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Nonparametric and Semiparametric Methods in Econometrics and Statistics

Nonparametric and Semiparametric Methods in Econometrics and Statistics
Proceedings of the Fifth International Symposium in Economic Theory and Econometrics

$58.00 (P)

Part of International Symposia in Economic Theory and Econometrics

Hidehiko Ichimura, Lung-Fei Lee, A. R. Pagan, Y. S. Hong, James H. Stock, Thomas M. Stoker, T. Scott Thompson, William A. Barrett, John Geweke, Piyu Yue, Stephen R. Cosslett, A. Ronald Gallant, David A. Hsieh, George E. Taucher, James J. Heckman, Charles F. Manski, Rosa L. Matzkin, Whitney K. Newey, David Pollard, James L. Powell, Lars Peter Hansen, Kenneth J. Singleton, P. C. B. Phillips, Peter M. Robinson, Halbert White, Jeffrey M. Wooldridge
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  • Date Published: June 1991
  • availability: Available
  • format: Paperback
  • isbn: 9780521424318

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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.

    Reviews & endorsements

    "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

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    Product details

    • Date Published: June 1991
    • format: Paperback
    • isbn: 9780521424318
    • length: 508 pages
    • dimensions: 229 x 152 x 29 mm
    • weight: 0.74kg
    • availability: Available
  • Table of Contents

    Editors' preface
    Part I. Methods and Applications Based on Kernels:
    1. Semiparametric last squares estimation of multiple index models: single equation estimation Hidehiko Ichimura and Lung-Fei Lee
    2. Nonparametric estimation and the risk premium A. R. Pagan and Y. S. Hong
    3. Nonparametric policy analysis: an application to estimating hazardous waste cleanup benefits James H. Stock
    4. Equivalence of direct, indirect, and slope estimators of average derivatives Thomas M. Stoker
    5. Equivalence of direct, indirect, and slope estimators of average derivatives: a comment T. Scott Thompson
    Part II. Methods and Applications Based on Series Expansions:
    6. Seminonparametric Bayesian estimation of the asymptotically ideal model: the AIM consumer demand system William A. Barrett, John Geweke, and Piyu Yue
    7. Semiparametric estimation of a regression model with sampling selectivity Stephen R. Cosslett
    8. On fitting a recalcitrant series: the pound/dollar exchange rate, 1974–84 A. Ronald Gallant, David A. Hsieh and George E. Taucher
    Part III. Methods for Independent Observations:
    9. A nonparametric method-of-moments estimator for the mixture-of-exponentials model and the mixture-of-geometrics model James J. Heckman
    10. Nonparametric estimation of expectations in the analysis of discrete under uncertainty Charles F. Manski
    11. A nonparametric maximum rank correlation estimator Rosa L. Matzkin
    12. Efficient estimation of Tobit models under conditional symmetry Whitney K. Newey
    13. Bracketing methods in statistics and econometrics David Pollard
    14. Estimation of monotonic regression models under quantile restrictions James L. Powell
    Part IV. Models for Dependent Observations:
    15. Computing semiparametric efficiency bounds for linear time series models Lars Peter Hansen and Kenneth J. Singleton
    16. Spectral regression for cointegrated time series P. C. B. Phillips
    17. Nonparametric function estimation for long memory time series Peter M. Robinson
    18. Some results on sieve estimation with dependent observations Halbert White and Jeffrey M. Wooldridge.

  • Editors

    William A. Barnett

    James Powell

    George E. Tauchen

    Contributors

    Hidehiko Ichimura, Lung-Fei Lee, A. R. Pagan, Y. S. Hong, James H. Stock, Thomas M. Stoker, T. Scott Thompson, William A. Barrett, John Geweke, Piyu Yue, Stephen R. Cosslett, A. Ronald Gallant, David A. Hsieh, George E. Taucher, James J. Heckman, Charles F. Manski, Rosa L. Matzkin, Whitney K. Newey, David Pollard, James L. Powell, Lars Peter Hansen, Kenneth J. Singleton, P. C. B. Phillips, Peter M. Robinson, Halbert White, Jeffrey M. Wooldridge

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