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Monte Carlo studies have shown that estimated asymptotic standard errors of the efficient two-step generalised method of moments (GMM) estimator can be severely downward biased in small samples. The weight matrix used in the calculation of the efficient two-step GMM estimator is based on initial consistent parameter estimates. In this paper it is shown that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the asymptotic variance of the two-step GMM estimator that utilises moment conditions that are linear in the parameters. This difference can be estimated, resulting in a finite sample corrected estimate of the variance. In a Monte Carlo study of a panel data model it is shown that the corrected variance estimate approximates the finite sample variance well, leading to more accurate inference.
Monte Carlo studies have shown that estimated asymptotic standard errors of the efficient two-step generalised method of moments (GMM) estimator can be severely downward biased in small samples. The weight matrix used in the calculation of the efficient two-step GMM estimator is based on initial consistent parameter estimates. In this paper it is shown that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the usual asymptotic variance of the two-step GMM estimator, when the moment conditions used are linear in the parameters. This difference can be estimated, resulting in a finite sample corrected estimate of the variance. In a Monte Carlo study of a panel data model it is shown that the corrected variance estimate approximates the finite sample variance well, leading to more accurate inference.
We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a finite sample corrected estimate of the variance of the two-step GMM estimator; the LM test; and three criterion-based tests that have recently been proposed. We consider both the AR(1) panel model, and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases.
The paper investigates the non-performing loans (NPLs) in Central, Eastern and South-Eastern Europe (CESEE) in the period of 1998–2011. The paper finds that the level of NPLs can be attributed to both macroeconomic conditions and banks’ specific factors, though the latter set of factors was found to have a relatively low explanatory power. The examination of the feedback effects broadly confirms the strong macro-financial linkages in the region. While NPLs were found to respond to macroeconomic conditions, such as GDP growth, unemployment, and inflation, the analysis also indicates that there are strong feedback effects from the banking system to the real economy, thus suggesting that the high NPLs that many CESEE countries currently face adversely affect the pace economic recovery.
This volume covers the latest results on novel methods in Risk Analysis and assessment, with applications in Biostatistics (which is providing food for thought since the first ICRAs, covering traditional areas of RA, until now), Engineering Reliability, the Environmental Sciences and Economics. The contributions, based on lectures given at the 9th International Conference on Risk Analysis (ICRA 9), at Perugia, Italy, May 2022, detail a wide variety of daily risks, building on ideas presented at previous ICRA conferences. Working within a strong theoretical framework, supporting applications, the material describes a modern extension of the traditional research of the 1980s. This book is intended for graduate students in Mathematics, Statistics, Biology, Toxicology, Medicine, Management, and Economics, as well as quantitative researchers in Risk Analysis.
Focusing on Low-Income Countries, we investigate the behavior of fiscal variables during and after elections. The results indicate that during election years, government consumption significantly increases and leads to higher fiscal deficits. During the two years following elections, the fiscal adjustment takes the form of increased revenue mobilization in trade taxes and cuts to government investment, with no significant cuts in government consumption. Using a new dataset on national fiscal rules and IMF programs, we find that both the presence of fiscal rules and IMF programs help dampen the magnitude of the political budget cycle in LICs. We conclude that elections not only imply a macroeconomic cost when they take place but also trigger a painful fiscal adjustment in which public investment is largely sacrificed.
The year-long consultations on Basel II mirror the international popularity of capital requirements as a regulatory instrument. Yet, the impact of capital re quirements on banks' behavior is not fully understood. The aim of this study is to contribute to this understanding by answering the following questions: How do banks adjust capital and risk after an increase in capital requirements? How do banks adjust their regulatory capital buffer over the business cycle? And what is the impact of banks' charter value on the regulatory capital buffer? The research undertaken for this study has benefited from support in terms of ideas, research facilities, and, not least, financial funding. My thanks go first of all to Claudia M. Buch for her constant encouragement, her continuous guidance, and her confidence in my research ideas. My thanks go also to the Kiel Institute for World Economics and its staff for providing a very fertile academic ground for my research and for providing excellent research facilities. In fact, conduct ing this study would not have been possible without the support of my colleagues at the Kiel Institute and elsewhere. In particular, I am grateful to Horst Siebert for providing me the freedom to pursue this topic. My special thanks go to Jorg Breitung, Kai Carstensen, and Dieter Urban for providing input on econometric issues. I am also grateful to Andrea Schertler for the long and productive discus sions I had on various parts of this study.
This timely Handbook comprehensively explores the complex relationships between trade and economic performance in developing countries, illustrating that it is not trade per se that is important but the context, at the firm, country and regional level, in which trade occurs.