David C. Kingsley

Preference Uncertainty, Preference Learning, and Paired Comparison Experiments

Results from paired comparison experiments suggest that as respondents progress through a sequence of binary choices they become more consistent, apparently fine-tuning their preferences. Consistency may be indicated by the variance of the estimated valuation distribution measured by the error term in the random utility model. A significant reduction in the variance is shown to be consistent with a model of preference uncertainty allowing for preference learning. Respondents become more adept at discriminating among items as they gain experience considering and comparing them, suggesting that methods allowing for such experience may obtain more well founded values. (JEL C25, D83)

Endogenous and costly institutional deterrence

Modern economies rely on central-authority institutions to regulate individual behaviour. Despite the importance of such institutions little is known about their formation within groups. In a public good experiment, groups selected the level of deterrence implemented by the institution, knowing that the administrative costs of the institution rose with the level of deterrence. Results suggest that groups readily self-impose costly deterrent formal institutions. The strictly deterrent institutions implemented here increased contributions sufficiently to completely offset the administrative cost and significantly increase earnings.

Estimating willingness to accept using paired comparison choice experiments: tests of robustness

Paired comparison (PC) choice experiments offer researchers and policy-makers an alternative nonmarket valuation method particularly apt when a ranking of the publics priorities across policy alternatives is paramount. Similar to contingent valuation, PC choice experiments estimate the total value associated with a specific environmental good or service. Similar to choice experiments, the questions posed to respondents are choices between alternatives. In contrast to both methods, respondents in PC choice experiments make choices between pairs of dissimilar alternatives including private goods, public goods, and monetary amounts. The alternatives may include competing policy alternatives, thus providing a ranking of the publics priorities among those alternatives. We investigate the robustness of estimated welfare measures to econometric modelling and choice set composition across two PC choice experiments. Results suggest that accounting for repeated observations increases the efficiency of welfare estimates but also reveals, contrary to previous research, sensitivity to choice set composition. Thus, while PC choice experiments may be advantageous in certain situations the results presented here suggest that further research is needed to better understand the sensitivities of the resulting welfare estimates.