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Semiparametric Regression for the Applied Econometrician
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  • 30 b/w illus. 22 tables
  • Page extent: 236 pages
  • Size: 228 x 152 mm
  • Weight: 0.35 kg
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 (ISBN-13: 9780521012263 | ISBN-10: 0521012260)

DOI: 10.2277/0521012260

Manufactured on demand: supplied direct from the printer

 (Stock level updated: 02:09 GMT, 28 November 2015)


This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price density estimation. The book should be of interest to a broad range of economists including those working in industrial organization, labor, development, urban, energy and financial economics. A variety of testing procedures are covered including simple goodness of fit tests and residual regression tests. These procedures can be used to test hypotheses such as parametric and semiparametric specifications, significance, monotonicity and additive separability. Other topics include endogeneity of parametric and nonparametric effects, as well as heteroskedasticity and autocorrelation in the residuals. Bootstrap procedures are provided.

• Offers practical nonparametric and semiparametric techniques for applied practitioners, filling a real gap in this advanced literature • Numerous empirical examples provided • Data and code (in S-Plus) will also appeal to practitioners


List of figures and tables; Preface; 1. Introduction to differencing; 2. Background and overview; 3. Introduction to smoothing; 4. Higher-order differencing procedures; 5. Nonparametric functions of several variables; 6. Constrained estimation and hypothesis testing; 7. Index models and other semiparametric specifications; 8. Bootstrap procedures; Appendixes; References; Index.

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