Abstract

The main objective of this research is to determine Key determinants of sovereign bond ratings. The analysis is based on determinants as identified by Moody’s, Fitch’s and Standard and Poor’s rating agencies. The researcher examines sovereign credit risk structural models and identifies variables expected in explaining variations in sovereign credit spreads. Approximation of the model indicates statistical importance and predicted signs. However, the model does not give explanations major part of the variation in sovereign credit spreads. Component Analysis indicates that regular factor is countable for majority of credit spreads variations.

 

According to the past literature, it is evident that international factors, specifically risk perception, plays an important role in illustrating government bond yields differentials. As local factors like liquidity and sovereign risk seems to be smaller, the two factors cannot be ignored as they are drivers of sovereign spreads. Moreover, the effects of local factors on sovereign bond ratings rose significantly during the crisis, at the time the major investors started discriminating more between nations. The research outcome is relevant to policymaking in addressing sovereign spreads.

Table of contents

CHAPTER 1

INTRODUCTION

Background of the Study

Countries within the European Union bloc that have weaker fiscal fundamentals have continued to experience the adverse effects of the economic crisis since its intensification in 2008. This trend is not just affecting the Euro zone economies but all economies must revisit their fiscal policies to ensure that their long-term bonds do not take an upward course beyond control of the regulators. This implies that rating of the bonds is an important undertaking that an economy must take to ensure the economy does not fall out of control.  Blending the knowledge of how the ratings are affected and what factors have an impact to the rating explains how uncontrollable trends interject the functions of the sovereign bonds in a number of ways. For instance, how an aggregate regional factor in the bond market is likely to affect the overall trend as observed by Santis (2012). The outcome of the past economic trends inter-married with turbulent economic times that followed necessitate accumulation of knowledge that points to better understanding of the sovereign bond ratings among other salient issues in the macroeconomic field. This study therefore aims to establish factors which help in determining the sovereign credit ratings provided by the major credit rating agencies such as Standard-&-Poor’s.

The credit rating agencies have been criticized for having too much influence and providing results that make economic downturns more severe (e.g. Steinberg (2010). Roubini (2001) emphasizes that the criticism that Credit rating agencies precipitated the European crisis is chiefly unjustified; their downgrades only reflect the weightiness of the problems that many Member states are presently facing. As a matter of fact, as confirmed by Trevino and Thomas (2001), in the majority of cases they have followed, rather than led, market sentiment. Additionally, the works of the three agencies have been complicated by having to work against a background of changing policy initiatives form EU Member States.

The downgrade of rating agency, in certain circumstances, exercises a disproportionate influence on markets, exacerbating fragile situations. Considering the fast changing nature of recent events and financial markets volatility after the economic meltdown in 2008, one can find out the degree to which rating agencies may have worsen the crisis (Trevino and Thomas, 2001).

According to Peters (2002), the credit rating agencies received deserved criticism for their role in the banking collapse on 2008. Their role in the ongoing European market crisis is considerably different, and justified anger over their former failures should not colour objective assessment of their current decisions relating to European sovereign debt (Trevino and Thomas, 2001). The global accredit rating industry is, as at now, an oligopoly.

Statement of the Problem

The banking and credit institutions witnessed an intensified crisis in late 2008, a crisis that escalated into another crisis of assurance in the financial health of some member States of the Euro area (Afonso, 2003).  As cited by Cantor and Packer (2008), there are a number of financial organisations in Europe that have embarked on confidence-building attempts where they have aimed at boosting confidence in European economy to prevent market concerns spreading to other economies in the Euro Zone. Attention has been drawn to the role and behaviour of credit ratings agencies and, in particular, the three main agencies: Moody’s, Standards and Poor’s and Fitch.

In 2008, many banks collapsed and the blame was visited on the failure of the rating agencies to provide accurate ratings of the financial products. This failure, some authors have recently argued, caused the collapse of the financial institutions to be more severe. The credit ratings are considered as important indicators of likely a country is going to repay its debts. They are important because if a government has bad sovereign credit rating, it implies that it cannot get debt finances.

An example of a country in the Euro Zone that is facing a lot of questions is Greece. Greece has been reported to be in the clutches of recession as the country was still having a negative growth rate of below -4.8% in the year 2011 (Athens News 2011). Steinberg (2010) pointed out that the downturn in Greece economy was due to the decline in the construction and tourism industry, which was occasioned by a sudden drop in the country’s rating. Central Intelligence Agency (n.d.) stated that this growth rate was -2% in the year 2009 and +2% in the year 2008. Athens News (2011) also reported that the inflation had risen to 5.2% due to an increase in the price level of the commodities. It has been conceptualized that when the national economy shatters, the functioning of various departments gets severely affected. National economy is integrally tied to the bond market since this is a major source of credit for the government. It seemed that the Greek citizens had started losing faith in the banks, the financial institutions, and the insurance companies.

Recently, the European parliament started a process of instituting an independent rating body that would provide alternative and better rating of the European economies. The argument is that the existing bodies need to be regulated because they have political influence and thus not providing proper and reliable information about their ratings (European Parliament 2012). Initially, according to Monfort and Mulder (2000), Politicians across Europe have opted for enhanced regulation and made suggestions that oligopoly of the rating agencies ought to be challenged by creating European credit rating agency.

While not essentially contrasting further regulatory measures to boost transparency, Peters (2002) recommends that the new framework be given time before further changes are made. This is hoped to assist ensure investor get the actual picture of the sovereign ratings: subjective predictions that depend upon the individual judgment of rating agency staff. Investor is not to follow the ratings blindly rather look at them as notions to be balanced and confirmed by other European indicators (Trevino and Thomas, 2001). Following the crisis, it is vital to analyse the suitability and applicability of Fitch Ratings, Moody’s and Standard and Poors ratings agencies. It is also crucial to critically analysing the key determinants of sovereign bond ratings.

 Aim of the Research

The research is aimed at analysing the key determinants of sovereign bond ratings reviewing the top three rating agencies: Fitch Ratings, Moody’s and Standard and Poors. The analysis will employ component Analysis in identifying the key factors affecting sovereign credit ratings.

