Daniel Kaufmann

Aart Kraay

Pablo Zoido-Lobatón

Updated governance indicators report estimates of six dimensions of governance for 175 countries in 2000-01. They can be compared with those constructed for 1997-98.

Updated Indicators for 2000-01

Governance Matters II

Governance matters VI : aggregate and individual governance indicators, 1996-2006

Introduction: In the first section, ways of modelling single name credit risks are introduced, in order to give an idea of how equity prices drive possible bond defaults, but more importantly introduce the models that are currently used in practice. Particular emphasis will be placed on Merton ́s model as a means of calculating default probability as it presents the basic idea of deriving the chance of default. Additionally it is the theoretical basis of commercial models like Moody ́s KMV and Credit Metrics. Merton ́s model will be described in detail in the following sections, also addressing the assumption of the Black and Scholes formula, as well as the estimation of the asset value of the firm using observable equity values. The importance of the structural models is that they impose some kind of threshold that has to be passed by the value of the assets of a firm in order for the bond to default. Threshold models are a more general way of implementing structural models and will be discussed in the section thereafter. In the following sections, some basic mathematical properties of copulae will be de- scribed especially paying attention to the way that by defining dependence through copulae one is able to separate the marginal distributions from the joint distribution. The reason for this emphasis is that by doing so desired effects like tail dependence can be implemented in the multivariate model, without having to change the marginal or single name distributions. Moody ́s KMV ́s CreditMetrics which is an industry standard, implicitly uses a Gauß copula in order to model the joint probability of default. Since tail risk is not captured by Gauß copulae, the use of another copula to model the joint default risk will be analysed and compared. As mentioned, the Student-t copula seems to be of special interest here, since although not requiring further dependence measures than the widely used Pearson ́s measure of correlation and a degree of freedom (DoF), it is able to model the tail risk and thus, assign a higher probability to multiple defaults, as it has been shown to be the case in the financial crisis. It remains to be seen if the models that measure tail risk are models that will only perform well in times of crisis. The Gauß copula has without question performed well in economically calm times. So that it may be of interest if and when models such as the Student-t copula will yield the best fit to data. [...]

The Modelling of Risk of Portfolios with Copulae

Scholars, policymakers, aid donors, and aid recipients acknowledge the importance of good governance for development. This understanding has spurred an intense interest in more refined, nuanced, and policy-relevant indicators of governance. In this paper we review progress to date in the area of measuring governance, using a simple framework of analysis focusing on two key questions: (i) what do we measure? and, (ii) whose views do we rely on? For the former question, we distinguish between indicators measuring formal laws or rules 'on the books', and indicators that measure the practical application or outcomes of these rules 'on the ground', calling attention to the strengths and weaknesses of both types of indicators as well as the complementarities between them. For the latter question, we distinguish between experts and survey respondents on whose views governance assessments are based, again highlighting their advantages, disadvantages, and complementarities. We also review the merits of aggregate as opposed to individual governance indicators. We conclude with some simple principles to guide the refinement of existing governance indicators and the development of future indicators. We emphasize the need to: transparently disclose and account for the margins of error in all indicators; draw from a diversity of indicators and exploit complementarities among them; submit all indicators to rigorous public and academic scrutiny; and, in light of the lessons of over a decade of existing indicators, to be realistic in the expectations of future indicators.

Governance Indicators:where are We, where Should We be Going?

Jonathan Isham

The Productivity of Investment Projects

The Forgotten Rationale for Policy Reform

Massimo Mastruzzi

Abstract: The authors report on the latest version of the worldwide governance indicators, covering 213 countries and territories and measuring six dimensions of governance from 1996 until end-2005: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. The latest indicators are based on hundreds of variables and reflect the views of thousands of citizen and firm survey respondents and experts worldwide. Although global averages of governance display no marked trends during 1996-2005, nearly one-third of countries exhibit significant changes [for better or for worse] on at least one dimension of governance. Three new features distinguish this update. (1) The authors have moved to annual reporting of governance estimates. This update includes new governance estimates for 2003 and 2005, as well as minor backward revisions to biannual historical data for 1996-2004. (2) The authors are, for the first time, publishing the individual measures of governance from virtually every data source underlying the aggregate governance indicators. The ready availability of the individual data sources underlying the aggregate governance indicators is aimed at further enhancing the transparency of the methodology and of the resulting aggregate indicators, as well as helping data users and policymakers identify specific governance challenges in individual countries. (3) The authors present new evidence on the reliability of expert assessments of governance which, alongside survey responses, form part of the aggregate measures of governance.

Daniel Kaufmann

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