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Fixed Effects Estimation in Panel Nonlinear Fractional Response Models

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  • Xiaoming Li

    (University of Connecticut)

Abstract

Estimations of nonlinear panel models that include individual specific fixed effects are complicated by the incidental parameters problem, that is, the asymptotic bias in the estimation of typical fixed effects panel models generally results in inconsistent estimates. In this paper, I characterize the leading term of a large-T expansion of the biases in the nonlinear least square estimator (NLSE) and estimators of the average partial effects in panel fractional response models. The resulting estimator after analytical bias correction is robust to the incidental parameters bias and reduces the bias order from O(T−1) to O(T−2). I also examine the finite sample performance of the proposed estimator using a new data generating process in which panel fractional response variables are collapsed from repeated, clustered cross-sectional binary probit choices. A proof showing the generated data satisfies the identification assumption at the cluster level has been given. Simulation results suggest that, in the static case, the bias corrected estimator performs comparably to the quasi-maximum likelihood estimator (QMLE), which is the standard approach in the literature, for 8 or more periods, while in the dynamic case, the bias corrected estimators are substantially superior to those QMLE’s.

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Bibliographic Info

Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2011-11.

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Length: 39 pages
Date of creation: Jun 2011
Date of revision:
Handle: RePEc:uct:uconnp:2011-11

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Related research

Keywords: Fractional responses; Panel Data; Unobserved effects; Probit; Partial effects; Bias; Incidental parameters problem; Fixed effects; Bias Correction;

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  1. 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.
  2. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  3. Xiaoming Li & AKM Rezaul Hossain & Stephen L. Ross, 2010. "Neighborhood Information Externalities and the Provision of Mortgage Credit," Working papers 2010-10, University of Connecticut, Department of Economics.
  4. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
  5. 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.
  6. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
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