 

Objectives

In order to achieve the set objective and for finer analysis, two objectives have been set to answer the research aim.

• To critically analyze the suitability and accuracy of Fitch Ratings, Moody’s and Standard and Poors ratings agencies.
• To critically analysing the key determinants of sovereign bond ratings using the three rating agencies.

 

By answering the above questions, the study endeavours to achieve several objectives of which the main objective is to investigate the specific factors that are used to determine the sovereign credit ratings of economies in the European credit market. Besides this broad objective, the study aims to establish ways of enhancing efficacy of the credit ratings. Another specific objective is to establish how the process of credit rating is conducted. This is important in establishing and understanding where problems might be coming from especially in the past where the figures have seemingly been unreliable and blamed on heightening of collapse of banking institutions in some European economies. Through this approach, the study also investigates other factors which the credit rating agencies need to put into consideration and yet are not being incorporated into the credit rating exercise. This bears in mind the economic dynamics that have seen the global economy since the late 1980s.

Scope of the research

The global credit market is inexhaustibly wide and beyond the scope of this study. In addition, even though the general contemporary credit market only started receiving increased scholarly attention in the recent past, the span of such coverage would still be beyond the scope of this study. Thus, the study only focuses on investigating the factors that are considered by the major credit rating agencies in rating the sovereign credit in the European credit market. Given the expansive nature of the economic diversities characterising world economies and the different economic subdivisions of economic blocs being affected by different factors, it would not be possible to cover all the regions. Nevertheless, it is hoped that the results of the study will have a major contribution to the existing body of literature and enhance the success of related future studies.

Significance and rationale of the study:

Since the Great Depression, scholars around the world have concentrated their efforts to studies focusing on the economic crises in different regions of the world. For instance, Stewart (2000) carried out a study on the prevention of economic crises that result from horizontal economic inequalities among nations and economies. In the study, Stewart observes that the approach taken to mitigate these crises depends on the economic level of the country among other factors. In the study by Barth, Caprio, and Levine (2001) the authors’ objective was to establish how best bank regulation and supervision would be done to achieve the best economic setup with no crises resulting. The number of studies is high. However, it is evident from the studies that most past studies focused on mitigation of economic crisis due to financial institutions failure rather than credit crisis.

The effects of economic crisis spiraling to many parts of the economy are not new since the end of the World War II. To echo the comments of the former US Federal Reserve Board president Allan Greenspan who reiterated that risk taking is a primary economic function for regulated entities including banks and other financial institutions. This serves to imply that even though the regulated bodies do and ought to take risk, the essence of regulation is to ensure that the risk taken is calculated. Nevertheless, what type of risk is taken by a credit rating body when issuing its credit ratings of a particular sovereign bond?  It is therefore imperative that the relevant financial systems are designed to address risk challenges. The risk challenges can only be well handled when the available information is relevant and current.

 

The central bank governors and policy makers from the Euro Zone countries have embarked on proactive measures to safeguard their institutions from increased financial risk during the economic crisis the way it was done for banks for the 1970/1980 crisis. For instance, (Patrick 2005) examines how the establishment of the Basel Committee helped to safeguard international financial institutions from the surging financial risks occasioned by the global economic depression. Similar strategies were employed in 1988 with the introduction of capital measurement system for regulation on requirements for exposure to market risks. The Basel accord has undergone tremendous development since its inception (Kevin 2004). Froot (2003) reveals that during the Asian economic crises of 1997 (BCBS 1999), economic integration and forces driven by globalization led to financial instabilities that necessitated refinement of the Basel accord.

 

Caruana (2003) holds that this led to the proposal of introducing guidelines for new capital adequacy frameworks in 1999. This new framework also refers to as the Basel two accords are made up of three pillars. One of the pillars identified is the minimum capital requirements. The second pillar identified under the Basel two accords is the supervisory review while the third pillar is the market discipline aspect of the guidelines. A critical analysis of the changes in the accord reveal that the main objective of revising the accord enacted in 1988 was to put in place a framework for stabilizing international banking systems (Hull, 2006). However, it is also notable that this review was also made to eliminate inconsistencies and competitive inequalities in players within the international banking sector, which effectively affects the credit bond markets as well (Caruana 2003). Under this project, it is very clear that although operational risks have been ignored in the past, such risks have the potential of crumbling the global international financial systems. It is under this realization that the committee included operational risks in the Basel two frameworks in line with emerging trends where operational risks have been shown to have greater value in defining international financial stability and trends. The increased attention on operational costs has also led the author to examine its definition, meaning the risk from internal and external factors.

 

Jack (King 1998) has also stated that operational risks may emanate from not only operational failures and internal challenges but also from such external factors like terrorism attacks, failure in management or natural disasters. As such, it is imperative that financial institutions and banks must be cushioned against financial risks which are the fundamental reason for the inclusion of operational risk compensation (Walter 2003).

 

On the research methodology, the researcher critically examines other studies on the differences between Basel one and Basel two as well as literature on the effect of these regulations on the global financial industry. In addition, (Walter 2003) reviews other literary works focusing on exploring how banks and other financial institutions are dealing with operational risk management issues as well as the calculation methods they are using arrive at capital charge and factors they consider. Based on the reliance on expert’s opinions on operational risks the study is qualitative.

 

Based on all these studies, it is evident that the efforts made are predominately focused on the banking sector and the financial stability of these institutions. Yet the sovereign bond market is a very important player in the stability growth and continuity of the financial institutions. This provides a philosophical rationale of this study which not only recognises the way this area needs more study but also the fact that it is a very important subsector of the whole financial network. In this regard, the identification of the factors considered in credit rating should not only help in generating wider knowledge of the practice but also elicit specific critic that will create a further fillip for greater efficiency and reliability of the practice.

 

Chapter two

Literature review

 

2.0. Literature Review

Sovereign debt in merging market economies affects the domestic economy through a variety of channel, some of which are not entirely apparent but still powerful. Few theoretical papers have analyzed the role of sovereign bonds, and most of the empirical literature on bonds spreads and debt crises have not explored that link.

