ECONOMIC FREEDOM AND STATE BOND RATINGS

Are state bond ratings, ceteris paribus, related to economic freedom? We test for the relationship between economic freedom and an aggregate index comprised of ratings by Standard & Poor, Moody's, and Fitch. We also test for a relationship between economic freedom and the ratings by these three agencies individually. With a sample covering all 50 states for the period 1995–2008, the evidence strongly indicates that state bond ratings are positively and significantly related to overall economic freedom as well as three sub‐categories of economic freedom. Our results show that the quantitative impact of economic freedom on bond ratings is comparable to the effect of state real income and the unemployment rate. (JEL E43, H71)     

EU Banks Rating Assignments: Is There Heterogeneity between New and Old Member Countries?

We model EU countries' bank ratings using financial variables and allowing for intercept and slope heterogeneity. Our aim is to assess whether “old” and “new” EU countries are rated differently and to determine whether “new” ones are assigned lower ratings, ceteris paribus, than “old” ones. We find that country‐specific factors (in the form of heterogeneous intercepts) are a crucial determinant of ratings. Whilst “new” EU countries typically have lower ratings than “old” ones, after controlling for financial variables we also discover that all countries have significantly different intercepts, confirming our prior belief. This intercept heterogeneity suggests that each country's rating is assigned uniquely, after controlling for differences in financial factors, which may reflect differences in country risk and the legal and regulatory framework that banks face (such as foreclosure laws). In addition, we find that ratings may respond differently to the liquidity and operating expenses to operating income variables across countries. Typically ratings are more responsive to the former and less sensitive to the latter for “new” EU countries compared with “old” EU countries.     

Overflow effect of credit rating announcements on stock exchange based on event study

This study is aimed to identify the impact of credit rating announcements on the stock returns in stock markets and for this purpose, four different sectors of Pakistan stock exchange were selected and from each of these four sectors, different business organizations were selected, i.e. total 32 business organizations were selected. The credit rating announcement data were collected for these 32 business organizations belonging to four different sectors. Totally 101 credit rating announcements were selected and the time period for which the credit rating warnings were selected include last three years period, i.e. from 2014 to 2016. The collected data were analysed by calculating abnormal returns for each of the selected security and average abnormal returns, and cumulative average abnormal returns were calculated for four different sectors. Event study methodology was applied, and t-test and t-stats value were calculated and results were analysed on the basis of t-statistics. The results of analysis identified that credit rating announcements have a significant impact on stock prices and investors and other market participants are earning abnormal returns during two-day period after the announcements are made. In addition, these abnormal returns were either negative or positive, depending upon the nature of credit ratings announced. If the credit rating announced was upgraded, investors enjoyed positive abnormal returns while in case when credit rating announcements were downgraded, then investors bear negative abnormal returns. Finally, the findings of the study identified the applicability of random walk hypothesis on the Pakistan Stock Exchange and Pakistan Stock Exchange confirms the efficient market hypothesis with its semi-strong form of efficiency.     

The effect of gender and race on student performance in principles of economics: the importance of personality type

This article analyses motion picture box-office gross revenue using a cross-section of films from 1997 to 2001. The dependent variable is total domestic box-office revenue. The independent variables investigated include: production budget; peak number of screens that the film was shown on in theaters; Consumer price index for movie tickets; personal income; season and year of the release in theaters; a measure of pre-existing audience; aggregate critic rating; MPAA rating; genre; word-of-mouth recommendation; the presence of popular stars and the award nominations. A distinction is made in the analysis between information available to the public prior to the release of the film in theaters (ex ante) and information available to the public after the film opens in theaters (ex post). Results for the ex ante ordinary least squares (OLS) regression reveal positive impacts of budget, summer and holiday release dates, critical reviews, sequels and several genres on gross revenue. Significant, positive determinants in the ex post OLS regressions include budget, the peak number of screens, sequels, critical reviews, summer and holiday releases, word-of-mouth, award nominations and star power.     

DETERMINANTS OF SOVEREIGN BONDS RATINGS: A ROBUSTNESS ANALYSIS

Several studies have attempted to deduce the determinants of sovereign bond ratings. In this study, Extreme Bounds Analysis is applied to approximately 30 factors proposed by the literature in order to assess their robustness with a focus on the relative importance that economic and political variables receive in the shaping of the ratings. We find that policies that constrain the public sector are among the most robust. Variables such as rule of law, openness to economic flows, central bank independence, and market friendly policies are found to be more robustly correlated with the ratings than foreign reserves, fiscal deficit, sovereign bond yields, and economic growth.     

