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Consistent estimation for the full-fledged fixed effects zero-inflated Poisson model

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  • Yoshitsugu Kitazawa

    ()
    (Faculty of Economics, Kyushu Sangyo University)

Abstract

This paper advocates the transformations used for the consistent estimation of the full-fledged fixed effects zero-inflated Poisson model whose zero outcomes can arise from both of logit and Poisson parts and which equips both parts with the fixed effects. The valid moment conditions are constructed on the basis of the transformations. The finite sample behaviors of GMM and EL estimators employing the moment conditions are investigated by use of Monte Carlo experiments.

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File URL: http://www.ip.kyusan-u.ac.jp/keizai-kiyo/dp66.pdf
File Function: First version, 2014
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Bibliographic Info

Paper provided by Kyushu Sangyo University, Faculty of Economics in its series Discussion Papers with number 66.

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Length: 18 pages
Date of creation: Apr 2014
Date of revision:
Handle: RePEc:kyu:dpaper:66

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Related research

Keywords: fixed effects zero-inflated Poisson model; predetermined explanatory variables in Poisson part; moment conditions; GMM; EL; Monte Carlo experiments;

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  1. Stanislav Anatolyev, 2005. "GMM, GEL, Serial Correlation, and Asymptotic Bias," Econometrica, Econometric Society, vol. 73(3), pages 983-1002, 05.
  2. Durham, Catherine A. & Pardoe, Iain & Vega-H, Esteban, 2004. "A Methodology for Evaluating How Product Characteristics Impact Choice in Retail Settings with Many Zero Observations: An Application to Restaurant Wine Purchase," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(01), April.
  3. Wooldridge, Jeffrey M., 1997. "Multiplicative Panel Data Models Without the Strict Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 13(05), pages 667-678, October.
  4. Ramalho Joaquim J.S., 2005. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-20, March.
  5. Simon Jackman & Christian Kleiber & Achim Zeileis, 2007. "Regression Models for Count Data in R," Working papers 2007/24, Faculty of Business and Economics - University of Basel.
  6. Sheng-Pin Hsueh & Wei-Ming Lee, 2012. "A revisit to the relationship between patents and R&D using empirical likelihood estimation," Economics Bulletin, AccessEcon, vol. 32(2), pages 1208-1214.
  7. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  8. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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