receipt of the first loan until the end of 2013. Herewith, banks were obtaining loans at 0.25% per annum, provided the loan volume at least was not reduced. In case the loan portfolio volume was reduced, for example by 5% or more, the rate would increase to a maximum level of 1.5%4. Not only large UK banks, such as HSBC, Royal Bank of Scotland Group PLC, and 4â&#x20AC;&#x201A; British banks received 60 bln GBP within the framework of Funding for Lending.

Lloyds Banking Group PLC, have taken part in the implementation of this scheme, as it was designed to encourage lending interaction between banking and real sectors of economy by providing cheap central financing in the limited resources conditions, but also the European Central Bank. It decided to launch a similar program Longer-Term Refinancing Operations (LTRO), with the only difference that the access to the preferential terms would be provided to those banks that would agree to lend to the real sector of the economy, and provide shorter crediting period (4 years for FLS, and 3, 6, 9, and 12 months for LTRO) 4. Thus, the rate shall vary, depending on the dynamics of the

Review of Business and Economics Studies

loan portfolio: the initial rate is 0.25%, and, in case of reduction of the loan portfolio by 1%, the rate shall be increased by 0.25% to the maximum level of 1.5%. It is believed that the new technology of bank lending will allow for the expansion of volumes and accessibility of lending for the real sector enterprises by providing cheap central financing. The majority of UK banks have joined the implementation of this scheme.

creasing interest rates and the reduction of financial resources supply in the first place), will lead to greater economic recession, and further spiral increase of inflation. There are historical examples of focusing monetary policy on more than one key goal (which is considered to be a traditional option for monetary paradigm development). For example, the USA and China have effectively applied the bi-purpose system within different time periods. For the purpose of economic recovery and acceptable growth rates within monetary regulation, it is required, in the first place, to focus on refinancing mechanism, to affect its scope and interest rates level correlated with the needs of the economy. Particularly, these tools are major leverages in advanced countries, and they allow to seriously affect financial markets, as well as national economy as a whole. In our opinion, the Bank of Russia has to revise the fundamental directions of national monetary policy towards ensuring economic growth in the country, in the first place. It is also necessary to pay attention to the best international practice and adopt its positive aspects, in particular, to develop long-term lending to commercial banks for the purpose of providing investment credit resources to the enterprises of the real sector of the economy, as well as to establish various key interest rates, depending on the purposes of attracting resources by commercial banks. Now we see some steps of the Central Bank in this direction: decrease of key rate to 14% and grown M2. It is not enough, but is a good sign.

8. CO N C L U S I O N S

Volume 3, Number 1, 2015

It should be mentioned that unfortunately, nowadays the Russian monetary policy acts as a negative factor of economic growth. Despite some positive changes that took place recently the objective to promote economic growth is not reached de facto. Along with the rising inflation, the interest rates are too high, resources are growing in price, money supply and volumes of lending to the real sector are decreasing, the size of the latter is being reduced, and, as a consequence, there is absence of the so much-needed economic growth, which is particularly complicated due to the geopolitical and international economic situation. However, in Russia, inflation is of non-monetary nature, and, therefore, the struggle against it by implementing austerity measures does not lead to the desired result, as the current situation proves. Moreover, in current economic situation, the inflation targeting includes more threats than benefits, leading to financial instability, the negative effects of which will ultimately affect entrepreneurs. The latter aggravates business situation more and puts pressure on economic growth. In our opinion, at current stage, it would be reasonable to shift the R E F E R E N C E S focus of the monetary regulatory approach from inflation targeting to ensuring economic growth. MosPrime Rate. Official website of the Bank of Russia, www. The nature of inflation is too complicated and cbr.ru. ambiguous. Struggle against it by exclusively fis- China statistical yearbook, 2013, National Bureau of Statistics cal measures leads to mainly negative results, of China. such as the decrease in production, the decline in The World Bank, GDP growth (annual%). GDP growth, along with the increasing inflation rate. The Statistics Portal, (accessed 12 December 2014). That’s not the amount of money we need to The indices of Moscow Exchange. Moscow Exchange, http:// fight against, but the weakness of Russian econmoex.com/ru/indices (accessed 25 March 2015). omy, and serious structural imbalances, as those The index of intensity as to the production of goods and serare the reasons for “invincible” inflation. Consevices in basic economic activities. Monthly report. Institute quently, the aim is to ensure economic growth, to “Center of Development” National Research University — allocate resources specifically for these purposes. Higher School of Economics. The fight against inflation will only exacerbate Michael McLeay, Amar Radia, Ryland Thomas (2013), Money the existing problems (namely, the enterprises of creation in the modern economy, www.bankofengland.co.uk the real sector of the economy suffer from the in(accessed 25 March 2015)

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Market Concentration and Competition in Vietnamese Banking Sector* Le Hai TRUNG Banking Faculty, Banking Academy of Vietnam trunglh@hvnh.edu.vn Abstract. The wave of financial liberalization raises questions about the competitiveness of Vietnamese commercial banks against those from other countries. The main purpose of this paper is to measure the market concentration using the k banks concentration ratio (CRk) and the Hirschman-Herfindahl index (HHI) and speculate on the market competition in Vietnamese banking sector under Panzar-Rosse approach. Overall, Vietnamese banking sector is found to be highly concentrated although it is experiencing a decreasing trend. Also, the speculation of market competition indicates a monopolistic behavior of Vietnamese commercial banks. Аннотация. Волна финансовой либерализации поднимает вопрос о конкурентоспособности вьетнамских коммерческих банков по отношению к банкам других стран. Основная цель данной работы заключается в измерении рыночной концентрации с помощью коэффициента концентрации (CRk), индекса ГерфиндаляГиршмана (HHI) с использованием модели Панзара-Росса. В целом вьетнамский банковский сектор является сильно концентрированным, хотя испытывает тенденцию к ослаблению централизации. Кроме того, отмечается монопольное поведение вьетнамских коммерческих банков. Key words: Market concentration, competition, banking sector, commercial banks, Vietnam.

1. INTRODUCTION In 1986, Vietnamese government launched an economic renewal campaign named “Doi Moi” to promote economic development and turn the country’s economy into a more open and market-oriented one. It is undoubted that Vietnamese banking sector has contributed a large part to the economic expansion recently. The banking sector has been developing substantially in recent years since the banking market was opened to both foreign and private sector banks in 1991. The number of banks in Vietnam reached 104 banks (as of 31/12/2012), including 1 state-owned commercial bank (Agribank), 4 partially state-owned commercial banks (Vietinbank, Vietcombank, BIDV and MHB), 33 jointstock commercial banks, 5 wholly foreign-owned banks, 4 joint-venture commercial banks and 55 foreign banks’ branches and subsidiaries. By the end of 2011, the total domestic credit provided by banking sector constituted 120.8% of GDP, while domestic deposit to banking sector accounted for 106.56% of GDP. High-level of credit growth of around 30% in a long period of time was one of the most important factors in the high growth rate of the Vietnamese economy. One of the most striking feature of the Vietnamese banking sector is the domination of state-owned banks

and partially state-owned banks (from now onwards, they are all called state-owned banks — SOCBs, as the government has controlling right in all of these banks with over 51% of total chartered capital). These stateowned banks’ assets account for about 50% of the total banking sector’s assets, together with 48% in deposit and 52% in credit market-share, leading to very high market concentration. However, this market concentration has been decreasing considerably due to the increase in market share of domestic joint-stock commercial banks and foreign banks. In addition, the Vietnamese banking system has been under an unavoidable financial globalization trend as well as dramatic advancement in information and banking technology. According to Linda S. Goldberg (2008), globalization can help the host countries receive the services of globally-oriented banks. It can also have positive effects on real foreign direct investment, technology transfers, and productivity enhancement. Hence, for developing countries such as Vietnam, it is a crucial requirement to participate in globalization process. Globalization in the banking sector could change the market structure and behavior of Vietnamese banking industry. For instance, the increased presence of foreign banks has imposed the

* Рыночная концентрация и конкуренция в банковском секторе Вьетнама.

Review of Business and Economics Studies

needs to enhance the competitiveness and strength of domestic commercial banks, including partially privatizing SOCBs and strengthening bank capital requirement. As a result, measuring and understanding the current state and trends in market concentration and competition in Vietnamese banking industry could give some implications to government and banking supervisor (State Bank of Vietnam — SBV) to improve the strength and efficiency of banking system. In theory, there are two main approaches to measure the market concentration and competition. From the structural approach, bank concentration and competition is measured by the number of banks and the market share of each bank. The most popular method is the Hirschman-Herfindahl index (HHI). In the non-structural approach, different frameworks are developed with the most popular models such as the Iwata model (Iwata, 1974), the Bresnahan and Lau model (Bresnahan and Lau, 1982) and the Panzar-Rosse model (Panzar and Rosse, 1977; 1987). This paper proceeds as follows: Section 2 will give a brief overview about Vietnamese banking system. Section 3 will provide some theoretical review about the market concentration and competition in banking sector. Section 4 will describe the data and methodology employed in this study. Section 5 will present and analyze the empirical result by both structural and nonstructural approaches. Finally, the conclusion will be given in Section 6.

2. OVERVIEW OF VIETNAMESE BANKING SYSTEM

Indonesia

Malaysia

Philippines

Volume 3, Number 1, 2015

Early reform in Vietnamese banking sector was a part of the broader set of market-oriented reforms that the government began in the mid-1980s, focusing on decentralizing and privatizing financial services. Prior to 1990, the SBV operated as both the central bank and a commercial bank. It then separated its four main departments to form four new SOCBs in 1990, each targeted at different sectors of economy. The central bank’s industrial and commercial lending department converted into the Vietnam Industrial and Commercial Bank (Incombank — now is Vietinbank). The agricultural department was converted into the Vietnam Bank for Agricultural and Rural Development (Agribank), while its international trade department and infrastructure department converted into the Bank for Foreign Trade of Vietnam (Vietcombank) and the Bank for Investment and Development of Vietnam (BIDV), respectively. Since the first reform, Vietnamese banking sector has been playing a vital role in the economic development and growth. In 1992, domestic credit provided by banking sector accounted for only 15.7% of GDP. From this point onward this ratio increased dramatically, peaking at 135.8% of GDP in 2011. Vietnamese stock market is still in early stage of development, as we can see in the Figure 1. The stock market capitalization only accounted for 21.1% of GDP in 2012, which has been recently announced to be increased to about 30% of GDP in 2013.

Singapore

Thailand

Vietnam

350 300 250 200 150 100 50 0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Figure 1. Stock market capitalization of Vietnam and other countries in ASEAN. Source: World Bank data.

Review of Business and Economics Studies

Indonesia

Malaysia

Philippines

Volume 3, Number 1, 2015

Singapore

Thailand

Vietnam

200 180 160 140 120 100 80 60 40 20 0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Figure 2. Domestic credit provided by banking sector of Vietnam and other countries. Source: IMF data.

Table 1. Brief statistic about financial assess of Vietnamese banking sector. Indicator/Year Number of banks Deposit with banks (% of GDP)

2007

2008

2009

2010

2011

2012

101

100

91.7

106.36

121.39

106.56

119.67

Commercial banks branches per 1000 km 2

6.83

6.98

7.77

6.91

Commercial banks branches per 100000 adults

3.31

3.32

3.25

3.57

3.18

15.52

24.74

31.38

36.87

43.05

46.02

7.68

11.98

14.91

17.22

19.79

21.16

ATMs per 1000 km

ATMs per 100000 adults

97.25

Source: IMF data.

The size and development of Vietnamese stock market is considerably lower than that of neighboring countries, including Thailand, Singapore, Indonesia and Philippines, with the ratio of over 100% of GDP in 2012. As a result, domestic credit provided by banking system is the main capital source for financing firms and as well as the whole economy. Figure 2 shows a dramatic increasing trend in the ratio of the economy’s domestic credit to GDP. Although the credit growth of banking sector has slowed down in recent years due to the severe effects of global crisis, there is no doubt that the banking sector will continue to contribute a large part to the development and growth of Vietnamese economy in the next few years. Additionally, the Vietnamese banking sector has continued to widen financial access to Vietnamese residents recently. Table 1 provides some brief statistics about the financial assess in Vietnam, collected from IMF data. The financial assess of Vietnamese banking sector has improved significantly in all indicators, high-

lighting the expansion of financial and banking services available to residents. Vietnamese banking sector seems to have a high concentration with the dominance of SOCBs. 4 main state-owned commercial banks including Agribank, Vietcombank, Vietinbank, BIDV account for 38% of total chartered capital and 49% of total assets of the whole system. They also dominate in both bank credit and deposit markets, as seen in Figure 3. However, the market concentration in banking sector is decreasing as a part of Vietnam’s increasing participation in international trade and investments agreements, such as the US-Vietnam Bilateral Trade Agreement (BTA) in 2001, and the new role as an official member of the WTO in 2007. Since 2006, the State Bank of Vietnam (SBV) has granted licenses to five foreign banks to operate as wholly foreign-owned banks, as well as to six joint venture banks and over 50 subsidiaries of foreign banks. To adhere to WTO regulations, from January 1st, 2011,

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 3. Market share by lending and deposit. Source: IMF report.