Measuring the Effect of Corruption on Sovereign Bond Ratings

Abstract

Instrumenting for sovereign corruption, we find that Transparency International’s Corruption Perceptions Index which ‘ranges from 10 (highly clean) to 0 (highly corrupt)’, is a significant predictor of the Standard and Poor’s sovereign bond ratings ranging from 1 (Sovereign Default) to 22 (AAA) in panel data from 52 countries from 1993 to 2002. Corruption downgrades the creditworthiness of sovereign bonds by diverting loan proceeds from productive projects to less productive ones, if not to offshore accounts. In particular, a one point worsening of the corruption perception index leads to an estimated one‐notch reduction out of 22 in the sovereign bond rating.     

Rating of Network-Integrated Corporations

While conventional rating systems are still focused on individual companies, in reality stand-alone business of a single enterprise respectively debtor is more likely the exception than the rule. Joint business activities of two or more companies (organizational networks) are becoming ubiquitous and have a critical influence on each partners’ success. In order to avoid that rating that turns into some rather useless ritual, network characteristics, such as network assets, network capital, network securities, network management competency, network business opportunities and network structure have to be taken into account when evaluating solvency of a network-embedded corporation. Using primary credit cooperatives as an illustrative object, this paper gives an overview on those new rating criteria becoming relevant in conjunction with network-embeddedness, so that workable opportunities can be shown to improve the reliability of ratings.      

Sovereign credit ratings,growth volatility and the global financial crisis

Using monthly data from January 1996 to May 2010 for a panel of 76 developed and emerging economies and adopting an instrumental variable (IV) estimation technique by correcting for both heterogeneity and endogeneity with the generalized two-stage least squares (G2SLS, EC2SLS) procedure method suggested by Balestra and Varadharajan-Krishnakumar (1987) and Baltagi and Li (1995), this article provides empirical evidence that volatility of per capita GDP growth is reduced when there are positive changes in credit ratings; in other words when sovereign credit risk improves. To deal with potential simultaneity between sovereign credit ratings and output volatility, a system (3SLS) approach is undertaken, and our findings remain robust. By weakening the volatility dampening effects of ratings changes, it is found that the global financial crisis (GFC) has enhanced macroeconomic volatility. One of the channels via which sovereign rating changes affect growth volatility is the financial markets’ repricing of sovereign default risk that is reflected in sovereign credit default swap (CDS) spreads and its volatility.     

Do movie contents influence box-office revenues?

This article studies the determinants of box-office revenues in the motion picture industry. We first adopt an approach that takes into account quality signals (e.g. talent concentration, movie budget and Oscar awards, among others) to analyse the empirical relationship between category-specific parenthood ratings (R-ratings) and box-office revenues. Then, by matching movie contents with economic performance records, our original approach reveals that offensive contents like profanity or nudity may be a hindrance to achieve economic returns, while violent contents seems to enhance box-office revenues. Further research is needed to clarify the interaction in this regard between production budget and movie contents.     

Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample

The accuracy of sovereign credit ratings renewed interest toward sovereign credit ratings in the aftermath of the 2008 financial crisis. The controversy over the accuracies encouraged internal credit scoring systems to reduce reliance on sovereign credit ratings. By employing classification and regression trees (CART), multilayer perceptron (MLP), support vector machines (SVM), Bayes Net, and Naïve Bayes; we explore the prediction performance of several artificial intelligence (AI) techniques in predicting sovereign credit ratings in a heterogeneous sample. The results suggest that AI classifiers outperform the conventional statistical technique in terms of accurate prediction. According to within one notch and two notches accurate prediction measure, the prediction performances of the AI classifiers exceed 90% accuracy whereas the performance of the conventional statistical method is around 70%. The results further reveal that the prediction performance of the models declines around the threshold rating that is located between investment grade and speculative grade which is not necessarily the result of inadequacy of the models. Rather, this is potentially due to CRAs' cautious behaviour toward those countries around threshold rating which can be interpreted as the certification price of upgrading to investment grade.     

