Examining efficiency gains through combining revealed and stated preferences, and issues related to scope with contingent valuation

An increase in the statistical efficiency for non-market valuation techniques is often desired in order to narrow the confidence intervals and provide better policy recommendations for resource managers. This is important to assist the managers in conducting benefit-cost analysis for the scare resources at their disposal. This dissertation examines the gains that come from combining revealed and stated preference data, exploring how estimation techniques can reduce the variance of a WTP amount.;This first parts of this dissertation looks at why resource managers would be interested in methods of combining Revealed and Stated preference data and measurement of the gains. One chapter does this by combining DC CVM with an MNL travel cost study. The following chapter examines the role anchoring can play in DB CVM studies for an onsite user of a beach resource. The final part of this dissertation studies the issue of scope in CVM studies through a meta-analysis. This dissertation finds that, in organizing the collected survey data, there are low cost methods to increase the efficiency of estimators that provide a significant reduction in variance. This reduction is critical for the resource manager wanting to examine if the project or policy would pass a benefit cost test. It also finds that the key factors necessary to reflect scope require more research with CVM.