Contingent Valuation and Revealed Preference Methodologies: Comparing the Estimates for Quasi-Public Goods

Abstract

A literature search provides 83 studies from which 616 comparisons of contingent valuation (CV) to revealed preference (RP) estimates are made. Summary statistics of the CV/RP ratios are provided for the complete dataset, a 5% trimmed dataset, and a weighted dataset that gives equal weight to each study rather than each CV /RP comparison. For the complete dataset, the sample mean CV/RP ratio is 0.89 with a 95% confidence interval [0.81-0.96] and a median of 0.75. For the trimmed and weighted dat:asets, these sumrnarJ statistics are (0.77; [0.74~0.81]; 0.75) and (0.92; [0.81-1.03]; 0.94), respectively. Tne Spearman rank correlation coefficients between the CV and RP estimates for the three datasets are 0.78, 0.88, and 0.92, respectively, with the Pearson correlations a bit larger. Non-parametric density estimates are provided, as well as the results of regressions of the observed CV /RP ratios on the basic RP technique used and the broad class of goods valued.

Traffic related noise and air quality valuations: evidence from stated preference residential choice models

“…This is consistent with evidence in the broader area of environmental valuation where there have been many more studies that have compared different methods (Bishop and Heberlein, 1979;Brookshire et al, 1982;Boxall et al 1996;Carson et al, 1996;Foster et al, 1997;Adamowicz et al, 1994, 1997, 1998, Hanley et al, 1998a, 1998b, 2002. As Hanley et al (2001) point out, the evidence is clear that the values obtained from and the intended payments of CVM are generally less than the values and payments of actual behaviour.…”

Eliciting public support for greening the electricity mix using random parameter techniques

“…The difference between stated and revealed values is referred to as "hypothetical bias." Carson et al (1996) review more than 600 studies, and demonstrate that stated preference tasks typically average about 90% of the corresponding revealed valuation, hence, slightly underestimate the benchmark of revealed valuation. Murphy et al (2005) conduct an econometric meta-analysis of hypothetical bias, and found evidence of a positive but small bias.…”

Cost Benefit Analyses versus Referenda

“…Therefore, if strategic responses to stated preference surveys are common, we ought to see systematic differences in the conclusions of analyses based on revealed and stated preferences. The survey of many revealed and stated preference cost benefit analyses conducted by Carson et al (1996) does not support this conclusion. In sum, both arguments suggest that respondents behave sincerely when they participate in stated preference surveys.…”