Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/155260 
Erscheinungsjahr: 
2001
Schriftenreihe/Nr.: 
Nota di Lavoro No. 97.2001
Verlag: 
Fondazione Eni Enrico Mattei (FEEM), Milano
Zusammenfassung: 
Selectivity bias caused by protest responses in Contingent Valuation studies can be detected and corrected by means of sample selection models. This paper compares two methods: the Heckman 2-steps method and the full ML, applied to data on forest recreation - where WTP is elicited as a continuous variable. Either method has its own drawback: computational complexity for the ML method, susceptibility to collinearity problems for the 2-steps method. The latter problem is observed in our best fitting specification, with the ML estimator outperforming the 2-steps. In this application, overlooking the effect of protest responses would cause an upwards bias of the final estimates of WTP.
Schlagwörter: 
Contingent valuation
protest responses
sample selection
MLE
two-steps method
JEL: 
C35
C51
C81
D60
H41
Q26
Dokumentart: 
Working Paper

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