100 by International Journal

Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in

Estimation of Basic Economy and Classification of Major Urban Centers of Ethiopia Temam Awel Beshir1 & C. Venugopal Rao2 1

PhD Candidate, Department of Geography, Osmania University, Hyderabad, India Professor of Geography, Department of Geography, Osmania University, Hyderabad, India

Abstract: The main objective of this study is to examine the economic bases of the major urban centers (16) by identifying the basic industries and estimating the basic economy of each of the urban centers. Employment data for 21 types of industries in 16 urban centers was collected. To achieve its objective the study has employed the Location Quotient technique and the Basic Employment Index for analysis. With the Location Quotient the study identifies the basic and the nonbasic industries; while the Basic Employment Index (BEI) was used to estimate the number of basic employments in the basic industries. Thus, the amount and the impact of basic employments in each urban centre were estimated. Then, top three basic industries were identified for each urban centre. In due course; the urban centre s were labeled in eight (8) major categories of urban functions. Based on the study the economic base of most of the urban centre s in Ethiopia is generally founded on service industries. And none of them satisfy the 1:1 basic non-basic ratio that is theoretically assumed to exist. It seems that policy makers, planners and decision makers should work on the development of the basic industries so that development of towns can be improved and sustained. Key terms: Major urban centre s; Industry; Basic Industry; Non-Basic Industry; Location Quotient; Basic Employment; Basic Employment Index; Basic Economy

1. Introduction According to [12] the main concern of regional planners and practitioners is the creation of employment opportunities primarily through industrialization and then through urbanization. The growth and development of urban areas has shown an increasing demand for labor, due to expanding industrialization and which then requires scrupulous planning and researching. Regional/ urban and fiscal planners, policy makers, economic development practitioners and business people have much to gain from a careful concern of both the local and the national economy

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[8]. A good grasp of the trends, the spatial patterns, and the anomalies of economic development indicators is of a great importance to equip stakeholders with the necessary knowledge for any economic decision that they demand at local, sub-regional/urban, and regional or at national level. The rapid urban growth in the 20th century (particularly since the mid 1940s) combined with the challenge it brought for planners trying to predict and influence this growth, has made certain the demand for regional economic models in the studies of urban centre s [9]. According to [8], local economic base analysis has been regarded as a useful tool in the public administration and business environment. The economic base model originates from economic base theory, which instructs that inflow of money generated from the export sector is the main source of growth in an economy and determines the rate of employment and employment growth of the nonbasic sectors which serves local consumption. For Schaffer [13], the economic bas analysis is an analytical tool used by economists; and regional and urban planners to develop the profile of their local economy. Such analysis was started with the need to estimate the impacts of new economic activities or industries on the growth and development of cities and regions. So, studying of regions or urban areas in the framework of the economic base model is of great importance to open up or widen or give up a business (an industry. Even though, the economic base model has been probably remained to be the only such instrument available for regional economic analysis since the 1900s, it gained much attention from scholars of regional science only in the period between 1950 and 1985 [9]. Nowadays, a new version of economic base analysis has become an integral part of planning about the growth and development of regions and or urban areas. The concept of the model in its simplest form entails the notion that the growth of urban areas depend up on the behavior of a set of economic activities in an area [12]. The set of economic activities deemed to serve as engine of the local economy are those industries which could bring income to the locality they are located. The

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in model divides the economy of an area into two categories: basic and non-basic. It also further elaborates that the growth of a region depends up on the development of the basic industries. In the study of economic bases of a region or an urban centre , identification of basic industries (mostly by calculating Location Quotient) and estimation of Basic Employment (Analysis of Surplus Workers Index), are the most widely used empirical tools employed [3]. This study involves the location quotient analysis and Basic Employment Index (BEI) with the intention to meet the main objective it stands for. As it is well addressed in different articles the analysis of economic bases of a region or an urban area involves various techniques of identifying the basic and the non basic industries of the economy in a region or urban places. The most notable ones are: a) The Assumption Technique, b) Location Quotient, c) The Survey Method and, d) The Minimum Requirement Technique. The first two are widely used and simple to apply for the study of urban areas [3]. In this study, however, the Location Quotient, for its simplicity and applicability for employment data, has been chosen to categorizing industries as basic and non-basic. The study of economic bases of urban centre doesnâ&#x20AC;&#x2122;t end up with on the identification of the basic and non basic industries in the urban centre s. It also involve the use of a relatively sophisticate method that would filter the results to a better quality. The use of the Basic employment Index in this regard is of great importance to enable researchers to estimate the role or impact of the basic industries in their locality. Even though, the economic base model is applicable for the analysis of economic bases of regions or urban places using income, export, import and employment data, this study gives emphasis only to the use of employment data for 21 industries in each of the selected (16) urban centre s. Indeed, employment data has been widely applicable by economists and; regional or urban planners to minimize risks which may, otherwise, arise due to unavailability of complete data on other variables; such as income, export and import data. This situation would have been more severe in developing countries where the availability of income/export/import data is absolutely incomplete; so unrealistic and inaccurate. The study focuses on 16 urban centers of Ethiopia. Ethiopia is a country located in Eastern part of Africa. The country has lived and attained long aged history of civilization since time immemorial. It had been in both imperial and military forms of administrations until 1991. The year 1991 is a landmark in the history of the country. It marked the demise of the military regime and heralded the introduction of a relatively

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democratic and capitalist oriented government. Since then, the state administration has taken the format of Ethnic Federalism by which the country is divided into nine regions and two city administrations. The capitals of the nine (9) regions, the two (2) city administrations (Addis Ababa and Dire-Dawa) and five (5) other major towns; totally 16 urban centre s, have been considered and included as economic regions in this study.

2. Objective of the study The objective of this study is to examine economic bases of the major urban centre s of Ethiopia by using the applications of Location Quotient, the Basic Employment Index and the Base Multiplier Index. The identification of basic industries and examination of their impacts in the urban centre s are specific components to which the study aims.

