Policies and Interest Rates During the Crisis by Daniele Stanizzi

POLICIES AND INTEREST RATES DURING THE CRISIS: A DYNAMIC MODEL APPROACH Daniele Stanizzi 2012 University of Central Lancashire

Tutor: Zakaria Ali–Aribi

Contents Acknowledgment.......................................................................................................................................................II Introduction............................................................................................................................................................... III Literature Review ....................................................................................................................................................... 1 Financial Crisis: Overview .................................................................................................................................... 1 The shadow banking ............................................................................................................................................... 5 Instruments of monetary policy...........................................................................................................................9 Open Market Operations..................................................................................................................................... 10 Standing Facilities .................................................................................................................................................. 11 Minimum Reserve Requirements for Credit Institutions.......................................................................... 12 Transmission channels ......................................................................................................................................... 13 Inflation Targeting ................................................................................................................................................. 14 Term Structure of Interest Rates – The Expectation theory..................................................................... 16 Yield Curve and Interest rates spread .............................................................................................................. 16 Fiscal Policy ............................................................................................................................................................. 17 Methodology.............................................................................................................................................................. 20 The Overnight Rates ............................................................................................................................................ 20 Monetary policy through Inflation targeting................................................................................................. 21 Interest Rate, Production and Inflation ......................................................................................................... 25 Yield curve and interest rates spread .............................................................................................................. 29 Towards the equilibrium – the Dynamic IS–LM model .............................................................................33 Fiscal Policy – Implementation ..........................................................................................................................38 Conclusion .................................................................................................................................................................. 43 Appendix..................................................................................................................................................................... 46 Bibliography ............................................................................................................................................................... 47

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To my parents and my family, whose endless love and support have made all my achievements possible. And to Clare, for her love, patience and encouragement.

ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

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Introduction The following research thesis is a study of the recent crisis that struck the global economic system in recent years. Throughout this study, we will focus on the cause and effect of the recession, and the actions that governments and authorities have undertaken to contain adverse consequences. The first step is to give an overview of what happened, examining the historical facts that have followed through these recent years, starting with a description of the mortgage crisis in the United States, which was also the triggering event. We will illustrate its functioning and how the bubble swelled and burst in 2007 as a consequence of the ceasing of the upward trend in housing market prices. Then we will discover how this paralysis spread beyond the American system, infecting the main economies all around the world. This study is mainly concerned with the British, European and American macro areas, and for each of which an attentive analysis will be carried out. Indeed, the following step is the purpose of this research, and it will consider the measures employed by governments and central banks to control the adverse consequences of the crisis. Specifically, a thorough examination will be conducted to estimate the effects that were yielded in the aforementioned economies. This analysis will also allow us to conduct a ‘diagnosis’ of these macro systems and simulate hypotheses over the evolution of the recessive trend. We will look in detail at the monetary and fiscal policies undertaken by the Bank of England, European Central Bank, Federal Reserve and their respective governments. A crucial theme to the analysis is that of interest rates; we will see how this variable is fundamental within the economy and markets in general. As a matter of fact, the influence of interest rates is somehow dominant in every aspect and for this reason we will look at their direct and indirect effects on the main macroeconomic variables, such as inflation, GDP, production and economic growth, in order to evaluate the conditions of the economies at the focus of this study. The research will be conducted as follows: we will gather and plot economic, macroeconomic and financial data over the period of the last twelve years. This will clarify the trend of the economies even before the crisis, starting from the dawn of the new millennium; this will provide a significant visual disruption that, unsurprisingly, coincides with years 2007 and 2008. As previously mentioned, we have decided to limit the selection of our analysis to the areas of the United Kingdom, Eurozone and the United States; we believe this choice is the most sensible not only because they are the three biggest macro economies we are influenced by, but also because they are very influential on the rest of the global economies. Furthermore, these are the systems that are suffering the most adverse of consequences as a result of the recession; therefore, their analysis is crucial for a thorough understanding of the ©2012 – Daniele Stanizzi

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events that will allow us to examine the whole development and evolution of the crisis from the origin to the expansion in the global markets. The report contains two main sections entitled literature review and methodology. The literature review outlines the theoretical framework and the instruments utilised to conduct the research, as well as the technical findings and observations derived from other papers, reports or articles developed by economists and specialists in general. This literature review is of crucial importance for the complete understanding of the rest of the study; in fact, it is imperative that the notional background on which the models and concepts are based upon is clear and understood, so that the reader will be able to appreciate the value of the analysis developed in the impending methodology. Specifically, we will look at the macroeconomic principles that governments have adopted to contain the recession (i.e. monetary and fiscal policies, inflation targeting model, expectation theory and term structure of interest rates). Other than the theoretical framework, the literature review will contain some of the history of the crisis, and will look into some of the important financial aspects found to be playing a crucial role in the crisis. In particular, we will focus on the shadow banking system; a financial system per se that has become a highly debated matter at the heart of the markets. We will explain how this system has affected the banking sector and, consequently, investors and companies, leading to the crisis of finance as we know it today. Finally, we will provide some of the possible solutions that have been suggested throughout the vast literature review relative to this topic. The methodology is the core of this study and involves the application of the whole theoretical approach directly to the economic systems under investigation. For this reason, a few words must be spent relative to the method adopted to conduct the following study. Being that this is an examination over financial and economic matter, we will deal with vast amounts of data, of which great parts will consist of primary data. Therefore, we have opted for a quantitative approach to conduct the research, considering such a choice to be the most useful and appropriate, when handling such a volume of raw data that, thanks to its nature, is the most suitable for statistical computation and modelling. Throughout the research we will show the fitting of each model only in relation to one case of the three available, in order to understand its functioning. As for the remaining areas, only the outcomes of the same model will be explained, clarifying the results throughout a theoretical approach, along with an appropriate explanation and, subsequently, a comparison of the results and an evaluation of the findings. This method will allow us to directly associate the same model to our different cases, illustrating the main features just once and giving way to the more interesting interpretation of the outcomes. Where necessary, the data will be processed with the help of the statistical software RÂŠ, which will support our research on the ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

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computational side. This will be in the case of regression tests on datasets and correlation tests between variables. Moreover, the support of statistical software will allow us to take a step further in the analysis. Indeed, it will be possible to carry out a calculation to estimate future values of some macroeconomic variables and, therefore, forecast how these variables could fluctuate within the short–period, using a time series approach. Next, we will consider the evolution of the IS–LM theory by Olivier Blanchard, the most important model for dynamic analysis. As before, we will relate the model to a real case in order to understand its functioning and also to clarify the fundamental rules on which the authorities base their choices of monetary and fiscal policy. All specific information about data will be contained in the Appendix, to be found at the back of the research thesis.

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Literature Review Financial Crisis: Overview The first question we want to answer is how we came to the point where several banks collapsed and the major economies are now in trouble. Notably, the responsibilities fall on different subjects; the banks are likely to be the first in line. Time has listed 25 people who are to blame for the crisis (2009) whose professional belonging leads essentially to banks, governments, rating agencies or important companies. The most severe financial crisis of the last decade began in the United States in August 2007 in a moderately small market segment: subprime mortgage loans. Today we all point the finger at some American financial companies (i.e. Fannie Mae, Freddie Mac) whose unwary behaviour triggered a series of events that led the major economies to the dire situation in which they find themselves today. Let us then illustrate how all of this happened. Before a bank or a financial services company lends money to an individual or any legal person, they want to make sure that the loan is going to be repaid according to an amortisation plan, which is set up beforehand. This is because of the presence of what behavioural finance defines as adverse selection. This term refers to one of the information asymmetries that are likely to occur when dealing with risk management. Precisely, it implies that borrowers that are subject to a higher credit risk are more likely to require a loan (Redhead, 2008), which as we will see later, are defined as subprime. In order to face this problem, lenders base their final decision on several aspects which include: borrower’s credit score, LTV ratio, interest rate, loan amount, and level of indebtedness (Demyanyk, Van Hemert; 2009). Only after an accurate analysis, can they finally make the decision to grant or reject a loan request. The first critical mistake we have to point out has been made by some banks, when they decided to concede mortgage loans to the above mentioned segment of subprime borrowers, that is, those individuals with a higher–than–average risk profile whose ‘financial health’ was not in a sufficiently good state to ensure the payback. The first step that encouraged American financial institutions to this obviously dangerous behaviour is a change in regulation in 1980 when the Deregulation and Monetary Control Act (DIDMCA) was adopted. This act essentially legitimated to “charge high rates and fees to borrowers”. Secondly, in 1986, another modification introduced the Tax Reform Act which made high–cost mortgage debt quite cheap (even cheaper than consumer debt), permitting uncontrolled access to credit for subprime borrowers (Chomsisengphet, Pennington, 2006). Indeed, the analysis of this specific market reveals some serious facts as shown ©2012 – Daniele Stanizzi

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Figure 1: The steady growth of subprime loans from 1995 to 2003.

Source: Chomsisengphet, Pennington, p. 38

in Figure 1 above: risky lending registered a steady growth from 1990, hiking from 28.4% in 1995 to 58.8% in 2003. A further examination, though, reveals an abnormal peak registered from 2003 to 2006 (Figure 2). This boom can be easily explained just by looking at the housing market trend in those years. Figure 3 shows the firm increase of house prices from 1990. This was due primarily to the economic growth of the late 1990s and low interest rates in the 2000s (Labonte, Makinen; 2008). This upward drift was injecting financial institutions with confidence because in the case of delinquency, they could still count on the foreclosure and claim their properties back (Chomsisengphet, Pennington, 2006). The mechanism worked fine during the growth but it jammed up when the housing market bubble burst in late 2006, when this appreciation stopped and began its fall. The bubble was being inflated even by speculative behaviours: many were the investors who were buying houses and selling them at a higher value in the future pushed by a market that was flourishing and registering growing demand and consequently rising prices. It was on 7th of September 2006 when Nouriel Roubini, an economics professor at New York University, held a speech warning the United States about the housing bubble and its immediate consequences (Mihm, 2008). During a long interview he held in 2008 he forecasted a big recession and hundreds of banks failing in view of “mounting losses as a result of the housing bust” (Reuters, 2008). Indeed, the turmoil began when the Fed decided to raise its interest rate in 2004 (reasons will be explained at a later stage in ©2012 – Daniele Stanizzi

Figure 2: The peak of subprime loans.

Source: Federal Reserve Bank of San Francisco

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the

research)

leading

downturn of the housing market

$70

as a consequence of the higher

$60

cost of borrowing. However, a

$50

most severe effect was taking

$40

place: the default on mortgages with adjustable rates. According to a speech of Chairman Bernanke

Lehman Brothers HLD

$30 $20 $10 $0

(2007), by August 2007 about 16% of loans compromised.

were The

already financial

tumult was made even worse by

Figure 4: LEHMQ historical stock prices pointing out the plummet from October 2007 to its bankruptcy.