Why Credit Rating Agencies Exist

Although credit rating agencies exist and are important to the capital markets, there remains a question of why they should exist. Two standard theories are that rating agencies correct a problem of information asymmetry and that they de facto regulate investments. These theories do not fully answer the question. This paper suggests an alternative explanation. While rating agencies produce little new information, they sort information available in the credit market. This sorting function is needed due to the large volume of information in the credit market. Sorting facilitates better credit analysis and investment selection, but bond investors or a cooperative of them cannot easily replicate this function. Outside of their information intermediary and regulatory roles, rating agencies serve a useful market purpose even if credit ratings inherently provide little new information. This alternative explanation has policy implications for the regulation of the industry.     

Procyclicality and the new Basel Accord - banks’ choice of loan rating system

Summary. The Basel Committee on Banking Supervision is proposing to introduce, in 2006, new risk-based requirements for internationally active (and other significant) banks. These will replace the relatively risk-invariant requirements in the current Accord. The new requirements for the largest bank will be based on bank ratings of the probability of default of the borrowers. There is evidence that the choice of loan ratings which are conditional on the point in the economic cycle could lead to sharp increases in capital requirements in recessions. This makes the question of which rating schemes banks will use very important. The paper uses a general equilibrium model of the financial system to explore whether banks would choose to use a countercyclical, procyclical or neutral rating scheme. The results indicate that banks would not choose a stable rating approach, which has important policy implications for the design of the Accord. It makes it important that banks are given incentives to adopt more stable rating schemes. This consideration has been reflected in the Committees latest proposals, in October 2002.Received: 25 October 2003, Revised: 27 April 2004, JEL Classification Numbers: D58, E44, G28. Correspondence to: Dimitrios P. TsomocosThe authors are grateful to Pamela Nickell for carrying out some of the calculations and Nicola Anderson, Charles Goodhart, Andy Haldane, Glenn Hoggarth, Nobu Kiyotaki, William Klein, Alistair Milne, William Perraudin, Hyun Shin, Paul Tucker, seminar participants at the Bank of England XI European Workshop on General Equilibrium Theory, Federal Reserve Bank of Boston, INSEAD, LSE, the University of Oxford and especially H.M. Polemarchakis for helpful comments and remarks. However, all remaining errors are ours. The views expressed here are those of the authors and do not necessarily reflect those of the Bank of England, and the Bank of Spain.     

The brighter side of being socially responsible: CSR ratings and financial distress among Chinese state and non-state owned firms

We examine the effect of corporate social responsibility (CSR) quality ratings on the financial distress levels of Chinese enterprises by using the previously unexplored new China-specific Altman ‘Z_China Score’ in the context of CSR and data from 749 firms over the 2009–2014 period. First, we find that CSR quality ratings significantly reduce Chinese firms’ distress levels. Second, we find that the ability of CSR to reduce distress levels in non-state-owned Chinese firms is higher than state-owned ones. Finally, we find similar results when we divide the data into high-low CSR ratings and levels of distress. Our results are robust to potential endogeneities.     

The impact of peer ratings on cooperation: The role of information and cost of rating

In this study, we experimentally analyze the effectiveness of payoff‐irrelevant peer‐to‐peer ratings as a cooperation enforcement device in a finitely repeated public goods game setting. We run two treatments that differ in the amount of information on own and others' received rating points provided to the players, whereas, in a third treatment, we analyze peer approval when assigning ratings to others is costly. In particular, we wonder whether, even under anonymity and in the absence of reputational concerns, (a) players rate others' contribution decisions in the expected direction and (b) the peer rating mechanisms under study foster cooperation and welfare. Our findings reveal that, in the two costless rating treatments, peer rating concerns lead to higher contributions and efficiency, compared to our control. Introducing a small fixed cost for assigning rating points results in a very high percentage of subjects deciding not to rate others' behavior, so that cooperation cannot be enforced.     

Does it really pay to do better? Exploring the financial effects of changes in CSR ratings

Previous literature on the link between corporate social responsibility (CSR) and financial performance has focused mainly on the financial implications of a firm’s level of CSR without considering the potential effects on financial performance of variations in CSR rating. We try to fill this gap by studying whether variations in a firm’s CSR rating affect systematic risk, firm value, and portfolio performance. First, our results show that an increase in firms’ CSR efforts, as reflected by an increase in their CSR ratings, significantly reduces systematic risk. Second, a positive variation in CSR ratings significantly improves firm value. Finally, from a portfolio perspective, a strategy that consists of buying stocks that have experienced a CSR ratings increase and selling stocks that have experienced a CSR ratings decrease (or remain stable) leads to lower financial performance. Taken together, our findings provide new evidence and financial implications for firms and portfolio managers.     