Table 2. Comparison of financial assess of Vietnam and other ASEAN countries. Vietnam

Thailand

Commercial bank branches per 1000 km

6.91

12.55

618.57

9.24

ATMs per 1000 km 2

46.02

89.7

3684.29

35.15

34.56

Commercial bank branches per 100000 adults

3.18

11.77

9.76

9.59

19.91

ATMs per 100000 adults

21.16

84.16

58.12

36.47

52.94

Singapore

Indonesia

Malaysia

Source: IMF data.

foreign banks and branches have received equal treatment as domestic banks. The increasing presence of foreign banks and branches has enhanced the competitive pressure in banking sectors, forcing domestic banks to improve their competitiveness and strength. Despite significant expansion since 1990s, Vietnamese banking sector is still an infant industry with high potential growth. Only around 20% of the 90m population in Vietnam has bank accounts. As shown in Table 2, financial access to banking services compared to that of other ASEAN countries is much lower. In addition, with a young population and increasing income, the demand for modern banking services is expected to increase substantially in the near future. Hence, together with the unavoidable wave of financial liberalization and deregulation, Vietnamese banking sector will soon receive much higher interests and investments from foreigners and global institutions, which in turn, will change the nature of market concentration and competition of banking sectors. Since the recent global crisis, Vietnamese banking sector has exposed many weaknesses, slowing down the

recovery of the whole economy. This is due to the fact that Vietnamese banking sector is excessive in number, but lacking in the services quality. Despite a low average profitability in comparison with other fields (ROE and ROA at 0.5% and 4%, respectively), bank profit has been deteriorating recently as 24/125 credit institutions experienced losses, 100/125 gained, but 57 of them had negative y-o-y profit growth (as of 30/6/2013). Bank credit growth continues to stay low, with some months being in negative growth, due to the weak domestic demand and high level of NPLs in the banking system. As a result, on March 01, 2012, the banking sector reform strategy was approved with the key objectives is to “restructure fundamentally and comprehensively the system of credit institutions to develop … a modern, safe, sound efficient system compliant with international banking standards and practices”. One of key element of the plan to improve the competitiveness of domestic banks is restructuring weak institutions via mergers and acquisitions (M&A) deals, with the number of domestic banks being expected to decrease to about 15 to 17 units in 2017. Apparently, this restructuring progress will have

Review of Business and Economics Studies

significant impacts on the market concentration and competition of Vietnamese banking sector as well as the market behaviors of each commercial bank in the near future. Understanding the current state of market concentration and competition in banking sector could give some implications to Vietnamese government and SBVs in policy decisions to successfully implement the banking reform strategy.

Saurina, 2007). Boyd et. al. (2005) indicated that larger banks in a concentrated banking system have higher profit, protecting them against financial shocks. The role of larger banks is also supported by the view of Boot and Thakor (2000), who proposed that larger banks did not need to give credit to risky investors, and could therefore select their clients, increasing both return on investment and the soundness of the credit portfolio.. Allen and Gale (2000) concluded that banking sector with a few larger banks is easier to monitor than one with many smaller banks. In the supporting view to bank competition, riskshifting paradigm, argues that higher competition could contribute to financial stability as increase in market power and the resulting higher loan rates have the potential to negatively affect the stability of banks due to moral hazard and adverse selection on the part of borrowers, as the borrower may choose higher risk project and increase their own risk of bankruptcy. This is, in turn, higher probability that loans turn non-performing, leading to higher bankruptcy risk for bank and greater financial instability (Boyd and De Nicolo, 2006). Mishkin (1999) also indicated the “too-big-to-fail” problem in banking sector as a result of lessening the degree of competition. He stated that larger banks are more likely to receive public support, and this worsens the moral hazard problems as larger banks may take more risky investment under a government safety net. Berger et al. (2008) also shared this view, indicated that policy-makers are more concerned about bank failures in more concentrated banking sectors with few large banks. Concerns about contagion and financial crisis resulting from the failure of larger banks make regulators reluctant to let them fail in the event of solvent problem. As a result, in highly concentrated markets, financial institutions may believe they are “too big to fail” and this may lead to riskier investments. He also added that larger banks have more complex organizational structure and may be associated with lowered transparency, which makes them more difficult to monitor. According to the social welfare, creation of a competitive environment encourages financial firms to adopt cost-reducing measures and to use resources more efficiently. In a competitive environment, financial firms are forced to increase the quality of service such as faster clearing of payments, more rapid processing of loan applications, and extended working hours for customers. Besides theories, large amount of empirical data were used to examine the impact of banking system structure on the stability and efficiency of banking sector. They all give different results and do not offer concrete evidences. The approaches of measuring concentration and competition in banking sector could be

3. LITERATURE REVIEW The competition in financial sector is important since it affects the efficiency of production of financial services, the quality of financial products and the degree of innovation in the sector. The degree of competition in financial sector can affect access of firms and households to financial services which in turn influences overall economic growth. As in other industries, higher competitive nature in banking sector is expected to fuel the efficiency and maximize social welfare to the whole economy. However, banking industries have some special properties as well as high influence to other industries with its important intermediating role in capital allocation in the economy. As a result, there is a conventional debate among academicians about the economic role of market concentration and competition in banking sector regarding the financial stability and social welfare. This debate is getting more and more interest from policy makers as we have experienced a wave of financial liberalization and deregulation, removing barriers to entry as well as protective policies for domestic institutions, which is expected to promote market competition in banking sector. There are two main arguments in the theory about the economic role of market concentration and competition in banking sector. One argument based on the “franchise value hypothesis”, indicating that banking system could be more fragile and less stable resulting from higher market competition and lower market concentration. In contrast, the second view based on “risk shifting paradigm” argues that financial stability would be enhanced as the banking sector becomes more competitive. Franchise value hypothesis focuses on the risk incentive of banks and analyses the effects of competition on bank’s risk taking behavior. It states that higher competition erodes profits margin causing banks’ franchise value drop, thus reducing incentives to prudential behavior and leading to more aggressive risk taking in an attempt to earn higher profits. Banks may choose more risky and lower quality portfolios, taking on more credit risk, lowering capital levels. This behavior, then, increases the probability of higher non-performing loan ratio and more bank bankruptcies resulting in greater fragility and financial instability. (Beck, 2008; Jimenez,

Volume 3, Number 1, 2015

Review of Business and Economics Studies

divided into two main lines: structural and non-structural method. Structural approach based on the traditional industrial organization literature includes StructureConduct-Performance paradigm (SCP) and Efficiency Structure Hypothesis: SCP paradigm links between structure and performance of industries. Structure accounts for degree of concentration in the market. Conducts refer to the behavior of firms in price-setting, making research and development. Performance refers to efficiency of firms, defined by the market power, with greater market power implying lower efficiency. The paradigm is based on the hypotheses that structure influences conducts (lower concentration leads to more competitive behavior of firms); conducts influences performance (more competitive behavior leads to less market power, then greater efficiency) and structure therefore influences performance (lower concentration leads to lower market power and then greater efficiency). As a result, competition in the sector could be measured by the degree of concentration. One of the most popular approaches is the use of Herfindahl-Hirschman Index. Efficiency Structure Hypothesis (EH), argued by Demsetz (1973) and Peltzman (1977), states that efficient firms increase in size and, therefore, in market share due to their ability to generate higher profits, leading to higher market concentration. Under EH, there is no direct relationship between market concentration and competition, and the highly concentrated sector is the logical outcome of market forces. In contrast with structural approach, non-structural approach measures the competition directly. Two most popular approaches are the models developed by Panzar and Rosse (1987) and Bresnahan (1989). While Bresnahan (1989) used the condition of General Market Equilibrium with the basic idea that profit-maximizing firms in equilibrium will choose prices and quantities such that marginal costs equal marginal revenue, which coincides with the demand price under perfect competition or with the industrial marginal revenue under perfect collusion, Panzar and Rosse used bank level data and investigated the extent to which a change in factor input prices is reflected in revenues earned by a specific bank. In other words, the competition in a sector is measured by the elasticity of output revenue due to changes in input prices. Under perfect competition, an increase in input prices raises both marginal costs and total revenues by the same amount as the rise in costs. Under a monopoly, an increase in input prices will increase marginal costs, reduce equilibrium output and, consequently, reduce total revenues. A number of papers have applied both structural and non-structural approaches to investigate the degree of

concentration and competition as well as the impact of market concentration and competition in banking sector in developed countries, but just a few of them targeted on developing countries. For instance, Bikker and Groeneveld (2000) investigated a sample of European countries between 1989 and 1996 and found no evidence of increasing competition during this period. Bikker and Haaf (2002) then extended the analysis to 23 OECD countries over the period 1988 to 1998. For every single country, results described a monopolistic competition environment. They then divided sample banks to large, medium and small-size banks and found that competition appears to be stronger to large banks and weaker to small banks. Claessens and Laeven (2004) explored a multi-country analysis of banking competition with the largest bank data by computing H-statistic for 50 developed and developing countries for the period 1994â&#x20AC;&#x201C;2001. They found a monopolistic competition in the banking sectors of all countries under consideration. They then regressed the estimated H-statistic on a number of country-specific characteristics with the presence of foreign banks, activity restrictions, entry regime, market structure and some general macroeconomic conditions being under review. They did not found a clear relationship between competition and concentration, but did find that fewer entry and activity restrictions resulted in more competition. Weil (2004) measured the banking competition for a sample of 12 EU countries over a period from 1994â&#x20AC;&#x201C; 1999 and found that there is a decreasing pattern of monopolistic competition. He then explored the relationship between competition and efficiency measured by efficiency scores being estimated using a stochastic frontier approach, together with a set of macro factors and geographical dummies. He found that relationship between competition and efficiency tends to be negative. This result was supported by the research of Casu and Girardone (2006) on a sample containing 15 EU member countries. The only difference was that Casu and Girardone estimated the efficiency of banks by efficiency scores conducted by a non-parametric Data Envelopment Analysis. In term of developing countries, Perera et al. (2006), by applying Panzar and Rosse test, found a monopolistic competition in banking sector during the period 1995 to 2003. They also compared the competition in traditional market-based products market, and fee- and commission-based products markets. Under their investigation, Bangladesh and Pakistan had more competitive nature in traditional market-based products markets, while Indian and Sri Lankan competition was greater in fee- and commission-based products market.

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Gelos and Roldos (2004) were concerned about the market structure in emerging markets banking systems and found that market competition in banking sector did not decrease due to a significant process of bank merger and acquisition wave during 1990s. They also suggested that lowering entry barriers have prevented a decline in competitive pressures. In their research on the market concentration and competition in Nepalese banking sector, Gajuel and Pradham (2012) found a decreasing trend and low level of market concentration in the period of 2001–2009. They also indicated more competition in interest-based market than fee-based market. In my knowledge, the market competition and concentration in Vietnamese banking system has not been investigated fully. Vietnamese banking system competition was only a part of data in the research of some academicians for multi-country sample, such as Bikker et al. (2012) and Sentiyono and Tarazi (2014). As a result, this study could be the first research that employs both structural and non-structural approaches to investigate the degree on concentration and competition in Vietnamese banking sector. The results of this study could give some policy implications in the hope of strengthening the competitiveness of Vietnamese commercial banks.

4.2. METHODOLOGY

4. DATA AND METHODOLOGY 4.1. DATA The main data employed in this study was collected from bank database of Bankscope by Bureau van Dijk. It includes annual bank level data of all Vietnamese commercial banks during the period from 2004 to 2013 due to the availability of data, except for Vietnamese Bank for Social Polices and Vietnam Development Bank for clear representation of commercial bank behaviors in conducts and performance. The data for foreign banks’ branches and subsidiaries are also dropped from the sample as their behavior and performance mainly contributed to their foreign parent bank. Hence, the minimum data available is only 10 banks in 2004 to 34 banks in 2012 maximum, resulting in an unbalanced data with the total bank year observation accounting to 224. The commercial banks sample consists of both state-owned banks, jointstock banks and wholly foreign-owned banks, hence, it is expected to represent all features of Vietnamese banking sector. The data also concerned about the ownership of commercial banks as well as whether they have foreign involvement in operation, either as an owner or an investor, in order to investigate different competitiveness of different type of commercial banks under consideration.

Volume 3, Number 1, 2015

4.2.1. Structural approach Under structural approach, the market concentration and competition in banking sector is measured by the “k-bank” concentration ratio, and more intuitive Herfindahl-Hirschman Index (HHI-index). The “k-bank” concentration ratio is measured by the sum of market share of k largest banks in the sector. The higher the ratio, the more concentration there is in the banking sector with larger market power to largest banks in the banking sector. K

CRk  MSi i

On the other hand, HHI-index is calculated by squaring the market share of each banks competing in the banking sector. The HHI-index is expressed as follows: N

HHI  �MSi2 i 1

The higher the ratio is, the higher the degree of concentration becomes, and therefore the lower the competition in the banking sector is. The US Merger Guidelines pointed out that a HHI- index below 0.01 indicates a highly competitive market, a HHI-index of between 0.01 and 0.1 belongs to un-concentrated market, a HHI-index ranged from 0.1 to 0.18 indicates moderate concentration while HHI-index above 0.18 comes from highly concentrated banking sector. 4.2.2. Non-structure approach This research applies the reduced-form revenue equation specified by Panzar and Rosse (1987), which is one of the most widely used method to differentiate between oligopolistic, monopolistically competitive and perfectly competitive markets. The methodology of Panzar-Rosse is based on the general equilibrium market theory. Assuming long-run market equilibrium, individual firms will decide their productions in quantity and prices by setting marginal revenue equal to marginal costs.







Rim yi* ;� Z iR �  Cim yi* ;Wi ;� Z iC



Where Ri (.) and Ci (.) are the revenue and cost functions of bank i, yi is the output of firm, Wi is the K-dimension vector of factor input prices of bank i, Wi = (w1i; w2i; …; wKi); Z iR is a vector of exogenous factors affecting C the revenue function, Z i is a vector of exogenous factors that shift the cost function. Panzar-Rosse approach measures the degree of competition though H-statistic, and evaluates the elasticity of total revenues with respect to changes in the factor input prices.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 3. Concentration ratios of Vietnamese banks. 2007

2009

2012

Assets

Deposit

Loan

Assets

Deposit

Loan

Assets

Deposit

Loan

CR4

66.70%

73.07%

71.70%

53.84%

58.21%

62.84%

49.53%

52.6%

59.91%

CR6

77.95%

81.41%

83.04%

65.36%

68.55%

71.53%

58.26%

61.9%

68.33%

HHI

0.130

0.149

0.166

0.093

0.107

0.124

0.077

0.087

0.106

H  � ( K 1

Ri* wki * ) wki Ri*

The empirical application of Panzar and Rosse approach assumes log-linearity in the specification of the revenue and cost equation. The reduced-form of revenue equation is:

 

k 1

q 1

 

Ln Ri*  � �  k Ln wki   �q Ln zqi

Where Zi is a vector of Q bank-specific variables, wki is k input factor prices. Then H-statistic is calculated by K

H  �k k 1

The H-statistic, then, will indicate the overall level of competition in the market under consideration. According to Panzar and Rosse, H-statistic value ranges from minus infinity to unity. Under perfect competition, Hstatistic takes unity value that means 1 percent change in cost will lead to 1 percent change in revenues. Under monopoly market structure, H-statistic will take value from minus infinity to zero, meaning 1 percent change in cost will lead to a fail in revenue. H-statistic value ranges from zero to unity will indicate a monopolistic competition in the market, with higher H-value indicate higher competition. P — R approach assumes market equilibrium, hence, a test for long-run equilibrium is required with ROE or ROA is used as a dependent variable. The same H-statistic value will be recalculated and it is supposed to be significant equal to zero in equilibrium and significant negative in disequilibrium. This is based on the view that in equilibrium, rate of return does not depend on the level of input prices.

