IDEAS home Printed from https://ideas.repec.org/p/bri/uobdis/06-591.html
   My bibliography  Save this paper

GMM for panel count data models

Author

Listed:
  • Frank Windmeijer

Abstract

This chapter 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," Bristol Economics Discussion Papers 06/591, School of Economics, University of Bristol, UK.
    • Handle: RePEc:bri:uobdis:06/591
    as

    Download full text from publisher

    File URL: http://www.bristol.ac.uk/efm/media/workingpapers/working_papers/pdffiles/dp06591.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Woodridge, J.M., 1991. "Multiplicative Panel Data Models without the Strict Exogeneity Assumption," Working papers 574, Massachusetts Institute of Technology (MIT), Department of Economics.
    4. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    5. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    6. 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.
    7. 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.
    8. Chirok Han & Peter C. B. Phillips, 2006. "GMM with Many Moment Conditions," Econometrica, Econometric Society, vol. 74(1), pages 147-192, January.
    9. Morgan Kelly, 2000. "Inequality And Crime," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 530-539, November.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. repec:ebl:ecbull:v:3:y:2005:i:13:p:1-6 is not listed on IDEAS
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. repec:cup:etheor:v:13:y:1997:i:5:p:667-78 is not listed on IDEAS
    27. 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.
    28. 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.
    29. 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.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yoshitsugu Kitazawa, 2012. "An improved theoretical ground for the linear feedback model and a new indicator," Discussion Papers 58, Kyushu Sangyo University, Faculty of Economics.
    2. Yoshitsugu Kitazawa, 2007. "Some additional moment conditions for a dynamic count panel data model," Discussion Papers 29, Kyushu Sangyo University, Faculty of Economics, revised Aug 2008.
    3. Yoshitsugu Kitazawa, 2009. "A negative binomial model and moment conditions for count panel data," Discussion Papers 34, Kyushu Sangyo University, Faculty of Economics.
    4. 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.
    5. Wang, Ning & Hagedoorn, John, 2014. "The lag structure of the relationship between patenting and internal R&D revisited," Research Policy, Elsevier, vol. 43(8), pages 1275-1285.
    6. Yoshitsugu Kitazawa, 2009. "Equidispersion and moment conditions for count panel data model," Discussion Papers 33, Kyushu Sangyo University, Faculty of Economics.
    7. Yoshitsugu Kitazawa, 2010. "Size of economic activity and occurrence of fatal traffic accidents: a count panel data analysis on Fukuoka prefecture in Japan," Discussion Papers 41, Kyushu Sangyo University, Faculty of Economics.
    8. Shiferaw Gurmu & Fidel Pérez-Sebastián, 2008. "Patents, R&D and lag effects: evidence from flexible methods for count panel data on manufacturing firms," Empirical Economics, Springer, vol. 35(3), pages 507-526, November.
    9. Almodóvar, Paloma & Nguyen, Quyen T.K. & Verbeke, Alain, 2021. "An integrative approach to international inbound sources of firm-level innovation," Journal of World Business, Elsevier, vol. 56(3).
    10. Jochmans, Koen, 2015. "Multiplicative-error models with sample selection," Journal of Econometrics, Elsevier, vol. 184(2), pages 315-327.
    11. Uchida, Yuichiro & Cook, Paul, 2005. "Innovation and Market Structure in the Manufacturing Sector: An Application of Linear Feedback Models," Centre on Regulation and Competition (CRC) Working papers 30702, University of Manchester, Institute for Development Policy and Management (IDPM).
    12. Davis, James C. & Henderson, J. Vernon, 2008. "The agglomeration of headquarters," Regional Science and Urban Economics, Elsevier, vol. 38(5), pages 445-460, September.
    13. Hwang, Jungbin & Kang, Byunghoon & Lee, Seojeong, 2022. "A doubly corrected robust variance estimator for linear GMM," Journal of Econometrics, Elsevier, vol. 229(2), pages 276-298.
    14. Hayakawa, Kazuhiko, 2019. "Alternative over-identifying restriction test in the GMM estimation of panel data models," Econometrics and Statistics, Elsevier, vol. 10(C), pages 71-95.
    15. Kaiser, Ulrich & Kongsted, Hans Christian & Rønde, Thomas, 2015. "Does the mobility of R&D labor increase innovation?," Journal of Economic Behavior & Organization, Elsevier, vol. 110(C), pages 91-105.
    16. 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.
    17. Yoshitsugu Kitazawa, 2010. "A forward demeaning transformation for a dynamic count panel data model," Discussion Papers 39, Kyushu Sangyo University, Faculty of Economics.
    18. Stefan Boes, 2010. "Count Data Models with Correlated Unobserved Heterogeneity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(3), pages 382-402, September.
    19. Hwang, Jungbin & Valdés, Gonzalo, 2023. "Finite-sample corrected inference for two-step GMM in time series," Journal of Econometrics, Elsevier, vol. 234(1), pages 327-352.
    20. Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022. "Spatial panel count data: modeling and forecasting of urban crimes," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-29, December.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bri:uobdis:06/591. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Vicky Jackson (email available below). General contact details of provider: https://edirc.repec.org/data/sebriuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.