 

Sovereign bonds have become an increasingly significant source of financing for European countries. One significant feature of the sovereign bonds is its substantial credit spreads owing sovereign default risk. Various theories and notions regarding sovereign bonds ratings have come up since the economic meltdown in 2008. Though there are claims about the accuracy and suitability of the rating agencies, it is clear that various factors have effects on the sovereign bond ratings.

 

McKenzie (2002) through a research found that world interest rate and domestic. Fundamental account for 40 percent of movement in bond spreads. Few empirical studies include the exchange rate policy into assessing sovereign default risk.

 

The literature review will collect the secondary information from the journal and books regarding the three rating agencies and information related to sovereign bonds ratings. This section reviews the existing literature about sovereign bond ratings the chapter commences by presenting the general literature on bond ratings and access to financial markets by European countries. The chapter then analyses the functions of sovereign risk and ratings in capital flow and corporate access to credit in Europe. Next, the chapter summarizes the literature on the costs and consequences of sovereign poor ratings to the economy of Europe.  Literature review is essential in finding relevant information and the former theories and facts about sovereign bonds rating in the European market. It is essential therefore to analyze the three rating agencies in turn and their efficiencies.

 

2.1 Impact of sovereign risk and ratings

Taking a broad historical perspective, Gibson and Sundaresan (2001) and Lee (2003) highlight the critical role of sovereign risk for cross-border external capital. According to the three authors, European countries normally lose all access to private capital markets when sovereign ratings fall below a crucial threshold. In contrast, countries with very high ratings tend to have continuous access to capital, even during recessions and crisis periods. For the in-between group of countries, middle-income emerging markets, access to capital is volatile and depends on various external and internal factors. In worst times, with ratings falling and fundamental deteriorating, these countries face the risk of rapidly rising interest rates and a sudden loss of access to market financing. The three authors conclude by stating that countries with weak political and institutional systems and a history of sovereign defaults are able to tolerate only very low levels of external indebtedness.

McKenzie (2002) expands the argument, emphasizing the link between historical defaults and present’s sovereign risk levels. According to Mulder and Perrelli (2001), sovereign rating changes have various impacts on both bond and stock markets in emerging markets. The authors emphasise that a downgrade in ratings results to a rise in bond market spreads of about 3% points and to a drop in stock market returns of 2% point. Other authors states that sovereign risk has little effects (Obstfeld and Rogoff 2003). Clark (2007) for instance state that sovereign risk, as measured by mean ratings, is not an important determinant of capital flows in a cross-sectional framework.

Private credit ratings and the covering ceiling

Emerging market economies started to seek credit ratings in the 1990s, when they once again started to issue bonds in global markets. Even though bonds had formerly been the major borrowing instruments of sovereigns, the instruments basically disappeared from global financial markets after the economic collapse in the 1930s, and international syndicated bank loans became the dominant mechanism for developing countries borrowing in the 1970s. These loans went largely into default in the early 1980s, and the restructuring of the debts into “Brady Bonds” created the current version of the international bond market for these economies.

Prior to 1990s, standard and Poor’s rated only a few sovereigns, and almost all the ratings were at the top of the rating category. Similarly, Moody’s had rated only eleven countries up to 1980s, and the ratings were all in the investment grade range. The indication here is that there exists a fairly short experience in observing the changes of sovereign ratings, specially compared with the century-long corporate ratings (Moody’s, 2003). Before the 190s ratings, the only data available about ratings for emerging economies were those assigned by publications for example Institutional Investors, and Euro-money. In contrast to the credit ratings agencies these financial publications have rated sovereigns on the basis of surveys of investors and analysis. Even though the ratings are expressed on s scale that is broadly consistent with that of the credit rating agencies, it is important that these are merely survey measures, while the rating agencies provide a professional service to bond issuers and their ratings are a factor in investment mandates and capital requirements.

A sovereign bond rating is the assessment of the chances of default in government debt. According to Clark (2007) government default results in cases where the government misses to pay the debt or where there is a distressed debt exchange meaning a reduced financial obligation by the government. One of the factors that is considered by the credit rating agencies is a 5-year horizon. The rating agencies also evaluate a large number of political and economic factors, and assess the factors both qualitatively and quantitatively in the rating process. However, as stated by Haque and Mathieson (2000), eight variables explain more than 91% of the sovereign ratings variances allocated by both Moody’s and Standard and Poor’s ratings. Haque and Mathieson (2000) list the eight variables as inflation, fiscal balance, per capita income, GDP growth, debt-to-export ratio, current account balance, an indicator of variable of advanced economy, and an indicator variable of default since 1970.

Even though the three rating agencies have claimed that they are successful in predicting sovereign default in comparison to corporate defaults (Moody’s, 2003), there have been various failures in the ratings. An instance is seen in the Asia crises where the rating agencies were criticised for delaying to react and later for overreacting, notably in case of Korea (Jüttner and McCarthy (2000). As a matter of fact, the rating agencies have been blamed for aggravating financial crises as they were too pro-cyclical in their ratings. It can be assumed that ratings too sticky rather than too pro-cyclical.

Credit ratings

According to Jüttner and McCarthy (2000) and the rating agencies, sovereign credit ratings has noted a significant bearing on the ratings attained by private companies and financial institutions. For instance, Standard and Poor’s emphasises that sovereign credit risk is normally key consideration in credit risk assessments in financial institutions. The argument is that governments facing a condition of financial distress or default may force private sector defaults by imposing exchange controls and other restrictive measures. As argued by Obstfeld and Rogoff (2003), evidence from default episodes indicates that sovereign default does not normally mean corporate default. Therefore, sovereign ceiling might not capture corporate risk effectively.

Role of rating agencies

When assessing municipal bonds, the main concern of the person investing is the ability of the issuer to meet its financial obligations, the full payment of its debt service on timely manner. The issuers are expected to disclose their financial conditions through various supportive documents that are supposed to be available to the investors. However, not all the financial institutions have the ability and capability and training needed in accessing the reviewing such data and reaching accurate determination of the issuer’s ability to fulfil its financial obligations

The other avenue that the investor can use is the credit card ratings. Credit ratings are significant benchmark since they reflect a professional assessment of the issuer’s ability of meeting its financial obligations and so the importance of rating agencies. Although various banks have their own rating methods, credit rating by the rating agencies have gained market acceptance. The rating agencies have the primary role of assessing the probability of timely and payment of debts.

