Suchergebnisse

There are many possible connections between VSL and behavioral economics. A list of topics includes endowment effects, risk salience, ambiguity aversion, present bias, reference groups, reference points, and experienced versus decision utilities. There are also nudges that connect to estimating or using VSL in government decisions and cousins of behavioral economic research including interpersonal heterogeneity, experiments, neuroeconomics, and beauty or personal attractiveness. Current evidence suggests that VSL and behavioral economics best connect via (1) possible multi-attribute reference group effects and (2) a possible distinction between decision utility and experienced utility.

Our research investigates the effects of residential energy efficiency audit programs on subsequent household electricity consumption. Here there is a one-time interaction between households, which participate voluntarily, and the surveyors. Our research objective is to determine whether and to what extent the surveys lead to behavioral changes. We then examine how persistent the intervention is over time and whether the effects decay or intensify. The main evaluation problem here is survey participants' self-selection, which we address econometrically via several non-parametric estimators involving kernel-based propensity-score matching. In the first method we use difference-in-differences (DID) estimation. Our second estimator is quantile DID, which produces estimates on distributions. The comparison group consists of households who were not yet participating in the survey but participated later. Our evidence is that the customers who participated in the survey reduced their electricity consumption by about 7%, on average compared to customers who had not yet participated in the survey. Considering the total number of high-usage households participating in the survey in 2009, we estimate that electricity consumption was reduced by an aggregate of 2 million kWh per year, which is approximately equal to the monthly consumption of 3500 typical households in California with an estimated 1527 metric tons less of carbon dioxide emissions. Because the energy audit program is inexpensive ($10–$20 per household) a key issue is that while the program is cost-effective, is it regressive? We find that as the quantiles of the outcome distribution increase, high-use households save proportionally less electricity than do low-use customers. Overall, our results imply that program designers can better target low-use and low-income households, because they are more likely to benefit from the programs through energy savings.