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  • 1
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    Handbook of economics; Volume 6B / (2007)
    Amsterdam [Netherlands] :North Holland,
    Details
    UID:
    almahu_9947367784602882
    Umfang: 1 online resource (1057 p.)
    Ausgabe: 1st ed.
    ISBN: 1-281-11223-2 , 9786611112233 , 0-08-055655-8
    Serie: Handbooks in economics ; v. 2
    Inhalt: 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 ess
    Anmerkung: Description based upon print version of record. , pt. 18. Econometric evaluation of social programs -- pt. 19. Recent advances in econometric methods. , English
    Weitere Ausg.: ISBN 0-444-53200-5
    Sprache: Englisch
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    HU Berlin
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    Charité
  • 2
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    Handbook of econometrics (1983)
    Amsterdam [u.a.] : Elsevier
    Details
    UID:
    b3kat_BV040913852
    Umfang: 1 Online-Ressource
    Serie: Handbooks in economics 2
    Anmerkung: Bd. 1 (1983) bis Bd. 7,A (2020) im Rahmen einer Nationallizenz (ZDB-1-HBE) verfügbar.
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-88766-5
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-86187-0
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-86186-3
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-53200-8
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-50631-3
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-82340-3
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-444-86185-6
    Sprache: Englisch
    Fachgebiete: Wirtschaftswissenschaften , Mathematik
    RVK:
    QH 300
    RVK:
    SK 980
    Schlagwort(e): Ökonometrie ; Aufsatzsammlung
    URL: Volltext
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  • 3
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    Handbook of econometrics : volume 6B (2007)
    Amsterdam : Elsevier/North Holland
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    UID:
    gbv_1655625683
    Umfang: Online Ressource (1 volume)
    ISBN: 9780080556550 , 0080556558 , 0444532005 , 9780444532008
    Serie: Handbooks in economics 2
    Inhalt: 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
    Anmerkung: Includes bibliographical references and indexes. - Print version record , Front cover; Handbook of Econometrics; Copyright page; Introduction to the Series; Contents of the Handbook; Preface to the Handbook; Contents of Volume 6B; Part 18: Econometric Evaluation of Social Programs; Chapter 70. Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation; Chapter 71. Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Ef.
    Weitere Ausg.: ISBN 9780444532008
    Weitere Ausg.: ISBN 0444532005
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe Handbook of econometrics. Volume 6B Amsterdam ; London : Elsevier/North Holland, 2007 ISBN 9780444532008
    Weitere Ausg.: ISBN 0444532005
    Sprache: Englisch
    Schlagwort(e): Electronic books ; Electronic books
    URL: lizenzpflichtig
    URL: Volltext  (Deutschlandweit zugänglich)
    Mehr zum Autor: Heckman, James J. 1944-
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  • 4
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    Handbook of econometrics; Vol. 6B (2007)
    Amsterdam [u.a.] : Elsevier, North Holland
    Dazugehörige Titel
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    UID:
    gbv_556100824
    Umfang: XXVII S., S. 4780 - 5751, S. I-1 - I-52 , graph. Darst., Tab.
    Ausgabe: 1. ed.
    ISBN: 9780444532008
    Serie: Handbooks in economics 2
    Anmerkung: Literaturangaben
    In: Vol. 6B
    Sprache: Englisch
    Schlagwort(e): Handbuch
    Mehr zum Autor: Heckman, James J. 1944-
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  • 5
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    Chapter 74 Implementing Nonparametric and Semiparametric Estimators (2007)
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    UID:
    gbv_1831646676
    ISBN: 9780080556550
    Inhalt: This chapter reviews recent advances in nonparametric and semiparametric estimation, with an emphasis on applicability to empirical research and on resolving issues that arise in implementation. It considers techniques for estimating densities, conditional mean functions, derivatives of functions and conditional quantiles in a flexible way that imposes minimal functional form assumptions. The chapter begins by illustrating how flexible modeling methods have been applied in empirical research, drawing on recent examples of applications from labor economics, consumer demand estimation and treatment effects models. Then, key concepts in semiparametric and nonparametric modeling are introduced that do not have counterparts in parametric modeling, such as the so-called curse of dimensionality, the notion of models with an infinite number of parameters, the criteria used to define optimal convergence rates, and “dimension-free” estimators. After defining these new concepts, a large literature on nonparametric estimation is reviewed and a unifying framework presented for thinking about how different approaches relate to one another. Local polynomial estimators are discussed in detail and their distribution theory is developed. The chapter then shows how nonparametric estimators form the building blocks for many semiparametric estimators, such as estimators for average derivatives, index models, partially linear models, and additively separable models. Semiparametric methods offer a middle ground between fully nonparametric and parametric approaches. Their main advantage is that they typically achieve faster rates of convergence than fully nonparametric approaches. In many cases, they converge at the parametric rate. The second part of the chapter considers in detail two issues that are central with regard to implementing flexible modeling methods: how to select the values of smoothing parameters in an optimal way and how to implement “trimming” procedures. It also reviews newly developed techniques for deriving the distribution theory of semiparametric estimators. The chapter concludes with an overview of approximation methods that speed up the computation of nonparametric estimates and make flexible estimation feasible even in very large size samples.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite 5369-5468, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:5369-5468
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06074-6
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 6
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    Chapter 70 Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation (2007)
    Dazugehörige Titel
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    UID:
    gbv_1831646714
    ISBN: 9780080556550