Source: Yahoo! Finance

what has been defined as shadow banking. This vast ‘wild’ quantity of securities, of which we will talk in the next section, made it hard to measure the risk exposure for many financial institutions which led to an increase of market uncertainty and instability; banks suddenly raised the interest rates they were charging each other and started claiming all their funds back, triggering a liquidity crisis. The effects immediately hit Wall Street generating the first catastrophic consequences. Some banks (Lehman Brothers, AIG, Fannie Mae, Freddie Mac) were on the verge of bankruptcy. On 15th September 2008, after a sharp fall of 80% on stock prices over the past year, the financial services company Lehman Brothers collapsed. The seriousness of the situation was now evident: this was the biggest–ever bankruptcy in history (Checkler, 2011). After a while, the crisis struck Europe as well. This happened because the banking system is internationally linked; hence, each event shakes more or less all markets around the world. Europe is in fact economically and financially strictly linked to the American system. Precisely, many European and British banks were holding a considerable amount of American mortgage securities among which subprime residential mortgage–backed securities (RMBS) (Whittall, 2009) and that eventually led to significant losses. We are currently going through probably the biggest recession since the Great Depression of the last century; several European countries are in serious trouble with their public debt and after the most recent events such as the Greek bailout and the election that took place in the same country, even the Euro itself has been brought into question (The Guardian, 2012). It is interesting to understand the main mistakes that have been made during the Great Depression and notice how we have learned from the past, avoiding dangerous behaviours that could have made the plummet even worse. Some argue that the crisis that hit the United States in 1929 brought the entire economy to its knees because of several errors made by the ©2012 – Daniele Stanizzi

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American government (IlSole24Ore, 2008). There were essentially four causes that led to the disaster: firstly, the restoration of protectionism; this caused a severe drop in exports and enhanced the recessive effects; secondly, the government adopted a monetary restriction (instead of an expansion), which increased panic among investors and savers and literally dragged down consumption and output; also, the government’s decision to not mediate when the first bankruptcies happened; finally, a fiscal restriction increased taxes with the purpose of keeping public finances under control. This, instead, caused an even larger fall in consumers’ consumption, bringing the economy to a severe stall (The Economist, 2011 and IlSole24Ore, 2008). Nowadays, five years on from the beginning of the plummet, the situation is still quite serious. Recovery appears to be very fragile, with high rates of unemployment, debt and low growth in many developed countries, as mentioned by a Press Release by the World Bank (2012). Currently, Europe seems to be in trouble as the stability of unique currency Euro is undermined after only

350

ten years since its introduction.

300

facing a recession as their GDP has been plummeting for several quarters now. Andrew Oxlade (2012) created a remarkable chart (Figure 5) relative to the United Kingdom and presented in the next page; it compares the

250 Prices

Most of the richest countries are

CPI

200 150 100 50 0 mag-90

ott-95

apr-01

ott-06

apr-12

Figure 3: This is the House Price Index and it shows the trend of house prices.

Note how prices stopped rising and began to fall by the end of 2006. Source: Moody’s Economy (Freelunch.com)

GDP of the previous crisis with the current one, giving an outlook over the possible duration of the recession and the recovery timing. As we can see, the UK, as well as the rest of the countries, is still far from the normal GDP levels which don’t seem to be growing either. A part from economic growth, another severe problem that is being faced during the production of this study, is the public debt of some European countries like Greece, Italy and Spain. Notably, Greece, which is probably the country in deepest trouble, is hanging in the balance between remaining in the EU or leaving the Union and its currency. This scenario is known to be the worst (Craft, 2012) because not only it would set a precedent for other countries, but also it would trigger a series of events that would bring the current situation from bad to worse. Indeed, as mentioned in an article by BBC News (2012), the consequences would be the meltdown of the country and the default of both public and sovereign debts, bank runs, many bankruptcies, political backlash and recession. ©2012 – Daniele Stanizzi

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Figure 5: How the recovery from recession compares with those of the past.

Source: ThisIsMoney

The shadow banking It is not an easy task to provide a definition of shadow banking system, although many have attempted to describe it one way or another. However, we came across an exhaustive definition that seems to provide the most precise and accurate description of this typically American phenomenon. This definition has been presented by Willem Buiter in 2008, who stated that “the shadow banking sector consists of the many highly leveraged non–deposit–taking institutions that lend long and illiquid and borrow short in markets that are liquid during normal or orderly times but can become illiquid when markets become disorderly.” According to this explanation, thus, there are several institutions that are allowed to act like banks, but seem to have more independence when operating in markets. Indeed, Buiter also states that these societies are “barely supervised and regulated” and “are not subject to any meaningful prudential requirements as regards liquidity, leverage or any other feature of their assets and liabilities”. The low–regulation attitude that dominates the UK’s markets has surely attracted this category of financial institutions. A report from the Federal Reserve Bank of New York (2010) lists some examples of these shadow banks, in which activity has swelled incredibly during the last twenty years, eclipsing the size of the traditional system (Breslow, 2012) and pushing shadow liabilities up to over $20 trillion in 2008 – about double the level of commercial bank liabilities in that year (Figure 6). These institutions include asset–backed commercial paper (ABCP) conduits, structured investment vehicles (SIVs), credit hedge funds, money market mutual funds, securities lenders, limited–purpose finance companies (LPFCs), and the government–sponsored enterprises (GSEs)” (FRBNY, 2010). Governor Daniel Tarullo held a conference at the Federal Reserve Bank of San Francisco over the shadow banking system (2011). According to his words, this ‘buried’ activity ©2012 – Daniele Stanizzi

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refers

the

composition of assets that

are

only,

theory, safe, short– term and liquid; these characteristics are an illusion to investors who consider these assets

‘cash

equivalents’

and,

therefore, similar to deposits ordinary

the

banking

system. The crisis has,

Figure 6: The tremendous growth of Shadow Bank liabilities in relation to Traditional Bank Liabilities, $ trillion

however,

Source: Flow of Funds Accounts of the United States as of 2011:Q3 (FRB) and FRBNY throughPozsar (2012)

revealed

their profound difference in respect to insured deposit. According to the authors of the FRBNY report, these financial intermediaries who specialised in shadow banking are directly involved in the run–up to the crisis of financial markets. Moreover, a recent article (Whitney, 2011) points the finger at traditional banks, because they utilise short– term loans on the repo markets (which stands for repossession agreements and are part of the shadow banking system) in order to acquire their funding. Indeed, the article continues, this is a way for commercial banks to reduce the credit risk that looms over their balance sheets, and therefore cutting the costs for their operation. These financial institutions support this system, arguing that borrowers will benefit from cheaper cost of credit, and that it generates a higher quantity of activities, producing a faster growth in the economy. However, the risks that this type of operation involves are significantly greater and cannot be contained without proper regulation; this was substantiated when financial markets burned trillion of dollars as a consequence of the meltdown of 2008 (FoxNews, 2008), an aftermath that has seen the value of the activities in the shadow banking system deflating by more than a half over the last few years (Breslow, 2012). Let us try to understand in what way this system compounded by a massive amount of ‘wild’ liabilities has affected the global financial system. Ironically, the crisis hit after the release of Basel II, the set of rules imposed by the Basel Committee on Banking Supervision (BCBS) that aimed to create an international standard for banking institutions. However, according to Buiter (2008), this agreement contains essentially three fatal flaws in Pillars 1 and 2, flaws that have been highlighted ©2012 – Daniele Stanizzi

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even by other specialists (Redak, Tscherteu, 2012). In particular, the first problem arises with financial procyclicality; this issue is related to the potential dangerous behaviour that would lead banks to lower their loans in response to the rise of credit risk during recessive periods, further worsening the conditions of the economy. The second problem is the advantage that bigger credit institutions would have on smaller ones in terms of ease of obtaining more sophisticated instruments of credit risk analysis, further increasing their competitive advantage over small institutions. The last issue is concerned with rating agencies, that is, the goodness of the risk– weightings rating processes of now–discredited rating agencies. We have linked the beginning of the economic crisis with the collapse of Lehman Brothers on 15th of September 2008. However, the article by Whitney (2011) notes the words of P. McCulley, in August 2007, where he argues that the financial turmoil began on August 9, 2007. His words assert that the crisis started “in France, when Paribas Bank (BNP) said that it could not value the toxic mortgage assets in three of its off–balance sheet vehicles, and that, therefore, the liability holders, who thought they could get out at any time, were frozen”. Indeed, in the United States, many funds suffered significant capital losses at the collapse of the asset–backed commercial paper market in 2007 ; reportedly, this happened because support for small losses provided by the Reserve Primary Fund ceased to exist when issues regarding the safety of these monetary funds arose (Tarullo, 2012). Panic started to spread among investors, triggering an expected “run–on–repos” that caused a withdrawal of nearly $200 billion in just two days. The entity of the turmoil was such that, for the first time, the Treasury and the Federal Reserve had to intervene, injecting liquidity and reassuring the markets. Nevertheless, the real level of risk investors were bearing (but could not perceive) was now clear, as well as the fact that the borrowers were entities who could actually go bankrupt. Therefore, the problem was caused by these banks that created dodgy loans, aware of the fact that the level of risk of the borrowers was not adequate to the amount of the credit. Moreover, in order to further obscure the inadequacies of these contracts, their dodgy loans had been fractionated into complex products of financial engineering, mainly mortgage–backed–securities, and sold to other companies, funds or private investors (Whitney, 2011). Notably, these instruments have been defined toxic assets because, by that point, no one was really able to make a correct estimation and provide an accurate value anymore; indeed, markets had not adjusted the price of these assets yet. However, the banks had been utilising these securities in order to acquire funding in the repo market; securities that were gradually losing their value, ensuing a drop in liquidity for these banks. Remember the vast volume of funding that counted trillions of dollars, and that was quickly depreciating. As confidence among financial institutions was decreasing, the liquidity crisis was approaching, adding even more uncertainty in the markets. Indeed, according ©2012 – Daniele Stanizzi

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to Adrian and Shin (2009) these failures of the market are the “root of the crisis”. Professor A. R. Admati teaches Finance and Economics at the Graduate School of Business at Stanford University; in one of her articles on the New York Times (2011) she asserts that “Housing policies alone […] would not have led to the near insolvency of many banks and to the credit–market freeze. The key to these effects was the excessive leverage that pervaded, and continues to pervade, the financial industry”. The European market seems to have suffered less the consequences of shadow banking. In fact, according to the vice–president of the ECB, lending activity usually takes place in the regulated markets. Moreover, the volume of securitisation activity in the Euro area cannot be compared to the American (Constâncio, 2012). Also, he continues, repos markets are defined as Over–The– Counter, that is, markets where there is no complete source of information in Europe because rates and volumes are very hard to monitor. The ECB has published an Occasional Paper (2012) relative to the shadow banking system in Europe; reportedly, the main components are four: securitisation activities, money market funds, the repo market and hedge funds. Moreover, it confirms the difficulties in providing an accurate estimate of the volume of shadow banking in Europe, due to a limited quantity of economic and financial statistics. However, some findings have demonstrated a growing interconnection between the standard banking system and shadow banking. Fortunately, there are some solutions that could contain this uncontrolled speculation that has undermined global finance and triggered catastrophic effects. Tarullo argued that, despite the important contraction of the shadow banking since the peak of the housing bubble, the possibility that some forms of such speculation still exist and are somehow linked to that bubble is concrete. It is worth noting that the whole of the literature we have consulted in regard to this topic is concordant over the regulation of the shadow banking. Tarullo, indeed, continues by stating that only appropriate policy changes could prevent these channels for shadow banking from growing and becoming dangerous again. In fact, “at the European level, the need for the creation of a single EU regulator for any given market segment, responsible for all financial institutions engaged in significant cross–border activity (including foreign subsidiaries and branches) is now paramount. It is key that the Bank of England should follow the example of the ECB and extend its list of eligible collateral at the standing lending facility and in open market operations to include routinely private securities, including asset–backed securities. It should also extend the maturity of its standing lending facility loans from overnight to up to one month, taking a leaf from the Fed this time. Finally, it should extend the list of eligible counterparties at the standing lending facility and in its repo operations to include not just banks and similar deposit–taking institutions” (Buiter, 2008). ©2012 – Daniele Stanizzi

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Tarullo also complains about a large fragment of the repo market still being obscure today, highlighting the need for greater transparency in relation to the shadow banking, and precisely to its markets and transactions. Some financial departments are, in fact, currently working on enhancing transparency in order to provide more information about the shadow market. The volume of bilateral repo transactions is, indeed, still very difficult to quantify. Moreover, it is important to further reduce the risk of runs (repo runs and runs on money market funds); the Bank of England have suggested the setting of new limits on banks’ funding which is generated from money market funds; this appears to be an effective strategy. Buiter (2008) also remarks that some changes should be made to the credit rating agencies sector; precisely, he believes that these agencies should be “unbundled” and reconstituted as companies aimed only to sell ratings, in order to eliminate the clear current conflict of interest. In conclusion, a Staff Report of The Federal Reserve Bank of New York (Adrian, Shin, 2009) sets the standard on how the regulation should be carried out. There are essentially four steps to take: (1) constraints in leverage ratio that will stop it from reaching excessive levels; (2) the application of a forward–looking provisioning scheme, already in use in Spain, that regulates each loan made by financial institutions. It is, in fact, proven that such an approach maintains the banking system more solid; (3) explicit rules on countercyclical capitals and, finally, (4) rules of base capital adequacy over measures of systemic risk for certain institutions.

Instruments of monetary policy So far, we have provided an overview of the crisis as an uncontrolled fall; as a plummet that seems to progress before the general powerlessness of governments and authorities. Conversely, central banks are capable of taking action on the events with some very effective instruments; this is exactly what we are going to analyse throughout the course of this study so we can understand what are these instruments and how they are at the disposal of monetary authorities and governments. Monetary policy is the pool of actions that central banks can undertake to influence the economy of the area they operate. The primary objective of this process is to maintain price stability1 and also “support the general economic policies” (Council of European Union, 2010). According to the European Central Bank (referred to as ECB from now on) and the Bank of England, price stability brings positive outcomes such as low inflation and confidence in the currency and consequently “full employment” and “balanced economic growth”. However, while the objective of price stability has 1

According to The Treaty on the Functioning of the European Union, Article 127 (Council of the European Union, 2010)

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been clarified, no precise definition or description has been provided of what is intended by it. The ECB’s Governing Council has, thus, introduced the HICP (Harmonised Index of Consumer Prices) which aims at controlling the fluctuation of prices. A more detailed discussion will be carried out when introducing the concept of inflation at a later stage in this study. Notably, the operational framework of monetary policies consists of the following instruments: 

Open Market operations



Standing facilities



Minimum reserve requirements for credit institutions

Open Market Operations This first set of instruments is of primary use in implementing a monetary policy and involves the buying or selling of government bonds by the central bank. These transactions take place in the open market and usually involve the trading of large amounts of bonds, ensuing deep changes in the markets in

Interest rate

terms of money supply. Precisely, open market operation’s

functioning can be easily explained as it follows: when the

MS1

central bank performs an OMO that involves the acquisition of a set amount of bonds, liquidity in the

markets increases, destabilising the current equilibrium.

In fact, money supply is too high, and only a decrease of the interest rate could guide the economy towards a new equilibrium.

This

particular

case

illustrates

MD Q of Money Figure 7: The functioning of open market operations

expansionary policy and it is clearly explained in Figure 7. OMO’s, hence, and permit the control over the base money and the short–term interest rate, which is exactly the variable that central banks regulate. OMOs can be divided in four types which can have different purpose, regularity and process.  Main refinancing operations  Longer–term refinancing operations  Fine–tuning operations  Structural Operations Remarkably, one of the most important manoeuvres adopted by the Bank of England refers to a purchase of £75bn of asset, especially gilts, in 2009. As described by an article by Julia Kollewe (2009) on The Guardian. The measure was important and compared to 5% of GDP. The result of the measure, as expected, was meant to push yields lower and reduce borrowing costs for ©2012 – Daniele Stanizzi

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individuals and businesses. A particular case has to be mentioned about the Euro zone. In fact, ECB president Trichet announced in 2010 that no purchase of government bonds were about to take place (The Guardian, 2010); the decision stemmed from the idea that governments had to follow their stabilisation programmes in order to avoid Spanish, Irish and Portuguese debt to reach unmaintainable levels.

Standing Facilities2 Standing facilities is the instrument that permits control on overnight market interest rates and thus overnight liquidity. These are the rates at which credit institutions can lend (deposit facility) and borrow (marginal lending facility) money from the national central bank. In order to better understand how this tool works, let us examine Figure 8. The chart displays the corridor over the past years relative to Euro area, whose

floor

and

ceiling

are

determined respectively by the deposit facility and the marginal lending made

facility. to

obviously

this

Each

change

% 6.00 5.00 4.00 3.00

corridor

adjust

will 2.00 interbank 1.00

overnight rates whenever they 0.00 exceed the boundaries set by floor and ceiling, according to the following rational: in case the deposit facility was greater than

Eonia

Deposit Facility

Marginal Lending Facility

Figure 8: The overnight rate always moves ‘inside’ the corridor set by the central bank.

the interbank rate, no bank would ever offer in the market their excess reserves; likewise, if the marginal lending facility is smaller than the interbank rate, no bank would be interested in borrowing reserves available in the market, willing to deal directly with the central bank. It is possible to observe this effect by comparing the movement of the corridor showed in Figure 8 and the linked interbank rate which fluctuates inside of it. Figure 9 shows how the transmission mechanism processes a change of interest rates and illustrates how it affects real economy and, ultimately, inflation.

The name of Standing Facilities relates to the Eurozone and the UK. The American correspondent is defined as Discount Window.

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Figure 9: The transmission mechanism of monetary policy

Source: The Bank of England

Minimum Reserve Requirements for Credit Institutions. According to the Bank of England, reserves accounts are the safest assets a bank can hold. All banks must retain some liquidity in order to face daily necessities such as customers’ withdrawals. The reason for the introduction of these requirements primarily lies on the necessity to protect savers’ deposits. However, this instrument has soon become a mechanism of monetary policy at the disposal of central banks; monetary authorities, indeed, could control money supply by changing the minimum reserve requirements among banks. This monetary policy tool is used to “stabilise money market interest rates and create (or enlarge) a structural liquidity deficit in the banking system” (ECB, 2009). British banks have no minimum reserve requirement set; this means that, potentially, they could retain no liquidity. This particular case (similar to the system of Canada and New Zealand) raises a question that has been widely discussed by economists. A case study conducted by Sellon and Weiner (1997) reveals how these three countries adopt successful monetary policies without counting on reserve requirements. Also, they “raised concerns about the effectiveness of monetary policy in a low reserves environment”, willing to suggest a different scenario where money supply is controlled discarding the reserve requirements tool. However, since 1998, United Kingdom has registered an average of 3.1% on reserves. As for the United States, reserves have been sensibly decreasing over the last decades. According to a research by Bennett and Peristiani (2005), reserve requirements are rapidly losing relevance. In many countries this instrument has been reviewed and reassessed, preferring an approach more pricing–based, rather than quantity–based, to manage account balances. In any case, in the United States, this institution is directed in relation to the size of transactions, and precisely: 

Until $11.5 million: no minimum reserve requirement



Between $11.5 and $71 million: ratio must be 3%



Over $71 million: ratio must be 10%

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In the Eurozone, this system is slightly more complicated as the reserve coefficient implies a calculation based on maintenance period, standardised reductions and lump–sum allowance. On average, though, the coefficient fluctuates around 1%. As already mentioned, reserve requirements changes have rarely been used recently because Market operations are a much more precise tool. However, how does this instrument work? Generally, banks are not willing to hold liquidity in their vaults because it would only generate costs (notably, inflation and opportunity cost). For this reason, credit institutions tend to lend as much as they can. Reserve requirements set the minimum liquidity amount that they need to retain, that is, a percentage of cash they cannot lend out. When a central bank imposes such a threshold, money stock is affected this way: an increase in reserve requirements reduces the volume of deposit that can be supported and, thus, decreases the money stock and increases the cost of credit. Conversely, a decrease of the ratio, leads to an initial excess of reserves, which encourages an expansion of bank credit and, ultimately, causes a fall of interest rates.

Transmission channels Monetary policies, then, have the power to influence economies with the aim of stabilise variables such as inflation, production and money supply. Now, let us have a closer look at their technical functioning, trying to provide detailed explanation of how they influence markets through different transmission channels. In the first instance, it is important to understand that, in order to face a recessive drift, central banks adopt an expansionary monetary policy. This particular type of manoeuvre has been broadly used recently in order to face the crisis and its recessive effects. As explained, there are different channels by which this policy can be adopted. Indeed, such a manoeuvre entails different effects, depending on the channel the central banks have decided to utilise. The Interest rate channel is chosen when the policy is implemented by operating cuts on short–term interest rates that lead to an expansion of the money supply. As a result, the real interest rate and capital cost drop, stimulating investments. In addition, consumers change their attitude, preferring immediate consumption over saving and, hence, raising aggregate demand. It is possible to summarise this relationship with the following: The credit channel spreads its effects in two sub channels: bank lending channel and balance sheet channel. The former is based on the fact that cuts on interest rates reflect on credit institutions’ customers; thus, the diminishing of financing costs lead to an increase of investment and consumer spending and, consequently, to higher growth and inflation. Balance sheet channel, instead, occurs because monetary policies affect corporate policy; companies, indeed, may decide to borrow in ©2012 – Daniele Stanizzi

Page 13

order to improve their return on equity when under particular circumstances. Lower interest rates, then, boost companies’ return on equity (ROE) and, therefore, affect investment behaviour3. Exchange rate channel involves domestic deposits’ attractiveness; an expansionary policy, indeed, decreases their attractiveness compared to those denominated in foreign currency. Domestic deposits, then, lose value, and so does domestic currency. This depreciation makes domestic products cheaper than imported ones, increasing demand for domestic goods and aggregate output4. Wealth channel involves the transmission of monetary policies through the price of asset such as real estate and stocks and it is described by three effects. First, Tobin’s Q effect, which states that:

Clearly, an increase of Q is triggered either by a lower cost of capitals or a higher value if installed capital; both cases, which will cause a swell of Q, lead to an increase of investment made by businesses. Expansionary policies can make Q grow for two possible reasons: either because market interest rates are decreasing or because they have more money at their disposal, redirecting families to invest more in private equity. Stock prices rise, Q raises, investments rise. Secondly, wealth effect occurs because expansionary manoeuvres increase stock prices and, hence, raise household wealth, encouraging spending. This is certain the case of dot–coms market in 1996–1999, when the value of high–tech indexes swelled incredibly, increasing spending. The third and last effect is called real estate effect; indeed, lower interest rates mean lower mortgage costs, augmenting demand for houses and, thus, an increase of price.

Inflation Targeting As already mentioned above, central banks have the power to undertake manoeuvres of monetary policy which ultimately aim to control price stability. In order to do so, they need to supervise the inflation rate. The Maastricht Treaty (Eurozone) (1992), as well as the Chancellor (Bank of England), has clearly established the primary objective of the central bank and set the new inflation target. The ECB’s Governing Council has announced a quantitative definition: “Price stability is defined as a year–on–year increase in the Harmonised Index of Consumer Prices (HICP) for the euro area of below 2%.” (ECB, 2012). Also, “The Governing Council has clarified that, in the pursuit 3 4

This effect is called financial accelerator effect (B.S. Bernanke, 2007). Strength of exchange rate channel increases as an economy is more open.