Implications of sovereign defaults

As sovereign risk approaches peak levels during episodes of sovereign defaults, it is usual to expect “top-down’ risk spillovers to be particularly strong during and after default episodes. For the past crises in Uruguay, Afonso (2003) state that sovereign distress affects the behaviour of depositors and may result to runs in the banks. Along similar lines, Bulow and Rogoff (2003) provide evidence that debt crises may trigger systematic banking crises.

Ratings

Each bonding-rating company has its own alphabetical coding for rating bonds and other types of credit issues. For instance a firm night note a rating as strong and this may differ from other firms. One cannot easily tell which firm is more accurate unless after following the ratings for some time, after which one can understand the system the firm uses and how the system works. The accuracy of rating agencies can hence be determined after the long follow up.

Since various rating agencies may differ drastically, one needs to check out ratings from various firms and understand what each firm means by each rating term.

Credit rating definitions by three agencies

Highest credit quality: AAA as in Fitch ratings and Standards and Poor’s rating and Aaa as in Moody’s denote the lowest probability of credit risk. The ratings are assigned majorly in cases of exceptionally strong capacity for payment of financial commitments. This capacity is highly unlikely to be adversely affected by foreseeable events.

High Credit quality: This is denoted by Aa in moody’s, AA in both Fitch and Standards and Poor’s ratings. The rating is assigned in cases of low expectations credit risk and it indicates a very strong capacity for payment of financial commitments. This capacity is not significant vulnerable to foreseeable events.

High credit quality: This has a symbol of “A” in all the three rating agencies. It denotes expectations of low credit risk and indicates strong capacity for payment of financial commitments. This capacity may, nevertheless, be more vulnerable to change in circumstances or in economic conditions than is the case for higher ratings.

Good credit quality: This is denoted by Baa in moody’s, BBB in both Fitch and Standards and Poor’s ratings. It indicates that there exist presently expectations of low credit risk. There is just sufficient capacity of the financial payments, even though advance changes in circumstances and economic conditions are more likely to impair this capacity.

Speculative: This is denoted by Ba in moody’s, BB in both Fitch and Standards and Poor’s ratings. This is an indication that there is a chance of credit risk developing, particularly due to adverse economic change with time. However, the alternatives of businesses or financial institutions may be available to allow financial commitments to be met.

Highly Speculative: For issuers and performing obligations, B ratings as in Fitch and Standard and Poor’s rating and b in Moody’s ratings indicate that there is notable credit risk currently, but limited margin of safety remains. For personal obligations, highly speculate ratings indicate distressed or defaulted obligations with potential for extremely high recoveries.

High default risk: The high default risk denoted by Caa and CCC or CC in both Standards and Poor’s and Fitch ratings that there is a possibility of defaults. For personal obligations, CCC ratings indicate distressed or defaulted obligations with potential for average to superior levels of recoveries.

Moody’s rating agency

According to Moody’s rating agency, the long term ratings are intended to measure the expected loss, and therefore incorporate elements of both probability of default and severity of loss in the event of default. Moody’s long-term ratings are opinions of the credit quality of individual obligations or of an issuer’s general creditworthiness, without regard to personal debt obligations or other specific securities.

In this rating, four main factors considered when rating bonds are: economy, debt, finances and administration/management strategies. Moody’s credit ratings are comprised of nine symbols ranging from Aaa to C, the highest ratings and lowest ratings respectively. The rating also comprises of conditional ratings using the prefix, where the security for bond issues us dependent upon four factors: a) earnings of a project under construction, b) earnings of a project with limited operating experiences, c) rentals required to begin upon project completion, and d) payments upon some other limiting condition

Standard and Poor’s ratings

This is one of the premiere bond-rating firms. The company’s founder, Henry Poor, built his financial information company on the “investor’s right to know”. The first attempt at providing this type of financial information can be found in his 1860 book, History of Railroads and canals of the United States, where he included financial information about the railroad industry. Today, Standard and Poor’s rating is among the leading in independent credit ratings, risk evaluation, and investment research.

According to Moody’s and Standard and Poor’s statements on rating, the two agencies list various economic, social and political factors that determine their ratings (Bulow, 2002). Determining the connection between the two rating agencies criteria and real ratings is complex since some of the criteria used are not measurable. In addition, the two rating agencies have very less guidance concerning the comparable weighs they allocate to each other. Even for measurable factors, finding the weighs allocated by the two rating agencies is hard since the Moody and Standard and Poor agencies depend of huge number of criteria.

Fitch Ratings

This is the latest rating agency compared to standard and poor and moody’s rating agencies. John Knowles Fitch founded Fitch Publishing Company in 1913, and the business started as a publisher of financial statistics. In 1924, Fitch introduced the credit-rating scales that are very familiar presently. Fitch is best known for its research in the area of complex credit deals and is thought to provide more rigorous surveillance than other rating agencies on such deals.  According to Fitch, generally, its international long-term ratings are used as a benchmark measure of chances of default. The main exception is within public finance or municipal where market convention between issuers and their underlying obligations.

Fitch bank ratings include individual and support ratings. Support ratings entail five rating categories that reflect the likelihood that a banking institution will receive support either from the owners or the governmental authorities if it runs into difficulties. The availability of support, though critical, does not reflect completely the likelihood that a bank rating to evaluate credit quality separately from any consideration of outside support. This rating is commonly viewed as assessing a bank where it is independent and could not rely on external support. It supposedly takes into consideration such factors as profitability and balance sheet integrity, franchise, management, operating environment, and prospects.

In the past years, the need for covering credit ratings has risen drastically. This is the risk assessment allocated by credit rating agencies to central government’s obligations. Various governments with larger default risk various organizations domiciled in more risky nations are borrowing from international bond markets.