    Inhalt: This chapter relates the literature on the econometric evaluation of social programs to the literature in statistics on “causal inference”. In it, we develop a general evaluation framework that addresses well-posed economic questions and analyzes agent choice rules and subjective evaluations of outcomes as well as the standard objective evaluations of outcomes. The framework recognizes uncertainty faced by agents and ex ante and ex post evaluations of programs. It also considers distributions of treatment effects. These features are absent from the statistical literature on causal inference. A prototypical model of agent choice and outcomes is used to illustrate the main ideas. We formally develop models for counterfactuals and causality that build on Cowles Commission econometrics. These models anticipate and extend the literature on causal inference in statistics. The distinction between fixing and conditioning that has recently entered the statistical literature was first developed by Cowles economists. Models of simultaneous causality were also developed by the Cowles group, as were notions of invariance to policy interventions. These basic notions are updated to nonlinear and nonparametric frameworks for policy evaluation more general than anything in the current statistical literature on “causal inference”. A formal discussion of identification is presented and applied to clearly formulated choice models used to evaluate social programs.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite 4779-4874, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:4779-4874
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06070-9
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 7
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    Author Index of Volumes 6A and 6B (2007)
    Dazugehörige Titel
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    UID:
    gbv_1831646579
    ISBN: 9780080556550
    Inhalt: This chapter is an index to the names of the authors who have contributed towards this publication Handbook of Econometrics , volume 6A and 6B. The chapter also highlights the page numbers where author's names appear in the text.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite I1-I31, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:I1-I31
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06203-4
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 8
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    Chapter 72 Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation (2007)
    Dazugehörige Titel
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    UID:
    gbv_1831646692
    ISBN: 9780080556550
    Inhalt: This chapter develops three topics. (1) Identification of the distributions of treatment effects and the distributions of agent subjective evaluations of treatment effects. Methods for identifying ex ante and ex post distributions are presented and empirical examples are given. (2) Identification of dynamic treatment effects. The relationship between the statistical literature on dynamic causal inference based on sequential-randomization and the dynamic discrete-choice literature is exposited. The value of well posed economic choice models for decision making under uncertainty in analyzing and interpreting dynamic intervention studies is developed. A survey of the dynamic discrete-choice literature is presented. (3) The key ideas and papers in the recent literature on general equilibrium evaluations of social programs are summarized.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite 5145-5303, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:5145-5303
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06072-2
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 9
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    Chapter 77 Linear Inverse Problems in Structural Econometrics Estimation Based on Spectral Decomposition and Regularization (2007)
    Dazugehörige Titel
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    UID:
    gbv_1831646641
    ISBN: 9780080556550
    Inhalt: Inverse problems can be described as functional equations where the value of the function is known or easily estimable but the argument is unknown. Many problems in econometrics can be stated in the form of inverse problems where the argument itself is a function. For example, consider a nonlinear regression where the functional form is the object of interest. One can readily estimate the conditional expectation of the dependent variable given a vector of instruments. From this estimate, one would like to recover the unknown functional form. This chapter provides an introduction to the estimation of the solution to inverse problems. It focuses mainly on integral equations of the first kind. Solving these equations is particularly challenging as the solution does not necessarily exist, may not be unique, and is not continuous. As a result, a regularized (or smoothed) solution needs to be implemented. We review different regularization methods and study the properties of the estimator. Integral equations of the first kind appear, for example, in the generalized method of moments when the number of moment conditions is infinite, and in the nonparametric estimation of instrumental variable regressions. In the last section of this chapter, we investigate integral equations of the second kind, whose solutions may not be unique but are continuous. Such equations arise when additive models and measurement error models are estimated nonparametrically.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite 5633-5751, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:5633-5751
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06077-1
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 10
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    Chapter 76 Large Sample Sieve Estimation of Semi-Nonparametric Models (2007)
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    UID:
    gbv_183164665X
    ISBN: 9780080556550
    Inhalt: Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite-dimensional parameter spaces that may not be compact and the optimization problem may no longer be well-posed. The method of sieves provides one way to tackle such difficulties by optimizing an empirical criterion over a sequence of approximating parameter spaces (i.e., sieves); the sieves are less complex but are dense in the original space and the resulting optimization problem becomes well-posed. With different choices of criteria and sieves, the method of sieves is very flexible in estimating complicated semi-nonparametric models with (or without) endogeneity and latent heterogeneity. It can easily incorporate prior information and constraints, often derived from economic theory, such as monotonicity, convexity, additivity, multiplicity, exclusion and nonnegativity. It can simultaneously estimate the parametric and nonparametric parts in semi-nonparametric models, typically with optimal convergence rates for both parts. This chapter describes estimation of semi-nonparametric econometric models via the method of sieves. We present some general results on the large sample properties of the sieve estimates, including consistency of the sieve extremum estimates, convergence rates of the sieve M-estimates, pointwise normality of series estimates of regression functions, root- n asymptotic normality and efficiency of sieve estimates of smooth functionals of infinite-dimensional parameters. Examples are used to illustrate the general results.
    In: Handbook of econometrics, Amsterdam : Elsevier/North Holland, 2007, (2007), Seite 5549-5632, 9780080556550
    In: 0080556558
    In: 0444532005
    In: 9780444532008
    In: year:2007
    In: pages:5549-5632
    Sprache: Englisch
    DOI: 10.1016/S1573-4412(07)06076-X
    URL: Volltext  (Deutschlandweit zugänglich)
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