3. Theoretical framework 3.1. Definition of key terms Reference Economy: this study considers Urban Ethiopia as a reference or broader spatial area within which sub regions (urban centers) are contained. Major urban centers: refers to those selected (16) towns/ urban areas: nine (9) regional capitals, two (2) city administrations and five (5) major towns with population more than100, 000 as per the 2015 UEUS [1]. Industry: refers to all economic activities, be it governmental or privately owned, primary or secondary or tertiary activities, service or manufacturing as it is categorized by the [1]. This sort of definition has been examined and proved to be effective as it is made applicable in Greytak [6]. It also includes those activities owned and carried out by non-governmental organizations Basic industries are those industries exporting from a region and bringing wealth from outside; local resource oriented firms like mining; and manufacturing are usually considered to be basic industries; because their production largely depends on non local factors and they usually rely on export trade and collecting wealth from outside of the region [11]. They are assumed to be the engine of the whole economy because the growth of which lifts the growth of the service industries in particular and the local area in general. They are industries found concentrated in urban regions with calculated LQ>1 [3]. Non basic (or service) industries support basic industries and hence they are called region or

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in city serving or “town fillers” as used by Sombart and mentioned in Schaffer [13]. They are economic activities producing goods and services for consumption inside a region [11]. As shown [3] and in many other literatures, non-basic industries are functions in the urban regions with calculated LQ<1. Location Quotient is a measure of an industry’s concentration in an area in relation to a reference area i.e a nation [3]. Basic Employment refers to the amount of the basic employment in a basic sector. This concept emanates from the notion that there would be nonbasic employments even in the basic sectors [5]. Davidson and Schaffer (1973) in the Atlanta Economic Review used the term ‘excess’ employment to refer to the basic employment because the workforce in this category is above the line of local self-sufficiency and is to be employed or exported to outside of the region in the form of productions. In other literatures like in Solomon (2008) it is mentioned as Surplus workers. Basic Employment Index also called Surplus Workers Index (as used particularly in [14]) is one of the best indices used to measure the impact of the basic industries on the non-basic sector and on the development of the local regions. It defines the amount or magnitude of the Basic employment or “excess” employment in the industry [2]. Basic Economy: refers to the amount of local economy measured in terms of the sum of amounts of the basic employment of in the basic industries of an urban centre.

3.2. Economic base theory It is clear that the origin of the economic base model is the Economic base theory. The theory emphasizes that economic activities can be classified into two categories as basic and nonbasic [11]. According to [3] the theory states that the development of the local economy is dependent on the growth of the basic sector. The basic industries being the drive to the economy of a spatial entity, the non-basic are subordinates to it and only serve the local demand. As such the Economic base model has used as an approach of classifying regions based on the identification of basic and non-basic activities. Frederick Nussbaum gives the credit of paternity of the concept to a German historical economist, Sombart, who distinguished the basic and the non basic industries as “town builders” and “town fillers” in his earlier study in 1916 [13]. Kurmme (1968) as sited in [9] also mentioned the fact that Sombart had once used phrases such as the "actual city founders" and “passive or derived or

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secondary city founders" to refer to what we now call the basic and the non-basic industries respectively. In the early 1920s Olmsted forwarded his own commentary reflection as “primary and ancillary economic activity” referring to what had been noted by Sombart as above. Moreover, we can also read the names of other individuals taking part in commenting and revising the model in different times [13]. As it is made clear above, [9] remarks: “…although Sombart was the first to observe formally the seeming duality of urban and regional economic activity, the remarks of his contemporaries Olmsted and Arrouseou make it abundantly clear that the concept was ripe for expression.” Particularly since the mid 1940s the rapid regional and urban growth has made certain the demand for sophisticated regional economic models. In our opinion it was due to the impacts of the 1930s great depression in the USA and the WWII and hence the change of mood of politics all over the world that had required scholars to search for a better economic analysis models. In due course again, the economic base model had passed numerous tests and critics. However, the model gained much attention from scholars of regional science only in the period between 1950 and 1985[9]. Richard B. Andrews as cited in [7], however, put it clear that the Economic base model with the fashion it exists now was developed by Homer Hoyt while working for the Federal Housing Administration of the US in the late 1930s. On the onset we noted that the model originates from economic base theory, which states that inflow of wealth caused by the basic sector (export sector) is the “engine” of growth in an economy and determines the rate of growth of the local region by enhancing the growth of employment in the non-basic industries. The analogy of the proverb “the rising tide lifts all boats” would apply for the fact that the basic industries would lift the employment in the nonbasic industries. According to the theory the opening of new basic activities would directly increase the demand for extra labor which would serve as necessary or as “excess”i requirement to the growth of the local economy [2].Thus, identifying the basic industry is the primary task in the study of economic base of regions or urban places. In short, it argues that the means of growing the local economy is to foster the basic industries as they are the engines of the economy. This being, the concept, the economic base model tries to analyze the broad economic structure of the local economy by dividing the economy into two sectors: (1) the basic or export sector - goods and services sold outside the local region; and (2) non-basic

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in sectors-which includes all output that is sold within the local economy. The concept entails that the local economy is the sum of the basic and the nonbasic sector or industries. The model, thus, tries to primarily identify the basic and the non-basic industries by using different techniques. The simplest and widely used technique of identifying the basic and the non-basic industries is the Location quotient technique. In fact, only identifying the basic and the non-basic industries may not indicate the basic-ness of that particular industry; because an industry which is identified as basic may have non-basic jobs/employments in it. Therefore, it is necessary to estimate the number of the basic employment in the basic industry before deciding whether an industry is basic. So, secondly the model tries to estimate the amount of the total basic employment in the basic industry or in the basic sector. Knowing the magnitude of the basic employment is important to determine the current role and prospect of the industries to the local region. Different researchers used different indices to calculate the amount of the basic employment in the basic industries. The index of surplus workers is one of the best indices and used here to estimate the basic employment. 3.3. Empirical analysis [12] on employment multiplier of 105 sample of Indian cities and towns reveals that the basic industries are source of the majority of employment created during the study periods, 1961 and 1971. The paper examines the employment multiplier of 105 sample urban centre s in the population range of 50,000 and above by its size and function. The study made it clear that the economic base model can be applied to the study of cities and towns in developing countries. The study implies the use of a disaggregated employment data by urban centre s for the year 1961 and 1971 and hence it had been easier for the researcher to research nearly 105 cities and towns. Obtaining such sort of data in developing countries like Ethiopia is very unlikely. A study of the Economic Bases of Ethiopian Urban centre s by [14] using the Index of Surplus workers classified Ethiopian urban centre s based on their functions. The study shows that it was done based on the 1994 census data. However, according to CSA, the 1994 population census data in Ethiopia doesn’t give a disaggregated employment data by urban centre s. So, the source of data for that particular study is remained unknown to us. Such data in Ethiopia have been made available only since 2009. This argument has been made clear in [4] with the study of Analysis of the Changing Functional Structure of Major Urban Centre s in Ethiopia. The study shows that the previous surveys do not have disaggregated

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employment data by industrial divisions even for the major towns considered in the study. Both studies, indeed, have put ‘finger prints’ to the application of models in the classification and study of Ethiopian urban centre s. 4.