 

Availability of information allows the researcher to give estimations the quantitative indicators which are weighed in determining the ratings in evaluations of the predictive power of ratings. Various literatures indicate that to a greater extent, Standards and Poor’s and Moody’s ratings nearly weigh similar.

 

Determinants of field spreads

The main determinants of yield spreads are credit risk, liquidity consideration, and risk aversion changes.

Credit Risk

This risk arises for the bank from the possibility that due to circumstances special to the borrower, there will be a delay in loan repayment or default on the loan. This risk is faced by any commercial bank and is not peculiar to the UK currency operation. But this risk takes on an added dimension for a UK bank because loans are generally of large denominations, and unsecured.  The lack of collateral for loans granted is attributable to the intensity of competition among banks and the generally high standing of borrowers.  In recent years the usage of formal collateral and guarantees has increased as banks have sought some security on loans granted to oil deficit countries.  During normal circumstances when banks use floating rate loans, match deposits to loans in terms of currency and maturity of the roll-over period, the only risk that they still face is the credit risk.  This risk is, therefore, most significant, and least in the banks power to control.

The impact of loan losses can be felt on the level of cash reserves held by bank and on its capital account. Changes in cash reserves are a consequence of granting and repayment of loans. When loans are granted cash reserves decline while repayment increases these reserves. Default (or delay) by a borrower on a loan due, means that an expected repayment or inflow of cash did not materialize. A bank’s cash reserves are subject to this uncertainty. Losses in the capital account are likely over the longer term, most obviously, because of insolvency of the debtor. A bank has information on the ability of respective debtors to repay their obligations in a probabilistic sense only. These losses can also stem from short term, losses on cash reserves (due to insolvency or delay by debtors to repay obligations) which force bank portfolio rearrangement such as borrowing of deficits at unfavourable rates, incurring of losses in selling of assets and transaction cost (Baltensperger, 1992).

Apart from the adjustment in the interest rate that takes into account the credit risk, there are other ways a bank can also reduce this risk. Baltensperger has shown that there are important links between a banks’s operating expenses and its risk characteristics. A bank is able to trade off risk costs (costs of having to rearrange a portfolio quickly when the future is not anticipated correctly) for more operating costs. For example, it can spend resources to acquire more information on its debris and so reduce some of the uncertainty of default, and thus avoid costly adjustments in its cash or capital accounts later on. In this manner it is substituting operating expenses on acquiring information for costs of risk. The optimal level of such an information seeking outlay would be given when the “marginal reduction in risk costs resulting from the increased knowledge is equal to the additional information cost” (Baltensperger, 1992). We would expect banks to spend resources on information seeking activity, therefore.

In the UK market, however, since the market is international in nature, the cost of such information gathering on borrower credit worthiness and their usage of funds can be very high. A bank, customarily, does not know how much a borrower has obtained from other sources and questions of country risk compound the difficulties of obtaining useful information. But, UK banks have tried to keep informed of tendencies in the overall market by active involvement the interbank market. Here a typical bank acts both as a lender and borrower of interbank funds at the same time. By churning out deposits of a cosmetic kind this market provides traders “with information both about demand and supply, and it allows traders to stay in close touch with the market’s ‘feel’ for the ability and soundness of individual traders and banks… trading deposits may in a sense be an efficient way of trading information about individual banks and their techniques” (Dufey and Ian, 1998).The costs of this information should be negligible, as indicated by the spread between bid and offer rates on interbank placements, but is does demand reciprocity of actions. During times of crisis these costs are likely to increase because of general erosion of confidence. The observed “tiering” of banks in terms of size, credit worthiness, stockholder support and recourse to external assistance reflects the increased cost of seeking information needed to reduce the heightened credit risk during panic conditions of interbank placements.

Baltensperger also suggests that banks cushion the possibility of credit by holding reserves of cash and capital. It is because of uncertainty that a bank holds inventories of reserves and capital accounts. Were it not for these reserves a bank would have to incur deficit costs of borrowing needed amounts at favourable rates, selling of assets at capital losses and transaction costs. But, the holding of inventories also entails an opportunity cost for the bank in terms of income foregone in not being fully loaned up. If the expected opportunity costs exceed deficit costs, it pays to hold a smaller inventory of excess funds. The optimal inventory size would be one where the marginal deficit cost is equated to the marginal opportunity cost.

For UK banks, it has been suggested earlier that reserve holdings are negligible. This means that they exploit income producing avenues to the maximum at least in the short run. Presumably, the deficit costs of inadequate reserves must not be high during normal times given easy access to the interbank market and parent institutions, while the opportunity costs of incomes foregone is rather high.

The need for an adequate capital is of crucial importance over the longer term. We are interested, because of credit risk considerations, in the protection a bank has against the risk of general collapse due to widespread debtor default. To protect against this risk it would be expected that banks would be operating with high capital to asset ratios. In recent years, however, observers of the UK currency market have been alarmed at the decline in these ratios for most banks. This decline indicates a greater willingness by banks to take risk and an acceptance of reduced protection against it. The problem is further compounded if we were to account for the erosion of capital resulting from inflation since most of the bank’s equity consists of monetary assets. This erosion of the real value of the bank capital puts on added pressure to be fully loaned out so as to generate increased earnings to cover for inflation.

The observation that UK banks have resorted to operating with lower capital to asset ratios can be theoretically justified, if, even for the longer term horizon, the expected opportunity cost of holding inventories of capital exceeds the deficits cost of portfolio adjustments to a general collapse.

Chapter three

Research Methodology

Methodology

The methodology section describes the philosophy to be employed in the research. The research methodology will entail the instruments and the market to studied (European Market). The chapter will further include a description of the sampled market, sampling procedure used and the rationale and how information was collected from the sampled market. The aim of research is to critically analyze the application and credibility of the three agencies as sovereign credit ratings in the European market. In so doing the common factors that determine credit ratings in the European market will be identified.

 

Data Collection

Only secondary research methods will be used in data collection. The secondary data collection technique will entail collecting data already existing from various sources to give a platform for the research. Among the secondary sources will be journals and books.

