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Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects

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  • Amaresh Tiwari
  • Franz Palm
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    Abstract

    We develop a two step estimation procedure to estimate nonlinear panel data models. Our approach combines the “correlated random effect” and the “control function” approach to handel endogeneity of regressors that are correlated with both the unobserved heterogeneity as well as the idiosyncratic component. The novelty here lies in integrating out the unobserved heterogeneity on which the structural equations are conditioned. The integration is performed with respect to the posterior distribution of the individual effects obtained from the first stage reduced form estimation. Our framework suggests separate tests for correlation between unobserved heterogeneity and the covariates, and correlation between idiosyncratic component and the covariates. Average partial effects (APEs) of covariates are also easily obtained.

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    File URL: http://www2.ulg.ac.be/crepp/papers/crepp-wp201113.pdf
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    Bibliographic Info

    Paper provided by Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège in its series CREPP Working Papers with number 1113.

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    Date of creation: 2011
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    Handle: RePEc:rpp:wpaper:1113

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    1. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2008. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP25/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148.
    3. Badi H. Baltagi & Byoung Cheol Jung & Seuck Heun Song, 2008. "Testing for Heteroskedasticity and Serial Correlation in a Random Effects Panel Data Model," Center for Policy Research Working Papers 111, Center for Policy Research, Maxwell School, Syracuse University.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Whitney Newey, 2009. "Quantile and average effects in nonseparable panel models," CeMMAP working papers CWP29/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    6. Ivan Fernandez-Val, 2007. "Fixed Effects Estimation of Structural Parameters and Marginal Effects in Panel Probit Models," Boston University - Department of Economics - Working Papers Series WP2007-009, Boston University - Department of Economics.
    7. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
    8. Biorn, Erik, 2004. "Regression systems for unbalanced panel data: a stepwise maximum likelihood procedure," Journal of Econometrics, Elsevier, vol. 122(2), pages 281-291, October.
    9. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
    10. Anastasia Semykina & Jeffrey M. Woodridge, 2010. "Estimating Panel Data Models in the Presence of Endogeneity and Selection," Working Papers wp2010_10_01, Department of Economics, Florida State University.
    11. Tiemen Woutersen, 2002. "Robustness against Incidental Parameters," UWO Department of Economics Working Papers 20028, University of Western Ontario, Department of Economics.
    12. Hahn, Jinyong & Kuersteiner, Guido, 2011. "Bias Reduction For Dynamic Nonlinear Panel Models With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 27(06), pages 1152-1191, December.
    13. Papke, Leslie E. & Wooldridge, Jeffrey M., 2008. "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 121-133, July.
    14. Baltagi, Badi H. & Li, Qi, 1994. "Estimating Error Component Models With General MA(q) Disturbances," Econometric Theory, Cambridge University Press, vol. 10(02), pages 396-408, June.
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