Methodology

4.1. Sources of data In order to obtain richer set of data and carry out the best qualitative and quantitative analyses based on the model used in this research, both primary and secondary data types have been used. The primary data used in this study were those opinions, beliefs, and judgments of the researcher developed during field visit and data collection. Data which are readily available as published and unpublished materials such as books, journals, articles, reports, magazines, and letters are elements of the secondary data set. One of the important sources of the required statistical secondary data is/was reports of concerned governmental and non-governmental agencies. Of which, reports of the Employment Unemployment Survey (UEUS) done by the national Central Statistical Agency (at national, regional and urban levels) is the main constitute. Employment data in 21 types of industries for 16 urban centre s for the year 2015 was the main set of statistical data we have used. The types of industries used in the study are based on the classification by CSA since 2012 (as indicated in the Appendix). The agency provides different statistical reports and analytical documents for sell in its premises. The required data for the year 2015 was fully available in disaggregated, organized, and compiled form. However, the Agency lacks to organize disaggregated employment data by urban levels for the periods prior to 2009. A recent study by Engida [4] is a proof for the absence of so long data for the major urban centre s in Ethiopia.

4.2. Study design Regional analyses as part of regional studies involve various methods. The economic base model, the input-output technique, the shift share analysis, and others are regional analysis techniques. From among these analysis methods we have tried to employ the LQ and the Basic Employment Index to study the economic bases— the concentration of industries and impacts of basic employments in the industries in the major urban centers of Ethiopia during the year 2015. In the Empirical analysis section of this paper it is mentioned that two journal articles have been published so far regarding the classification of urban centers in Ethiopia based on the economic

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in base model. The old one, by Solomon [14] uses the Index of Surplus workers as basis of classifying urban centers on the bases of basic functions. The index of surplusii workers is simply another name for Basic Employment Index. Even though methodologically acceptable, the study is not without pitfalls. Its main deficiency is the unreliability of the data used. The paper presents its work as if it had used a disaggregated set of employment data by industries for all urban centre s for the 2007 census data. Employment data disaggregated with industries for towns, except for Addis Ababa and Dire Dawaiii, had never been organized and documented by CSA before 2009. Addis Ababa and Dire Dawa as city administrations have been considered like regional states and; hence, we can find long range data for such kind of analysis for these two cities. So, the study seems a generalization on the basis of the information obtained with regard to the two cities. Methodologically, however, it is the most preferable one. A recent study by Engida [4] is, on one hand, a proof for the absence of so long data for the major urban centre s in Ethiopia. This study, on the other hand, shows the use of the LQ to classify the urban centre s based on their functions. It seems an application of the older view of the economic base model as it tries to classify urban centre s based on LQ only. In this study we prefer to use Solomon’s approach whereby the Surplus Workers Index / Basic Employment Index has become a fit to our intention of examining the major urban centre s based on their basic functions. As the economic base model being rooted in the economic base theory primarily aims at identifying the basic and the non-basic economic sectors or industries of a spatial entity; we tried to identify the basic and the non-basic industries using LQ. The details of which, has been discussed under topic 4.3. Secondly, the economic base model with its component of Basic Employment analysis has been used to estimate the amount of basic employment in the basic industries. This concern of the model is a recent finding after various researches emerge with the idea that there are non-basic employments even in the basic sectors [5]. Thus, it then became clear that estimating the net basic employment in the basic industries is an essential task to purely measure the role of industries in their respective local regions. To this effect, the application of the index of Basic employment has been used. The index measures the magnitude (the number) of the excess labor force concentrated in an industry. Negative results of the index imply that the industry is non-basic and show that there is shortage of employment to that size to meet only the local demand. Positive results of the index

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indicate the presence of basic or “excess” employment. Actually for basic industries the Basic Employment Index would never be negative or zero. With excess employment by mean a local region / an urban centre is capable of supplying its own market and markets beyond its geographical influence. It should be made clear that Basic Employment Index is the measure of estimation of labor force in an industry where as Location Quotient is the measure of concentration of an industry in an area. The Base Multiplier Index was also used to estimate the role of the basic industry in the local economy.

4.3. Study tools and procedures i. Location quotient Location Quotient is a measure of an industry’s concentration in an area in relation to a reference area i.e a nation [3]. It compares the share of employment in a particular industry within the local economy to the proportion of employment in that same industry within a larger reference economy or state [15]. Location quotient shows how jobs are spread out by studying the share of jobs in an area relative to the national average. According to [3] and many others, location quotient can be computed with the formula shown as in caption (1). (1) Where, LQi= Location Quotient for an industry ‘i’ (in the local economy) ei= employment in industry ‘i’ in the local economy e= total employment in the local region (urban centre s) Ei= employment in industry ‘i’ in the national or reference economy. E= total employment in the national or reference economy The following is an example of LQ computation done for the construction (‘i’) industry in the town of Dire Dawa based on employment data of the year 2015. ei= employment in the construction industry ‘in Dire Dawa= 9419 e= total employment in Dire Dawa = 116325 Ei= employment in the construction industry in the urban Ethiopia = 507,021 E= total employment in the urban Ethiopia = 7083094 LQi = (e/ei)/(Ei/E) = (9419/116325)/(507021/7083094) =1.13

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in After all the computational processes are completed the LQ analysis is made based on the assumption that if the value of the calculated LQ is greater than one (LQ>1) we label the industry as Basic because it means the industry is capable enough to provide its products or services to the areas beyond its territory and moreover it would mean that that particular industry has the capacity to attract wealth from other urban centers outside of its regions, if the LQ is calculated to be one (LQ=1) it tells that the industry is non-basic but sufficient with its products or services to support the urban centre where it is located in, and if the LQ appears to be lesser than one (LQ<1) the industry is labeled as non-basic because it is not capable enough to support its own locality. In the example shown above the computed result indicates that the construction industry is basic for Dire Dawa during the stated period. The same was done for each industry in all the urban centre s; in due course basic and non-basic industries were identified and summarized in Table 1. ii.