5. EMPIRICAL RESULTS 5.1. STRUCTURAL APPROACH The structural approach in measuring market concentration and competition in Vietnamese banking sector taken by the concentration ratio of four and six largest banks in the industry as well as HHI-index, both in term

of total asset, deposit market and loan market, for three years including 2007, 2009 and 2012. Table 3 below summarizes these concentration ratios in Vietnamese banking sector, including CR4, CR6 and HHI-index. As expected, Vietnamese banking sector is dominated by four state-owned commercial banks, which are also four largest banks in the industry both in term of assets, deposit and loan markets. However, there is a clear decreasing trend in total assets, loan and deposit markets. Their assets accounted for 66.7% of the whole banking sector’s total assets in 2007 before being dropped considerably to 53.84% in 2009 and slightly below 50% in 2012. It could be due to the fact that their assets had to be increased as all Vietnamese commercial banks had to meet the capital requirement of at least VND 3 trillion by 31/12/2010, required by Decree 141/2006/NDD-CP by the Government on 22/11/2006. Similarly, this trend is also the same in deposit and loan markets, with the ratio CR4 decreasing from 73.07% in 2007 to 52.6% in 2012 and 71.7% to 59.91%, respectively. When we added 2 largest commercial banks to calculate CR6 ratio, the result was absolutely the same. The significant decrease in the market share of four largest banks and six largest banks suggests the change in the market structure in Vietnamese banking sector to a more competitive nature. Interestingly, the concentration in loan market decreased with a faster pace than that of total asset and deposit market. The main drawback of using “k largest banks” ratio is that it does not account for the number of banks in the market although it could give a direct indication to measure the concentration and competition in the industry. Herfindahl-Hirschman Index is usually used to overcome this disadvantage. The changes in value of HHI in term of total asset, deposit and loan markets confirm a decreasing trend in market concentration and increasing competitive nature in Vietnamese banking sector. HHI-index changed from a moderately competitive nature, with 0.13 in total assets, 0.149 in deposit and 0.166 in loan markets respectively, to an unconcentrated market in 2012, with the value coming to only 0.077; 0.087; 0.106, respectively. To sum up, all these ratios suggested a decreasing trend in the concentration of Vietnamese banking sector as a result of financial liberalization, deregulation and

Review of Business and Economics Studies

Volume 3, Number 1, 2015

loosening entry for foreign banks due to wider assess of the country to global trade. One of the striking features is that loan market seems to have higher competitive nature in comparison with deposit market. It could be due to the fact that domestic credit from banking sector contributes the largest part to economic development and growth, while Vietnamese people still have low access to banking services, particularly in deposit products, as only about 20% of Vietnamese population has bank accounts.

of labors, represented by the ratio of personal expense to total assets while the ratio of total operating expense to total assets is used as proxy for the cost of physical capital, PKit. Some bank specifics factors are included in the model to capture the differences between characteristics of each bank in the sample, including CAPit (the ratio of total equity to total assets); LOANit (the ratio of net loan to total assets) and ASSit (total assets). The ratio of total equity to total assets is used to capture the difference between capital structures of banks. The ratio of net 5.2. NON-STRUCTURAL APPROACH loan to total assets used for measurement of elasticity of This research employs the revenue reduced-form model banks toward loans financing, while total assets is used to conduct H-statistic by Panzar-Rosse approach that is as a proxy of bank economic of scope. usually used in previous empirical researches. As sugHowever, as Panzar-Rosse approach bases on the asgested in literature, all these variables should be used in sumption that the market is under long-run equilibrium, hence, we also estimate the following equation to test natural logarithm form. whether Vietnamese banking system is under equilibln( NITAit )  � 1� 2lnPFit  � 3lnPLit  rium as suggested in the theory. (1)   lnPK  �  lnBSF  4

 j 5

Where NITAit is the ratio of net interest revenue to total assets as the dependent variable; PFit is the ratio of total interest expense to total loanable funds; PLit is the ratio of total personal expense to total asset; PKit is the ratio of total operating expense to total asset; BSFit is the set of bank specific factors that could affect the performance of a commercial bank. The subscript i represents the bank i and the subscript t denotes the time period t. The H-statistic at time t is calculated as

Ht = β1t + β2t + β3t

The choice of variables in this research followed the model suggested by Claessens and Laeven (2003). The main reason of choosing NITAit as the dependent variable, representing the output price in revenue reducedform model, is that the interest-based products is the core function of commercial banks, especially in Vietnam. In term of inputs used by banks, there is a common agreement between literature amongst three main inputs, namely loanable funds (refers to deposit and loans in wholesale market); labor and physical capital (fix assets), according to Rozas (2007); Claessens and Laeven (2003); Sufian and Habibullah (2013). PFit refers to the cost of loanable funds, proxy by the ratio of total interest expense to total loanable funds. PLit refers to the cost

ln(ROAit )  � 1� 2lnPFit  � 3lnPLit   4 lnPK it  �j lnBSFit it

(2)

j 5

In the equilibrium test, ROAit is used as the dependence variable instead of NITAit as suggested by Rozas (2007); Claessens and Laeven (2003), Shaffer (1982) or Bikker and Haaf (2002). We will test the whether E = 0 using a F-test with

Et = α1t + α 2t + α 3t

If we reject the hypothesis of E = 0; then the banking sector is not under equilibrium, hence, using H-statistic to measure the concentration and competition of Vietnamese banking sector is no longer suitable. The idea behind this test is that under equilibrium, returns on bank assets should not be related on input prices. There is a significant difference between mean and median value, especially in ASSit ratio, revealing a high concentration in Vietnamese banking system with the dominance of state-owned commercial banks. One striking feature in the summary statistic table is huge gaps between maximum and minimum value in each variable together with high standard deviation that could result from low competition level in the banking sector. The earlier empirical researches tended to use a Pooled Ordinary Least Square method to estimate the H-statistic. However, this method could give a biased and inefficient parameter estimates as well as inaccurate standard errors, leading to heterogeneity bias, especially with an unbalanced panel data as used in this research. Hence, there are two popular panel estima-

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 4. Summary statistic of all variables.

Mean Median Maximum Minimum Std. Dev.

NITA

LOAN

CAP

ASS

ROA

3.148371 3.1105 7.259 -0.193 1.061202

7.167903 7.05 14.71 1.12 2.450226

0.722075 0.674473 1.93752 0.043764 0.32038

0.858705 0.747599 4.926743 0.06558 0.459419

50.67881 52.327 84.477 2.48 18.49874

11.7789 9.1025 94.286 1.08 10.78547

112783.5 56880.02 1212403 226.1568 155621.6

1.313317 1.338 6.403 -5.993 0.978742

Table 5. F-test for Fixed — effect.

Redundant Fixed Effects Tests Equation: EQ03 Test period fixed effects Effects Test

Statistic

Period F Period Chi-square

d.f. 3.303912 29.983801

Prob. -9,169 9

0.001 0.0004

Table 6. Breusch and Pagan Lagrangian multiplier test for random effect.

Breusch and Pagan Lagrangian Multiplier test for random effects lnNITAit[Year,t] = Xb + u[Year] + e[Year,t] Estimate result

lnNITAit e u

Var 0.132301 0.078721 0.007844

Test

Var(u) = 0

sd=sqrt(Var) 0.363732 0.2805733 0.0885633

chibar2(01) = 6.76 Prob>chibar2 = 0.0047 tor approaches usually used to overcome these limits, namely fixed-effect and random-effect models. In order to produce stable results, the model is firstly tested by F-test and LM-test (Breusch and Pagan Lagrangian Multiplier test) to decide whether Pooled OLS or fixed effect and random effect method could give better results, respectively (Table 5 and Table 6). The results suggest that both fixed-effect and random-effect models would provide more stable results than that of Pooled OLS. The next step is deciding whether fixed-effects model could be more appropriate than random-effects

model or vice versa. Hausman test is used in Table 7 with the null hypothesis in favor of using randomeffects and the alternatives supports fixed-effects approach for estimations. The p-value of 0.1018 in result table indicates that we cannot reject the null hypothesis at 10 percent of significance, hence, we should go with random-effects model in this research. Finally, as the panel data used in this paper is a short panel data, hence, a “within” random-effect to explore difference in error variance components across time-period is considered.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 7. Hausman test for random effect and fixed effect.

Correlated Random Effects - Hausman Test Equation: EQ02 Test period random effects Test Summary

Chi-Sq. Statistic

Period random

Chi-Sq. d.f.

10.592843

Prob. 6

0.1018

Table 8. Equilibrium test result.

Wald Test: Equation: Equilibrium test Test Statistic F-statistic Chi-square

Value

df 1.390236 1.390236

Probability (1, 168) 1

The equation (2) is estimated firstly in order to test for the market equilibrium assumption required to use Panzar-Rosse method. Table 5 gives a short result, using Wald test with the null hypothesis being market equilibrium (E = 0). The value of both F-statistic and Chisquare value failed to reject the null hypothesis, hence, we could use Panzar-Rosse approach to estimate the concentration and competition of Vietnamese banking sector appropriately. Finally, Table 9 below shows the results of equation (1) estimations using “within” random-effects models for the whole samples and four sub-samples concerning state-owned feature and foreign-owned feature. The H-statistic in overall model and both four subsamples take values between 0 and 1, indicating a monopolistic competitive nature in Vietnamese banking sector. The null hypothesis of monopoly competitive nature (H = 0) and perfect competition in banking sector (H = 1) tested by Wald test are rejected with statistical significance, except a highly significant level for the competition between domestic commercial banks. Hence, if everything is kept constant, empirical findings suggest that Vietnamese commercial banks are competing in a monopolistic competitive nature. It is worth noting that the higher the H-statistic, the higher the degree of competition in the sector. The Hstatistic for overall sample is as 0.259172, reconfirming the findings of high concentration and low competition in Vietnamese banking sector in structural approach via HHI-index. Additionally, state-owned commercial banks are competing more intensively in comparison

0.24 0.2384

with joint-stock commercial banks while whole foreign banks compete harder than domestic banks. One striking feature of the H-statistic value is that it reveals, to some extent, the degree of competitiveness of a commercial bank as it measures the elasticity of total interest revenue due to changes in input prices. Hence, the higher the H-statistic, the more competitive a bank is as it could turn 1 percent of increase in input prices to a higher degree of total revenue. Therefore, in state-owned feature of banks, state-owned banks have much higher competitiveness in comparison with jointstock commercial banks. This is an unsurprising result as state-owned banks have much more comparative advantages than joint-stock commercial banks such as economies of scope and scale, higher supports from central banks and governments, wider branches networks, longer operational time with better customer bases. In term of foreign-owned feature, wholly foreignowned commercial banks seem to have higher competitive behaviors than domestic competitors. This could be due to the fact that Vietnamese domestic banks are still in an early stage of development as most of them have been operating for about 20 years since 1990. The signs of the coefficients of cost of loanable funds PFit, cost of labor PLit and cost of physical capital PKit give implications about the impacts of input prices to the total revenue of banks. An increase in the cost of loanable funds tends to reduce the total revenues of banks, except for the case of state-owned banks. The costs of loanable funds actually have positive effects on total revenue of state-owned banks as they have more

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 9. Result output. Variable Constant

Overall

State-owned feature State-owned banks Joint-stock banks

Whole foreign-owned feature Domestic banks

Foreign banks

0.582957 (-1.506678) -0.173652*** (-2.70297) 0.325263*** (5.300601) 0.107561 (1.485205) 0.053321*** (4.320089) 0.048753** (2.264953) -0.009399 (-0.247538) 0.358254 18.1196 0.259172 12.73942 0.0000 Reject 104.0904 0.0000 Reject Monopolistic

1.273779 0.825657* 1.36585*** -1.731737*** (1.201556) (1.792558) (3.224943) (-3.969901) 0.282036** -0.179307** -0.307278*** 0.066052 lnPF (2.061729) (-2.469979) (-3.845358) (1.297268) lnPL 0.189031** 0.324523*** 0.388387*** -0.151444 (2.159762) (3.890277) (5.424917) (-1.51058) lnPK -0.069673 0.134813 0.054114 0.387355*** (-0.602042) (1.570821) (0.682795) (3.999428) -0.172534** 0.236272*** 0.157837** 0.470507*** lnCAP (-2.161917) (3.600346) (2.47875) (8.484036) lnASS 0.084972 0.02595 0.013697 0.065797* (1.458519) (0.955573) (0.595581) (2.000372) -0.33437 -0.013639 0.000343 0.252289*** lnLOAN (-1.383279) (-0.326311) (0.008215) (3.963006) 0.573905 0.365683 0.287346 0.780673 Adjusted R-square F - statistic 9.081361 15.12421 11.81932 13.45794 H - statistic 0.401394 0.280029 0.135223 0.301963 10.95635 10.04946 2.911799 13.53325 Wald test (H=0) 0.0024 0.0019 0.0899 0.0022 (p - value) Result Reject Reject Reject Reject 24.36696 66.4302 119.0883 72.3195 Wald test (H=1) 0.0000 0.0000 0.0000 0.0000 (p - value) Result Reject Reject Reject Reject Test result Monopolistic Monopolistic Observations 185 37 148 162 23 Note: All of these regressions used "within" random effect to calculate the value of H under Panzar and Rosse approach These selected confidence level are 90% (*); 95% (**) and 99% (***) respectively. Values in parenthese are t-value and evaluated by White test for heteroscedasticity.

Source: Result output from Eview 6 software.

