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|Title:||A guide to modern econometrics.||Authors:||Marno Verbeek.||Keywords:||1. Econometrics 2. Regression analysis.||Issue Date:||2017||Publisher:||John Wiley & Sons||Abstract:||The field of econometrics has developed rapidly in the last three decades, while the use of up-to-date econometric techniques has become more and more standard practice in empirical work in many fields of economics. Typical topics include unit root tests, cointegration, estimation by the generalized method of moments, heteroskedasticity and autocorrelation consistent standard errors, modelling conditional heteroskedasticity, causal inference and the estimation of treatment effects, models based on panel data, models with limited dependent variables, endogenous regressors and sample selection. At the same time econometrics software has become more and more user friendly and up-to-date. As a consequence, users are able to implement fairly advanced techniques even without a basic understanding of the underlying theory and without realizing potential drawbacks or dangers. In contrast, many introductory econometrics textbooks pay a disproportionate amount of attention to the standard linear regression model under the strongest set of assumptions. Needless to say that these assumptions are hardly satisfied in practice (but not really needed either). On the other hand, the more advanced econometrics textbooks are often too technical or too detailed for the average economist to grasp the essential ideas and to extract the information that is needed. This book tries to fill this gap. The goal of this book is to familiarize the reader with a wide range of topics in modern econometrics, focusing on what is important for doing and understanding empirical work. This means that the text is a guide to (rather than an overview of) alternative techniques. Consequently, it does not concentrate on the formulae behind each technique (although the necessary ones are given) nor on formal proofs, but on the intuition behind the approaches and their practical relevance. The book covers a wide range of topics that is usually not found in textbooks at this level. In particular, attention is paid to cointegration, the generalized method of moments, models with limited dependent variables and panel data models. As a result, the book discusses developments in time series analysis, cross-sectional methods as well as panel data modelling. More than 25 full-scale empirical illustrations are provided in separate sections and subsections, taken from fields like labour economics, finance, international economics, consumer behaviour, environmental economics and macro-economics. These illustrations carefully discuss and interpret econometric analyses of relevant economic problems, and each of them covers between two and nine pages of the text. As before, data sets are available through the supporting website of this book. In addition, a number of exercises are of an empirical nature and require the use of actual data. This fifth edition builds upon the success of its predecessors. The text has been carefully checked and updated, taking into account recent developments and insights. It includes new material on causal inference, the use and limitations of p-values, instrumental variables estimation and its implementation, regression discontinuity design, standardized coefficients, and the presentation of estimation results. Several empirical illustrations are new or updated. For example, Section 5.7 is added containing a new illustration on the causal effect of institutions on economic development, to illustrate the use of instrumental variables. Overall, the presentation is meant to be concise and intuitive, providing references to primary sources wherever possible. Where relevant, I pay particular attention to implementation concerns, for example, relating to identification issues. A large number of new references has been added in this edition to reflect the changes in the text. Increasingly, the literature provides critical surveys and practical guides on how more advanced econometric techniques, like robust standard errors, sample selection models or causal inference methods, are used in specific areas, and I have tried to refer to them in the text too. This text originates from lecture notes used for courses in Applied Econometrics in the M.Sc. programmes in Economics at K. U. Leuven and Tilburg University. It is written for an intended audience of economists and economics students that would like to become familiar with up-to-date econometric approaches and techniques, important for doing, understanding and evaluating empirical work. It is very well suited for courses in applied econometrics at the master’s or graduate level. At some schools this book will be suited for one or more courses at the undergraduate level, provided students have a sufficient background in statistics. Some of the later chapters can be used in more advanced courses covering particular topics, for example, panel data, limited dependent variable models or time series analysis. In addition, this book can serve as a guide for managers, research economists and practitioners who want to update their insufficient or outdated knowledge of econometrics. Throughout, the use of matrix algebra is limited. I am very much indebted to Arie Kapteyn, Bertrand Melenberg, Theo Nijman and Arthur van Soest, who all have contributed to my understanding of econometrics and have shaped my way of thinking about many issues. The fact that some of their ideas have materialized in this text is a tribute to their efforts. I also owe many thanks to several generations of students who helped me to shape this text into its current form. I am very grateful to a large number of people who read through parts of the manuscript and provided me with comments and suggestions on the basis of the first three editions. In particular, I wish to thank Niklas Ahlgren, Sascha Becker, Peter Boswijk, Bart Capéau, Geert Dhaene, Tom Doan, Peter de Goeij, Joop Huij, Ben Jacobsen, Jan Kiviet, Wim Koevoets, Erik Kole, Marco Lyrio, Konstantijn Maes,Wessel Marquering, Bertrand Melenberg, Paulo Nunes, Anatoly Peresetsky, Francesco Ravazzolo, Regina Riphahn, Max van de Sande Bakhuyzen, Erik Schokkaert, Peter Sephton, Arthur van Soest, Ben Tims, Frederic Vermeulen, Patrick Verwijmeren, Guglielmo Weber, Olivier Wolthoorn, Kuo-chun Yeh and a number of anonymous reviewers. Of course I retain sole responsibility for any remaining errors. Special thanks go to Jean-Francois Flechet for his help with many empirical illustrations and his constructive comments on many early drafts. Finally, I want to thank my wife Marcella and our three children, Timo, Thalia and Tamara, for their patience and understanding for all the times that my mind was with this book when it should have been with them.||URI:||http://dspace.uniten.edu.my/jspui/handle/123456789/15354|
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