Basic employment index

Estimation of the basic employment of an industry is important to understand the impact of the basic industry in the local economy. The concept emanates from the notion that there would be non-basic employments even in the basic sectors [5]. Davidson and Schaffer [2] in the Atlanta Economic Review used the term ‘excess’ employment to refer to the basic employment because the workforce in this category is above the line of local self-sufficiency and is to be employed or exported to outside of the region. By using the surplus workers index we can compute the amount of basic employments or basic jobs in a basic industry in particular and a region as a whole as follow: or BEI=ei- (ei/LQ)

(2)

Where, ‘BEI’ is the amount of basic employment in the industry ‘i’, ‘e’ is the total employment of an urban centre s, ‘ei’ is employment of an industry (i) in an urban centre , ‘Ei’ is the national- urban employment in the industry (i) and ‘E’ means total national urban employment and ‘ LQ’ is the Location Quotient. It is clear that if the industry is basic it is possible to estimate the amount of the basic employment within the industry. Example, in the analysis procedure done for the construction industry in Dire Dawa LQ is computed to be 1.13 implying that the industry is/ was basic during the stated year. Once the LQ is computed it is easy to compute the BEI as shown below.

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Thus, ei = employment of an industry (i) =9419, and LQ=1.13 for the construction industry in Dire Dawa. Assuming the second formula, BEI = ei- (ei/LQ) =9419- (9419/1.13) = 1092. This means of the total employment in the construction industry in Dire Dawa 1092 were assumed to be surplus and are/were in the export economy. The BEI of all industries in all urban centre s has been computed and summarized in Table 2. iii. Advantage and limitations of the tools Location Quotient is the oldest as well as the simplest method of determining the concentration of industries/ economic activities in a region. It is also one of the widely (both spatially and literary) used techniques of economic base studies. However, it has three major limitations. The quotient shows variation with change in the size of the reference economy. The LQ of an industry can also be affected by the level of industry aggregation. The more the data is aggregated by industry, the more likely a basic industry would be obscured. Moreover, LQ doesn’t give the amount of concentration of industry. As a method it doesn’t also convey meaning to our focus to how intense the concentration of the industries in one area is. In spite of all the limitations mentioned above location quotients could be functional techniques in both identifying basic activities in the local economy and in estimating the share of basic employment in such activities within the considered locality [10]. In this study too, the LQ is meant only to identify the basic and the non basic industries within the selected urban centre s. However, the LQ value of a basic industry can also be used in computing the amount of basic jobs in it. In the estimation of the economic bases of a region / an urban centre, the application of the BEI has been a tradition. The BEI is useful in that it enables the researcher to estimate the amount of the “excess” employment in an industry and opens up ideas for policy measures as it reveals information regarding the capacity of the area. However, the index doesn’t show the structural changes within the national economy. So, it is clear that another method is duly required to see trends and patterns of urban growth and economic development.

5. Identification of basic and non-basic industries in the urban centers As it is made clear in the introduction part of this paper there are four important techniques of indentifying the Basic and the Non-basic industries

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in in studying the economic bases of regions or urban centre s. One of those techniques adequately discussed and selected to be used for this study is the Location Quotient (LQ). The LQ is the simplest technique by which we can easily label an industry as Basic or Non-basic. However, it only tells us the degree of concentration of a particular industry in a particular area. It has the deficiency of informing the analyst how much of the employment in the basic industries are really Basic and how much are non-basic. It has no the capacity to respond to the

notion that there is a possibility for a non basic employment /job to occur even in the basic sectors. In old traditions the LQ had been used to label out the functional roles of industries in a region where they prevail. Nevertheless, the magnitude of the role an industry could play cannot be measured with LQ. Thus in this study the LQ serves only to identify whether an industry is basic or non basic only as a preliminary task for further analysis using a different way i.e the Basic Employment Analysis using the basic employment index.

Table 1. Basic industries of urban centers based on LQ for the year 2015 Major Industries Urban centre s AF F* Adama (RC) Addis Ab.(NC) Asayita (RC) Assosa (RC) Bahir Dar (RC)

NB NB NB NB

M Q 1.2 3 N B N B 1.6 4

3.2 1

0.8 3

Bishoftu

1.1 9

Dessie

1.7 1 N B N B N B 3.7 1 N B N B N B 1.0 1 1.5 6 1.2 7

Dire Dawa Gambell a (RC) Gondar Harar (RC) Hawassa (RC) Jijiga (RC) Jimma Mekele (RC) Shasham ene S

