Modelling winners and losers in contingent valuation of public goods: appropriate welfare measures and econometric analysis

J. Peter Clinch and Anthony Murphy ()

No 199812, Working Papers from School of Economics, University College Dublin

Abstract: Contingent Valuation is now the most widely used method for valuing non-marketed goods in cost benefit analysis. Yet, despite the fact that many externalities manifest themselves as costs to some and benefits to others, most studies restrict willingness to pay (WTP) to being non-negative. This paper explores appropriate welfare measures for assessing losses and gains and demonstrates how these can be elicited explicitly. Statistical / econometric methods are presented for modelling such responses. Median WTP is estimated non-parametrically. Grouped regression / Tobit and grouped regression / hurdle models are used to identify the determinants of WTP and to estimate mean WTP.

Keywords: Contingent valuation; Public good; Externality; Public bad; Welfare measures; Cost benefit analysis; Non-parametric distribution; Hurdle model; Tobit; Contingent valuation; Cost effectiveness; Public goods--Econometric models (search for similar items in EconPapers)
JEL-codes: C24 H41 Q26 (search for similar items in EconPapers)
Date: 1998-08
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10197/3044 First version, 1998 (application/pdf)

Related works:
Journal Article: Modelling Winners and Losers in Contingent Valuation of Public Goods: Appropriate Welfare Measures and Econometric Analysis (2001)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ucn:wpaper:199812

Access Statistics for this paper

More papers in Working Papers from School of Economics, University College Dublin Contact information at EDIRC.
Bibliographic data for series maintained by Nicolas Clifton ().