Page 14

of price stability, it (price stability) aims to maintain inflation rates below, but close to, 2% over the medium term.” (ECB, 2012). The same target has been set by the Bank of England, which has also specified that this does not necessarily mean that the rate will be held constant at 2% all the time; inflation is, indeed, susceptible to fluctuations due to innumerable variables. Therefore, “monetary policy is aiming to ensure that the inflation rate is 2.0% on average over time” (Bank of England). There are several benefits that arise from low inflation: according to a paper released by the Bank of Canada (2009) a low and stable inflation involves firms and consumers being more confident and optimistic in regards to investments, and an improvement of their long–range plans due to the stable purchasing power of the currency. Moreover, it leads to low expected interest rates which reduce the cost of borrowing, thus causing an expansion of private consumption (households) and a raise in investments (businesses). Also, low inflation leads to stable and low inflation because individuals and

Figure 10: Moving average of inflation and inflation Range, CPI

Source: FRED Economic Database.

companies do not persistently seek a rise in wages as a response to a contraction of purchasing power. All this, brings a rise in long–run aggregate supply and an increase of rates of future economic growth. R. H. Rasche and M. M. Williams (2005) have conducted a research to test the effectiveness of monetary policies in relation to inflation targeting regime. They found out that on a “medium run” horizon, central banks have been effective, managing to control inflation and consistently meeting their targets. As shown in Figure 10, for instance, policies in the United Kingdom and United States have brought inflation to levels fixed by central banks. The subsequent statistical computation of historical rates of inflation will show that this variable is the most correlated with fluctuation of short–term interest rates, which are directly controlled by the central bank. Furthermore, we will analyse the effects on the production; the latter, indeed, strictly correlated and very sensitive to movements of interest rates and inflation. ©2012 – Daniele Stanizzi

Page 15

Term Structure of Interest Rates – The Expectation theory The following section is very important to our research. Though, in order to better understand it, we need to clarify what the expectation theory is and what it implies. The latter is the mechanism used by central banks to control long–term rates. Let us see how: this theory based on two fundamental assumptions: transaction costs are absent and bonds of different maturities are perfect substitutes. It postulates that the yield of a long–term bond is equal to the average of the current short–term rate and the following short–term rates expected for the next periods on the same bond, until its expiration. Thereby, in equilibrium and with no arbitrage, the following applies:

where R is the long–term rate and r is the short–term rate. The term structure of interest rates (or yield curve), which intuition will be explained in the next paragraph, plays an essential role in the economy, and its functioning is guaranteed by the expectation theory mentioned above. The importance of the curve lies in its capacity to reflect future expectations of interest rates (Fisher, 2004) and to reveal the conditions for monetary policy (Irturk, 2006). Indeed, as already specified, monetary manoeuvres do not have a direct impact on long–term rates, which central banks are willing to control. However, authorities know that, in accordance with the expectation theory, any action they will undertake will have a precise effect on long–term rates.

Yield Curve and Interest rates spread Therefore, the yield curve has powerful forecasting skills because when central banks set the short– term interest rate, markets properly readjust long–term rates. Medeiros and Rodríguez (2011) have conducted a research based on U.S data that showed that “it is possible to explain variations across U.S. Treasury securities with different maturities over the estimation period in terms of three yield–factors, namely the level, slope and curvature”. This means that the term structure is correlated with monetary Figure 11: U.S. Treasury Yield Curve. The steepest slope ever.

Source: Yahoo! Finance

policy and market expectations about Page 16

future short–term interest rates. Consequently, they pointed out that inflation and federal funds rate were influenced by the slope of the yield curve. Now that we have explained the relationship between long–term rates and short–term rates, it is interesting to look at their spread; that is, the difference between the cited interest rates. This spread provides a powerful tool which reflects the impact of the current monetary policy on the market’s future trend. During regular periods, the spread between the two rates is positive; this indicates that the economy will benefit from an expansion and growth. Conversely, when the spread is negative, the economy will move towards a contraction. This is the case of the last crisis that hit the global economy, when the spread registered a negative trend. The spread is also used to draw the yield curve; as a result, the examination of the latter gives a clear indication of the two mentioned scenarios. Therefore, the spread is a good predictor because it represents the slope of the curve, which could be defined as “a representation of the relationship between market remuneration rates and the remaining time to maturity of debt securities” (ECB).

Fiscal Policy Fiscal policy is another powerful instrument of monetary policy at the disposal of central banks, and the last one we will analyse for the purpose of this study. The focus of this paragraph is based on the theory elaborated by John Maynard Keynes (1936), which has been developed as a revision of the Classical Theory of economics during the Great Depression. The stimulus for a correction occurred, indeed, when economists decided to rely on the Classical Theory’s assumption, according to which markets would self–correct and recover from recession. However, the situation deepened into the most severe crisis, questioning the hypothesis contained in the theory, and making some corrections necessary. Reportedly, Keynes’ intuition is based on the importance of an accurate fiscal policy, especially during periods of recession, undertaken in the short run by governments, because “in the long run, we are all dead” (Keynes, 1924). Fiscal policies base their functioning on two transmission channels essentially; remarkably, a recessive trend should be opposed, firstly, with an increase of public spending to boost the economy, and, secondly, with a reduction of taxes that would grant households more resources, encouraging them to spend more. These two channels ensure important results in term of macroeconomic variables. They, indeed, lead to a higher aggregate demand, which stimulates businesses to increase their output, raising employment rates and, ultimately, improving households’ incomes. Conversely, Keynes suggests a reduction of public spending and an increase in taxes, in periods of rapid–growing inflation. By doing so, economy will slow down and inflationary pressure reduces. Nevertheless, Keynes points at the public spending ©2012 – Daniele Stanizzi

Page 17

as the most effective channel between the two; this is due to the fact that government spending directly affects aggregate demand. The whole theory is considered being a strong tool for creating a solid economic structure and stable growth. An article by Clark Johnson (2012) agrees with the importance of government’s actions to contain recessions. Precisely, he confirms economic literature by Keynes, Taylor and Krugman, whereby stabilisation of agents’ expectation is crucial, so they can trust in an on–going boost that will not be withdrawn soon. Monetary policies work, as broadly explained, through the mechanism of interest rates. However, interest rates are subject to a margin of manoeuvre, which means that adjustments of expansionary policies are limited when rates are already very low. This is well explained in Keynes’ General Theory (1936). According to the English economist, there is a point where motetary policies are no longer effective, and they need to be supported by fiscal policies. This circumstance is known as the Liquidity Trap. The thinking behind this theory is quite straightforward: monetary expansions lower interest rates with the aim of stimulating investment and output gap. However, when nominal rates are close to zero, the possibility for central banks to operate further cuts disappears. These traps have already occurred in 1929 in the United States during the Great Depression and in Japan in the nineties during the Great Deflation. Liquidity traps then trigger a particular situation where open market operations (and, in general, increases of money supply) lose all traction and even purchases of governments debt are uninfluential and no longer affecting the interest rate (Krugman, 2008). Moreover, in this state, the economy expresses a production capacity that is a far cry from the actual potential, in spite of the fact that the cost of borrowing is so low that it would stimulate investment and consumption during regular periods. Therefore, the current situation of markets is quite severe, due to interest rates bordering on zero. For example, back in July Libor hit 0.53%, Eonia 0.18% and Federal Funds 0.16%. Such values reduce the margin of intervention that central banks can operate through monetary measures, making the need for governments’ fiscal policies fundamental. According to Keynes, thus, an increase of public expenditure and tax reliefs would help markets to recover and GDP to restore; this would bring employment rates back to regular values (Spilimbergo, S. Symansky, Blanchard, Cottarelli, 2008). As stated in Keynes’ Treatise on Money (1930), indeed, monetary expansions are not consistently effective, and the aid of public investment and taxes is required. The English economist also commented on Roosevelt’s recover programme which began in 1933; remarkably, he mainly applauded his efforts to correct unemployment operating on large–scale public spending, and the break of gold standard. The Occasional Paper by an ECB Fiscal Policies Team has analysed the adjustments undertaken between 2008 and 2009 by the European Central Bank, arguing that “there is no doubts that exceptional fiscal policy measures and monetary policy reaction to the ©2012 – Daniele Stanizzi

Page 18

crisis have helped to stabilise confidence and the Euro area economy” (ECB, 2010). The report concentrates on the importance of public spending that has been carried out by several EU countries in terms of guarantees for interbank lending, recapitalisation of financial institutions and increased coverage of the retail deposit insurance schemes. These interventions have increased markets’ confidence contrasting main adverse effects that hit the European economy and limiting the impact of government deficit relative to the same area. As for the United Kingdom, we want to refer to the previous office guided by Gordon Brown. A research conducted by the Institute for Fiscal Studies (2009) has examined the measures of fiscal policy implemented to contain the crisis and how they affected people. The research mostly concentrates on the temporary cut of Value Added Tax from Figure 12: The fiscal policies undertaken in the UK in the last few years have decreased taxes during the crucial phase of the crisis. The trend is now changing.

17.5% to 15% over the period 1st of December 2008 – 31st of December 2009. The target of the measure was, obviously, to perform a cut in prices and encourage households’ spending. However, many have argued that the manoeuvre was too quick and some speculations were made about an increase of VAT to 18.5% by 2011. Apparently, this has significantly limited the positive effects of tax reduction. Figure 12 shows the cuts on taxes began in 2008 and forecasts for the following years.

Page 19

Methodology So far we have outlined the theoretical framework behind the functioning of monetary policies and their effect, in the first instance on interest rates and subsequently on the other economic variables. Throughout the following section, we will combine the aforementioned models and concepts at the focus of this study in order to build a picture of the current economic situation in the three biggest macro areas (UK, Europe and U.S.). First, we will gather data for the most fundamental macroeconomic and financial variables and then we will conduct a quantitative analysis. Such an approach will clearly illustrate the effects of monetary policies undertaken by central banks on the economy, and will allow us to observe fluctuations and movements of the markets, focusing on those changes resulting as a response to the strategies carried out by governments.

The Overnight Rates The first set of variables we want to consider is given by the overnight interest rates. These are the shortestâ&#x20AC;&#x201C;term rates at which financial institutions lend and borrow money from each other. Considering the macro areas we are examining (Eurozone, United Kingdom and United States), the variables we aim to study are respectively EONIA (acronym of Euro Overnight Index Average), LIBOR (London Interbank Offered Rate) and Federal Funds. We have gathered the monthly rates of the last twelve years, in which the trend is well explained, not only for the decisions on monetary policy undertaken by the central bank, but also marking the main financial and economic events that happened throughout the timeline. Indeed, as shown in Figure 13, big fluctuations are associated with large alterations due to the events that hit the markets. According to the rules of monetary policy, in order to

7.00

slow down a recessive trend

Oil Peak

6.00

5.00

economy,

4.00

expansionary

3.00

could be the solution. In fact,

2.00

when the crisis hit the

1.00

markets in 2007, the Fed

Eonia

Jan-12

May-11

Sep-10

Jan-10

May-09

Sep-08

Jan-08

Sep-06

Jan-06

May-05

Sep-04

Jan-04

May-03

Sep-02

Jan-02

May-01

Sep-00

Jan-00

Libor

May-07

Liquidity Crisis

0.00

FedFunds

Figure 13: Confrontation between overnight interest rates, Eonia, Libor, Federal Funds.

ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

manoeuvre

began to operate several cuts on interest rates. The chart on the left shows specifically the

commencing

the

Page 20

turmoil and the immediate response of governments and central banks. The aggressiveness of the American policy is well represented in Figure 13: a manoeuvre that drove the cost of money to approximately zero. In the UK, the LIBOR, which initially started to increase as a consequence of the credit crunch and the US mortgage problems (BBC News, 2007), began to fall as a response to the monetary policy of the Bank of England. Similarly, the same strategy was undertaken by the ECB a few months later, triggering a similar effect in the rest of Europe; by the end of 2008, interest rates reached their lowest level, aiming to stop the recessive trend of the economy and to stimulate investment by injecting confidence among investors. The tendency for interest rates to decrease is confirmed during the following research, where we will show a growth of production and GDP. This is because a lower interest rate increases aggregate demand and consequently stimulates an economic growth. The research will focus on the consequences of these movements.