NB NB 3.7 3 NB NB NB NB NB NB

Mf G 1.2 3 1.1 2 1.1 3 NB

1.0 5

W W N B N B N B N B

2.1 2

1.5 7

1.3 8

1.5 8

0.6 3 1.3 9

1.5 1 N B 1.1 3 N B 1.1 4 N B 1.3 7 1.0 8 1.0 7 1.2 9 N B

NB NB NB

EG A NB NB 1.6

2.6 6 2.6 4 1.3 3

1.1 6

1.7 3 2.8 7

1 1.8 N B N B 1.3 3 2.2 6 N B N B N B

C O 1.1 2 1.0 4 N B 1.7 7

WR T 1.1 7

1.3 8 1.4 1 N B 1.0 9

AF S 1.3 2 N B N B N B

0.8 1

1.3 4

1.3 9 1.0 6 1.4 3

0.9

NB 1.4 9 NB NB NB 1.5

NB 1.4 NB 1.3 5 1.0 3 NB 1.2 9

0.7 2 1.1 3 0.8 5 1.1 8 0.8 4 1.4 7 1.7 8

1.1 2 2.3 5 2.2 7 N B

FI A N B 1.6 7 N B N B

1.5 9

N B

N B N B N B 1.2 1 N B N B 1.7 2 N B 1.1 1 N B 1.0 3

N B 2.5 1 N B N B N B N B 1.7 9 N B N B 1.4 6 1.2 4

N B N B N B 1.9 8 N B N B N B 1.0 4 N B N B N B

N B 1.1 5 N B N B N B N B N B N B N B 2.2 8 N B

N B N B N B 1.6 9 N B N B N B

N B 4.1 1 N B N B

1.2 4 1.8 1 1.3 1 1.6 9

1.2 N B N B 1.1 6

AD S

PA D

1.5 9

NB NB

1.2 2 4.6 5

1.0 3

1.7 3

2.2 9

NB NB NB

2.4 7 1.5 3 1.7 8

Ed N B N B N B 1.1 8 N B N B 1.2 3 N B 1.0 7 N B 1.2 7 1.3 7 1.2 1

2.1

1.2 3

1.5 8

N B N B

HS A NB 1.0 9 NB 1.0 7 NB NB 1.3 7 1.0 7 1.9 5 NB 1.9 6 1.4 1 1.1 1.9 6 1.4 1 NB

A R N B 1.6 2 N B 1.0 8

O T N B N B N B N B

Hh E N B 1.1 5 N B N B

E O N B 1.6 5 N B 1.3 5

1.4 7

N B

1.1 7 N B N B N B N B N B 1.2 4 N B N B 2.9 7 N B

N B 1.0 9 1.0 9 N B N B N B N B 1.1 8 1.0 9 N B 1.7 6

N B N B 1.1 1 1.5 2 2.2 1 N B N B

N B N B N B 3.8 1 N B N B 1.4 9 2.5 5 N B 1.2 3 N B

1.1 1.4 6 1.1 8 N B

Source: Computed from CSA (2015) NB- Non-basic industry (LQ<1) NC-National Capital RC-Regional capitals * For acronyms see the Appendix The Location Quotient analysis could be done using data obtained for number of employees, amount of export, amount of import, amount of expense or income of the industries in a particular region or urban centre. As mentioned earlier the availability and the simplicity of using the employment data has become apparent and hence, chosen as the only variable for this study. With

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this in mind we have collected the total national Employment in all industries (E), the national Employment for each industry (Ei), the total employment of each urban centre (e), and the employment in each industry for all urban centre s (ei). Then the LQ is computed using the customary formula and procedures indicated in caption1. Based on Table 1 Gondar (3.73), Bahir Dar

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in (3.21) and Bishoftu (1.19) are more concentrated with Agriculture, Fishing and Forestry industries (AFF). The concentration of AFF in both Gondar and Bahir Dar is more than 3 times higher than the national average. This happens so because these towns are largely inhabited by people who primarily practice agriculture. The result suggests that these urban centers are better specialized in this sector. In the area of Mining and Quarry, the LQ is higher for Gondar (3.73), Bishoftu (1.71) and Assosa (1.64). These urban centers are generally known for mineral excavation in the country. High LQ in manufacturing has been computed for Adama and Bishoftu, showing that the sector is considerably more concentrated in these towns than elsewhere. Located at the heart of the â&#x20AC;&#x153;manufacturing industry beltâ&#x20AC;? along the main trade route of the country, these towns took the lead in this sector. Assosa (1.77), Bishoftu (1.51) and Hawassa (1.37) have the top three LQ for the construction industry implying that the industry is more concentrated in these urban centre s than anywhere else. These towns are the hub of mega projects being developed by the central government. Wholesale and retail trades are more concentrated in Dessie (1.5), Asayita (1.49), Jigjiga (1.35) and Dire Dawa (1.34). Indeed, these towns are known for their commercial activities as they are located near markets outside of the country. Asayita and Dire Dawa also serve as Break-of-bulk points as chosen by the central government. As compared to other towns Shashemene, Adama, Bishoftu and Addis Ababa are more specialized in the transport industry. They are nodal urban centre s functionally linking regions around them. One of the fascinating results in the LQ analysis is the corresponding values of LQ to the towns of Hawassa (1.72), Bahir Dar (1.59) and Adama (1.32) in the AFS industries. It is natural that Accommodation and food service industries would better flourish in areas where traveler or guests arrive frequently. These three towns in Ethiopia are known for hosting tourists, national conferences and students. Hawassa and Bahir Dar are lacustrine towns for which they are able to

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attract a good number of tourists annually. Addis Ababa followed by Mekele is dominated by Real estate (RE) industries. Information communication (IC) industries are also better concentrated in Addis than other regions. These industries however have no greater impacts on the local economy as compared to the transport sector (TS). As the political as well as the economical centre of the country the city has been concentrated with more than 10 industries. This is a marker of existence of primacy in the country as a whole. The Education (Ed) and Health Service Activities (HSA) are nearly twice more concentrated in the town of Jimma than the average share of urban Ethiopia as a whole. The town is the home of one of the biggest university in the country. The town of Harar stands second in the concentration of the Education(Ed) and HAS sectors. The presence of health colleges / institutions as well as two big hospitals might have influenced its economy. Generally, the diversity of the basic industry is low for most of the urban Centre s. Some urban centers, such as Addis Ababa, Jigjiga, Dessie and Mekele have each more than 10 types of basic industries. High diversification means low specialization. In this regard, Gondar has the lowest diversification.

6. Economic bases of urban centers In the above LQ analysis, we tried to identify the basic and the non-basic industries. It only shows the degree of concentration of industries within the urban centre. A further analysis therefore seems to be mandatory to estimate the amount of basic employments in the basic industries to enable to rank out the basic industries based on the impact they caused in the local economy of the urban centre s. To this effect, we have used the Basic Employment Index as shown in caption 2 and the result for each industry in each urban centre has been summarized in Table 2. The shaded values corresponding to each urban centre s show the top three basic employing industries within the urban centre.

