Laszlo Matyas – författare

The generalized method of moments (GMM) estimation has emerged 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 is to offer a complete 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. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.

The generalized method of moments (GMM) estimation has emerged 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 is to offer a complete 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. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.

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 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.

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.

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.

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 furtherand 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 book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. The first, theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models,networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies.

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. The first, theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models,networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies.

This book takes stock of and analyses the direct and indirect effects of the war in Ukraine, the policy response to the shock across countries, as well as the potential medium-term economic and social implications and policy challenges.

This volume honors the life and legacy of renowned economist and econometrician Marc Nerlove, who passed away in July 2024.

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. The last two decades or so, the use of panel data has become a standard in many areas of economic analysis.

Indeed, our ability to estimate and test nonlinear models have dramatically improved and issues such as the unobserved heterogeneity in nonlinear models, attrition and selectivity bias have received considerable attention.

Indeed, our ability to estimate and test nonlinear models have dramatically improved and issues such as the unobserved heterogeneity in nonlinear models, attrition and selectivity bias have received considerable attention.

Part II deals with nonlinear models and related issues: logit and pro bit models, latent variable models, duration and count data models, incomplete panels and selectivity bias, point processes, and simulation techniques.