| Document Type
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BL
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| Record Number
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655777
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| Doc. No
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dltt
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| Main Entry
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Horowitz, Joel
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| Title & Author
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Semiparametric and nonparametric methods in econometrics\ Joel L. Horowitz
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| Publication Statement
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New York :: Springer,, c2009
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| Series Statement
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Springer series in statistics
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| Page. NO
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1 online resource (x, 271 p.) :: ill
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| ISBN
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9780387928708
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: 0387928707
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9780387928692
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0387928693
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| Bibliographies/Indexes
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Includes bibliographical references and index
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| Contents
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Preface; Contents; 1 Introduction; 2 Single-Index Models; 3 Nonparametric Additive Models and Semiparametric Partially Linear Models; 4 Binary-Response Models; 5 Statistical Inverse Problems; 6 Transformation Models; Appendix: Nonparametric Density Estimationand Nonparametric Regression; References; Index
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| Abstract
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Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally distributed. Such assumptions simplify estimation and statistical inference but are rarely justified by economic theory or other a priori considerations. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparam
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| Subject
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Econometrics
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| Subject
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Estimation theory
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| LC Classification
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HB139.H645 2009
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