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in Table 2. Basic employments of major urban centers by major industries, 2015 Major urban centers

Adama Addis Ab. Asayita Assosa Bahir Dar Bishoftu Dessie Dire Dawa Gambella Gondar Harar Hawassa Jijiga Jimma Mekele Shashamene. S

Percent(%) of Basic Employment of Major Industries

Tot al Bas ic

AF F

M Q

Mf G

EG S

W W

C O

WR T

AF S

FI A

R E

PT A

Ad S

PA D

N B

0. 9

24. 9

N B

7.5

29. 6

17. 3

15. 1

1. 0

N B

3.7

N B

12. 5

N B

2.3

17. 8

N B

12. 7

1. 8

11. 2

9.6

N B

0. 0

11. 2

1.3

N B

67. 6

N B

8. 9

N B

0. 0

3.8

N B

1. 2

0.1

N B

20. 1

1.7

N B

71. 0

N B

1.4

1.8

10. 9

N B

13. 6

N B

11. 7

2. 6

57. 3

0.0

N B

27. 5

N B

3.1

1.9

N B

63. 8

1.9

N B

0. 0

4.0

N B

7.5

55. 8

18. 8

N B

0.4

2.6

N B

63. 3

3. 9

N B

3.0

N B

0. 0

N B

0. 0

N B N B

HS A

AE R

OS A

Hh E

E O

N B

100 .0

N B

1.9

3.4

10. 2

5.6

100 .0

N B

7.3

N B

100 .0

4.5

N B

65. 8

4.3

0.7

0.2

N B

1.4

100 .0

0. 0

N B

1.3

N B

100 .0

N B

0. 0

N B

0.9

N B

100 .0

9. 6

N B

0. 1

N B

0.9

9.2

6.1

3.4

N B

100 .0

N B

1.6

4.7

7.6

N B

100 .0

N B

5.1

N B

9.9

N B

5.1

6.3

26. 5

1.9

10. 6

18. 6

13. 0

100 .0

N B

0. 0

N B

29. 9

N B

100 .0

N B

40. 2

3.5

N B

35. 1

8.7

12. 5

N B

100 .0

1.7

17. 2

3.8

N B

27. 0

5. 4

N B

17. 0

16. 2

7.1

1.1

N B

3.6

100 .0

N B

5.1

3.1

36. 9

5.1

N B

0.6

0. 0

1.8

N B

19. 8

7.2

1.4

5.9

4.3

8.8

100 .0

1.4

N B

3.0

3.4

N B

3.9

N B

0. 0

N B

45. 0

15. 8

3.3

24. 1

N B

100 .0

2. 0

15. 8

4.2

N B

15. 3

19. 0

N B

3. 5

N B

0. 7

N B

8.3

N B

8.1

10. 1

11. 1

1.9

100 .0

0. 8

N B

35. 1

25. 1

N B

1. 5

N B

1.6

7.0

N B

27. 7

N B

100 .0

Source: Computed from CSA (2015) * For acronyms see the Appendix The summary of basic employment analysis for each basic industry in each major urban centre is presented in Table 2. From the table one can easily understand that there is slight deviation from the results obtained in the LQ analysis. In some cases, we may find non-basic jobs even in the basic industries. This would affect the basicity of that particular industry being dealt. The basic employment index enables us to ranks basic economic activities based on the role they play in the local economy. In this regard, the great share of basic employment of Adama has been taken by WRT (29.6%), MfG (24.9%) and TS (17%) industries. The basic employment in the town seems to be fairly distributed among economic sectors. So, these industries have more chance to create additional jobs than others. The economy of Addis Ababa is most affected by TS, FIA and MfG industries as they share mere than 40 % of the basic employment of the city. As we said earlier Addis Ababa is the

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political as well as the economic hub of the country. Hence, inflow and out of goods and passengers to this city is natural. This may be the reason why the transport sector seems to have dominated the export employment of the city. Owing to the growing trend of Banking and insurance activities in the country, Addis Ababa has got a good deal of basic employment in the Financial and Insurance service industries. The city is generally suitable for businesses oriented to customers; and that require relatively better security. AFF industry is still among the top three basic employing industries for Gondar and Bahir Dar. As we justified it earlier, the towns are inhabited by people who partial and fully practice farming and fishing activities. Moreover, Bahir Darâ&#x20AC;&#x2122;s location at the shore of Lake Tana might have played its role to have its basic employment engulfed in to the AFF industry. Areas that tend to be tourist destinations have higher basic employment for Accommodation

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in trade route to Djibouti.

and Food Service (AFS) industries. Hawassa gains much of its basic employment from accommodation and food service industries. A number of Hotels and restaurants have flourished because of the inflow of tourists towards the town. The beauty of the town owing to its location at the shore of Lake Hawassa can attract a considerable number of local and international tourists annually; in return creating more employment opportunities. Assosa and Gambella towns remain to sustain on public administration and defense (PAD) activities. As capitals for economically backward regions and as peripheral towns as they are, these towns offer opportunities of employment primarily in government offices and national defense services. Hence, the basic economy lies on these ‘soft’ industries. Even though, the town of Dire Dawa has been given much attention by the government to make it the eastern corridor for the manufacturing industry since long time before, the town, however, couldn’t go to the length it should go. The basic employment of Dire Dawa is dominated by the service industries; mostly wholesale and Retail trade (WRT), Transport service (TS) and activities of household employers (HhE). In our LQ analysis we noted that, as home of one of the largest universities in the country, the town of Jimma is primarily specialized with Education. The Basic employment Index similarly shows the fact that nearly 45% of the basic employment of the town lies in the Education sector. The sector is therefore the backbone of Jimma town.

7. Basic economy of the major urban centers After computing the basic employment in each basic industry for each urban centre we add up all the basic employments to enable to estimate the share of the basic economy of the urban centre s. Then, percent of the Basic employment was computed. The result has been summarized in Table 3. One way of examining the basic economy of a region is an analysis to be made on the basis of the Base Multiplier Index. Base Multiplier can be calculated for a specific basic industry and or for a specific region. Base Multiplier, for an industry, is the function of the ratio of the total employment of an industry to the basic employment of the same industry in the same year. It explains the role of a basic industry in the local economy by estimating the amount of non-basic employments carried by one basic job. For a region or an urban centre the base Multiplier is the ratio of the total local employment (e) to the total basic employment (BE). This is done because the total employment is assumed to be the sum total of the basic and the non-basic employments. In this regard, we have tried to calculate the Base Multiplier ratio for each urban centre. The value, as said before, indicates the amount of nonbasic jobs created by a basic employment in a particular urban centre. For instance, the Base Multiplier effect for Dire Dawa is 8.0 for the data of 2015. This means that one basic job in the city creates seven (7) non-basic jobs other than itself. The effect of one basic employment in Dire Dawa is lesser than the effect of a basic job in Adama (8.4) or Mekele (7.4) or Addis Ababa (7.8), indeed, higher than the other urban centers. This in other way means, one basic job in Adama creates higher opportunities for a non basic job to emerge around it and that farther would mean there is a relatively stronger polarity or linkage (may be backward or forward) between businesses in Adama.