Monetary policy through Inflation targeting In 1993, John B. Taylor developed a model that relates interest rates with current levels of inflation and output gap. This model sets the basis for the inflation targeting model, of which it is an extension. A study conducted by M. Woodford (2001) argues that the rule incorporates the basis for optimal application of monetary policies. In fact, it permits an ultimate control on prices according to the following equations:

Where  denotes the inflation, y denotes the output gap and  is a variable that includes possible shocks that may hit the system. The definition of output gap in one period of time with the following equation:

By looking at the variables presented, it becomes somehow clearer how the model can be used to predict and, thus, control future inflation. For instance, let’s assume that one period corresponds to one year; equation (1) above, points out the relation between the inflation expected in two years time and the levels of inflation, production and shocks that will be registered over next year. Though, only by looking at equation (2) it is possible to notice how monetary policies are involved. Indeed, it defines the short–term rate which is directly controlled by the central bank. Also, it is clear how time plays an essential role because, although some effects are quite immediate and occur as soon as the policy is implemented, the most important results will only take place starting from ©2012 – Daniele Stanizzi

Page 21

t+1, or later, depending

Inflation

6.00

on the variable; this is Oil peak

5.00

precisely the case of the

Katrina spike

4.00

inflation targeting model

3.00

(Bagliano,

2.00

2009). Figure 14 shows

1.00

the levels of inflation Jan-12

May-11

Jan-10

Sep-10

May-09

Sep-08

Jan-08

May-07

Sep-06

Jan-06

May-05

Sep-04

Jan-04

May-03

Sep-02

Jan-02

May-01

-2.00

Sep-00

-1.00

Jan-00

0.00

Liquidity crisis

Eurozone

U.S.

Figure 14: Confrontation of inflation levels in the UK, Europe and US. Notice how it tends to move together especially during the recessive period.

over

the

Marotta,

last

twelve

years; the most notable effects from plotting the data, is that, from the beginning of the crisis,

the range of fluctuation has significantly increased; this indicates that markets are going through a period of instability, in which its intensity is given by the width of the range. Discarding the largest fluctuations (i.e. the peak reached in the U.K. during September 20085), we want to verify whether the (1) applies in this case; that is, if the adjustments undertaken by the Bank of England, the ECB and the Fed, have significantly affected the inflation rate. Also we want to know in what extent the adjustments adopted, influenced the economy. Precisely, we want to investigate the quickest and most accurate way to do so, that is, the implementation of a multivariate regressive test of the type:

where

is the dependent variable (or regressand) and denotes the vector of future’s inflation,

the first regressor and indicates the vector of the interest rate and

is the second regressor and

stands for vector of current inflation. By the equations, we expect to observe a negative effect of interest rates and a positive effect of inflation on future’s inflation. Let us run the test considering the dataset relative to the UK system. It is important to know that, whilst running the test, we have considered a periodic lag of six months on the inflation according to the model. This investigation will compute the alterations of today’s inflation and interest rate (Libor) on inflation in six months’ time. Textbox 1 contains the results of the regressive test performed with R©. The first parameter we want to focus on is the Multiple R–squared. This 5

The reason behind the peak lies in a steep increase in energy charges (gas and electricity), air transports and communication services. (BBC News, 2011). Obviously, we want to discard these fluctuations as they interfere with the movements due to central banks’ intervention.

Page 22

coefficient tells us how

much of the observation

dataDF)

explained

model and,

Min

inflation). it

statistical

Median

Max

–1.8940 –0.5119 –0.1862

0.4658

2.8810

data

Estimate Std. Error t value Pr(>|t|) (Intercept)

today’s

libor inflation

While this has

0.28524

–0.09711

0.04314

0.55130

0.07334

Signif. codes:

great

5.133 1.01e–06 *** –2.251

0.026 *

7.517 8.10e–12 ***

0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.8423 on 130 degrees of freedom

significance

Multiple R–squared: 0.4313,

Adjusted R–squared: 0.4225

F–statistic: 49.29 on 2 and 130 DF,

because the variable is subject to a great level of disturbance,

1.46417

–––

percentage might seem small,

inflation,

Coefficients:

variables

and

the

(respectively,

Libor

libor

Residuals:

(future’s inflation) is

and

lm(formula = inflation1 ~ libor + inflation, data = dataDF)

43% of the variability of

explicative

lm(inflation1

Call:

goodness of fit. About

<–

> summary(regression)

the

thus, its

explained

regression

p–value: < 2.2e–16

Textbox 1: Multivariate regression for the U.K. Effect of today’s inflation and interest rates on future’s inflation.

often

making the application of theoretical models highly complex. However, the significance of the regression we have just conducted is confirmed by the F–statistic value (49.29), in which comparison with the tabulated F reveals that the model is valid in its entirety. Let us now focus on the obtained betas to identify the extent of the alterations that affected . As expected both values are acceptable. Indeed, variable. The value of

is negative and equal to –0.097, this implies a negative effect on the is, instead, positive, involving a positive effect on the inflation. One final

set of values to be examined are the p–values associated with the variables. This is to establish whether the explicative variables are to be considered or discarded. In this case: p–value

1.01e–06

p–value

0.026

p–value

8.10e–12

(significant)

(significant) (significant)

With a t–test on the p–values we find that all regressors are significant because they are smaller than 0.05, which represents the significance code; therefore the null hypothesis H:0 can be refuted and the ©2012 – Daniele Stanizzi

Page 23

model can be considered valid. We have, hence, verified that future’s inflation () is strictly negatively correlated with the short–term interest rate, but positively correlated with today’s inflation. However, inflation targeting is not preferred during high inflation periods. The fear of losing credibility pushes the authorities towards other choices of monetary policy, choosing this model for periods of low inflation, which makes the target easier to achieve (Hu, 2003). The chart below (Figure 15) offers a visual overview over the fluctuations of short–term interest rates and inflation for the remaining areas from 2007. The results clearly show how  begins to rise some time after central banks operate cuts on interest rates. As Eonia and Fed Funds start to drop in mid–2008, inflation begins to increase in in

Eurozone

5.00

mid–2009. Running the regressive test on the Euro

4.00

area

have,

however,

obtained

3.00

statistically significant values only in relation to

2.00

today’s

1.00 Jul-12

Jan-12

Jul-11

Jan-11

Jul-10

Jan-10

Jul-09

Jan-09

Jul-08

Jan-08

Jul-07

Jan-07

Eonia

Inflation

and

p–value

we have obtained relative to the interest rate (Eonia), it seems that future’s inflation is not affected by today’s rates. The same outcomes

U.S.

have aroused from the test conducted on US data; however, we discovered that the optimal lag is three months, instead of six. In any case, it

Fed Funds

Jul-12

Jan-12

Jul-11

Jan-11

Jul-10

Jan-10

Jul-09

Jan-09

Jul-08

Jan-08

Jul-07

is possible to observe a significant alteration Jan-07

6.00 5.00 4.00 3.00 2.00 1.00 0.00 -1.00 -2.00 -3.00

(

). Specifically, observing the p–value

0.00 -1.00

inflation

caused by today’s inflation, of which the explicative variable has

. Nevertheless, we strangely came

Inflation

Figure 15: The relation between inflation and short–term interest rate in Europe and the United States.

and p–value

across a positive relationship with the interest rate (Federal Funds) which we cannot accept as

economically significant. Finally, the values relative to R–squared (respectively 18% for the Eurozone and 45% for the US) and F–statistic (16.37 and 61.03) for both cases allow us to confirm that the regressions explains enough of the variability of

and both models can be accepted in their

entirety. We now want to attempt a forecast of what inflation will be in six months based on the latest records of inflation and interest rates. Precisely, a further step in the regressive test will permit us to estimate future values fitting the regression line we have obtained. The computation for the United Kingdom follows: ©2012 – Daniele Stanizzi

Page 24

predict(regression,

data.frame(inflation=2.6,

libor=0.531),

interval="confidence") fit

lwr

1 2.845919

2.56748

upr 3.124357

The predict function has estimated that, by January 2013 and in accordance with today’s adjustments and standard error, inflation should be

with an expected (fitted)

value of 2.84. A very recent article by S. Zhelev (2012), argued that inflation is indeed expected to rise in response to the recent increases in petrol prices. Also, the price of food and energy may swell significantly in the next months, pushing up the CPI. Let us run the function for Eurozone: >

predict(regression,

data.frame(inflation=2.4,

eonia=0.1842),

interval="confidence") fit 1 2.220111

lwr 1.943344

upr 2.496878

Results for Euro area forecast an inflation of

, with a fitted value of 2.2 in six

months’ time. Finally, let us compute predictions for United States: >

predict(regression,

data.frame(inflation=1.4,

fedfunds=0.16),

interval="confidence") fit

lwr

1 1.595078

1.34664

upr 1.843515

By October 2012, the American system should be facing a level of inflation of about 1.59, with a variance of 0.41.

Interest Rate, Production and Inflation In the following paragraph, we want to conclude our discussion over inflation taking into account also the variable of production. It is, indeed, evident from the equations, how this factor is affected by monetary policies and, thus, how alterations of the real interest rate modify the behaviour of businesses and, consequently, production. From the three charts in Figure 16, it is possible to understand that the sink of production started in conjunction with the beginning of the crisis, which lowered growth levels to negative values. The fall hit Europe in 2008 with a delay of only a few months in respect to United States; the response by central banks was immediate and they operated severe cuts in interest rates. According to the inflation targeting model, the production ©2012 – Daniele Stanizzi

Page 25

was expected to recover within one period’s time. Indeed, it is clear from the chart that production growth started to rise returning to positive levels by the first months of 2010. It is interesting to point out how, in all of the three macro–areas, the crisis hit in such a violent way, freezing the economies and spreading fear among investors and companies alike, which resulted in business coming to a stand–still. We are now going to test the outcomes of the inflation targeting model taking into account the output gap, in order to verify whether the model applies. Let us consider the Euro area; we want to discover whether or not, and to what extent,

U.K.

10.00

in accordance with the equations, production is positively correlated with today’s inflation

5.00

and negatively correlated with today’s interest Jun-12

Jan-12

Aug-11

Oct-10

Mar-11

May-10

Dec-09

Jul-09

Feb-09

Sep-08

Apr-08

Nov-07

Jun-07

-5.00

Jan-07

0.00

rates. In other words, we want to establish if the sharp dive and the sudden steep recovery in output gap between mid–2008 and mid–

-10.00

2010, can be attributed to the measures -15.00

Libor

Inflation

adopted by authorities. Notably, Eurozone’s

Production

Eurozone

15.00

production has fallen by 23% in only fourteen

10.00

months and quiclky recovered to 2005 levels in

5.00

just thirteen months. To run the following Jun-12

Jan-12

Aug-11

Oct-10

Mar-11

May-10

Dec-09

Jul-09

Feb-09

Sep-08

Apr-08

Nov-07

-10.00

Jun-07

-5.00

Jan-07

0.00

regression, we have considered the variable Gross Domestic Product6, instead of the

-15.00

production. This decision stems from the fact

-20.00

that absolute variables are more accurate and

-25.00

Eonia

Inflation

indicative in terms of statistical computation

Production

U.S.

