Skip to main content
SpringerLink
Log in

Some GMM Estimation Methods and Specification Tests for Nonlinear Models

  • Chapter
The Econometrics of Panel Data

Part of the book series: Advanced Studies in Theoretical and Applied Econometrics ((ASTA,volume 33))

Abstract

In this chapter we investigate the asymptotic and some small sample properties of various estimators and test procedures for nonlinear models using panel data with a large number of individual units and a moderate number of time periods.1 For these models, in may cases, full information maximum likelihood (FIML) estimation either involves tight restrictions on the multivariate distribution of the error terms, or requires high dimensional numerical integration over probability density functions which are for many distributions infeasible when T is larger than four. Although, some progress has been made recently in approximating these integrals by simulation methods (see Hajivassiliou [1993], Keane [1994] and Chapter 23), these procedures are still computationally quite burdensome.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Avery, R., Hansen, L. and Hotz, V. [1983]: Multiperiod Probit Models and Orthogonality Condition Estimation, International Economic Review,24, 21–35.

    Article  Google Scholar 

  • Bertschek, I. and Lechner, M. [1995]: GMM-Estimation of Panel Probit Models: Nonparametric Estimation of the Optimal Instruments, SFB 373 Discussion Paper No. 25, Humboldt University Berlin.

    Google Scholar 

  • Bekker, P.A. [1994]: Alternative Approximations to the Distribution of Instrumental Variable Estimators, Econometrica, 62, 657–682.

    Article  Google Scholar 

  • Breitung, J. and Lechner, M. [1994]: GMM-Estimation of Nonlinear Models on Panel Data, Beitr age zur Angewandten Wirtschaftsforschung, University of Mannheim,500.

    Google Scholar 

  • Butler, I.S. and Moffit, R. [1982]: A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model, Econometrica,50, 761–764.

    Article  Google Scholar 

  • Chamberlain, G. [1980]: Analysis of Covariance with Qualitative Data, Review of Economic Studies,47, 225–238.

    Article  Google Scholar 

  • Chamberlain, G. [1984]: Panel Data, in Griliches, Z. and Intriligator, M.D. (eds.), Handbook of Econometrics,Vol. II, Ch. 22, Amsterdam: North-Holland.

    Google Scholar 

  • Chamberlain, G. [1987]: Asymptotic Efficiency in Estimation with Conditional Moment Restrictions, Journal of Econometrics,34, 305–334.

    Article  Google Scholar 

  • Chamberlain, G. [1992]: Comment: Sequential Moment Restrictions in Panel Data, Journal of Business and Economic Statistics,10, 20–26.

    Article  Google Scholar 

  • Davidson, R. and MacKinnon, J.G. [1984]: Convenient Specification Tests for Logit and Probit-Models, Journal of Econometrics,25, 241–262.

    Article  Google Scholar 

  • Davidson, R. and MacKinnon, J.G. [1993]: Estimation and Inference in Econometrics, Oxford: Oxford University Press.

    Google Scholar 

  • Gabler, S., Laisney, F. and Lechner, M. [1993]: Seminonparametric Estimation of Binary-Choice Models With an Application to Labor Force Participation, Journal of Business and Economic Statistics,11, 61–80.

    Article  Google Scholar 

  • Gallant, A.R. and Nychka, D.N. [1987]: Semi-Nonparametric Maximum Likelihood Estimation, Econometrica, 55, 363–390.

    Article  Google Scholar 

  • Gourieroux, C., and Monfort, A. [1989]: Statistique et Modeles Econometrique, Paris: Economica.

    Google Scholar 

  • Gourieroux, C., Monfort, A., Renault, E. and Trognon, A. [1987]: Generalised Residuals, Journal of Econometrics,34, 5–32.

    Article  Google Scholar 

  • Guilkey, D.K. and Murphy, J.L. [1993]: Estimation and Testing in the Random Effects Probit Model, Journal of Econometrics,59, 301–317.

    Article  Google Scholar 

  • Hajivassiliou, V.A. [1993]: Simulation Estimation Methods for Limited Dependent Variable Models, in Maddala, G.S., Rao, C.R. and Vinod, H.D. (eds), Handbook of Statistics, Vol. 11: Econometrics,Ch. 19, Amsterdam: North-Holland.

    Google Scholar 

  • Hansen, L.P. [1982]: Large Sample Properties of Generalized Methods of Moments Estimators, Econometrica,50, 1029–1055.

    Article  Google Scholar 

  • Heckman, J.J. [1981]: The Incidental Parameters Problem and the Problem of Initial Conditions in Estimating a Discrete Time - Discrete Data Stochastic Process and Some Monte Carlo Evidence, in Manski, C. and McFadden, D. (eds): Structural Analysis of Discrete Data,Cambridge: MIT-Press.

    Google Scholar 

  • Honoré, B. [1992]: Trimmed LAD and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects, Econometrica,60, 533–565.