 

Alternatively, those in favor of secondary analysis feel that using available data is the best mechanism to contribute to knowledge base. The secondary analyses identify gaps in the knowledge base and suggest problem formulations, hypothesis, and research methods that require primary collection. The research will majorly depend on the secondary data. Relevant information concerning the analysis of the ratings done by the three agencies will be used for analysis.

 

Secondary data has a number of uses in the process of consultancy research ranging from helping identify the problem and setting objectives through to helping interpret data and making recommendations. Effective planning of secondary data collection is essential, and the researcher is to assess what they are looking for, where to look and how to look for such data. Through secondary method, the researcher will also be able to collect a large volume of data necessary for analysis and so its adoption in this research. Through the secondary methods, the suitability and accuracy of Fitch Ratings, Moody’s and Standard and Poors ratings agencies will be determined.

 

Rationale for choosing secondary research

Secondary research has various distinct advantages compared to primary data collections.

1. The secondary research is generally less expensive to use. This is true when there are costs associated with data collection. When information is needed quickly then the best approach is secondary research. Suppose stringent budget and time constraints are imposed on primary data collection, secondary research may provide higher-quality data than could be obtained with a new research project.
2. Secondary sources provide an important starting point for extra research by suggesting problem formulations, research hypotheses, and research methods. Consultation of the secondary materials provides a means for increasing the efficiency of the research dollar by targeting real gaps and oversights in knowledge. The method can also provide useful comparative tool. New data can be compared with the old data and various assertions can be compared for examining differences and trends in a given phenomenon.
3. A secondary data search can be accomplished in a much shorter time frame than primary data collection that requires design and execution of primary data collection instrument.

Disadvantages of secondary research

Although the advantages of secondary research outweigh the disadvantages, there are limitations of the method. Many of the problems that secondary analyst encounters are intrinsic to the survey method, but some are unique to secondary analysis. A major problem is data availability. Despite development of data archives, researchers sometimes have trouble locating what they need. Some topics lend themselves more readily to secondary analysis than others.

The second disadvantage of the method is data availability. One does not always know how accurate the secondary data are. In case the degree of accuracy is high, the use of such dubious data involved undermines the utility of a research study. In most cases, it is difficult to know units what case secondary data have been collected and tabulated.

Selection of explanatory variables

The possible determinants of sovereign debt, and sovereign ratings chosen by various empirical models were derived from theoretical models on sovereign default, former observed evidence or the reports given by the three rating agencies. Based on the assertions by Grossman and Huyck (2001), sovereign credit risk can be assessed by small number of economic and political variables. The variables of sovereign credit risk do not differ from one scholar to another.

Sovereign credit ratings and data collection

Sovereign credit rating is the assessment of the possibility of the government paying the principal and interest of its debt in timely manner. The ratings are the estimates of the default occurrence. The ratings approximate future chances of government defaults but do not tackle default risk of other financial institutions in a country. Sovereign ratings are carried out considering the qualitative and quantitative variables considered reliable by rating agencies. The quantitative variables entail various economic and financial measures.

The ratings are taken in comparison to other countries in regard to their creditworthiness. The borrower is allocated a grade based on its creditworthiness. The sovereign credit ratings range from AAA (for Fitch and Standard and Poor) and Aaa for Moody to D and Caa the lowest rates respectively. Although symbols are used in the ratings, the system allows changing the rating symbols to numbers.

The data used in the research entailed foreign currency ratings of 86 European countries from December 2003. The ratings from the three rating agencies were used whenever a relevant data was found. Since the ratings by the three rating agencies were discrete variable, it was easy to transform into continuous variable through a linear scoring system. Using the system, 21 means the highest ratings of AAA and 0 means the lowest ratings or D. the mean was calculated for the values from each country rated. The differences between mean averages for the rated countries by each rating agency were determined.

Rating agencies	Differences
Moody’s and Fitch ratings	0.34
Standard and Poor and Fitch	0.04
Standard and Poor and Moody’s	0.36

Moody’s rating is greater than Standard and Poor’s rating in two occasions. This is observed in Argentina and Turkmenistan. Additionally, the two countries are rated lower on the scale. The rating disparity can be as a result of the range of rating by Moody and Fitch and Standard and Poor which have scale of up to 21 and the later two each having up to 24. 

An aggregate of 49 economic social and political variables were collected from the countries as from 1998 to 2002. The variables were from Fitch ratings which collected information from various sources. The information collected from the rating agency was grouped into eight different categories. This was in line with the Fitch’s classification method used in ratings. The categories were: Money and banking, economy, openness of trade, society, demographics, external assets and liabilities and income. Information in connection to sovereign defaults on official debt were obtained form World Bank. The information was changed into dummy variables. Countries which never paid their debt in time or postponed them at least once were rated one and countries that never defaulted were rated zero.

 

 

Chapter four

Analysis

4.1 Introduction

This chapter give an analysis of the possible determinates of sovereign ratings and their effects on the ratings. Three steps are undertaken during the analysis. In the first step, the available information collected form the three rating agencies are reduced based on their relevance and variables. Variables are ranked based on their explanatory powers using Principal Component Analysis (PCA).

Principle component analysis

To determine the determinants of sovereign credit ratings, it was essential to consider solvency facts and aspects like political system stability, social cohesion and the independence degree from other financial systems. Through analysis, it was also noted that sovereigns, unlike to corporate issuers, are less likely to be claimed by creditors suppose default arises. This is confirmed as a fact by Gibson and Sundaresan (2001) even suppose the government have an incentive to make payments, as a result of the likelihood of capital market autarky.

Based on the statement by McKenzie (2002) there are various factors that can influence the attribution of higher or lower rating levels to each sovereign issuance. Among the factors are range of external debt and the country’s political stability among others.

In get the determinants of sovereign ratings, principal component analysis was used. The method allowed the researcher to reduce the available information from the rating agencies. The variable noted x_i with changing varying from 1 to n. this was done by eliminating redundant variables and getting factors with the greatest explanatory powers. The factor noted at k, and variable t were connected by the following formulae

Where p had values 1,2,….n.