10.00

with R©. Furthermore, the theory behind

Jun-12

Jan-12

Aug-11

Oct-10

Mar-11

May-10

Dec-09

Jul-09

Feb-09

Sep-08

-5.00

Apr-08

Exactly as we did for the previous regressive Nov-07

0.00 Jun-07

Taylor rule is based on GDP records. Jan-07

5.00

-10.00

displays the outcome of the test. In the first FedFunds

Inflation

Production

Figure 16: Levels of interest rates and inflation in relation to the growth of output gap.

months to simulate the time gap. Let us now run a multivariate regression again. Textbox 2

-15.00 -20.00

test, the variable GDP has been lagged by six

instance, let us focus on the Multiple R–squared

The variable GDP is expressed in US$ and as Per Capita and conditioned by Purchasing Power Parity (PPP).

Page 26

and the Adjusted R–squared values. This time only about 14% of observations are explained by the explicative variables X1 and X2. Although lower than the previous regression, this percentage is still significant in terms of test validity. Again, this is, in fact, confirmed by the comparison of F– statistic (11.38) that is greater than tabulated F, that is, the degrees of freedom of the numerator. Also, extremely important are the p–values relative to the explicative variables; precisely, both esteems calculated on

and

(respectively

and

) are smaller than 0.001

and, hence, we can reject the null hypothesis H:0 and confirm the validity of the model. Having confirmed the significance of the statistical computation and its outcomes, it is now possible to concentrate on the results for the two regressors. As expected, the values of betas verify the model’s goodness of fit, and reveal the following statistics: , relative to the variable EONIA, each increase of 1% in interest rates

with a value of

entails a decrease of GDP of around €173 per person, each year. with a value of

, each increase of 1% in the inflation entails a growth of GDP of around

€246 per person, each year. Similarly, the run of the test for the UK and the US have confirmed that the test is statistically significant in both cases, with acceptable values of F–statistic and, thus, we can accept the model in > regression <– lm(gdp ~ eonia + inflation, data = dataDF) > summary(regression) Call: lm(formula = gdp ~ eonia + inflation, data = dataDF) Residuals: Min

1Q Median

–903.0 –454.7

–41.7

Max

295.1 1285.9

Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 20811.29 eonia

143.11 145.424

< 2e–16 ***

–172.97

38.70

–4.469 1.59e–05 ***

246.58

69.81

3.532 0.000556 ***

inflation ––– Signif. codes:

0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 575 on 143 degrees of freedom (5 observations deleted due to missingness) Multiple R–squared: 0.1373,

Adjusted R–squared: 0.1253

F–statistic: 11.38 on 2 and 143 DF,

p–value: 2.587e–05

Textbox 2: Multivariate regression for Euro area. Effects of inflation and interest rates on future’s GDP.

Page 27

its entirety. As for the UK, our findings are satisfactory only in relation to the explicative variable of inflation, which

confirms its positive effect on GDP in almost 20% of the observations

made. The p–value of this explicative variable is, indeed, 2.15e–07 and Multiple R–squared is 0.197 However, we cannot accept the results obtained for the first regressor (interest rate) because of its strictly positive correlation with GDP. Hence, we need to discard

because, although statistically

significant, it is not economically acceptable. As for the American system, we have found out that the correct lag of this economy is five months instead of six; under this condition, indeed, we have obtained the best results. Precisely, we came across p–values of

(interest rate) and

(inflation)

that both have great statistical significance (respectively 0.043 and 0.004). The t–test, hence, validates their acceptability. Also, a look at their respective betas reveal that an increase of 1% in Federal Funds will lead to a decrease of GDP by almost $104 per capita in five months’ time. Conversely, a rise of 1% in inflation will result in a bounce of GDP per capita of about $230 within the same period. Let us now proceed with the estimations for future’s months. The computation for the Euro area follows: >

predict(regression,

data.frame(eonia=0.1842,

inflation=2.4),

interval="confidence") fit 1 21371.21

lwr

upr

21149.25

21593.18

The adjustment of the regression to today’s values of the interest rates and inflation estimate that the European GDP per capita should be around €21,371.21 in six months’ time, in which discrepancies can cause fluctuations between €21,371.21 and €21,593.18. The prediction for the United Kingdom is worth: >

predict(regression,

data.frame(libor=0.531,

inflation=2.5),

interval="confidence") fit 1 27536.7

lwr

upr

27239.9

27833.5

The estimation, hence, predicts a per capita income between £27239.9 and £27833.5 with a fitted value of £27536.7 by January 2013. Finally, let us run the valuation for the American economy: >

predict(regression,

data.frame(fedfunds=0.16,

inflation=1.4),

interval="confidence") fit 1 37002.36

lwr 36713.53

upr 37291.19 Page 28

According to the regression parameters, today’s level of Fedfunds (1.6%) and inflation (1.4%) will correct the amount of the American GDP per inhabitant, which will total $37002.36, with an error allowance that could make it fluctuate between $36713.53 and $37291.19

Yield curve and interest rates spread As explained in the literature review, the yield curve is a sound way to forecast future trends of the economy (Culbertson, 1956). During this section of the study we are going to calculate the term structure of interest rate and conduct an analysis in order to find out whether the yield curve provides significant data, allowing us to forecast the future trend of economy, and if the main events were somehow already predicted by the model. Since the spread between short and long term rates provides the slope of the cited curve, we will try to compute an estimation utilising the difference between the one and twelve months Libor and

7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00

UK 2007 2008 2009 2010 2011 1 Month 3 Months 6 Months

Euribor7 rates. Figure 17, aside, represents the term

6.00

structure of interest rates, constructed in

5.00

accordance with the

have

4.00

gathered. At this point of the research, the

3.00

big drop on interest rates registered

2.00

data we

between 2008 and 2009 should not be a surprise. However it is interesting to notice

12 Months

EU 2007 2008 2009

1.00

2010

0.00

2011 1 Month 3 Months 6 Months 12 Months

how the curve starts flattening out in 2007 and 2008. A closer look to the data, reveals that during those years the difference between short and long term rates is, in

6.00

5.00

2007

4.00

2008

3.00

fact, very small for all the areas. Reportedly,

2.00

economic growth suffered a contraction;

1.00

2010

this means that aggregate demand fell,

0.00

2011

followed by production and, thus, GDP. Notice that the curve relative to the United States during 2007 draws a negative trend: 7

2009

1 Month 3 Months 6 Months

12 Months

Figure 17: Term structure of interest rates (or Yield curve) for the three macro areas relative to 2007–2011. Note the dive registered in each economy between 2007 and 2008.

Libor applies for both U.K and U.S. because, as for the US, $Libor has been considered.

Page 29

this is another indication of how hard the crisis hit american markets. Indeed, short–term Libor was greater than its one–year correspondent. In simple words, returns on a one–year bond were abnormally lower than returns on one–month bonds. Gary North (2009) stated that an inverted yield curve happens rarely, and it is generated by investors’ fears. This anomalous condition is usually followed by a plummet of stock markets within the next six months, and is “almost always followed by a recession” that usually begins with a six month lag. According to the expectation theory, the curve was forecasting a period of economic contraction. The predicting power of the term structure of interest rates is, thus, confirmed by the events that took place. A report by the National Bureau of Economic Research (2010) announces that in December 2007 the american economy had reached its peak and was entering a

2.00

recessive phase. The peak 1.50 marked

the

end

expansion that began in 2001 and

lasted

However,

1.00

months. 0.50

during

the 0.00 following years the curve started to draw a positive trend again. We can explain

1 Month

3 Months

6 Months Eurozone

12 Months

Figure 18: The current yield curve gives us some forecast for a future’s economic trend.

this recovery as a result of the effective monetary policies undertaken by central banks and a subsequent mitigation of the distress generated by the turmoil. Also, by examining the curve relative to 2012 (Figure 18), deliberately omitted in the charts on page 29, it is possible to provide a potential scenario in one year’s time. Figure 18 shows the term structure as it is today, relative to the three areas: in accordance with their slope, today’s panorama for the future converges to a growth, we can then expect a positive trend of the economy where agregate demand, GDP and production will increase. Indeed, in a scenario where economy expands, investors expect higher inflation and interest rates, which is negative for a long–term bond holder; for this reason, the longer the maturity of a bond, the higher the rate of return they demand. However, it is important to remember that the model’s predictive skills are only based on today’s information, therefore, a potential shock that might strike, could shake markets and throw then back into turmoil, changing the attitude of agents and, eventually, the trend of the curve as we see it today. Finally, we want to take some time to focus on the slope of the curve, paying particular attention to its rapidly changing structure, matching the speedy fluctuation of markets. Having clarified that the slope of the yield curve is given by the spread of returns, that is, the difference between long–term and ©2012 – Daniele Stanizzi

Page 30

short–term

2.00

interest

rates, we have carried 1.50

out a monthly analysis considering

1.00

spreads

over the last twelve 0.50

years. includes, Apr-12

Sep-11

Feb-11

Jul-10

Dec-09

May-09

Oct-08

Mar-08

Aug-07

Jan-07

Jun-06

Nov-05

Apr-05

Sep-04

Jul-03

Feb-04

Dec-02

May-02

Oct-01

Mar-01

Jan-00

Aug-00

0.00 -0.50

Figure

19 thus,

monthly changes of the term structure for the UK, Europe and

-1.00

Euro

Trend

the US. Notice the

Figure 19: Monthly fluctuations of the spread between short–term and long–term interest rates.

significant

fluctuations, especially from the beginning of the turmoil, at which point the curve was inverted, forecasting very low future rates and a contraction in economy. The same situation can be found in 2001; even then, the curve predicted the short recession that took place in that year and only lasted 8 months. Also, we traced a trendline that shows the direction the economy is heading towards. What is really interesting to highlight, is the correlation among the three variables. Although their connection is visible, we ran a Spearman correlation test in order to measure the actual co– movements. The three tests, respectively reported in Textbox 3, 4 and 5, have been conducted separately (UK–EU, UK–US , EU–US) so that it becomes easier to also examine a possible greater correlation between two specific areas. From the Spearman test, it is clear how these three economies are strictly linked, at least in terms of future expectations. Indeed, we see how United Kingdom and Europe are the most correlated

> cor.test(uk, euro, method = "spearman")

with a rho () of 0.8262. We then consider Spearman's rank correlation rho

United Kingdom and United States, with a coefficient of 0.7. This value reflects exactly

data:

what is stated by the British embassy,

S = 101717.2, p–value < 2.2e–16

relative to the UK & the US economic facts.

to 0

Remarkably, these countries are “each

sample estimates:

others” largest foreign investors, biggest partners in services importantly,

trade and most

“partners in science and

uk and euro

alternative hypothesis: true rho is not equal

rho 0.8262065

Textbox 3: Correlation of the yield curve between UK and Eurozone

Page 31

innovation”. Precisely, as for stock markets, UK investments in the US totals $ 432.5 billion, which equals to 18% of total FDI8. Equally, US investment in the UK sums to $508.4 billion, that is, more than 25% of total investments in 2010/2011. Moreover, the american market is the first export destination for the UK. Thus, this makes quite clear why the correlation between the two countries is such a large number. Finally, the last test between Europe and United States returns a , which, although being the lowest value among the three, still confirms the solid link between the two economies, due to the significant amount of assets the countries have invested in each other. > cor.test(uk, us, method = "spearman") Spearman's rank correlation rho data:

uk and us

S = 175107.7, p–value < 2.2e–16 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.7008117

Textbox 4: Correlation of the yield curve between the UK and the US. > cor.test(euro, us, method = "spearman") Spearman's rank correlation rho data:

euro and us

S = 230594.9, p–value < 2.2e–16

alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.6060065

Textbox 5: Correlation of the yield curve between Eurozone and the US

Foreign direct investment.

