Handbook of Econometrics

Edited by

  • James Heckman, University of Chicago, IL, U.S.A.; University College Dublin, Ireland
  • Edward Leamer, University of California, Los Angeles, CA, USA

As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice behavior and social interactions. All of the essays in this volume and its companion volume 6A offer guidance to the practitioner on how to apply the methods they discuss to interpret economic data. The authors of the chapters are all leading scholars in the fields they survey and extend.Handbook of Econometrics is now available online at ScienceDirect — full-text online from volume 1 onwards.
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Graduates, academics and professionals with an interest in econometrics


Book information

  • Published: December 2007
  • Imprint: NORTH-HOLLAND
  • ISBN: 978-0-444-53200-8

Table of Contents

Preface James J. HeckmanPART 18: Econometric Evaluation of Social Programs Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy EvaluationJames J. Heckman and Edward Vytlacil Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Economic Estimators to Evaluate Social Programs and to Forecast Their Effects in New EnvironmentsJames J. Heckman and Edward Vytlacil Econometric Evaluation of Social Programs Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy EvaluationJaap Abbring and James J. Heckman PART 19: Recent Advances in Econometric MethodsNonparametric IdentificationRosa MatzkinImplementing Nonparametric and Semiparametric EstimatorsHidehiko Ichimura and Petra Todd The Econometrics of Data CombinationRobert Moffitt and Geert Ridder Large Sample Sieve Estimation of Semi-Nonparametric Models Xiaohong ChenLinear Inverse Problems and Structural Econometrics Estimation Based on Spectral Decomposition and RegularizationMarine Carrasco, Jean-Pierre Florens, and Eric Renault