Table 10. H-statistic of some Asian countries.

China Hongkong Indonesia Malaysia Philippines Singapore Thailand Average Asia Nation 0.508 0.462 0.441 0.614 0.673 0.349 0.361 H-Statistic 0.324 Source: Setiyono and Tarazi, 2014.

comparative advantages in raising deposits and wholesale funding due to their economies of scope and scale together with better consumer base than their competitors. The cost of labor has positive signs in all the models, implying that an increase in the cost of labor could lead to higher total revenue with statistically significant level. In contrast, only in foreign-owned banks, cost of physical capital has significantly positive impacts on the total revenue. It could be due to the fact that operating cost could contribute a large part to the performance of foreign-owned banks as they should have to pay higher initial cost in the new market. Turning to the impacts of bank specific factors, only the capital structure of banks could influence the to-

tal revenue of banks with positive signs in almost all models, except for the case of state-owned banks. This shows that better capitalization leads to lower costs of going bankrupt, thus reduces the cost of funding overall. In the case of state-owned banks, the negative sign of coefficient could results from the increase of opportunity costs as they already have better capitalization and lower bankruptcy cost in comparison with joint-stock banks. The positive sign of lnASSit in overall model confirms the existence of economies of scope and scale in Vietnamese banking sector while only foreign-owned banks expect a rise in their ratio of loans to total assets as it could be a signal of higher market penetration in host country.

Review of Business and Economics Studies In the comparison with the H-statistic of other Asia countries collected from the work of Setiyono and Tarazi (2014), provided in Table 10, Vietnamese banking sector seems to have a lower level of competition in the banking sector as well as a lower level of competitiveness of commercial banks. This could be a disadvantage of Vietnamese commercial banks in the international competition of financial and banking services, especially in the unavoidable wave of financial liberalization.

Volume 3, Number 1, 2015 Policy Research Working Paper Series 4656, The World Bank.

Berger, A. N., Klapper, L. F., & Turk-Ariss, R. (2009). Bank Competition and Financial Stability. Journal of Financial Services Research, 35 (2), 99–118. Bikker, J., & Groeneveld, J. (2000)., Competition and concentration in the EU banking Industry. Kredit und Kapital, 33, 62–98. Bikker, J., & Haaf, K. (2002). Competition, concentration and their relationship: An empirical analysis of the banking industry. Journal of Banking & Finance, 26 (11), 2191–2214. Bikker, J., Shaffer, S., & Spierdijk, L. (2012). Assessing Competition

6. CONCLUSION Vietnamese banking system is under a large reforming and restructuring progress to create a safely proficient system and improve the efficiency of commercial banks. Enhancing competitiveness and strength of domestic commercial banks is a crucial mission of policy makers and supervisors to face with unavoidable globalization in financial and banking services market. Obviously, understanding the current state of the competitive nature in banking sector is the first task. Empirical findings in both structural and non-structural approaches revealed that Vietnamese banking sector is under monopolistic competitive nature, but still close to the monopoly market with high concentration and low competition. Fortunately, the competition has tended to increase recently, thanks to the higher access of the economy to the international field with lower entry to foreign institutions and lower protective policies toward domestic banks. Additionally, the equilibrium test indicated that the industry is in equilibrium. State-owned commercial banks and wholly foreignowned banks have better competitiveness in comparison with their competitors, joint-stock commercial banks and domestic banks. The effect of cost of loanable fund and total asset to total revenues suggest the existence of economies of scope and scale in Vietnamese banking system while an increase in the capitalization of joint-stock banks could improve their competitiveness and total revenue. To sum up, as indicated by H-statistic and HHI-index, Vietnamese banking sector still has much room for improvement in the competitive nature as we still have low competition in comparison with that of other Asian countries. The regulators should continue recent financial liberalization in financial and banking services markets to further improve the competitive market behavior among commercial banks.

with the Panzar-Rosse Model: The Role of Scale, Costs, and Equilibrium. The Review of Economics and Statistics, 94 (4), 1025–1044. Boot, A. W., & Thakor, A. V. (2000). Can Relationship Banking Survive Competition? Journal of Finance, American Finance Association, 55 (2), 679–713. Boyd, J. H., & Nicolo, G. D. (2005). The theory of Bank Risk Taking and Competition Revisited. Journal of Finance, 60 (3), 1329–1343. Bresnahan, T. F. (1989). Empirical studies of industries with market power. In R. Schmalensee, & R. Willig (Eds.), Handbook of Industrial Organization (1st ed., Vol. 2, pp. 1011–1057). Elsevier. Casu, B., & Girardone, C. (2006). Bank Competition, Concentration And Efficiency In The Single European Market. Manchester School, University of Manchester, 74 (04), 441–468. Claessens, S., & Laeven, L. (2004). What Drives Bank Competition? Some International Evidence. Journal of Money, Credit and Banking, 36 (3), 563–583. Gajurel, & Pradhan. (2012). Concentration and Competition in Nepalese banking. Journal of Business, Economics and Finance, 1 (1). Gelos, G., & Roldos, J. (2004). Consolidation and Market Structure in Emerging Market Banking Systems. Emerging Market Review, 5 (1), 39–59. Gudmundsson, R., Ngoka-Kisinguh, K., & Odongo, M. T. (2013). The Role of Capital Requirements on Bank Competition and Stability: The Case of the Kenyan Banking Industry. Kenya Bankers Association — KBA Centre for Research on Financial Markets and Policy Working Paper Series. Jiménez, G., Lopez, J. A., & Saurina, J. (2007). How does competition impact bank risk-taking? Federal Reserve Bank of San Francisco. Mishkin, F. S. (1999). Financial consolidation: Dangers and opportunities. Journal of Banking & Finance, 23 (2–4), 675–691. Panzar, J. C., & Rosse, J. N. (1987). Testing for “monopoly” equilibrium. The Journal of Industrial Economics, 35 (4), 443–456. Pereraa, S., Skullya, M., & Wickramanayake, J. (2006). Competition and structure of South Asian banking: a revenue behaviour approach. Applied Financial Economics, 16 (11), 789–801. Rozas, L. G. (2007). Testing for competition in the Spanish banking industry: The Panzar-Rosse approach revisited. Banco de Espana Working Paper Series. Sufian, F., & Habibullah, M. S. (2013). Financial sector consolidation

REFERENCES Allen, F., & Gale, D. (2000). Financial Contagion. Journal of Political Economy, 108 (1), 1–33. Beck, T. (2008). Bank competition and financial stability: friends or foes?

and competition in Malaysia: An application of the Panzar-Rosse method. Journal of Economic Studies, 40 (3). Weill, L. (2004). Measuring Cost Efficiency in European Banking: A Comparison of Frontier Techniques. Journal of Productivity Analysis, 21 (2), 133–152.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Remittances and Economic Growth in Vietnam: An ARDL Bounds Testing Approach* Dang The TUNG Banking Academy of Vietnam dangtunghvnh@gmail.com Abstract. This paper investigates the relationship between remittances and economic growth in Vietnam during the period 1996–2012. To do that, we applied an autoregressive distributed lag (ARDL) bounds testing approach to co-integration; in addition, an error correction model derived from the ARDL model was used to examine short-run dynamics among variables. We provide empirical evidence that remittances have significant positive effects on economic growth in both the short and long run. Аннотация. Целью данной работы является исследование взаимосвязи денежных переводов с экономическим ростом во Вьетнаме в период с 1996 по 2012 гг. Основным методом исследования является выявление коинтеграции всплесков авторегрессии распределенного лага (ARDL). В дополнение используется метод коррекции ошибок (ECM), основанный на модели ARDL, с целью выявления связи между переменными в краткосрочном периоде. В заключение мы приведем эмпирические свидетельства значимой и положительной взаимосвязи денежных переводов с экономическим ростом как в долгосрочном, так и в краткосрочном периоде. Key words: Vietnam, remittances, economic growth, ARLD.

1. INTRODUCTION From 1996 to 2012, along with impressive development of the economy, Vietnam experienced a boom in remittance inflows, which led the country to become one of the largest remittance-receiving countries in the world. Moreover, remittances have been one of the largest sources of external private finance for the country, and in comparison with other financial flows such as foreign direct investment (FDI) and official development assistance (ODA), they have been more stable and predictable. Remittances therefore have played an important role in the Vietnamese economy in the context of a persistent trade deficit, excessive government expenditure, a considerable funding gap and fluctuations in FDI and ODA flows as ratios of GDP. In some years, the share of remittances in GDP was larger than that of FDI in GDP. Indeed, between 2002 and 2012, the remittances to GDP ratio far exceeded the ratio of ODA to GDP (Appendix Figure 1). However, there is no consensus

on the impact of remittances on economic growth in Vietnam. Hence, we conducted research to investigate the impact of remittances on economic growth in Vietnam in the 1996–2012 period, in order to examine the roles of remittances in the Vietnamese economy. The study has two main findings. Firstly, remittances are positively and significantly correlated with economic growth in the country in both the short and long run. Secondly, remittances have de facto been a substitute for financial services in spurring economic growth. These results contribute to literature on the relationship between remittances and economic growth in recipient countries and provide more evidence on whether remittances and financial development act like substitutes or are complementary in promoting GDP growth. The rest of the paper is organized as follows. Section 2 provides literature on the impact of remittances on economic growth in recipient countries. Section 3 discusses methodology to be applied in the study. Section 4 presents empirical results. The last Section concludes the study.

* Влияние денежных переводов на экономический рост во Вьетнаме.

Review of Business and Economics Studies

2. LITERATURE REVIEW

a similar method with the study in 2005, in another study in 2009, using data of 100 developing countries, they show that remittances promote economic growth in countries with less developed financial systems since significant negative coefficients on interaction terms are found. Together with generally negative outcomes above, a series of studies also find a positive impact of remittances on economic growth in recipient countries. Some studies show a positive correlation between remittances and financial development, thus promoting economic growth. Using data of 109 developing countries in the period 1975–2007, a study conducted by Aggarwal, Demirgüç-Kunt and Martínez Pería (2011) indicates that remittances have positive impacts on ratios of bank deposits to GDP and banking credit to the private sector to GDP. In other words, remittances are positively correlated with financial development in the recipient countries. Like the study carried by the IMF (2005), using total remittances, by applying the ordinary least squares (OLS), Faini (2006) conducts a regression on a data set of 68 countries from 1980 to 2004 and shows that the impact of remittances on economic growth is statistically significant positive. Nevertheless, by conducting the instrumental variable method, the study finds positive but insignificant effect of remittances on economic growth. A study by Catrinescu, Leon-Ledesma, Piracha and Quillin (2006) covers 114 countries in the 1991–2003 period and finds a positive correlation between total remittances and economic growth. In addition, a study by the World Bank (WB) (2006) provides more empirical evidence to support those above-mentioned studies. The WB study uses a data set of 67 countries between 1991 and 2005 and indicates that remittances have a positive effect on economic growth in recipient countries. By dividing Latin American and Caribbean countries into lower and upper income countries, Ramirez and Sharma (2008) apply Fully-Modified OLS methodology and indicate that remittances positively and significantly affect economic growth in those countries. However, the effect of remittances is higher in upper income countries because remittance-recipient households in such countries have more opportunities to use remittances for profitable investments. Another study conducted by Fayissa and Nsiah (2010) for 18 Latin American countries in the period 1980–2005 illustrates a positive and significant impact of remittances on economic growth since remittances are utilized for investment in the context of the less developed financial system. In addition, remittances also help ease liquidity constraints in those countries.

The relationship between remittances and economic growth has shown mixed results and has been a controversial issue both among academics and policy makers. By using a data set of 83 countries in the 1970–1998 period, Chami, Fullenkamp and Jahjah (2003) run panel regressions of real GDP per capita growth rate on both workers’ remittances as a share of GDP and annual change in this ratio1. This study shows significant negative effects of remittances on economic growth. Furthermore, in order to account for endogeneity problem, an instrumental variable method is employed. This method also finds that annual changes in remittances negatively influence economic growth in remittance-receiving countries. Moreover, another study by Chami, Barajas, Cosimano, Fullenkamp, Gapen and Montiel (2008) uses data of 108 countries over the 1970–2004 period, and the instrumental variable method. The study indicates that it is not always clear that the direct impact of workers’ remittances on economic growth is positive. Additionally, by using interaction between workers’ remittances and financial depth2, the study finds evidence that a greater remittances to GDP ratio together with higher development of the financial system may be connected to lower economic growth rates since coefficients on interaction terms in most regressions tend to be negative and significant. A study by the International Monetary Fund (IMF) (2005) uses the total remittances variable, which is the sum of workers’ remittances, employee compensations and migrant transfers; and similar to Chami et al. (2003, 2008), the IMF study also applies the instrumental variable method; in particular, two instruments for remittances are “distance from the migrants’ home to the main destination country, and a dummy measuring whether the home and main destination country shared a common language”3. Using data of 101 countries in the period 1970–2003, the study finds that total remittances do not have a statistically significant impact on economic growth. Another study by Giuliano and Ruiz–Arranz (2005) collects the data of 73 countries over the period 1975–2002, then calculates the five-year average for all variables to eliminate business cycles. These researchers find that there is no significant impact of remittances on economic growth. However, applying Other independent variables are ratio of investment to GDP, inflation rate, net private capital flows to GDP ratio and regional dummies. 2 M2 to GDP ratio represents financial depth in the recipient countries 3 Chami et al., 2008

Volume 3, Number 1, 2015

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Furthermore, according to Mohamed and Sidiropoulos (2010) in their study for seven Middle East and North Africa countries, the level of development of the financial system and the quality of institution are critical factors for the positive correlation between remittances and economic growth. Moreover, they also argue that high institutional quality helps remittances to be used more efficiently and remittances help to overcome liquidity constraints, thus promoting economic growth in recipient countries. Supporting positive views of the effect of remittances on economic growth, some studies have been conducted to show the relationship between remittances and economic growth in Pakistan. Javid, Arif and Qayyum (2012) report positive and significant effect of remittances on economic growth by empirically testing data from 1973 to 2010 with the ARDL approach. Waheed and Aleem (2008) use co-integration and the error correction model to test impact of remittances on economic growth in the long and short run, respectively from 1981 to 2006. The study indicates that remittances have a significant negative influence on economic growth in the long run, but in the short run a positive and significant correlation is found. Moreover, with the same purpose as Waheed and Aleem (2008), Ahmed, Zaman and Shah (2011) use a bound testing approach and the error correction model with annual data from 1976 to 2009, and indicate that remittances significantly and positively affect economic growth in both the short and long run in Pakistan.