Page 32

Towards the equilibrium – the Dynamic IS–LM model In this paragraph we want to describe the dynamic IS–LM model, developed by Olivier Blanchard (American Economic Review, 1981). This model differs from the standard IS–LM model because, other than being dynamic, it takes into account the difference between short–term and long–term interest rates and it considers stock markets as well. The application of this model will allow us to comprehend how the economic system shifts to a new equilibrium as a result of the modifications to the monetary policy. By doing so, it is possible to understand theoretically the current situation and provide an overview of the future equilibrium. Before applying the model, which utilises the monetary channel, we need to make some assumptions to simplify the analysis. Other than the absence of arbitrage and the absence of transaction costs, we want to condense all monetary policies undertaken from 2007 until today, in a unique large manoeuvre. Moreover, due to the fast evolution of the crisis and to the briefness of the period of time elapsing from the announcements of the policies made by the central bank to the actual implementation, we want to consider the corrections as unanticipated. Indeed, short–term interest rates in the UK plummeted in just a few months, dropping from an average of 5.20% in 2008 to an average of 0.82% in 2009, reaching their lowest in 2010 (0.56%). Therefore, let us imagine that this large manoeuvre takes place in 2010, and that previously, the economy was in equilibrium. According to Bagliano and Marotta (2010) and Blanchard (2009), the model develops as follows: the IS curve defines the equilibrium on the goods market and it is defined by:

, where Y is the aggregate demand, C is

consumption (which is the function of the disposable income), I is investments and G is public expenditure. The effect of a decrease of interest rates would lead to an increase of investments, goods demand and production. The IS curve, then, expresses the equilibrium level of production as a function of interest rates. The LM curve, instead, defines the equilibrium on the money market Figure 20: G denotes the General Equilibrium condition as a combination of the two curves

and its relationship is:

, where M/P is the

money stock in terms of goods, and the right side of the equation provides the real demand for money as a function of real income (Y) and z interest rate (i). Equilibrium in the money market demands that interest rate is positively related with production. Therefore, if we want to find the joint equilibrium of goods and financial markets, we will have to find the intersection between the two curves as showed in Figure 20. The extension of the IS–LM model we

Page 33

want to consider leads to two new dynamic equations described as it follows: aggregate goods demand (IS) is denoted by the linear equation

This equation

points out that aggregate demand is determined by three factors: production level y through the consumption function (c is the propensity to consume), the level of Tobin’s q and g, which denotes an overall index of fiscal policy. There are only three activities in the economy and they are money, short–term securities and stocks. In order to express the global equilibrium, we need the same procedure as the static model. Hence, we define the new dynamic equilibrium on the money Figure 21: A change in money supply due to an expansionary policy stimulates aggregate demand and, consequently, the output gap.

market:

Real money supply is determined, then, by production (positively) and by interest rate on short–term securities (negatively). m

We shall now apply our model utilising the real data we have gathered. We will be using the United Kingdom as an example, considering one–month Libor as

short–term rate and one–year Libor as long–term rate. Let us, then, consider short–term Libor in 2008 (5.20%) and

t2010

2010 (0.56%), and long–term Libor in

Figure 22: Dynamics of short–term and long–term interest rates during an expansionary monetary policy.

r,R

2008 (5.65%) and 2009 (1.41%). It is clear, then, that the Bank of England operated several cuts on short–term rates by an

5.20

amount of 4.64%, which in the most part happened in a few months between 2008 and 2009. It is important to remember

1.79

1.64

that we are assuming that the economy 0.68

1.41

0.65

was in equilibrium, hence

where R is the long–term rate and r is the short–term one. Figure 21 and 22 illustrate

0.56

the movement of the key variables at the t2010

t2011

t2012

implementation of monetary unanticipated expansion: before the manoeuvre took

Page 34

place, the economy was in equilibrium with set levels of money aggregate, m, and production, y. At the execution of the expansion, a growth of the money stock leads to a drop of interest rates (Figure 22). However, recalling the expectation theory, we know that r and R, which were equivalent during the steady state period, will be affected differently. Remarkably, the long–term rate will decrease to a lesser extent than the short–term rate; this happens because long–term interest rates immediately discount future rates of short–term ones, and adjust according to investors’ expectations. Indeed, r and R sink from a rate of 5.20 to a rate of 0.56 and 1.41, respectively (Figure 22). This new situation the system is in, t2010, is a condition of transitory instability because, according to the model, variables, especially production, require long time in order to converge to a new equilibrium. We have constructed Figure 22 adding t2011 and t2012, making it possible to provide an overview of the current situation and “graphically” understand how the system is moving. According to the dynamic IS–LM model, rates were expected to rise and converge to a higher level of rates; indeed, in t2011, short–term rates grew from 0.56 to 0.65, and kept increasing reaching the present value of 0.68. The same happened to long–term rates that swell from 1.41 to 1.64 hitting 1.79 in t2012. The chart clearly indicates that we are now going through a situation of adjustment, where the economy is slowly shifting towards the new equilibrium with higher interest rates, which are indeed, growing steadily. We do expect, therefore, that for

, r and R

will both converge to the new equilibrium rate, lower than the level they were before t2010. Let us consider again Figure 21, focusing on the production level. The model forecasts, as an obvious result of the policy, an upward drift for the variable, which is also confirmed by the chart in Figure 23; although it is impossible to obtain a strictly increasing function due to the infinite variables that could possibly affect the economy, we have traced a logarithmic trend line in order to outline the average growth that has been registered after the steep fall between 2008 and 2009. However, the charts examined so far display changes in interest rates, but the

92.0

dynamic adjustment is still not clear.

91.0

For this reason we have elaborated

90.0

the phase diagram in Figure 24, in accordance with Blanchard’s model

89.0

(1981). Before analysing the diagram,

88.0

we need to point out dynamic

87.0

equations for aggregate demand and Production

Log. (Production)

Figure 23: Overall positive trend of output gap in the UK from t2010

supply. Being an evolution of the static

IS–LM

model,

aggregate Page 35

demand’s relationship becomes: 0,0c1 Aggregate demand has now three determinants: level of stock prices

, output

through the

consumption function (c denotes the marginal propensity to consume) and a measure of the fiscal policy stance

. Since the only available assets are money, short–term bonds and stocks, only

two equilibrium conditions need to be satisfied, given that short–term bonds and stocks are considered perfect substitutes in investors’ portfolios. Equilibrium on the money market, hence, becomes: (3)

with a condition which ensures that any return differential on the short–term bonds and stock markets is equal to zero. This no–arbitrage condition is given by the following: ̇

(4)

The left–hand side of the equation represents the rate of return on stocks, made up of dividends and by the capital gain (or loss) generating from stock price changes. The aggregate supply, instead, becomes the following dynamic (differential) equation: ̇

(5)

Where ̇ denotes the change of output as a result of the excess demand for goods given by . The equilibrium (or steady state) of an economy, therefore, is achieved when ̇

that is, when the variables do not change over time. Let us now consider Figure 24; the diagram contains three moments indicated by three points and named A, B and C. Let us start from point A: the steady–state of the economy at this point “ensures that in the long run money neutrality prevails” (Bagliano, 2010). Notice that when the Bank of England implemented the monetary expansion in 2010, the higher quantity of money (m) that stemmed from it, did not affect ̇

, in which the curve remained unchanged. However, ̇

Page 36

crucial aspect of the model regards the new lower level that interest rates reach. Indeed, there is only one steady state that will conduct the economy to a new equilibrium. This state lies on curve , which is called saddlepath. At t2010, when the money supply was augmented, with output still at the initial equilibrium level yt2010, interest rates decreased to 1.35%, according to (3). Any other level of interest rates would have had an â&#x20AC;&#x2DC;explosiveâ&#x20AC;&#x2122; adjustment on the economy, as revealed by curves Î˛ and Ď&#x2019;; such a dynamic would result in an exponential distancing from the equilibrium. Indeed, from t2010 onwards, only when r matches the saddlepathâ&#x20AC;&#x2122;s level, the economy can begin its dynamic adjustment and slowly reach the new steady state marked by C. Also, in t2010, British markets were in a situation where the noâ&#x20AC;&#x201C;arbitrage condition did not hold, shares prices then immediately started to increase in order to equalise this disequilibrium. An increase of

boosts investment and the

aggregate goods demand, triggering a gradual growth in output. Finally, after the decline in t2010, interest rates start to rise as a result of the higher money supply. This effect becomes dominating to the point that, even though output and dividends are increasing, stock prices begin a decline towards the new equilibrium level. This is exactly what is happening to the UK economy, of which the current state is shown by point B: the interest rate is currently at 1.79% and slowly increasing following the guidance of the saddletpath; eventually, it will converge to the new steady state in C. Such an evolution of the system is based on the expectation theory mentioned previously in the R

đ?&#x2018;&#x2026;Ě&#x2021;

Î˛

đ?&#x2018;&#x2026;Ě&#x2021;

5.20 C

1.79 1.41

Ď&#x2019;

đ?&#x2018;ŚĚ&#x2021;

yt2010

yt2012

đ?&#x2018;Śđ?&#x2018;Ą

â&#x2C6;&#x17E;

Figure 24: The dynamic ISâ&#x20AC;&#x201C;LM model shows the dynamic adjustments of the economy in relation to interest rates and output gap.

ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

Page 37

research. Indeed, in t2010, when the policy took place, agents reformulated their (rational) expectations. They understood that, from then on, interest rates would be constantly lower than the level they were at the initial equilibrium A, and output and dividends would always be higher. Without forward–looking agents, indeed, it would be impossible to explain the later increase of interest rates and share prices.

Fiscal Policy – Implementation As we have already seen, the recent violent crisis has brought interest rates close to zero, reducing the margin of intervention of monetary policies. The purpose of this section is to understand how fiscal policies were undertaken by central banks, and how they affected each system. Let us consider again the English case and construct a fiscal policy model according to the dynamic IS– LM system (Bagliano, 2010). The data we have collected from the BoE’s database, regarding public spending, reveals that in three years (2008 to 2010), public spending has swollen from £549.4 billion to £669.8; an increase of £120.4 billion, which, converted into percentage, means a massive peak of 21% in three years. We can assume that the fiscal expansion was announced, because the HR Treasury periodically (usually every three years) carries out a governmental process called the spending review. This report outlines the amount of funds that will be allocated to public services. Precisely, as for the specific case we are considering, the CSR was released in October 2007, for which implementation was planned by 2008. Exactly as we did for the application of the monetary expansion model, in order to simplify its application, we have decided to incorporate all the increases of public spending in one large manoeuvre which took place in

Figure 25: Overview of the movements of the interest rate, stock prices and output gap due to a fiscal expansion (g1 > g0)

2010. Now, let us consider Figure 25, and assume, then, that t2009 is the date of the announcement, in which HR treasury declares that an

r q

increase in public spending g, will be

implemented

t2010.

