If treated as a single economy, the European Union is the largest in the world, with an estimated GDP of over 14 trillion euros. Despite its size, European economic policy has often lagged behind the rest of the world in its ability to generate growth and innovation. Much of the European economic research itself often trails behind that of the USA, which sets much of the agenda in mainstream economics. This book, also available as open access, bridges the gap between economic research and policymaking by presenting overviews of twelve key areas for future economic policy and research. Written for the economists and policymakers working within European institutions, it uses comprehensive surveys by Europe's leading scholars in economics and European policy to demonstrate how economic research can contribute to good policy decisions, and vice versa, demonstrating how economics research can be motivated and made relevant by hot policy questions. This title is available as Open Access on Cambridge Core.

If treated as a single economy, the European Union is the largest in the world, with an estimated GDP of over 14 trillion euros. Despite its size, European economic policy has often lagged behind the rest of the world in its ability to generate growth and innovation. Much of the European economic research itself often trails behind that of the USA, which sets much of the agenda in mainstream economics. This book, also available as open access, bridges the gap between economic research and policymaking by presenting overviews of twelve key areas for future economic policy and research. Written for the economists and policymakers working within European institutions, it uses comprehensive surveys by Europe's leading scholars in economics and European policy to demonstrate how economic research can contribute to good policy decisions, and vice versa, demonstrating how economics research can be motivated and made relevant by hot policy questions. This title is available as Open Access on Cambridge Core.

This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.

This completely revised and enhanced second edition of the volume first published in 1992 provides a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Much work has been done over the last three decades: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific difficulties associated with the use of panel data are also explored, such as attrition, heterogeneity, selectivity bias, pseudo-panels etc. The second, enhanced edition provides a complete and up to date presentation of these theoretical developments. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and probit models, latent variable models, incomplete panels and selectivity bias, point processes, etc. Nine additional chapters about instrumental variables and generalized method of moments estimators, duration models, count data models, simulation methods, etc. have been included. This volume also provides insights into the use of panel data in empirical studies. Part III deals with surveys in several major fields of applied economics, such as labour and investment demand, labour supply, consumption, transitions on the labour market, and finance. Two new chapters about foreign investment and production frontiers have been included. Audience: The double emphasis of the book (theoretical and applied), together with the fact that all the chapters have been written by well-known specialists in the field, means that it will become a standard reference for all those concerned with the use of panel data in econometrics: advanced students, professional economists or researchers.

This volume provides a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross-section and time-series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific difficulties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc. have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and probit models, latent variable models, incomplete panels and selectivity bias, and point processes. The second objective is to provide insights into the use of panel data in empirical studies. Since the beginning, interest in panel data has been empirically based, and over time has become increasingly important in applied economic studies. This is demonstrated by growing numbers of conferences and special issues of economic journals devoted to the subject. Part III deals with studies in several major fields of applied economics, such as labour and investment demand, labour supply, consumption, transitions on the labour market, and finance. The double emphasis of this book (theoretical and applied), together with the fact that all the chapters have been written by well-known specialists in the field, ensure that it will become a standard textbook for all those who are concerned with the use of panel data in econometrics, whether they are advanced students, professional economists or researchers.

This completely restructured, updated third edition of the volume first published in 1992 provides a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone.

Much work has been done over the last four decades: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models, the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific difficulties associated with the use of panel data are also explored, such as attrition, heterogeneity, selectivity bias, pseudo-panels etc. Recently, much work has been done about unit roots and co integration using panel data. Some other fields have also experienced a strong development such as the econometrics of policy evaluation and the analysis of qualitative and truncated dependent variable models, among others, which all are also discussed.

The third, enhanced edition provides a complete and up to date presentation of these theoretical developments as well as surveys about how these econometric tools are used to study firms and household s behaviors and/or more macroeconomic phenomena such as economic growth. It contains sixteen entirely new chapters while the others have been largely revised to account for recent developments in the field.

Part I is concerned with the fundamentals of panel data econometrics, both linear and non linear; Part II deals with more advanced topics such as dynamic models, simultaneity and measurement errors, unit roots and co integration, incomplete panels and selectivity, duration and count models, etc. This volume also provides insights into the use of panel data in empirical studies. Part III deals with surveys in several major fields of applied economics, such as investment demand, foreign direct investment and international trade, production efficiency, labour supply, transitions on the labour market, etc. Six new chapters about R&D and innovation, wages, health economics, policy evaluation, growth empirics and the impact of monetary policy have been included.

The generalized method of moments (GMM) estimation has emerged over the past decade as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume, the first devoted entirely to the GMM methodology, is to offer a complete and up to date presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia.

This book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric and machine learning techniques? 2) To what extent can machine learning techniques assist econometric investigation? Specifically, how robust or stable is the prediction from machine learning algorithms given the ever-changing nature of human behavior? 3) Can machine learning techniques assist in testing statistical hypotheses and identifying causal relationships in 'big data? 4) How can existing econometric techniques be extended by incorporating machine learning concepts? 5) How can new econometric tools and approaches be elaborated on based on machine learning techniques? 6) Is it possible to develop machine learning techniques further and make them even more readily applicable in econometrics? As the data structures in economic and financial data become more complex and models become more sophisticated, the book takes a multidisciplinary approach in developing both disciplines of machine learning and econometrics in conjunction, rather than in isolation. This volume is a must-read for scholars, researchers, students, policy-makers, and practitioners, who are using econometrics in theory or in practice.

This edited volume examines the development path of eight Central and Eastern European countries with an overlapping historical background that joined the European Union between 2004 and 2013, and identifies the main similarities and differences between the countries concerned. Based on wide comparative data analysis of Bulgaria, Croatia, The Czech Republic, Hungary, Poland, Romania, Slovakia, and Slovenia, each chapter in the volume provides detailed information about the state of the economy in a specific area preceding the pandemic shock. The book offers a detailed snapshot of the state of the different areas of the economy, starting from the time when the countries concerned came out of the 2008 financial crisis, up to the date when COVID-19 hit. Further, each chapter analyzes the effects of this unprecedented shock on a particular field, which is followed by highlighting the main problems the countries are facing at present and in the near future, together with identifying the available policy options. Finally, before concluding and making general and country-specific policy recommendations, some thoughts will be given to longer-term prospects. More specifically, the question of how the subject area could contribute to avoiding the "middle-income-trap" that this region may be facing will be addressed. The comprehensive approach makes this volume a must-read for scholars and students of economics, as well as policy decision-makers in Europe, interested in a better understanding of the region's economic development.

The generalized method of moments (GMM) estimation has emerged over the past decade as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume, the first devoted entirely to the GMM methodology, is to offer a complete and up to date presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia.