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Semiparametric estimation of on-stie count data models

Author

Listed:
  • Masaki Narukawa

    (Tohoku University)

  • Katsuhito Nohara

    (Tohoku University)

Abstract

This article proposes semiparametric estimation of on-site count data models based on a series expansion approach of Gurmu, Rilstone and Stern (1999, Journal of Econometrics 88, 123-150), which is flexible and adaptable for a form of overdispersion as long as the exponential mean parameterization is given. We also provide the empirical illustration of demand for a recreation site. The result suggests that the existing parametric approaches will cause wrong statistical inference for the on-site count data.

Suggested Citation

  • Masaki Narukawa & Katsuhito Nohara, 2011. "Semiparametric estimation of on-stie count data models," Economics Bulletin, AccessEcon, vol. 31(1), pages 584-590.
    • Handle: RePEc:ebl:ecbull:eb-10-00463
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    File URL: http://www.accessecon.com/Pubs/EB/2011/Volume31/EB-11-V31-I1-P56.pdf
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    References listed on IDEAS

    as
    1. Santos Silva, J. M. C., 1997. "Unobservables in count data models for on-site samples," Economics Letters, Elsevier, vol. 54(3), pages 217-220, July.
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    Cited by:

    1. Katsuhito Nohara & Masaki Narukawa, 2015. "Measuring lost recreational benefits in Fukushima due to harmful rumors using a Poisson-inverse Gaussian regression?," ERSA conference papers ersa15p344, European Regional Science Association.

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    More about this item

    Keywords

    On-site sampling; Semiparametric estimation; Series expansion; Unobserved heterogeneity;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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