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GMM for panel count data models

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  • Frank Windmeijer

    (Institute for Fiscal Studies and University of Bristol)

Abstract

This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parameters by GMM. As standard Wald tests based on efficient two-step GMM estimation results are known to have poor finite sample behaviour, alternative test procedures that have recently been proposed in the literature are evaluated by means of a Monte Carlo study.

Suggested Citation

  • Frank Windmeijer, 2006. "GMM for panel count data models," CeMMAP working papers CWP21/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:21/06
    as

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    File URL: http://cemmap.ifs.org.uk/wps/cwp2106.pdf
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    References listed on IDEAS

    as
    1. Martin Schellhorn, 2001. "The effect of variable health insurance deductibles on the demand for physician visits," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 441-456, July.
    2. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    5. Ángel Marcos Vera‐Hernández, 1999. "Duplicate coverage and demand for health care. The case of Catalonia," Health Economics, John Wiley & Sons, Ltd., vol. 8(7), pages 579-598, November.
    6. Chirok Han & Peter C. B. Phillips, 2006. "GMM with Many Moment Conditions," Econometrica, Econometric Society, vol. 74(1), pages 147-192, January.
    7. Frank Windmeijer, 2002. "ExpEnd, A Gauss programme for non-linear GMM estimation of exponential models with endogenous regressors for cross section and panel data," CeMMAP working papers CWP14/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    9. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    10. Manning, Willard G. & Basu, Anirban & Mullahy, John, 2005. "Generalized modeling approaches to risk adjustment of skewed outcomes data," Journal of Health Economics, Elsevier, vol. 24(3), pages 465-488, May.
    11. Montalvo, Jose G, 1997. "GMM Estimation of Count-Panel-Data Models with Fixed Effects and Predetermined Instruments," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 82-89, January.
    12. Jinyoung Kim & Gerald Marschke, 2005. "Labor Mobility of Scientists, Technological Diffusion, and the Firm's Patenting Decision," RAND Journal of Economics, The RAND Corporation, vol. 36(2), pages 298-317, Summer.
    13. Robert M. Salomon & J. Myles Shaver, 2005. "Learning by Exporting: New Insights from Examining Firm Innovation," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 14(2), pages 431-460, June.
    14. Bond, Stephen & Bowsher, Clive & Windmeijer, Frank, 2001. "Criterion-based inference for GMM in autoregressive panel data models," Economics Letters, Elsevier, vol. 73(3), pages 379-388, December.
    15. repec:cup:etheor:v:13:y:1997:i:5:p:667-78 is not listed on IDEAS
    16. Windmeijer, F A G & Silva, J M C Santos, 1997. "Endogeneity in Count Data Models: An Application to Demand for Health Care," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 281-294, May-June.
    17. J. M. C. Santos Silva & Silvana Tenreyro, 2006. "The Log of Gravity," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 641-658, November.
    18. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    20. Stephen Bond & Frank Windmeijer, 2005. "Reliable Inference For Gmm Estimators? Finite Sample Properties Of Alternative Test Procedures In Linear Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 1-37.
    21. Woodridge, J.M., 1991. "Multiplicative Panel Data Models without the Strict Exogeneity Assumption," Working papers 574, Massachusetts Institute of Technology (MIT), Department of Economics.
    22. Morgan Kelly, 2000. "Inequality And Crime," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 530-539, November.
    23. Wooldridge, Jeffrey M., 1997. "Multiplicative Panel Data Models Without the Strict Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 13(5), pages 667-678, October.
    24. Patrik Guggenberger, 2005. "Monte-carlo evidence suggesting a no moment problem of the continuous updating estimator," Economics Bulletin, AccessEcon, vol. 3(13), pages 1-6.
    25. repec:ebl:ecbull:v:3:y:2005:i:13:p:1-6 is not listed on IDEAS
    26. Andrés Romeu, 2004. "ExpEnd: GAUSS code for panel count-data models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 429-434.
    27. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    28. Crepon, Bruno & Duguet, Emmanuel, 1997. "Estimating the Innovation Function from Patent Numbers: GMM on Count Panel Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 243-263, May-June.
    29. Richard Blundell & Rachel Griffith & John van Reenen, 1999. "Market Share, Market Value and Innovation in a Panel of British Manufacturing Firms," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(3), pages 529-554.
    30. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    31. Chamberlain, Gary, 1992. "Sequential Moment Restrictions in Panel Data: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 20-26, January.
    32. Windmeijer, Frank, 2000. "Moment conditions for fixed effects count data models with endogenous regressors," Economics Letters, Elsevier, vol. 68(1), pages 21-24, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    GMM; exponential models; hypothesis testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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