3. METHODOLOGY Based on the growth literature, the hypothesized model specification is as follows:

lnGDPt  f lnREM t ,� lnX t 

(1)

where lnGDP: Real GDP in natural logarithm; lnREM: Remittances as a percentage of GDP in natural logarithm; lnX: Set of control variables: (i) ratio of credit provided by the banking sector to the private sector to GDP (lnCRD), (ii) FDI to GDP ratio (lnFDI), (iii) openness as total trade (sum of exports plus imports of goods and services) to GDP ratio (lnTRADE) and (iv) interaction between remittances and financial sector development (lnREMlnCRD) are all in natural logarithms. In order to investigate the relationship between remittances and economic growth in Vietnam, we apply the ARDL bounds testing approach to co-integration developed by Pesaran, Shin and Smith (2001). Indeed, that method has become more popular in recent studies. Additionally, the error correction model can be made from the ARDL approach. The error correction model “integrates the short-run dynamics with the long-run equilibrium” while keeping long-run relationship information4. By applying the ARDL bounds testing approach to co-integration, the ARDL model for economic growth is constructed as follows: p

i 1

i 0

lnGDPt  0 1lnGDPt 1 2lnREM t 1 nlnX t 1  i lnGDPt  i  i lnREM t  i  i lnX t  i  ut (2) where p, q and m are the optimal lag length i , �i , and i are short-run dynamic coefficients of the ARDL model 1 ,�2 ,…, � � n a re long-run multipliers is the first difference operator 0 � is constant term, and ut � is white noise error. In the first stage, Equation (2) is estimated by using the OLS method and the presence of long-run relationship among variables is detected based on an F-test (Wald-test) by setting the coefficients of one period lagged level of the independent variables equal to zero. The null hypothesis of no co-integration among variables in � 0,  � � 2 ≠ 0,…, � � n ≠ 0. In the Equation (2) is H0: 1 = �2 =…= n �= 0 against the alternative hypothesis H1: 1 ≠ 4

Shrestha and Chowdhury, 2005

Review of Business and Economics Studies

Volume 3, Number 1, 2015

order to reject or accept H0, the value of the F-test is compared with critical value bounds. For a small sample size between 30 and 80 observations, critical values computed by Narayan (2005) are appropriate to be used since critical values calculated by Pesaran et al. (2001) are applied for a large size of sample ranging from 500 to 40,000 observations5. For a given significance level, Pesaran et al. (2001), and Narayan (2005) generated two different sets of critical values. Lower critical bound values are calculated based on the assumption that all of the variables in the regression equation are I (0), while upper critical bound values are calculated based on the assumption that all of the variables in the regression equation are I (1)6. Therefore, “the two sets of critical values provide critical value bounds for all classification of the regressors into purely I (1), purely I (0) or mutually co-integrated”7. As a result, if a computed F-statistic lies outside the critical value bounds, the null hypothesis, H 0, is rejected which means there exists a long-run relationship among the variables concerned regardless of the order of integration of the variables. In contrast, if the computed F-statistic falls inside those bounds, the test is inconclusive8. In the ARDL model, the optimal lag lengths for independent variables can be selected based on the Akaike k information criterion (AIC) or the Schwarz Bayesian criterion (SBC) by searching across ( p  1) ARDL models9;

and smaller value of SBC or AIC is a better result. In this paper, we use SBC to decide the optimal lag lengths for ARDL model in the Equation (2). Moreover, according to Shrestha and Chowdhury (2005), as cited from Pesaran and Pesaran (1997), for quarterly data, 4 lags can be set as the maximum lag. If a long-run relationship (co-integration) among variables is found, the next stage is to examine the longrun and short-run relationships among selected variables. To test long-run relationship among the variables based on the ARDL approach, the following equation is built up p

i 1

i 0

lnGDPt  1  i lnGDPt  i  i lnREM t  i  �i lnX t  i � t �

(3)

Moreover, in order to examine the short-run dynamics from the ARDL model and to recheck the existence of co-integration found in the ARDL model, we also estimate the error correction model which is developed as follows: p

i 1

i 0

lnGDPt  2  i lnGDPt  i  i lnREM t  i  i lnX t  i ECM t 1 t

(4)

where the error correction term (ECM) can be expressed as in the following equation p

i 1

i 0

lnGDP   ECM t  lnGDPt   � 1   �  i t i � i lnREM t i �  � i lnX t i

(5)

If the coefficient of the ECM in the Equation (4) is negative and significant, there is a long-run relationship among the variables; and it also represents the speed of adjustment to the equilibrium. The sign of the coefficient on the interaction between remittances and financial depth indicates whether the level of development of the financial system influences the effect of remittances on economic growth. A negative coefficient shows that in country with less developed financial system, remittance inflows are more effective in promoting economic growth. To put it another way, remittances and level of financial depth act like substitutes. On the other hand, a positive coefficient provides evidence of complementarity between remittances and financial development10. More importantly, to determine the reliability of the ARDL results, the serial correlation, functional form, heteroskedasticity and normality of the ARDL model need to be checked. Additionally, the cumulative sum of recursive residuals test based on the cumulative sum of the recursive residuals is conducted. “This option plots the cumulative sum together with the 5% critical lines. The test finds parameter instability if the cumulative Narayan, 2005 Giles, 2013 7 Pesaran et al.,2001 8 ibid. 9 ibid., and p — maximum lag length, k — a number of variables 10 Giuliano and Ruiz–Arranz, 2009 5

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 2. ARDL co-integration tests. ARDL co-integration test Lag length

F-statistic

ARDL (2,4,2,3,0,4)

4.924** Critical values *

Significance level

Lower bounds I (0)

Upper bounds (I1)

1 percent

3.783

5.300

5 percent

2.835

4.090

10 percent

2.397

3.543

Diagnostic tests

2NORMAL  0.5502 (0.759493)

2SERIAL 

2BPG  3.212655 (0.2006)

2 WHITE 

12.62015 (0.9871)

21.43866 (0.7190)

Note: *, **, *** indicate significance at 10, 5 and 1 percent, respectively. Numbers in () are P-values * Cited from Narayan, 2005

sum goes outside the area between the two critical lines”11. The cumulative sum of squares of recursive residuals test also needs to be done. “The cumulative sum of squares is generally within the 5% significance lines, suggesting that the residual variance is somewhat stable”12.

4. EMPIRICAL RESULTS We first conducted unit root tests to investigate the order of integration of the variables and check that none of them is I (2). By applying an Augmented Dickey Fuller (ADF) test, we found that all the variables are I (1) at the 1 percent significance level, and there is no evidence of I (2), which satisfies conditions for applying the ARDL model. Unit root test results and decisions on the order of integration are presented in Appendix Table 1. The next step is to examine the presence of a long-run relationship or co-integration among the variables. To do that, using the OLS method, we estimate the Equation (2) and conduct the F-test by restricting the coefficients of one period lagged level of the independent variables equal to zero. Based on SBC, the optimal lag length for each variable in the ARDL model is chosen; it turns out that our model is in the form of ARDL (2,4,2,3,0,4) 13. The F-statistic, the optimal lag length, and diagnostic test results are displayed in Table 2. Table 2 shows that the computed F-statistic EViews 6 User’s Guide II ibid. 13 The optimal lag length of LNGDP, LNREM, LNCRD, LNFDI, LNTRADE and LNREMLNCRD are 2, 4, 2, 3, 0 and 4, respectively. 11 12

falls outside the critical value bounds at the 5 percent level of significance, which implies that we can reject the null hypothesis of no long-run relationship among the variables. Furthermore, our model also passes all the relevant diagnostic tests such as normality, serial correlation, heteroskedasticity and white noise. According to Pesaran et al. (2001), a key presumption for the ARDL model is that the errors of the Equation (2) must be serially independent, and that requirement may influence our final selection of the optimal lags for the variables in the model. Our model therefore meets the requirement of no serial correlation or does not suffer from serial correlation. As noted above, in order to test for parameter stability of model, the “cumulative sum of recursive residuals” and “cumulative sum of squares of recursive residuals” tests are also undertaken. Results for these tests are shown in Figures 2–3. As can be seen from Figure 2 and 3, since the cumulative sum of recursive residuals and the cumulative sum of squares of recursive residuals fall between the 5 percent significance lines, the parameters of the model are stable over time. By employing the ARDL bounds testing, we find evidence of co-integration among the variables; we therefore conduct an estimation of the long-run relationship among the variables. To put it another way, Equation (3) is estimated to show co-integration among the variables in our model. Econometric results for the long-run model are displayed in Table 3. In order to investigate the robustness of the short-run dynamics from the ARDL model and

Review of Business and Economics Studies

Volume 3, Number 1, 2015

1.4

1.2

1.0 0.8

0.6

0.4

-5

0.2

-10

0.0

-15 -20

-0.2 04

CUSUM

-0.4

5% Significance

Figure 2. Plot ofofcumulative sum Figure 2. Plot cumulative sum of recursive residuals. of recursive residuals.

CUSUM of Squares

5% Significance

Figure of cumulative sum of Figure 3. Plot3. of Plot cumulative sum of squares of recursive residuals. squares of recursive residuals.

Table 3. Econometric results for the long-run model. Dependent variable: LNGDP Independent variables

Coefficients

Independent variables

Coefficients

LNREM

0.1145** (2.1116)

LNTRADE

0.0585*** (2.8020)

LNCRD

0.0930*** (3.1748)

LNREMLNCRD

-0.0226** (–2.2562)

LNFDI

0.0022 (0.5371)

Note: Numbers in () are t-statistics *, **, *** indicate significance at 10, 5 and 1 percent, respectively

to recheck presence of the long-run relationship detected in the ARDL model, we proceed with the estimation of the error correction model 14 , and its results are presented in Table 4. As shown in the Table, the coefficient on the error correction term, ECM (–1), is significant and negative at the 1 percent level, which confirms the existence of the long-run relationship among the variables in our model found by the F-test. In addition, it also indicates a very speedy convergence to long-run equilibrium of the model. Tables 3 and 4 show that in Vietnam, the remittances to GDP ratio has a significant positive impact on economic growth in both the short and long run. In particular, a 10 percent increase in the ratio of remittances to GDP is associated with a 1.1 percent growth in real GDP in the short run, and leads The error correction model is derived from the ARDL model as noted above.

to a 1.15 percent rise in economic growth in the long run. There are several ways to interpret our results. Firstly, only a small proportion of remittances, around 15 percent, are used for consumption. Secondly, unofficial data reports that 15 to 20 percent of remittance inflows go to bank deposits. These savings can be used for investment purposes, thus resulting in enhanced economic growth. Lastly, Hernandez-Coss (2005) points out that Overseas Vietnamese (Viet Kieu) send their income back to the country for investment and business purposes. Moreover, according to Sakr (2006), remittance flows to Vietnam are heavily affected by the portfolio decisions of remitters. In other words, most remittance flows to the country are devoted to investment purposes, thus promoting economic growth. In addition, by using Vietnam Household Living Standards Survey (VHLSS) 2002 and 2004, Nguyen (2008) supports the argument of Sakr (2006) and reveals that a large part of remittances are used for

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 4. Econometric results for the error correction model. Dependent variable: ΔLNGDP Independent Variables ΔLNREM

Coefficients

Independent Variables

0.1105** (2.5886)

Coefficients

ΔLNFDI

0.0103*** (2.8024)

ΔLNREM (–1)

0.0311 (0.7353)

ΔLNFDI (–1)

0.0173*** (3.4751)

ΔLNREM (–2)

0.0956** (2.3344)

ΔLNFDI (–2)

0.0068 (1.3105)

ΔLNREM (–3)

0.0285 (0.7813)

ΔLNFDI (–3)

0.0076** (2.1832)

ΔLNREM (–4)

-0.1235*** (–3.641)

ΔLNTRADE

0.0890*** (4.072)

ΔLNCRD

0.1008*** (3.835)

ΔLNREMLNCRD

-0.0212** (–2.6773)

ΔLNCRD (–1)

-0.0634* (–1.9653)

ΔLNREMLNCRD (–1)

-0.0072 (–0.9001)

ΔLNCRD (–2)

0.0588* (1.8144)

ΔLNREMLNCRD (–2)

-0.0194** (–2.4831)

-1.2592*** (–5.2811)

ΔLNREMLNCRD (–3)

ECM (–1)

ΔLNREMLNCRD (–4)

-0.0079 (–1.1796)

0.0208*** (3.2363)

Diagnostic tests

2NORMAL  0.651212 [0.722089]

2SERIAL 

2BPG  0.8686 [0.7972]

2 WHITE 

10.97975 [0.9632]

16.49043 [0.7415]

Note: Numbers in () are t-statistics, and in [] are P-values *, **, *** indicate significance at 10, 5 and 1 percent, respectively

savings and investment. Indeed, in 2012, around 70 percent of remittances were allocated to business and production to help enterprises and household businesses overcome difficulties. As can be seen, FDI, as a part of total investment, has significant positive impact on economic growth in the short run but does not have an effect in the long run. It is an interesting finding and is a puzzle. Moreover, our findings show that the openness of the economy significantly and positively influences economic growth in both the short

and long run. Since implementing the open-door policy, Vietnam has been proactive in taking part in the global market and consequently, has attained an impressive growth in trade. Joining the international market provides Vietnam many opportunities to foster its economy. The country has succeeded in accessing new markets rather than depending on existing markets. Finally, Tables 3 and 4 state that coefficients on the interaction between remittances and financial depth are significant and negative in both the short

Review of Business and Economics Studies and long run. This finding is consistent with the literature since the Vietnamese financial system is still less developed. Moreover, this result provides evidence of substitutability between remittances and financial development, which supports findings by Giuliano and Ruiz–Arranz (2009) and other studies. By easing the liquidity constraints, remittances tend to offset the inefficiency of the financial market. Put another way, remittances have de facto been a substitute for financial services in spurring economic growth.

Volume 3, Number 1, 2015 Cointegration and PMG Techniques”, The Romanian Economic Journal, Year XIV, no. 42, 3–23.

Duasa, J. (2007), “Determinants of Malaysian Trade Balance: An ARDL Bound Testing Aprroach”, Journal of Economic Cooperation 28,3, 21–40. Faini, R. (2006), “Migration and Remittances: The Impact on the Countries of Origin”, Rome: University of Rome. Fayissa, B., & Nsiah, C. (2010), “Can Remittances Spur Economic Growth and Development? Evidence from Latin American Countries (LACs)”, Middle Tennessee State University, Department of Economics and Finance Working Paper Series. Giles, D. (2013), “ARDL Models — Part II — Bounds Tests”,

5. CO N C L U S I O N S In order to examine the impact of remittances on economic growth in Vietnam, we applied the ARDL bounds testing approach to co-integration developed by Pesaran et al. (2001), using quarterly data from 1996 to 2012. The error correction model derived from the ARDL model was used to investigate short-run dynamics among the variables. In the paper, two main results were found. Firstly, significant and positive correlation between remittances and economic growth was detected in both the short and long run. Secondly, in line with previous studies, our findings indicate that in Vietnam, like in other countries with less developed financial systems, remittances and financial development have acted as substitutes to enhance economic growth.

http://davegiles.blogspot.jp/2013/06/ardl-models-part-iibounds-tests.html. Giuliano, P., & Ruiz-Arranz, M. (2005), “Remittances, Financial Development, and Growth”, Washington, DC: Interntional Monetary Fund Working Paper WP/05/234. Giuliano, P., & Ruiz-Arranz, M. (2009). “Remittances, Fnancial Development, and Growth”, Journal of Development Economics 90, 144–152. Hernandez-Coss, R. (2005), “The Canada-Vietnam Remittance Corridor: Lessons on Shifting from Informal to Formal Transfer Systems”, Washington, DC: World Bank Working Papers No. 48. International Monetary Fund. (2005), “World economic outlook: Globalization and External Imbalances”, Washington, DC: The International Monetary Fund. Javid, M., Arif, U., & Qayyum, A. (2012), “Impact of Remittances on Economic Growth and Poverty”, Academic Research International 2, No. 1. Mohamed, S. E., & Sidiropoulos, M. G. (2010), “Does Workers’ Remittances Affect Growth: Evidence from Seven MENA La-

REFERENCES

bor Exporting Countries”, International Research Journal of Finance and Economics, 181–194.

Aggarwal, R., Demirgüç-Kunt, A., & Martínez Pería, M. S. (2011),

Narayan, P. K. (2005), “The Saving and Investment Nexus for

“Do Remittances Promote Financial Development”, Journal of

China: Evidence from Cointegration Tests”, Applied Econom-

Development Economics 96, Issue 2, 255–264. Ahmed, J., Zaman, K., & Ali Shah, I. (2011), “An Empirical Analysis of Remittances-Growth Nexus in Pakistan Using Bounds Testing Approach”, Journal of Economics and International Finance 3 (3), 176–186. Catrinescu, N., Leon-Ledesma, M., Piracha, M., & Quillin, B. (2009), “Remittances, Institutions and Economic Growth”, World Development 37, No. 1, 81–92.

ics, 37: 17, 1979–1990. Nguyen, C. V. (2008), “Impacts of International and Internal Remittances on Household Welfare: Evidence from Viet Nam”, MPRA Paper No. 25770. Orozco, M. (2004), “Remittances to Latin America and the Caribbean: Issues and Perspectives on Development”, Washington, DC: Organization of American States. Pesaran, M. H., & Shin, Y. (1999), “An Autoregressive Distrib-

Chami, R., Barajas, A., Cosimano, T., Fullenkamp, C., Gapen, M.,

uted Lag Modelling Approach to Cointegration Analysis.

& Montiel, P. (2008), “Macroeconomic Consequences of Re-

In S. Strom, Econometrics and Economic Theory in the 20th

mittances”, Washington, DC: International Monetary Fund,

Century: The Ragnar Frisch Centennial Symposium. Cambridge:

Occasional Paper 259. Chami, R., Fullenkamp, C., & Jahjah, S. (2003), “Are Immigrant

Cambridge University Press. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001), “Bounds Testing

Remittance Flows a Source of Capital for Development?”,

Approaches to the Analysis of Level Relationships”, Journal of

Washington, DC: International Monetary Fund Working Pa-

Applied Econometrics 16, 289–326.

per WP/03/189. Das, A., & Chowdhury, M. (2011), “Remittances and GDP Dynamics in 11 Developing Countries: Evidence from Panel

Rahimi, M., & Shahabadi, A. (2011), “Trade Liberalization and Economic Growth in Iranian Economy”, Hamedan: Bu-Ali Sina University.

Review of Business and Economics Studies

Ramirez, M. D., & Sharma, H. (2009), “Remittances and Growth in Latin America: A Panel Unit Root and Panel Cointegration Analysis”, Economic Studies of International Development

Volume 3, Number 1, 2015 Wollongong: University of Wollongong, Faculty of Business — Economics Working Papers.

Straubhaar, T., & Vãdean, F. (2005), International Migrant Remittances and their Role in Development. In OECD, Migration,

Vol.9–1. Sakr, K. (2006), “The Size, Benefits and Determinants of Migrants’ Remittances in Vietnam”, Washington, DC: International Monetary Fund, Country Report No. 06/20.

Remittances and Development. OECD Publishing. Waheed, A., & Aleem, A. (2008), “Workers’ Remittances and Economic Growth: Empirical Evidence from Pakistan”, Jour-

Shera, A., & Meyer, D. (2013), “Remittances and their Impact on

nal of Social Science and Humanities, Vol. 47 No.1, 1–12.

Economic Growth”, Social and Management Sciences 21/1, 3–19.

World Bank. (2006), “Global Economic Prospects: Economic Im-

Shrestha, M., & Chowdhury, K. (2005), “ARDL Modelling Ap-

plications of Remittances and Migration”, Washington, DC:

proach to Testing the Financial Liberalisation Hypothesis”,

The World Bank.

Appendices

12 10 8 6 4 2 0 1996

1998

2000

Remittances/GDP

2002

2004

2006

FDI implementation/GDP

2008

2010

2012

ODA disbursement/GDP

Figure 1. Remittances, FDI and ODA to Vietnam from 1996–2012 (as % of GDP). Source: Author’s calculation based on data collected from the International Monetary Fund and the World Bank

Table 2. Unit root test results and decision on the order of integration. Variable

ADF test statistic

Decision

LNRGDP ΔLNRGDP

-0.2447 –4.5987***

I (1)

LNREM ΔLNREM

-1.6536 –10.3439***

LNCRD ΔLNCRD

-1.6980 –6.0021***

Variable

ADF test statistic

Decision

LNFDI ΔLNFDI

-1.6771 –8.4799***

I (1)

LNTRADE ΔLNTRADE

-1.4397 –7.3858***

I (1)

LNREMLNCRD ΔLNREMLNCRD

-1.3196 –10.3061***

I (1)

Note: *, **, *** indicate significance at 10, 5 and 1 percent, respectively.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Corporate Insurance in the Russian Electric Power Industry* Nadezda KIRILLOVA, Professor Department “Insurance Business”, Financial University, Moscow nvk_66@mail.ru Victoria BAZHENOVA Financial University, Moscow vika.b@rambler.ru Abstract. In this article insurance risks of electric power industry of the Russian Federation, corporate insurance of electric power objects are considered. The special attention is paid to the types of insurance inherent in this branch, widespread in the Russian Federation, and also the types of insurance having development prospects in the country. Аннотация. В статье рассмотрены риски российской энергетической промышленности, которые могут быть компенсированы страховыми программами. Особое внимание уделено тем видам страхования, которые представляются наиболее перспективными для нашей страны. Key words: Power, insurance, system operator, NOREM, insurance of hydro-, thermal, nuclear power objects, especially dangerous objects, business interruption.

Insurance can be referred to as the important factor of risk management of the Russian companies, promoting growth of national economy, as it allows to minimize losses of the capital, business, or deterioration of corporate image. Formation of the market of insurance services in the sphere of power generation industry can provide protection of the enterprises against consequences of various financial, natural, technogenic or other adverse events. Now in many countries restructuring of economy in power generation branch is carried out. Also, the markets of electric power are developing. Modern reforming of this branch in Russia began with the Resolution of the Government of the Russian Federation of 11.07.2001 No. 526 “About the reforming of electric power industry of the Russian Federation”. This resolution defined liquidation of the national vertically integrated monopoly, represented by JSC RAO UES holding, due to its inefficiency (it was completely disbanded by July 1, 2008), division of assets of the company, according to kinds of activity — production, transfer and distribution, sale, dispatching control of electric energy. So, during 2000–2008, electric power consumption of GDP was decreasing by more than by 4% a year, and, finally, in 2007 level of production of 1990 was reached.

After the reform of the energy sector since 2003, the Russian Federation has moved to a new model of wholesale market of electricity and capacity (NOREM)1. The aim of this transformation was to create the conditions for development of competition in the industry, reduction of state regulation, transition of the power sector from centralized management to the competitive market. The growth of electricity consumption in the Russian Federation increases the risks and, accordingly, the insurance in the electric power industry is becoming increasingly important. Deregulation brought competition with new risks for incumbents, such as potential loss of the market share to new entrants and uncertainty about retail prices. Deregulation also brought more regulation — on how competition should be played, how distribution companies should be unbundled, and which acquisitions can be authorised2. Moreover, as more and more utilities are becoming listed enterprises, a larger proportion now faces 1 Markets of electric energy and power, Non-profit partnership (NP) “Market Council” Training center. — M, 2012. — 365 pp. 2 Risk Management in the Electricity Industry — White Paper I — Overall Perspective. EURELECTRIC group on Risk Management. — January 2007, 16 p.

* Корпоративное страхование в российской энергетической промышленности.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 1. Electricity consumption in the Russian Federation. Source: official site of SO EES (URL: www.so-ups.ru).

an increasingly risky environment on their own, with gradually less protection provided by their national governments.

1. ENTERPRISES OF ELECTRIC POWER INDUSTRY AS SPECIFIC OBJECTS OF INSURANCE Electric power industry3 is the branch of economy of the Russian Federation, which includes a complex of economic relations, arising in the course of production, transfer, sale and consumption of electric energy with the use of production, and other property objects, belonging to subjects of electric power industry, subjects of supervisory control in electric power industry. Subjects of electric power industry can be divided into groups: the persons, which are carrying out activity in this sphere, and electric power objects (generation facilities) — the property objects, which are directly used in processes of electric power industry. Russia takes the 8th place in export of electric energy abroad. The greatest development and distribution in Russia was generated by the public thermal power plants using organic fuel (gas, coal)4. As of November 1, 2014, in the wholesale market 90 suppliers, 249 resellers and 5 regulating bodies (infrastructure organizations) were registered5. In Rus3 The Federal Law of 26.03.2003 N 35-FZ (an edition of 21.07.2014) “About electric power industry”. 4 According to the Ministry of Energy of the Russian Federation (URL: www.minenergo.gov.ru) 5 According to the Non-profit Partnership (NP) “Market Council” (URL: www.np-sr.ru)

sia operate 32 power units, which generate 16% of all electric energy consumed in the country (Figure 1). In general, in Russia volumes of power industry are so great, that simultaneous modernization of all branch is too difficult to realize. Since 2003, no more than 10–15% of these objects were upgraded, therefore obsolescence of the equipment is the main problem of this branch. Insurance cost for the companies, operating on the power market, depends on their geographic location. So, the more densely the area around the enterprise is occupied, the more expensive the cost for the insurance is. For insurance in power industry, the major importance is taken by the definition of technological aspect of activity, where, the basis of functioning is made by a uniform electric network, territorial distributive networks and uniform system of supervisory control, see Figure 2. Power industry is still rather concentrated in part of the enterprises of generation and transfer of the electric power, where only large holdings are widespread (whose divisions work on over Russia). Services in supervisory control in power industry are the methods for the centralized management of technological operating mode of power generation facilities and the power receiving devices of consumers of electric energy for providing reliable power supply and quality of electric energy. They solve three major problems: the prevention of emergencies when they appear, timely localization of an emergency, revival of power supply in the shortest possible time.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 2. Participants of the electrical power market.

The System Operator is the specialized organization, which is individually implementing the centralized supervisory control within the power pool system of Russia (JSC SO EES). In order to protect property interests of subjects of electric power industry and consumers of electric energy, the System Operator is obliged to carry out insurance of risk of responsibility for breach of contracts of rendering services in supervisory control in electric power industry. The margin volume of the means, intended for the specified type of insurance, is defined according to federal laws and is included in payment for services in supervisory control in power industry. This amount has a target use. So, for example, the volume of the funds for insurance, considered in a tariff for services, of JSC SO EES in 2014 made 31360505,00 rubles6 (obligatory insurance of risk of responsibility for causing damage to subjects of power industry), and an insurance premium under the contract of insurance of JSC SOGAZ of 29133909,15 rubles7.

have no analogs on potential consequences for people around. Today, there are two main reasons for losses in energy industry: technogenic reasons and human factor. The first reason is connected with obsolescence of equipment, low-quality assembly and installation. Average age of the equipment of fuel power station in Russia is 30 years, thus the age structure of the equipment now (in % of set capacity): till 30 years — 41%; from 31 year to 50 years — 52%; more than 50 years — 7%. The second reason of losses is connected with the insufficient level of training of the personnel, aging of workers, shortage of the professional personnel and its elimination in other branches, physical activity and overfatigue. In Figures 3, 4 the number of fatal accidents from 1999 for 2009 is shown. Department of Power Supervision regularly carries out scheduled maintenance on injury prevention. Effectiveness is confirmed by a steady tendency of decrease in the number of group and fatal accidents on power installations. For the ten-year period total number of accidents decreased by 6 times. From January 1 till December 31, 2013, on power 2. RISKS IN ELECTRIC POWER INDUSTRY generation facilities and in installations of consumAny power object is subject to a large number of tech- ers of electric and thermal energy 112 accidents (for nological hazards. Scales of risks are the main features the similar period of 2012–180 accidents) were reof insurance of objects of fuel and energy complex. corded8. Investigation of the reasons is carried out by Losses, which arise in energy industry, are compara- Rostekhnadzor (the specialized governmental organible only with possible losses in space industry. The zation). The annual report of JSC SO EES for 2013. 7 Ibidem. 6

8 Rostekhnadzor has summarized the work of the state organs for 2013. Data of the Federal service for environmental, technological and nuclear supervision.