Determining the common factors affecting sovereign rating based on the three rating agencies was carried out through two stages. The first stage involved identification of the factors and second step entailed identification of the common factors. The factors which had lowest correlation using any pair were identified. The total variance of each factors was then determined. The main reason was to get factor with the highest portion of the variation in the original variation. The first factor had the greatest percentage of entire variation. The second factor had the largest share of the remnant variances, and not connected to the first factor. The process was repeated till the number of identified variances equalled the number of original variables. The components which explained a share of variances and were above a given threshold were then extracted. In Principal component analysis, the threshold is normally set at one.

Table 1:

The table below shows relative significance of 13 factors in illustrating the variation of sovereign ratings. The table represents a total of 48 indicators which were collected from various rating agencies.

Component	Total	% of variance explained	Cumulative % variance explained
1	10.1	21.05	21.05
2	5.57	11.6	32.65
3	4.65	9.7	42.35
4	3.56	7.42	49.77
5	2.86	5.95	55.72
6	2.38	4.96	60.68
7	2.08	4.33	65.01
8	1.69	3.52	68.53
9	1.5	3.12	71.65
10	1.46	3.04	74.69
11	1.28	2.67	77.36
12	1.12	2.34	79.7
13	1.05	2.18	81.88

 

A total of 13 factors were extracted. Table 1 shows the outcome of the results, and also shows the comparative significance of every factor in explaining sovereign rating variations. From the table, there is a marginal decrease in variations. The largest explanatory power has 21.05% and the least 2.18% of all the variables and all the factors accounts for 81.88%. This is an indication that the former data can be condensed from 49 factors to 13 factors with a loss of 18.12%.

The proceeding stage was to determine the importance of extracted components. For the purpose of identification, the researcher identified the variables that provided the best representation of the factors extracted in the first step.  This was done through computing the correlation matrix of the components as displayed in appendix 3.

The component with the largest explanatory power is rated the first. The high rated component is closely connected to the cost of labour per worker, perceived index of corruption and added value per employee. Public debt ratios and external debt are among the variables closely connected with the second factor. The analysis of all correlations coefficients of 0.5 and greater permitted the researcher to identify the nature of the extracted indicators. The proceeding table shows the factors that were extracted and their importance.

Table 3. Extracted factors

 

1. Development level
2. Public indebtedness
3. Quality of governance
4. political stability
5. Economic growth
6. Money supply
7. External Liquidity
8. External indebtedness and openness
9. Inflationary pressure
10. Net investment inflows
11. Size of the economy

	Agency	Aaa/AAA	Aa/AA	A/A	Baa/BBB	Ba/BB	B/B
MEDIANS Per capita income	Moody’s	23.56	19.96	8.22	2.47	3.30	3.37
	S&P	23.56	18.40	5.77	1.62	3.01	2.61
GDP growth	Moody’s	1.27	2.47	5.87	4.07	2.28	4.30
	S&P	1.52	2.33	6.49	5.07	2.31	2.84
Inflation	Moody’s	2.86	2.29	4.56	13.73	32.44	13.23
	S&P	2.74	2.64	4.18	14.3	13.23	62.13
Fiscal balance	Moody’s	-2.67	-2.28	-1.03	-3.50	-2.50	-1.75
	S&P	-2.29	-3.17	1.37	0.15	-3.50	-4.03
External balance	Moody’s	0.90	2.10	-2.48	-2.10	-2.74	-3.35
	S&P	3.10	-0.73	-3.68	-2.10	-3.35	-1.05
External debt	Moody’s	76.5	102.5	70.4	157.2	220.2	291.6
	S&P	76.5	97.2	61.7	157.2	189.7	231.6
Spread	Moody’s	0.32	0.34	0.61	1.58	3.40	4.45
	S&P	0.2	0.40	0.59	1.14	2.58	3.68
Number rated	Moody’s	9	13	9	9	6	3
	S&P	11	14	6	5	9	4
Indicator for economic	Moody’s	9	10	3	1	0	0
development	S&P	10	11	1	1	0	0
Indicator for default	Moody’s	0	0	0	2	5	2
history	S&P	0	0	0	0	6	3

1. Competitiveness
2. Debt servicing
3. Balance of payments

 

Various factors are evident from the table. First, there exists a correlation between weight of non manufactured material and measures of money supply. This is an indication that countries having low value-added goods do have economies with reduced degree of bank intermediation.

The table illustrates that any model which is meant for finding the rating countries can be condensed to the above thirteen mentioned factors. The same classification factors are used by other rating agencies.

 

Relationship between ratings and their determinants

In this section, the researcher determined the correlation between various independent variables.

Sample data from the three rating agencies: Table 2.

 

 

 

The table was obtained form world bank in relation to the three rating agencies.

Table 2 indicates that five of the variables are positively related referring to Moody’s and Standards and Poor’s’ rating agencies. Specifically, high per capita income is positively related to high ratings. Lower inflation and lower external debt are also related.

A high economic development level significantly increases the chance of rating of AA as in Standards and Poor’s ratings. Default history and ratings are negatively related as history where the government has various defaults, indicates the lower chances loaning. There is no clear boundary between the relationships between the three variables: GDP growth, external and fiscal balance.

There is no clear connection between GDP growth and the ratings since majority of the countries at times grow faster compared to developed countries. There is also no clear connection between sovereign ratings in the three rating agencies and external and fiscal balances.

 

Multiple regressions

Since some of the variable are not related to the ratings, there was need to estimate a multiple regression to help determine their combined explanatory power and group the variables as per their contributions to ratings. In this case, the Moody’s and Standard and Poor’s ratings are assigned numerical values. B3/B is assigned 1, B2/B assigned 2, and AAA/Aaa assigned 16 and so on. It was important to determine the mean of the two ratings in determining the ratings of a country. The regression analysis connected the numerical equivalents of the ratings.

One advantage of suing regression is the ability to predict large differences in various ratings. The mean ratings and rating differences are show in table 3.

 

Table 3: Showing the average and differences in ratings.

 

The first column indicates that a regression of the mean of the two rating agencies against the eight variables illustrates more than 90% of the sample variation.

 

Among the personal coefficient, per capita income, external debt, GDP growth and inflation and economic development indicator variables are important.

