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Nonparametric and Semiparametric Methods in Econometrics and Statistics : Proceedings of the Fifth International Symposium in Economic Theory and Econometrics - William A. Barnett

Nonparametric and Semiparametric Methods in Econometrics and Statistics

Proceedings of the Fifth International Symposium in Economic Theory and Econometrics

By: William A. Barnett (Editor), James Powell (Editor), George E. Tauchen (Editor)

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Published: 11th September 2014
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This collection of papers delivered at the fifth international Symposium in Economic Theory and Econometrics in 1988 is devoted to recent advances in the estimation and testing of models that impose relatively weak restrictions on the stochastic behavior of data. Particularly in highly nonlinear models, empirical results are very sensitive to the choice of the parametric form of the distribution of the observable variables, and often nonparametric and semiparametric models are a preferable alternative. Methods and applications that do not require strong parametric assumptions for their validity, that are based on kernels and on series expansions, and methods for independent and dependent observations, are investigated and developed in these essays by renowned econometricians.

"Nonparametric and Semiparametric Methods in Econometrics and Statistics gives a fairly thorough picture of recent advances in nonparametric and semiparametric analysis. It provides insight on recently solved problems in this area and also points towards some of the yet-unresolved issues." Journal of the American Statistical Association

Editors+ preface
Methods and Applications Based on Kernels
Semiparametric last squares estimation of multiple index models: single equation estimation
Nonparametric estimation and the risk premium
Nonparametric policy analysis: an application to estimating hazardous waste cleanup benefits
Equivalence of direct, indirect, and slope estimators of average derivatives
Equivalence of direct, indirect, and slope estimators of average derivatives: a comment
Methods and Applications Based on Series Expansions
Seminonparametric Bayesian estimation of the asymptotically ideal model: the AIM consumer demand system
Semiparametric estimation of a regression model with sampling selectivity
On fitting a recalcitrant series: the pound/dollar exchange rate, 1974+1984
Methods For Independent Observations
A nonparametric method-of-moments estimator for the mixture-of-exponentials model and the mixture-of-geometrics model
Nonparametric estimation of expectations in the analysis of discrete under uncertainty
A nonparametric maximum rank correlation estimator
Efficient estimation of Tobit models under conditional symmetry
Bracketing methods in statistics and econometrics
Estimation of monotonic regression models under quantile restrictions
Models For Dependent Observations
Computing semiparametric efficiency bounds for linear time series models Lars
Spectral regression for cointegrated time series
Nonparametric function estimation for long memory time series
Some results on sieve estimation with dependent observations
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780521370905
ISBN-10: 0521370906
Series: Cambridge Music Handbooks
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 508
Published: 11th September 2014
Publisher: CAMBRIDGE UNIV PR
Country of Publication: GB
Dimensions (cm): 23.37 x 14.99  x 2.79
Weight (kg): 0.77