The

amount of the expansion is worth,

as mentioned, £120.4 billion and it £669.8 bn

£549.4 bn

t2009

t2010

Page 38

future, markets re–

5000

elaborate

their

4500

based

4000

on the nature and

3500

content

3000

expectations

the

announcement, again

GBP

2500

the

2000

expectation theory. The

1500

according results

to of

1000

the

500

anticipated increase

of public spending by the

FTSE All-Shares (q)

Log. (FTSE All-Shares (q))

English

government are clear

Figure 26: Overall negative trend of stock prices in the UK from t2009. (^FTAS index)

even on a static IS–LM model. The new equilibrium will be constructed on a higher level of production y and a higher interest rate r. These are the new conditions on which markets will base their new expectations. Indeed, an expansion of y and r entail a change in q; precisely, stock prices will increase as a response to higher dividends and production, however, a decline of q will guide the overall negative trend of variable shown in the chart; this happens as a result of a higher convenience of gilts making the downtrend effect dominant. We have collected a time series dataset from Yahoo! Finance relative to the FTSE All–Shares (^FTAS) index, in order to verify whether stock prices q in the UK, behaved according to the expectations of the model. Figure 26 displays the negative trend of stock prices, as a result of the fiscal measure adopted, confirming that the model has empirical foundation. Output ̇

the only stationary variable that changes because of the modification of g: at the execution (t2010), the curve moves along ̇

, shifting downwards and reaching a lower level, and, thus, leading

to lower values of q. Exactly as the monetary expansion case, the new lower level will lie on the saddlepath, otherwise, any other level of q will lead to an ‘explosive’ adjustment of the dynamic system, and a consequent exponential distancing from the equilibrium indicated by point D. From t2010 onwards, as shown in Figure 27 relative to the UK production, notice how output gap starts to grow as a response to a higher aggregate demand. Let us now focus on the effect of the announcement, that is, the dynamics taking place from t2009 to t2010 as defined by (4) and (5). When the HR Treasury declared the future higher allocation of resources to the public spending, stock markets started to anticipate the increase of interest rates; this effect led to a migration of ©2012 – Daniele Stanizzi

Page 39

investment from shares to gilts,

101.1

dragging down q, and justifying the

101

dive of stock market at t2009. The

100.9

ensuing effect lowered investment

100.8

levels and, consequently, decreased

100.7

aggregate demand. Output, indeed,

100.6

registered a temporary fall in the UK

100.5

from, from 100.9 to 100.6 between

100.4 t2009

November 2007 and January 2008, hiking to 101.0 in February of the same year, immediately after the execution of the policy as shown in

UK Output

t2010

Figure 27: The output gap in the UK between the announcement of the fiscal policy and its implementation. Notice that on the horizontal axis, ticks mark different years because of the model simplifications that we are applying, but they refer to the ‘real’ period November 2007 – February 2008.

Figure 27. This turnaround of y is explained by the dynamic adjustment that brings the economy to point C, where the aggregate demand increases along with the interest rate, while share prices and investment continue their downtrend. Figure 28 illustrates the adjustment on the dynamic IS–LM: during the steady state phase that followed the announcements there was no change in exogenous variables. Whilst locus for stock prices does not change, an increase in public spending g triggers a downward shift of the stationary locus for production ̇

along the unchanged ̇

, once the

measure is implemented at t2010. The overall negative effect on q drags the system down to point C as a result of the news of higher public spending. Notice that the extent of dynamic adjustment of share prices shifts the economy down exactly to the saddlepath. Let us remember that this curve represents the only level of adjustment that will gradually guide the economy to the new steady state in D, and any other level entails an explosive dynamic that will bring the system further away from the equilibrium. When the policy is implemented, in t2010, the system starts shifting gradually from B to D, along with an unexpected fall in output gap. This awkward effect that produced in the UK between November 2007 and February 2008 (t2009 and t2010 in our model) has been defined as ‘perverse’ by Blanchard (1984). He argued that: “this type of fiscal expansion has temporarily perverse effects on output. The reason is simple. The initial current fiscal stimulus is small. It is, however, anticipated to be large and thus to lead to high short real rates later. As a result, long real rates increase, leading to a decrease in aggregate demand which more than offsets the fiscal expansion, at least initially. Thus […] the fiscal program and its growing projected deficits could well be initially contractionary. The model also suggests a way in which fiscal policy could be improved. As current deficits are expansionary and

Page 40

anticipated deficits contractionary, shifting of government spending towards the present would, by increasing current deficits and decreasing future deficits, increase aggregate demand and help the recovery.â&#x20AC;?

The effect has also been put in other words by Bagliano (2010) who stated that: â&#x20AC;&#x153;an apparently â&#x20AC;&#x153;perverseâ&#x20AC;? effect of fiscal policy (an expansion of investment and output following the announcement of a future fiscal restriction) can be explained by the forwardâ&#x20AC;&#x201C;looking nature of stock prices, anticipating future lower interest rates.â&#x20AC;?

As interest rates rise, markets begin discounting future expectations, leading to a growth of output gap and profit. Point C provides an idea of the current positioning of the UK economy which is slowly converging towards D along with the fall of stock prices. As for the United States, we came across even greater levels of public spending during the recession: the size of the fiscal policy was even more significant. Remarkably, between 2007 and 2010, we calculated an increase of about $992 billion, which means a massive hike of 36.4% of resources allocated to the public sector by the American government. For this reason, the model constructed above for the UK does also apply to the United States. Although the validity of this model has been confirmed through this study, the analysis of the data revealed that the average spending of the seventeen European countries taken into account, sums up to â&#x201A;Ź515 billion; this means a growth of 12% over the period. A growth that does not drift away significantly from the average growth registered during the years before the crisis. The severe problems of public debt q đ?&#x2018;ŚĚ&#x2021; A đ?&#x2018;ŚĚ&#x2021;

A B

đ?&#x2018;&#x17E;Ě&#x2021; t2010 t2009

Figure 28: Dynamic of the adjustment of the economy in response to an expansionary fiscal policy.

ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

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that some European countries are dealing with at the moment well explain the prudent public spending. It is a matter of fact that European Union has requested several countries (i.e. Greece, Italy, and Spain) undergo debt restructuring and fiscal consolidation.

ÂŠ2012 â&#x20AC;&#x201C; Daniele Stanizzi

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Conclusion This research study investigates the role of governments and monetary authorities and their behaviour during the recent crisis that hit the global economy. In particular, we focused on the United Kingdom, Europe and the United States. Throughout the study we have provided an overview of the crisis, examining how the housing bubble swelled, reaching an unsustainable level whereby it exploded, having severe repercussions, in the first instance, on the American market. Also we gave special attention to the shadow banking system and its effects, realising its importance in the events that have devastated the global economy. The effects ricocheted through Europe, whereby countries, including the United Kingdom, began to suffer the consequences of the crashing of the American economy. The subsequent effects were becoming more critical as the bubble was deflating at pace. The financial crisis has soon turned into an economic recession, forcing the authorities to adopt rigid measures. After the individuation of the theoretical models that have been implemented by the United Kingdom, Euro area and the United States, we have conducted a statistical analysis over the different policies. In the first instance, we have examined the monetary expansions that BoE, ECB and Fed have undertaken in response to the recessive trend. Our findings were statistically acceptable and in accordance with the model for all the three areas considered. Precisely, we found out that in the UK the policy has been effective and that a diminishing of interest rates, combined with appropriate control over the inflation, has permitted forecasting and adjustment of future’s inflation in compliance with the target of 2%. The extent of the adjustments is given by the relative regression line

. The same relevant findings are extendible to the

Europe and United States which returned the following regression lines: respectively and

. Notably, inflation in the UK is

expected to rise from the current level of 2.4%, hitting 2.84% at the beginning of the new upcoming year. The same trend should be registered in the US, where the CPI is expected to reach 1.59% within October 2012, compared to the current level of 1.4%. Conversely, a decline of inflation is estimated, with a fall from 2.4% to 2.22% over the next sixth months. However, it is necessary to highlight that the statistical importance of the last two predictions is not fully recognised, due to some inconsistencies in the estimation of the relative p–values and betas. It is likely that such imperfections mostly derive from the effects of some variables that, due to the particular conditions and high instability of the economic system, have interfered more than expected, and have somehow reduced the effects of the adjustments on the interest rate. The observations of the effects ©2012 – Daniele Stanizzi

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on the output gap through inflation targeting have also been measured via multivariate regression. Again, the statistical significance of the computation is confirmed by the values of F–statistic, p– values and R–squared relative to all the economies considered. Remarkably, we have found that, in the Euro area, levels of GDP are statistically related to the inflation and interest rates registered six months prior. In fact, we have discovered that a contraction of the short–term rate triggers an increase of income per capita within a few months, according to the negative value of beta we have found. The opposite effect has been registered as for the inflation, for which positive beta indicates they co–move. The relative regression line is

. The

findings relative to the UK economy bring appreciable results only in relation to the inflation, for which positive beta confirms our expectations of positive effects on future’s GDP. However, we have discovered that a significant positive influence of interest rates found during the test weakens the estimation relative to this economy, which can be identified with the regression line we have found:

. The error could be attributed to a jamming in the

transmission mechanism that triggered and inadequate response of agents to the adjustments of the interest rate. In spite of this flaw, we can affirm that altogether the monetary policy conducted by the BoE has been effective. As for the computation relative to the United States, the key values confirm the effectiveness of the monetary policy through inflation targeting. The quantitative extent of the efficiency is measured by the regression line , which validates our expectations over the effects of the regressors on future’s GDP. Moreover, we expect the European gross domestic product to remain almost unaltered from today’s level. The forecasts relative to the UK and US suggest that the income per capita will decrease in both areas and, precisely, of £500 and $700, respectively, in between of 2012 and beginning of 2013. The dynamic IS–LM model has provided a clear picture of the current conditions of the economy in the UK, for which the results also apply to Europe and the United States. The application of the model relative to the monetary expansion has outlined essentially three important aspects: (1) the starting point at which the economy was prior to the measure; (2) the adjustments that are taking place as a result of the implementation – including a picture of the current state; (3) the arrival point that marks the new steady state that the economy is steadily reaching. Precisely, we have seen how an increase of money supply performed by the Bank of England has a direct impact on both short–term and long–term Libor through the expectation theory. As a consequence, the borrowing becomes cheaper, stimulating investments and, ultimately, the output gap. Moreover, a closer look at the fiscal policy allowed us to comprehend their importance and their crucial support when adjustments of interest rates are so aggressive that monetary policies become ineffective. This ©2012 – Daniele Stanizzi

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last examination has also allowed us to take a step forward in expanding our findings; in fact, we have understood (4) how sensitive markets are to new information and how agents reformulate their expectations, profoundly changing the structure of the economy even before actual adjustments are implemented (period between announcement and implementation); also we came across (5) a “perverse” behaviour of the economy during this particular period. Furthermore, we have discovered how an increase of public spending raises the interest rate (in the long–term) increasing production (in the long–term), entailing a decrease of stock prices due to the subsequent higher convenience of gilts. These findings, as previously mentioned, can be extended to Europe and the US, although, for this particular case, we need to take into account Barack Obama’s modification to the American healthcare system, which resulted in a significant increase of public spending and might have altered the outcomes of the model.

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Appendix This section contains all details relative to the dataset used throughout this research study and its composition. This is for a more comprehensive look at the research; also, it will function as guidance for the reader who will be able to directly verify the data used and subsequently, this study, obtaining a more full and accurate understanding. Each dataset has been collected and analysed relative to the United Kingdom, Euro area and United States. As for the interest rates, the selection includes the following time range: one month, three months, six months, and twelve months. The following primary data has been gathered: 

Overnight Interest rates: overnight Libor, Eonia, Federal Funds



Interest rates: Libor (£), Euribor, Libor ($)



Standing facilities



Inflation



Production



Production growth



GPD (PPP)



GDP growth



House Price Index (American HPI)



Stock Prices (FTSE All–shares, ESTX50 EURP, S&P500)



Public spending

All data have been acquired from several official database and providers. Below the list: 

http://stats.oecd.org



http://sdw.ecb.europa.eu



http://www.freelunch.com



http://www.inflationdata.com



http://it.global–rates.com



http://epp.eurostat.ec.europa.eu



http://databank.worldbank.com

The database utilised has been included in an Excel file that goes along with this research and it is available at: https://dl.dropbox.com/u/27258095/Database.xlsx Finally, we want to clarify that all charts without direct mention of their source have been created based on the aforementioned database. ©2012 – Daniele Stanizzi

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