 

 

 

 

Variables     Intercept	Average     1.442	Moody’s ratings   3.408	S&P     -0.524	Rating differences   3.932**
	(0.633)	(1.379)	(0.223)	(2.521)
Per capita income	1.242*** (5.302)	1.027*** (4.041)	1.458*** (6.048)	-0.431*** (2.688)
GDP growth	0.151*	0.130	0.171**	-0.040
	(1.935)	(1.545)	(2.132)	(0.756)
Inflation	-0.611***	-0.630***	-0.591***	-0.039
	(2.839)	(2.701)	(2.671)	(0.265)
Fiscal balance	0.073	0.049	0.097*	-0.048
	(1.324)	(0.818)	(1.71)	(1.274)
External balance	0.003	0.006	0.001	0.006
	(0.314)	(0.535)	(0.046)	(0.779)
External debt	-0.013*** (5.088)	-0.015*** (5.365)	-0.011*** (4.236)	-0.004** (2.133)
Indicator for economic	2.776***	2.957***	2.595***	0.362
development	(4.25)	(4.175)	(3.861)	(0.81)
Indicator for default history	-2.042*** (3.175)	-1.463** (2.097)	-2.622*** (3.962)	1.159*** (2.632)
Adjusted R-squared	0.924	0.905	0.926	0.251
Standard error	1.222	1.325	1.257	0.836

 

 

Sources: International Monetary Fund; World Bank; J.P. Morgan; Federal Reserve Bank of New York estimates.

Note: Singe star (*) means 10% level, double star (**) 5% and triples star (***) 1% significance.

 

 

4.2. Rating determinants

After the initial analysis, where the correlation of various variables and rating were assessed, and the plausibility of financial relations, the below variables were chosen.

1. Rate of inflation

The rate of inflation has two negative impacts on the present stock of government debt. An rise in inflation enhances the public debt dynamics by decreasing the actual value of government debt and an increase in inflation negatively affects debt dynamics since it makes it necessitates the government to pay high interest rates.

Similarly, high inflation may lead to increased labour demand or distortion of the market. Additionally, high inflation implies that the country do not have the capacity to finance its public expenditures through the public funds. The inflation rate and level of rating are therefore negatively related.

1. Per capita GDP

This is supposed to be the measure of a nation’s development and is can be considered as a tax basis indicator in the economy. As well, nations with lower GDP per capita are less likely to deal with debt service problems through the implementation of austerity measures. Therefore, the grater the GDP per capita the higher the chance of the country to attribute a higher rating levels.

• Actual GDP growth rate

When all factors are retained constant, the economic actual growth on its own for decreased country indebtedness, make is easy to tackle coming debts service associated payments. Apart from this, an emerging economy has higher chances of absorbing extra labour supply, to reduce unemployment and boost the standards of living. Economic growth and rating levels are therefore positively correlated.

1. Default history

The history of defaults is significant factor to consider when assessing the credibility of government to fulfil its future obligations. Expectedly, when the government has a history of not paying the debts then it will have low rating level.

1. Development indicator and
2. Government deficit as a fraction of GDP

The following section gives some theoretical and intuitive explanations of how the factors are related to the sovereign bond ratings.

Conclusion

Sovereign credit ratings get considerable attention in financial markets. The analysis indicates that ratings depend on various factors. Of various criteria employed by Standard and Poor’s and Moody’s rating agencies, six factors are found significant and of great contribution to the sovereign ratings. The six factors found to be influence are: per capita income, GDP growth, inflation, external debt, economic development level, and default history. The analysis fails to identify any systematic connections between ratings and current deficits.

The analysis clears indicates that sovereign ratings effectually summarize and supplement the data entailed the macroeconomic indicators and are hence positively related with credit spreads. Majority of the correlations appeared to indicate same interpretations of the information as provided by the ratings agencies and various scholars. Even though, the analysis indicate that the rating agencies’ notions separately have impacts on credit ratings.

 

Chapter five

Conclusion

Sovereign rating adjustments may convey substantial new information about a personal country’s creditworthiness. Credit rating changes for long-time foreign currency debt may act as a wake-up call with upgrades and downgrades in one country affecting other financial markets within and across national borders.  Such a potential rating effect is likely to be stronger in merging market economies, where institutional investors’ problems of asymmetric information are more present. Therefore, this empirical study has analysed the determinants of sovereign ratings using rating agencies.

The results indicate that credit rating agencies have a substantial influence on the size and volatility of emerging markets lending. The empirical results are significantly stronger in the case of government’s downgrades and negative imminent sovereign rating actions such as credit watches and rating outlooks than positive adjustments while by the market participants anticipated sovereign rating changes have a smaller impact on financial markets in emerging economies.

Sovereign credit ratings play an important part in determining country’s access to international capital markets and the terms of that access, with the threshold between investment-grade and speculative-grade ratings having important market implications. Achieving investment grade status not only lowers financing costs for the sovereign and corporate with international capital market access that is constrained by the sovereign rating, it also expands the pool of potential buyers of a country’s bond issuances to institutional investors. For those countries with speculative ratings, identifying the main determinants of investment grade status can help policies towards achieving an upgrade.

Sovereign debt ratings are intended to be forward-looking qualitative measures of the chances of default elaborated by rating agencies. They are summary of a government’s ability and willingness to repay its debt in full and on time. The three major rating agencies indicate that their assessments of government risk are based on the analysis of a broad set of economic, social, and political factors, but are not explicit about the weights given to those variables in their final assessments.

Sovereign credit ratings are important for at least three reasons. First, they are key determinants of a country’s borrowing costs in international capital markets. Second, the sovereign rating generally sets a ceiling for the ratings assigned to domestic banks and companies, and therefore affects private financing costs. Third, some institutional investors have lower bounds for the risk and will choose their portfolio composition taking into consideration the credit risk signalled by the rating notations. Since sovereign ratings summarise a vast amount of information, empirical studies have tried to predict country ratings based on a parsimonious set of economic variables.

During the last decade, financial history has experience a real revolution. Several factors explain this change for example the development of financial econometrics and the huge increase of computer capacities.

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