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 3. Quantity of fatal accidents in power industry of the Russian Federation. Source: Newsletter of the Federal Service. Department of Power Supervision. Accident rate and traumatism at power stations and networks, electric installations of consumers in 2008â&#x20AC;&#x201C;8 p.

Figure 4. Claims and global catastrophe insured losses 2001â&#x20AC;&#x201C;2011

Figure 5 shows statistics of fatalities in the US for the same period. Comparing two figures, there can be pointed out some peculiarities: in Russia the number of fatal accidents has a strong decreasing trend and in the US the trend is slowly decreasing and the average is equal to 250. And we can see a slow tendency for the period of 2007â&#x20AC;&#x201C;2009 for reduction in the number of fatal accidents. In a nutshell, for the 10-year period,

Russian Federation could cut the significant number of accidents, and in 2009 statistics is better than in the US. According to the Department of Power Supervision, the analysis of traumatism on thermal and electrical units showed that for the first half of the year 2013 in comparison with the similar period of 2012 the number of accidents has not changed. Thus, the greatest number

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Figure 5. Trends in occupational electrical fatalities in the U.S 1999–2009. Source: Advancements in the Practice Electrical Safety, IEEE South Alberta Section IAS-PES Chapter, may 13–14, 2013 (URL: http://sites.ieee.org/)

Table 1. Traumatism indicators in the Russian Federation for 2008–2009 in the sphere of electric power industry. Number of accidents and victims

2008

2009

1. Fatal accidents, including:

144

104

in electric installations

139

104

in heat installations

2. Group accidents, including:

in electric installations

in heat installations

3. Victims with a deadly outcome, including:

156

115

in electric installations

150

115

in heat installations

Source: Newsletter of Federal Service. Department of power supervision. Accident rate and traumatism at power plants and networks, electric installations of consumers in 2008–8 p.

of fatal accidents in 6 months 2013 occurred 39 times: on electric installations of consumers — 30 (70%) and in electric networks — 9 (21%)9. In 2012 and 2013 on thermal and electrical units 125 and 101 were registered10. Along with the general decrease in number of accidents there was also a decrease in indicators of lethal 9 The analysis of efficiency control — scheduled maintenance on accident prevention on power generation facilities in 6 months 2013. Data of Federal service on ecological, technological and nuclear supervision. 10 Rostekhnadzor summed up the results of power supervision for 2013. Data of Federal service on ecological, technological and nuclear supervision.

traumatism at power stations, electric installations of consumers, in electric networks (see Table 1), and the majority of cases occurred in electric installations. Also, until recently, the risk of theft of wires was considerable. In the last years, considerable decrease in losses in this kind of risk is reached. If up to the middle of the 2000-s in the Central and Far East part of Russia it was one of the most typical losses for the network companies, on which large volume of compensations spread, now it has considerably decreased. At last, financial and economic risks include: fluctuations of financial market conditions, the change

Review of Business and Economics Studies

in price for fuel (gas, oil, coal), tariffs for the electric power, increase in interest rates on the credits, cancellation of contracts with the tenant, because of nondelivery of goods, undersupply of goods in the specified quality and quantity, the compelled idle times in work. Risks in energy industry, depending on the size of damage, can be divided into 4 groups: • Small (to 1 million rubles); • Average (to 10 million rubles); • Large (to 500 million rubles); • Catastrophic (over 500 million rubles). Small risks usually arise in case of refusal, failure, obsolescence of equipment (short circuits, fires, wire breakage). As a rule, this group of risks is not insured. Average risks include breakage of machines and mechanisms, falling of the high voltage line. They are insured more often, than small, if there is an economic feasibility. According to Federal Grid Company (FSK EES), the number of such accidents on 1000 c. u. of service of the company for 2013 decreased by 14,9%, having made 2,2911. Large risks mean failure of the large equipment, natural disasters, the all-station fire, and the companies seek to insure this group of risks, as the most dangerous to activity. According to the reinsurance company Swiss Re12, globally for 2012–2013 losses from large accidents made 196 and 130 billion dollars. Smaller-scale accidents happen in the world almost daily.

icies and reporting systems, standardized group-wide strategy, planning, and controlling processes, internal auditing activities, specific group-wide risk reporting based on the German Corporate Sector Control and Transparency Act (KonTraG), and the Risk Committee, which ensures the strategy agreed by the Board of Management in relation to the risk policy covering commodity and credit risks is implemented and complied with. The ENEL company’s management policies were developed for each category of risk, identifying management and control roles and responsibilities: the governance model for financial, commodity and credit risks, strategic policy-making responsibilities for risk management activities and supervision of risk management and control activities to special risk committees, both at the group level and at the division/ company level14. In the leading Russian companies risk management started developing rather recently, therefore, these measures, perhaps, include smaller organizational and technical support, but, nevertheless, have the high potential of development, in view of their considerable share in the market. In JSC Atomenergosbyt process of formation of the corporate control system of risks (CCSR) began in 2010, according to the Risk Management Policy: development of organizational structure; integration with business processes; development of methodology; development of knowledge and competences of participants. The main document, defining process of formation of documentation on risk strategy management and the corresponding indicator of efficiency of activity (KPE) in JSC RusHydro is the Provision on strategic management, and also the company annually makes the register of strategic risks with definition of owners of risks, which is approved by the Board15. Also, one of the methods of price risk management of the Russian companies is the use of derivatives. Existence of speculators in the market allows redistributing risks in parts from power branch to financial sector, and also to other sectors, anyway connected with electric power industry sector. The exchange and off-exchange urgent contracts, based on basic financial contracts or operations, can be referred to derivative tools (derivatives), for example: forward and future contracts, exchange and off-exchange options, swaps and exchange derivatives for swaps16. In Russia,

3. RISK MANAGEMENT OF THE POWER ENTERPRISES Fortum, ENEL, E.ON are the most significant foreign companies in the Russian electricity market. The main policy-related risks in Russia are linked to the development of the whole energy sector, part of which, namely wholesale power market, is liberated while other parts, like gas, heat, and retail markets, are not. Currently, there is the risk that the government will freeze tariffs of certain regulated products including gas, which creates a risk for Fortum’s efficient operations. Cross-subsidies, which are supposed to be eliminated but still exist, compromise the competitiveness of energy-efficient combined heat and power (CHP) production13. Besides, the key components of the E.ON company’s risk management system include group-wide pol-

ENEL Annual report 2013. The annual report of JSC RusHydro for 2013. 16 Pavlova O. S. Risk-management na rossiyskih energeticheskih predpriyatiyah [Risk-management on Russian energy enterprises]. Vestnik nauchno-tehnicheskogo razvitiya — News of technical and scientific development № 6 (46), 2011–43 pp. 14

The annual report of Federal Grid Company (FSK EES) for 2013. 12 Swiss Re. Sigma preliminary estimates: natural catastrophes and man-made disasters in 2013 cost insurers worldwide USD 44 billion, 18 DECEMBER 2013, ZURICH (URL: http://www.swissre.com). 13 Annual report 2013, Fortum. 11

Volume 3, Number 1, 2015

Review of Business and Economics Studies

this activity is carried out by Moscow Power Exchange open joint-stock company, but now the exchange does not have enough distribution among participants as means of hedging. Following the results of 2012 on the basis of exchange quotations by bidders, there were signed contracts on 21 600 MWh17, at the general consumption in 2012 about one thousand billion.

• Business interruption and contingent business interruption. Zurich offers property and casualty solutions for companies in these utility segments: • Power generation utilities; • Independent power producers; • Integrated water and power production; • Desalination facilities. In Canada Chubb offers property and casualty solutions for companies in these utility segments: • Gas and coal-fired power facilities; • Wind energy facilities; • Hydroelectric facilities; • Waste-to-energy facilities — biomass, municipal solid waste; • Solar facilities; • Geothermal facilities; • Electric and gas utilities. Chubb’ hallmark package product features a modular format and an automatic blanket limit of up to $250,000. Valuable features of Chubb’s package product for the renewable energy industries include: • All-risk property protection (turbines, boilers, transformers, powerhouses, solar panels, conveyors, fuel cells, shops and offices); • Machinery breakdown, electrical arcing and steam explosion perils can be incorporated into a package policy; • Business income and extra expense insurance are available. Liability insurance provides protection for bodily injury, property damage, personal injury and advertising injury. It includes general liability insurance for all power generation, transmission and distribution operations, as well as newly acquired or formed organizations. Liability enhancements in Chubb’s package approach for the power industry: • Simplified rating approach based on kilowatt hours and pounds of steam; • Failure to supply insurance protection. Since January 1, 2012 came into force the new law 256-FZ of 21.07.2011 “About safety of objects of fuel and energy complex”, obliging owners of these objects to insure responsibility for the harm, against the accidents which resulted from act of terrorism or diversion. This law was developed after the explosion on the Baksan hydroelectric power station, which happened in July, 2010, damages from which are assessed at over 800 million rubles. Also, the Federal Law No. 225-FZ “About obligatory insurance of a civil liability of the owner of dangerous object for infliction of harm as a result of accident on dangerous object” which obliges to insure hydraulic engineering constructions, and also nuclear power plants. Before the adoption of

4. INSURANCE OF THE POWER ENTERPRISES The most reliable and simple protection of the enterprise against influence of the internal and external risks of random and unforeseen character is complex insurance (CAR Insurance), which provides compensation in case of losses of the income and property. After disintegration of RAO UES of Russia, centralization and control over insurance of the enterprises of electrical power branch were lost. The largest enterprises of power industry still continue to insure the risks, some of them are insured in the affiliated companies, however, the majority of the enterprises continue to be insured in the market companies: ROSNO, Rosgosstrakh, AlfaStrakhovanie, etc. One of the largest consumers of electric power in the wholesale market, JSC Novosibirskenergosbyt, in 2013 signed contracts on the following types of insurance: voluntary medical insurance, voluntary insurance of vehicles, insurance of property upon all risks18. The structure of insurance of consumers and generators in the market is different, because consumers’ companies do not include the risks, connected with electricity generation. Insurance in the sphere of electric power industry can also include insurance of freights, insurance of machinery and equipment upon breakages, interruptions in production activity, obligatory insurance of a civil liability of the owner of dangerous objects (ODO). For example, some of the key products and features for the power generation and utilities industry of Zurich insurance company includes: • First-party property insurance; • Machinery breakdown; • Time element coverage; • Primary general liability, umbrella liability and workers compensation; • Every energy customer gets a single point of contact for all underwriting needs and a claims service account executive to coordinate claims service; • Broad policy coverage available including property damage and boiler and machinery; Annual report of Open Joint Stock Company Moscow Energy Exchange for the year 2012. 18 Results of procurement procedures of Novosibirskenergosbyt for 2013. 17

Volume 3, Number 1, 2015

Review of Business and Economics Studies

law, enterprises were compelled to allocate funds for insurance of dangerous objects from their profit, now these expenses are put in product cost. In one and a half years of action of the law, only about 200 million rubles were paid by insurers: accidents on dangerous objects happen not so often, but their consequences can be catastrophic for the whole region or several areas. Moreover, payments for such accidents often have the delayed character. Also, the structure of insurance can differ by the form of generation. The market of insurance of the companies of nuclear power in the Russian Federation has two segments: obligatory insurance of responsibility of the organizations, operating objects of use of atomic energy, and voluntary insurance of risks of the enterprises of nuclear power. The first (obligatory) segment in Russia corresponds to the developed international practice and requirements of the Vienna convention of 1963. In the territory of Russia requirements came into force in 2005. The largest supplier of atomic energy in the Russian Federation, Rosenergoatom Concern, annually signs the contract of insurance of responsibility, submitting to the requirements of the Vienna convention on a civil liability for nuclear damage. The insurance sum of JSC Rosenergoatom in 2012 reached 7 billion rubles, and an insurance premium — 366 million rubles19. Insurance is carried out by the Russian Nuclear Insurance Pool (RNIP) consisting of 23 insurance companies (according to the Russian Nuclear Community, in 2013 the greatest share belongs to the SOGAZ company). The total volume of collected insurance premiums in a segment of voluntary insurance of the enterprises of Rosenergoatom is estimated at 6–7 billion rubles, about 70% from them gather SOGAZ and MAX insurance companies. In 2014 SOGAZ insured property of all 10 Russian nuclear power plants for the total insurance sum of 1,2 trillion rubles. Level of coverage of power generation facilities insurance after liquidation of RAO UES of Russia (after 2003) significantly didn’t change. The largest company of producing hydroelectric power in Russia, JSC RusHydro, adds risk, specific to this fuel: risk of the inexact forecast of water content. Owing to a large number of the risks inherent in business, the company in 2013 carried out complex insurance protection on the following types of insurance: insurance of property upon all risks; insurance of a motor and water transport; insurance of construction risks (EAR Insurance); insurance of a civil liability of organizations operating dangerous production

facilities and hydraulic engineering constructions; voluntary medical insurance and insurance upon accidents; insurance of a civil liability of members of governing bodies and officials of JSC RusHydro. Insurance of risks of breaks in production (business interruption or BI) are single cases, generally used at the sales companies, which are carrying out services in resale of the electric power to consumers. BI means the financial loss of the owner, caused by the idle time of the enterprise, and it is applied in insurance companies such as Energogarant, AlfaStrakhovanie. This type of insurance is widespread in the international practice. Over the past five years, this risk has been in the steady increase. Energy companies are buying more business interruption cover, as refining and processing margins maintain their healthy levels in the US20. By various estimates, losses from the compelled idle times of the generating equipment of suppliers of the wholesale market of the electric power “take away” about 3% of revenue. Making out the policy of assurance of idle times, the enterprise gets confident, that the most part of losses during idle time will be compensated. So, it obtains a certain guarantee of economic stability. Insurance of the high voltage line and networks of data transmission on big distances in Russia is developed poorly. Generally, mobile network operators of communication are interested in cable insurance. The main risks on which they try to protect themselves are natural disasters and illegal actions of the third parties (plunder). As the cost of such insurance is usually carried by the customer of the project, the project organization, as a rule, refers to the insurance company, if it is needed by the initiator of works on research, so this type of insurance is not yet popular. Furthermore, in Russia insurance upon risks of designer, which is a very widespread type of insurance in Europe, can be developed. As expenses for this type of insurance are incurred usually by the customer of the project, the design organization, as a rule, addresses to insurance company, only if the initiator of works on research insists on it, therefore this type of insurance isn’t popular. Also insurers offer insurance of additional risks. The AIG company includes the following additions and extensions of insurance programs of power generation facilities: a compensation for expenses on ensuring access to the damaged property, clearing of blockages and fragments, automatic protection of small repair or construction projects, etc. Among other things, in the last five years, emerg-

The quarterly newsletter of “NASAO” for July, 2012, No. 3. — p. 4.