    Article  Google Scholar 

  • Honoré, B. [1993]: Orthogonality Conditions for Tobit Models with Fixed Effects and Lagged Dependent Variables, Journal of Econometrics, 59, 35–61.

    Article  Google Scholar 

  • Keane, M.P. [1993]: Simulation Estimation for Panel Data Models with Limited Dependent Variables, in Maddala, G.S., Rao, C.R. and Vinod, H.D. (eds.), Handbook of Statistics, Vol. 11: Ch. 20, Amsterdam: North-Holland.

    Google Scholar 

  • König, H. and Lechner, M. [1994]: Some Recent Decelopments in Microeconometrics - A Survey, Swiss Journal of Economics and Statistics, 130, 299–331.

    Google Scholar 

  • Lafontaine, F. and White, K.J. [1986]: Obtaining any Wald Statistic You Want, Economics Letters, 21, 35–40.

    Article  Google Scholar 

  • Laisney, F., Lechner, M. and Pohlmeier, W. [1993]: Semi-Nonparametric Estimation of Binary Choice Models Using Panel Data, Recherches Économiques de Louvain, 58, 329–343.

    Google Scholar 

  • Laisney, F. and Pohlmeier, W. [1994]: Panel Estimation of Count Data Models: A survey, mimeo.

    Google Scholar 

  • Lechner, M. [1991]: Testing Logit Models in Practice, Empirical Economics, 16, 177–198.

    Article  Google Scholar 

  • Lechner, M. [1995]: Some Specification Tests for Probit Models Estimated on Panel Data, Journal of Business and Economic Statistics,forthcoming.

    Google Scholar 

  • Nerlove, M. [1971]: Further Evidence on the Estimation of Dynamic Economic Relations From a Time Series of Cross Sections, Econometrica, 39, 359–383.

    Article  Google Scholar 

  • Maddala, G.S., Rao, C.R. and Vinod, H.D. [1993]: Handbook of Statistics, Vol. 11: Econometrics, Amsterdam: North-Holland.

    Google Scholar 

  • Manski, C.F. [1987]: Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data, Econometrica, 55, 357–362.

    Article  Google Scholar 

  • Newey, W.K. [1985]: Maximum Likelihood Specification Testing and Conditional Moment Tests, Econometrica, 53, 1047–1070.

    Article  Google Scholar 

  • Newey, W.K. [1990]: Efficient Instrumental Variables Estimation of Nonlinear Models, Econometrica, 59, 809–837.

    Article  Google Scholar 

  • Newey, W.K. [1993]: Efficient Estimation of Models with Conditional Moment Restrictions, in Maddala, G.S., Rao, C.R. and Vinod, H.D. (eds.), Handbook of Statistics, Vol. 11: Econometrics,Ch. 16, Amsterdam: North-Holland.

    Google Scholar 

  • Newey, W.K. and West, K.D. [1987]: Hypothesis Testing with Efficient Method of Moments Estimators, International Economic Review, 28, 777–787.

    Article  Google Scholar 

  • Pagan, A. and Vella, F. [1989]: Diagnostic Tests for Models Based on Individual Data: A Survey, Journal of Applied Econometrics, 4, S29–S59.

    Article  Google Scholar 

  • Poirier, R.J. [1980]: A Lagrange Multiplier Test for Skewness in Binary Logit Models, Econometrics Letters, 5, 141–143.

    Article  Google Scholar 

  • Tauchen, T. [1985]: Diagnostic Testing and Evaluation of Maximum Likelihood Methods, Journal of Econometrics, 30, 415–443.

    Article  Google Scholar 

  • Thomas, J.M. [1993]: On Testing the Logistic Assumption in Binary Dependent Variable Models, Empirical Economics, 18, 381–392.

    Article  Google Scholar 

  • White, H. [1982]: Maximum Likelihood Estimation of Misspecified Models, Econometrica50, 1–25, “Corrigendum”,Econometrica, 51, 513.

    Google Scholar 

  • Wooldridge, J.M. [1990]: A Unified Approach to Robust, Regression-Based Specification Tests, Econometric Theory,6, 17–43.

    Article  Google Scholar 

Download references

Authors
  1. Michael Lechner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jörg Breitung
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Monash University, Melbourne and Budapest University of Economics, Australia

    László Mátyás

  2. ERUDITE, Université de Paris-Val-de-Marne, France

    Patrick Sevestre

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Kluwer Academic Publishers

About this chapter

Cite this chapter

Lechner, M., Breitung, J. (1996). Some GMM Estimation Methods and Specification Tests for Nonlinear Models. In: Mátyás, L., Sevestre, P. (eds) The Econometrics of Panel Data. Advanced Studies in Theoretical and Applied Econometrics, vol 33. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0137-7_22

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-0137-7_22

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-0-7923-3787-4

  • Online ISBN: 978-94-009-0137-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation