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The Copula Approach to Sample Selection Modelling: An Application to the Recreational Value of Forests

Author

Listed:
  • Elisabetta Strazzera

    (DRES and CRENoS, University of Cagliari)

  • Margarita Genius

    (Dept. of Economics, University of Crete)

Abstract

The sample selection model is based upon a bivariate or a multivariate structure, and distributional assumptions are in this context more severe than in univariate settings, due to the limited availability of tractable multivariate distributions. While the standard FIML estimation of the selectivity model assumes normality of the joint distribution, alternative approaches require less stringent distributional hypotheses. As shown by Smith (2003), copulas allow great flexibility also in FIML models. The copula model is very useful in situations where the applied researcher has a prior on the distributional form of the margins, since it allows separating their modelling from that of the dependence structure. In the present paper the copula approach to sample selection is first compared to the semiparametric approach and to the standard FIML, bivariate normal model, in an illustrative application on female work data. Then its performance is analysed more thoroughly in an application to Contingent Valuation data on recreational values of forests.

Suggested Citation

  • Elisabetta Strazzera & Margarita Genius, 2004. "The Copula Approach to Sample Selection Modelling: An Application to the Recreational Value of Forests," Working Papers 2004.73, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2004.73
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    Cited by:

    1. Kostov, Philip & Patton, Myles & Moss, Joan E. & McErlean, Seamus, 2005. "Does Gibrat's Law Hold Amongst Dairy Farmers in Northern Ireland?," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24775, European Association of Agricultural Economists.
    2. Yu, Lining & Voit, Eberhard O., 2006. "Construction of bivariate S-distributions with copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1822-1839, December.
    3. M. Genius & E. Strazzera, 2005. "Modeling Elicitation effects in contingent valuation studies: a Monte Carlo Analysis of the bivariate approach," Working Paper CRENoS 200502, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    4. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
    5. G. Marletto, 2006. "La politica dei trasporti come politica per l'innovazione: spunti da un approccio evolutivo," Working Paper CRENoS 200605, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Casey Quinn, 2005. "Generalisable regression methods for costeffectiveness using copulas," Health, Econometrics and Data Group (HEDG) Working Papers 05/13, HEDG, c/o Department of Economics, University of York.
    7. OA Carboni & G Medda, 2007. "Government Size and the Composition of Public Spending in a Neoclassical Growth Model," Working Paper CRENoS 200701, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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    More about this item

    Keywords

    Contingent valuation; Selectivity bias; Bivariate models; Copulas;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources

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