Most of the major urban centres in the country have their basic employment outside of the manufacturing industry. The manufacturing industry is generally known to have the potential in transforming the economy of a region. Except for Adama, Addis Ababa, Asayita, Bishoftu and Mekele the rest of the towns have no basic employment in the manufacturing industry. These five towns are located along the Ethio-Djibouti main trade routes in the northern and eastern corridor. Four of them have been known for manufacturing since the imperial period. What is emerging recently is Mekele along the northern

Table 3. Estimation of basic economy of major urban centers of Ethiopia, 2015

Urban Centre s

Adama Addis Ab. Asayita

Total Employment (T) (2015)

Total Basic Employment (BE) (2015)

117828

14078

11.9

8.4

1362069

174185

12.8

7.8

12819

1907

14.9

6.7

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% of Basic Employment (2015)

Base Multiplier (T/BE) (2015)

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in Assosa

21112

5779

27.4

3.7

Bahir Dar

124310

31051

25.0

4.0

Bishoftu

57994

7679

13.2

7.6

Dessie

71530

11670

16.3

6.1

Dire Dawa

116325

14540

12.5

8.0

Gambella

27965

6693

23.9

4.2

162404

56073

34.5

2.9

59109

12162

20.6

4.9

124702

19052

15.3

6.5

Jijiga

40815

7937

19.4

5.1

Jimma

75289

12212

16.2

6.2

Mekele

131641

17864

13.6

7.4

54374

9254

17.0

5.9

Gondar Harar Hawasa

Shashemene

Source: Compiled and computed from CSA (2015) The value of a Base Multiplier cannot be less than one. When a Base Multiplier effect of an urban centre tends to fall including and between one (1.0) and two (2.0) (1<x<2), it implies that more of the employment in that particular area is involved in export based industries. That means the local role of the basic employment is lesser. For instance, the BM for Gondar is 2.9 which mean one (1) basic job in Gondar only serves nearly two (1.9) non-basic jobs of the town or nearly 34.5% of the employment in Gondar is basic. The local role of a basic employment in Gondar is lesser than the other’s town. As noted earlier, Agriculture, Fishing and Forestry is the primary basic industry in Gondar. A basic employment in such industries couldn’t create more opportunities for non-basic jobs to emerge around. And hence, a significant amount of employment in the AFF sector in Gondar is meant to serve areas outside of it. This is mainly due to the reason that such industries do not give chance for intra-industry job opportunities to occur locally. This situation is even worse when it comes to the traditional agricultural activities as in our case. To sum up, small BM (near to one) reveals the fact that a good amount of the total employment in the area is involved in export-based businesses that in turn is a gain for the local area. Table 3 was generated and presented here to enable us compare the Multiplier effect of a basic employment of each urban centers. Theoretically, it is assumed that the proportion of the basic employment to the total local employment should be 1:1. That means the basic employment should have taken 50% share of the total employment of the locality. Be that as it may,

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none of the towns in this category fulfill the assumption. It is only Gondar with 34.5% approaches to the theoretical assumption. This is one big weakness of the urban economy in the developing nations.

8. Functional classification and analysis of economic bases of major urban centers It is clear that many researches on a region or urban centers end up with the ranking of economic activities or urban functions based on the values of the location quotient. Our intention here is not to retain the old traditions. The importance of the location quotient in determining the basic and non basic industries has become apparent in this study too. The percent of the Basic employment, however, has been used to generate the 1 st, 2nd and 3rd economic base of the urban centre s because the method is thought to have the caliber to filter the residual non-basic jobs in the basic industries and refines the role of the basic industries. Table 4, therefore, shows the economic bases of urban centre s by 1st, 2nd and 3rd basic employing industries. It is assumed that basic industries in general are “engines” of the local economy. The growth or decline of these industries would imply the growth or decline of the urban centre s. From the analysis we have had so far, we try to classify the major urban centers of Ethiopia into 8 broader categories as in Table 5. Such classification in the country has not been accustomed so far.

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in Table 4. Functional classification of urban centre s by top basic employing industries, 2015

Urban centre s

First Basic Industry Second Basic Industry (2015) (2015) Adama WRT MfG Addis Ababa TS FIA Asayita WRT MfG Assosa PAD CO Bahir Dar AFF AFS Bishoftu MfG CO Dessie WRT IC Dire Dawa WRT TS Gambella PAD HhE Gondar AFF HhE Harar WRT PAD Hawassa AFS CO Jigjiga WRT PAD Jimma ED HhE Mekele TS MfG Shashamene WRT OSA Source: Compiled from Table 2 and CSA (2015) *For acronyms see the Appendix Those urban centers that tend to have greater index of Basic employment in the agriculture sector are generally labeled as agrarian towns. Even though the Mining and Quarry industries are week at national and regional as well as urban levels some towns have shown a considerable amount of basic employment in this sector. Hence, they are labeled as Mining towns. As the old tradition reads those towns along the EthioDjibouti trade route were called the â&#x20AC;&#x153;pearls of the manufacturing industryivâ&#x20AC;?. In our analysis, the same patter was revealed and labeled as manufacturing towns. The fourth group is the set of commercially active towns whose main activities encompass wholesale and retail trades. Such towns are located either near the centre or near boarder areas. Hence, they are referred to as commercial

Third Basic Industry (2015) TS MfG IC PTA CO AFF ED HhE HSA MQ HSA PAD EO HSA CO TS

towns. Those towns that have tourist attraction sites and are capable of accommodating and serving tourists are labeled as recreational towns. Towns in which Public administration and defense activities (PAD) dominate are named as Defense towns. Both historically as well as geographically, these towns have been found suitable to military camping and other defense activities. As the result shows, major towns which are located near the centre tend to have a good deal of their basic employment in the transport industry. Moreover, some of these towns today are designated by the government as dry ports. So, we prefer to call them Break-of-Bulkv points. However, such generalization would be better if done bases on results observed at two long range points of time. In this regard, a shift share analysis could be a better away.