PIGS or Lambs? The European Sovereign Debt Crisis and the Role of Rating Agencies

This paper asks whether rating agencies played a passive role or were an active driving force during Europe??s sovereign debt crisis. We address this by estimating relationships between sovereign debt ratings and macroeconomic and structural variables. We then use these equations to decompose actual ratings into systematic and arbitrary components that are not explained by previously observed procedures of rating agencies. Finally, we check whether systematic, as well as arbitrary, parts of credit ratings affect credit spreads. We find that both do affect credit spreads, which opens the possibility that arbitrary rating downgrades trigger processes of self-fulfilling prophecies that may drive even relatively healthy countries towards default.     

Prediction of bank financial strength ratings: The case of Turkey

Bank financial strength ratings have gained widespread popularity especially after the recent financial turmoil. Rating agencies were criticized because of their ratings and failure to predict the bankruptcy of the banks. Based on this observation, we investigate whether the forecast of the rating of bank's financial strength using publicly available data is consistent with those of the credit rating agency. We use the data of Turkish banks for this investigation. We take a country-specific approach because previous studies found that proxies used for environmental factors (political, economic, and financial risk of the country) did not have any explanatory power and it is hard to find international data for other important factors such as franchise value, concentration, and efficiency. We use two popular multivariate statistical techniques (multiple discriminant analysis and ordered logistic regression) to estimate a suitable model and we compare their performances with those of two mostly used data mining techniques (Support Vector Machine and Artificial Neural Network). Our results suggest that our predictions are consistent with those of Moody's financial strength rating in general.. The important factors in rating are found to be profitability (measured by return on equity), efficient use of resources, and funding the businesses and the households instead of the government that shows efficient placement of the funds.     

Reporting of Internal Control Weaknesses and Debt Rating Changes

This article examines the effect of corporate reporting of internal control weaknesses on debt rating changes. Bond rating agencies utilize (among other factors) financial statement information to assess a firm’s liquidity and long term solvency as important inputs in determining corporate debt rating. Reporting of internal control weaknesses increases the reliability and transparency risk of the financial statement information, which may lead rating agencies to revise corporate default risk. Our results indicate that reporting of internal control weaknesses is significantly associated with debt ratings after controlling for other firm specific factors. Specifically, these findings suggest that reporting of internal control weaknesses can result in downgrades of the firm’s outstanding debt.     

DID FOREIGN OWNERSHIP OF KOREAN CREDIT RATING AGENCIES IMPROVE THEIR RATINGS?

In this study, we investigate whether foreign equity participation fostered the growth of Korea's credit rating industry during the 2002–2013 period. We find that the rating quality deteriorated steadily even though the foreign ownership of Korea's credit rating agencies increased: Rating levels went up. Our analysis indicates that the Korean government's policy of gradually relaxing the restrictions on foreign ownership of local credit rating agencies was ineffectual. (JEL G24, F21, F65, D43)     

The Impact of the Rating Agencies' Through‐the‐cycle Methodology on Rating Dynamics

Surveys on the use of agency credit ratings reveal that some investors believe that credit‐rating agencies are relatively slow in adjusting their ratings. A well‐accepted explanation for this perception on rating timeliness is the through‐the‐cycle methodology that agencies use. Through‐the‐cycle ratings are intended to measure default risk over long investment horizons and to respond only to changes in the permanent component of credit quality. A second aspect of the through‐the‐cycle methodology is the prudent migration policy. In a benchmark study with a financial ratio‐based credit‐scoring models – an agency‐rating prediction model and default‐prediction models with various time horizons – we confirm the exclusive focus of agencies on the permanent component of credit quality and we model and quantify the agencies' prudent migration policy. A rating migration is triggered only when the rating predicted by the agency‐rating prediction model differs by at least a threshold level of 1.8 notch steps from the actual agency rating. If triggered, ratings are only partly adjusted by 70 per cent at the downside and 60 per cent at the upside. From a 1‐year point‐in‐time perspective, weighting temporary fluctuations in credit quality, the through‐the‐cycle methodology lowers the rating‐migration probability by a factor of 3.5. Both aspects of the through‐the‐cycle methodology contribute equally to this factor. The partial adjustment of ratings lowers the rating‐reversal probabilities on short term and introduces rating drift, the known serial correlation in agency‐rating migrations.