Volume 3, Number 1, 2015

Energy insurance trends. OIL & GAS Financial Journal, 16.12.2014.

Review of Business and Economics Studies ing and developing countries’ investments in solar and wind energy plants have virtually doubled21. Leading producers of wind power are the United States, China and Spain. The European Union intends to increase the renewable energy share of total energy production to 20% by 202022. So, if these sources of renewable energy are in high demand, the risks inherent in the transportation, construction and installation of transmission lines and power stations can be different in contrast with traditional energy resources. A downside of renewable energy particularly, wind and solar technologies, is the volatile supply of power and the location gap between consuming and producing. Many international companies, such as AIG and Allianz try to provide insurance services for all kinds of energy production. Robert Maurer, head of Engineering Germany at AGCS, explains how company tries to “…understand exactly what our customers do and can give them competent support when they develop their technologies and business models further”23. Non-life insurance premiums slowly grew by 2.5% in Central and Eastern Europe (especially in Russia — its growth was 1.5%)24. The growth was equal to 4.8% in 2012 (2011: 2%)25. It was driven by strong improvements in most business lines in Russia (13%), the largest market in CEE. Insurance of the enterprises of fuel and energy complex of Russia till 2009 can also be characterized by the annual growth of indicators of activity of insurance companies. In 6 years insurance premiums of the energy industry enterprises increased by 4 times, see Table 2. Peculiarity of power objects in terms of insurance is their allocation in category of hazardous production facilities. As the most perspective direction in insurance of energy industry, insurance of especially dangerous objects (a component of insurance of responsibility) in the volume of all Russian market in 2012 made 10–11 billion rubles (about 1,2% of all types of insurance collected), and in 2013–9,1 billion rubles (1% of all insurance collected), which means the decrease in growth rates of the market of insurance, reclassification of dangerous objects and growth of the maximum discount for the high level of safety. Insurance of power industry influences specifics of 21 CRO FORUM. Power Blackout Risks. Risk Management Options: Emerging Risk Initiative — Position Paper, November 2011, 31 p.). 22 Ibidem. 23 Global Risk Dialogue. Allianz Global Corporate & Specialty, Autumn 2013, 31 p. 24 Swiss Re sigma study on world insurance in 2013 says premium growth slowed largely due to weak life sales in advanced markets, Sigma, 25 JUNE 2014, ZURICH. 25 World insurance in 2012. Progressing on the long and winding road to recovery. Sigma No 3/2013, 42 p.

Volume 3, Number 1, 2015

risks; the companies partner only with those insurers, who are capable to provide efficiency of insurance and a guarantee of indemnification in fuel and energy branch. The main insurers by the volumes of insurance premiums in the first half of the 2014 year are SOGAZ, Rosgosstrakh, Capital, VSK, AlfaStrakhovanie — some of the largest insurance companies of the Russian market. Among important insurance events, it is possible to mention accident on August 17, 2009, driven by the destruction of fasteners on Sayano-Shushenskaya hydroelectric power station. As a result of accident, 75 people were lost, more than 40 tons of lubricating oil poured out to the water area of Yenisei river. Rosprirodnadzor assessed damages to the Yenisei at 883,63 million rubles. The property of Sayano-Shushenskaya hydroelectric power station was insured in ROSNO for $200 million, employees were also insured in ROSNO for 500 thousand rubles per person. The civil liability of the owner of hydroelectric power station was insured by AlfaStrakhovanie company. Risks under the contract were reinsured in the international market, mainly reinsurance was provided by Munich Re. The risk of a break of production of this enterprise was insured in Ingosstrakh, but even such record sum of insurance didn’t cover the cost of repair of station as damages were assessed at 7,5 billion rubles. In 2013 at the Zagorsk pumped storage power plant construction works were stopped because of an accident, which resulted from a sag of a plate of the base. The company had a contract of insurance of assembly risks with AlfaStrakhovanie, with a covering limit at 13,7 billion rubles and a cost of 10,4 million rubles, validity period of 2 years and 7 months. The damage was estimated at 14 billion rubles. Also, 1,8 billion rubles were paid to IDGC Holding for damage from sleet in 2010. About 95% of these losses were covered by insurance payments. Nowadays, after events on Sayano-Shushenskaya hydroelectric power station, control in the sphere of power industry is strengthened, additional investments are allocated for renovation, modernization of equipment. Also, some increase in volume of insurance due to modernization of the available objects or commissioning of new capacities is possible. In a nutshell, there can be pointed out 3 main types of insurance of the Russian energy industry enterprises: corporate insurance of staff of energy industry (voluntary medical insurance, pension insurance and insurance upon accidents and diseases), property insurance and insurance of a civil liability. Besides, corporate social responsibility in the energy industry enterprises is being developed: protection of staff of

Review of Business and Economics Studies

Volume 3, Number 1, 2015

Table 2. Insurance premiums, 2004–2009. Indicator

2004

2005

2006

2007

2008

2009

7,5

19,2

22,1

26,5

29,6

31,3

Insurance of staff of energy industry, %

21,3

23,4

26,2

33,4

33,2

Property insurance, %

74,7

72,4

75,1

64,2

63,6

2,8

1,7

2,2

3,2

Premiums, billion rubles

Insurance of responsibility, %

Source: How to insure energy industry really not to be afraid: Internet portal of energy industry community.

the energy industry enterprises, interests of the third REFERENCES parties and environment. Insurance is the main tool of complex system The Federal law of 26.03.2003 N 35-FZ (an edition of 21.07.2014) of risk management of the enterprise, urged to re- “About electric power industry”. duce all risk factors to a minimum. It is a source The Federal law No. 225-FZ “About obligatory insurance of a of compensation of loss of property of the owner, civil liability of the owner of dangerous object for infliction of if there are adverse events in the operation of the harm as a result of accident on dangerous object”. company. The Federal law of the Russian Federation of July 21, 2011 N 256-FZ “About safety of objects of fuel and energy complex”

CONCLUSION Increase of the competition and socialization, interindustry expansion are inherent in the market of insurance of energy industry. Their development, collaboratively with the growth rates of energy industry, will define the further formation of the market of electric power insurance and also fuel and energy complex in general, which is now characterized by the following: 1. Insurance protection in energy industry is at a very low level, which is caused not by the absence of supply in the market, but by a lack of understanding of requirements to insurance companies and to the offered products of insurers (absence of insurance risks included in insurance contracts). 2. Presence of the private companies in the market of insurance of energy industry increases, insurance premiums raise, their structure changes, the tendency of interindustry distribution of insurance of large risks is observed. 3. In the Russian power industry, several types of insurance, which provide a continuity and development of business activity, are insufficiently demanded: insurance of losses from breaks in production, insurance of construction risks. 4. Insurers are not engaged in financing the outdated, broken and low-quality production and consequences of their damages from accidents and the technogenic reasons, as this risk is an exception of an insurance covering of the majority of insuring companies. 5. Systems of internal audit demand considerable improvement with the aim of minimization of all possible risks.

The resolution of the Government of the Russian Federation of July 11, 2001 N 526 “About the reforming of electric power industry of the Russian Federation”. CRO FORUM. Power Blackout Risks. Risk Management Options: Emerging Risk Initiative — Position Paper, November 2011, 31 p. Dynamics of contributions on types of insurance, 2013. RAexpert E n e r g y i n s u r a n ce t r e n d s . O I L & G A S F i n a n c i a l J o u r n a l , 16.12.2014. Global Risk Dialogue. Allianz Global Corporate & Specialty, Autumn 2013, 31 p. Volkov L. V. Reforming of electric power industry of Russia: Intermediate results and further plans, in: L. V. Volkov, E. V. Hodyachikh, Effective crisis management. 2010. No. 2 (61). — 55 pp. Kirillova N. V. Bellucci A. Customer protection and investments choices in insurance market: Italian and Russian experience. Bulletin of Financial University #2, 2014, p. 113–124 Markets of electric energy and power, Non-profit partnership (NP) “Market Council” Training center. Moscow, 2012. Newsletter of the Federal Service. Department of power supervision. Accident rate and traumatism at power plants and networks, electric installations of consumers in 2008–8 p. Pavlova O. S . Risk-management na rossiyskih energeticheskih predpriyatiyah [Risk-management on Russian energy enterprises]. Vestnik nauchno-tehnicheskogo razvitiya — News of technical and scientific development # 6 (46), 2011–43 pp. The quarterly newsletter of “NASAO” for July, 2012, No. 3. — p. 4 The realities of insurance in the energy sector. The Power and industry of Russia newspaper, # 04 (240), 2014. Tsyganov AA, Bryzgalov D. New Forms of the Competition in the Insurance Market of the Russian Federation. Financial journal. Research Financial Institution. #3, 2014. P. 141–149 World insurance in 2012. Progressing on the long and winding road to recovery. Sigma # 3/2013, 42 p.

AIMS AND SCOPE Review of Business and Economics Studies (ROBES) is an editorially independent international academic journal launched by the Financial University under the Government of Russian Federation. ROBES publishes original research papers on emerging topics of business and economics with focus on advanced international finance, sustainability and emerging markets in Eastern Europe, CIS countries and China. Journal is published in English with Russian abstracts. Journal’s mission is to provide profound scientific perspective on wide range of topical economic and business subjects of Eurasian region. Choice of topics for this quarterly publication is based on discussion between editorial board members formed by renowned academics and practitioners from Russia, USA, Europe and Asia. We use double-blind peer reviewing for paper selection. Our journal aims to search what is currently most cited and discussed topics in economics and business science, select those topics that might be of interest in current social context for decision-makers in business and government, and connect business and state governance to academia by delivering deep qualitative insights, strongly reasoned with rigorous quantitative methodology. Our scope is emerging scientific research in finance, economics and management for the best interest of business and policymakers. Key topics of the journal are evolving around current research and citation trends in finance and economics, and range from sustainable development, green finance, energy economics, to corporate governance, organised markets studies, behavioral finance, knowledge economics, corporate social responsibility and social entrepreneurship. ROBES promotes integrity in academic publications and follows the COPE rules and internationally accepted academic procedures in publishing. INFORMATION FOR AUTHORS Review of Business and Economics Studies is especially interested in papers presented by researches who use quantitative methods and modeling techniques with potential impact on business and policy making. Readability and good writing style are important criteria for publication. Content and presentation must be of scholarly caliber. Manuscripts are received with the understanding that their content is original material not previously submitted for publication elsewhere. We will offer to our authors a rapid publication, high visibility, and user-friendly web-based editorial platform for submission and review. Inquiries relating to the submission of articles can be sent by electronic mail to robes@fa.ru. Title and author. Please limit titles to 12 words. Do not use all uppercase letters, or quotation marks for whole title. List names, academic degrees, affiliations, and e-mail address of each author. Include full mailing addresses, phone numbers of author (not to be displayed in publication). The Russian version of title and author information should be provided when possible. Abstract. The abstracts in English and in Russian (when possible) should be included in the manuscript. If you are unable to prepare a Russian abstract, please inform us in your letter. Abstracts should review the purpose, results, and significance of the paper. Abstracts should have approximately 100 – 200 words. Do not cite references. Do not use undefined acronyms or abbreviations. Key Words. Submit up to six unique, informative key words or short phrases. Avoid overly general terms and undefined abbreviations or acronyms. Editors reserve the right to replace key words. Text. Email us a MS Word file that includes the title, authors’ names/affiliation/contacts, English abstract, key words, manuscript, and references. Russian versions of title, abstract, and authors information should be provided when possible. Use Times New Roman 12 pt. font in the entire file, including tables, figures, headings, captions, and table notes. Use 1,5 line spacing. Do not use section or page breaks in the running text. Equations. The author is responsible for ensuring that equations are rendered in vector form. Use Word formula editor. Tables and Figures. Please do not submit low-resolution images or graphics, which are disproportionately large for the content. In your text please use references to illustrations with numbers. Avoid references such as see next page or see below. Number all tables and figures (in Arabic) as they are to appear in the text and ensure that all tables are mentioned in the text. Caption should be styled as: Example: Table 1. Relationship between… Figure 1. Distribution of… References. The author is responsible for ensuring that all references are cited completely in the text and in the list. Delete the hyperlinks. Examples of references: Reference in the text (citation): On the other hand, Jones et al. (1988) have reported that ... The List of References: A complete book: Jones, P.J. (1980), Introduction to Algorithms, London: Methuen. A chapter in an edited book: Hamza, K.A. (1988), «Vision Systems», in Jones, P.J., Smith, R. & Watson, E.P. (eds), Artificial Intelligence Reconsidered (2nd edition), New York: Wiley, pp. 12-34. An article in a journal: Carson, P.R. (1970), «An Approach to Intelligent Planning», Journal of Applied Artificial Intelligence 38(3), 4-11. Referencing online sources: Coxhead, P. (2009), «A Referencing Style Guide», http://www.cs.bham.ac.uk/~pxc/refs/refs.html [accessed 17 Oct 2009].