Table 5. General classification of major urban centre s of Ethiopia

No. General Classifications Towns Based on Priority Agrarian towns Gondar, Bahir Dar 1 Mining Towns Gondar, Mekele, Adama, Bishoftu, Assosa 2 Manufacturing towns Bishoftu, Mekele, Addis Ababa, Adama, Asayita 3 Commercial towns Dessie, Dire Dawa, Adama, Jigjiga, Harar, Shahsemene, Asayita 4 Recreational town Hawassa, Bahir Dar 5 Educational town Jimma, Harar, Hawassa, Dessie 6 Defense town Gambella, Assosa, Jigjiga, Harar 7 Break-of-Bulk points Adama, Dire Dawa, Shashemene, Mekele, and Addis Ababa 8 Source: Compiled from Table 1 and Table 2 and the analysis done above 9.

Conclusions and directions for future researches From the study and the analysis we have done,

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it can be concluded that the diversity of basic industry in most of the urban centre is high. Moreover, many of the urban centers under study contain more than 70-90 % their employment in the non basic industries. This leads to conclude that the

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Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017 ISSN: 2454-1362, http://www.onlinejournal.in 1:1 basic non basic ratio of the theoretical assumption has not been achieved by any of the urban centre s. Furthermore, except five (5) urban centre s none of them have basic employment in the manufacturing industry. This means it would be uneasy to transform their economy in a short period. The theory says that the way to strengthen and grow the local economy is to develop the basic sector. Model based study of urban centre s is mandatory. Government bodies should work on developing data bases regarding the demographic and economic contents of urban centre s. A well organized and easily accessible data would attract researchers to involve in model based researches. In this regard, if long range data of two points of time could be obtained, a study of this fashion would be done in a better quality using a shift share technique. In the case of Ethiopia, accessing long range data (15-30 years) collected with the same format is unthinkable. 10.

Acknowledgement

We are deeply grateful to all bodies who directly or indirectly contributed to the accomplishment of this work.

Holland Publishing Company. Metropolitan Studies Centre , Syracuse University, Syracuse, N. Y., U.S.A. [7] Isserman, Andrew M. (2000) “Economic Base Studies for Urban and Regional Planning” In the: Profession of city Planning Changes, Images, and Challenges 1950-2000. Eds. Lloyd Rodwin and Bishwapriya Sanyal. New Brunswick, NJ: Centre for Urban Policy Research. Copyright © 2000 by Rutgers, Centre for Urban Policy Research, The State University of New Jersey. [8] Kiser, Don. (1992) A Location Quotient and Shift Share analysis of Regional Economies in Texas. South Texas State University. (Unpublished Thesis done for the partial fulfillment for Degree of Master of Arts in Public administration). [9] Krikelas, C. Andrew. (1992) “Why Regions Grow: A review of Research on Economic-Base Model”: In the: Economic Review, Federal Reserve Bank of Atlanta. Pp.16-29. [10] Leigh, Roger (1970). “The Use of Location Quotients in Urban Economic Base Studies” In the: Land Economics, Vol. 46, No. 2 (pp. 202-205) Published by: University of Wisconsin Press.

11. References [1] CSA. (2015) Statistical Report on the 2015 Urban Employment Unemployment Survey, Statistical Bulletin, Addis Ababa: Central Statistical Agency [2]Davidson, Lawrence S. and Schaffer, William A. (1973) “An Economic Base Multiplier for Atlanta, 1961-1970” In: Atlanta Review. Vol. 23. No.4. [3] Dinc, Mustefa. (2002) Regional and Local Economic Analysis Tools. Prepared for the Public Finance, Decentralization and Poverty Reduction Program, World Bank Institute. The World Bank, Washington, DC. [4] Engida Esayas. (2015) Analysis of the Changing Functional Structure of Major Urban Centre s in Ethiopia. DOI:10.4314/ejbe.v4i2. Research Gate. Addis Ababa University. [5] Foreschle, R. (2005) What to do with all this Data? The Role of Economic Base Analysis in Regional Economic Development. Economic Base Analysis research. Unpublished. [6] Greytak, David. (1974) “Regional Industry Multipliers: An Analysis of Information” In the: Regional and Urban Economics 4 163-172. North-

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[11] Matthew Fisher & Assco.Inc. Economic Development Solutions. (2006) Economic Base Analysis and Rural Development Strategy for Oxford County, Ontario. An Economic Strategy. Pp.1-40. [12] Misra,V. N., Wishwakarm, R. K. and Sundaram, K. V. (1975)“Economic Base and Multiplier Analysis: A Study of Indian Towns and Cities” In the: Indian Journal of Industrial Relations, Vol. 11, No. 2, pp. 177-191 Published by: Shri Ram Centre for Industrial Relations and Human Resources. [13] Schaffer, William A. (2010) “Regional Models Of Income Determination: Simple Economic Base Theory” In the: Economic Review, Federal Reserve Bank of Atlanta. Pp.1-12 [14] Solomon Mulugeta. (2008) “The Economic Bases of Ethiopian Urban Centers” Journal of Ethiopian Studies, Vol.XLI, No. 1-2, JuneDecember 2008. [15] Strotebeck, Falk. (2010) The Location Quotient-Assembly and Application of Methodological Enhancements. Munic Personal RePEc Archive. MPRA paper no. 47988.

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12. Appendix Table 6. Classification of industries in Ethiopia

Code

Major Industries/occupations/ Functions

Categories*

AFF

Agriculture, Forestry & Fishing

Mining & Quarrying

Primary Economic Activities

MfG

Manufacturing

EGA

Electricity, gas steam and air conditioning supply

Water supply, waste management and remediation activities*

CO WRT

Construction Wholesale &Retail trade and repair of vehicles*

Transport, & storage

AFS

Accommodation and food service activities

IC FI

Information and Communication Financial and insurance activities

Real Estate activities

PT ADS

Professional scientific and technical activities Administrative and support service activities

PAD

Public administration and defense; Compulsory Social Security

Education

HSA

Human health and social work activities

Arts entertainment and recreation

Other service activities

HhE

Activities of households as employers; undifferentiated goods and service producing activities for own use Activities of extraterritorial organizations and bodies

Secondary Economic Activities

Tertiary Economic Activities

Source: Compiled from CSA (2015) i

as used in [2] to refer to basic employments Surplus here refers to the amount of basic employment which a region or an urban center could export it other regions/urban centers. iii Addis Ababa and Dire Dawa are city administrations designated based on proclamations. iv The phrase has been used in different literatures to refer to the arrangement of the towns along the trade route. v A point at which bulk commodities are loaded and unloaded; and stored for long term till needed for use. ii

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