The copula approach of sampling selection modelling: an application to the recreational value of forests

Margarita Genius and Elisabetta Strazzera

Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia

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.

Keywords: contingent valuation; selectivity bias; bivariate models; copulas (search for similar items in EconPapers)
JEL-codes: C34 C51 H41 Q26 (search for similar items in EconPapers)
Date: 2003
New Economics Papers: this item is included in nep-env
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Citations: View citations in EconPapers (2)

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