The statistical efficiency of conventional dichotomous choice contingent valuation surveys can be improved by asking each respondent a second dichotomous choice question which depends on the response to the first question—if the first response is “yes,” the second bid is some amount greater than the first bid; while, if the first response is “no,” the second bid is some amount smaller. This “double‐bounded” approach is shown to be asymptotically more efficient than the conventional, “singlebounded” approach. Using data from a survey of Californians regarding their willingness to pay for wetlands in the San Joaquin Valley, we show that, in a finite sample, the gain in efficiency can be very substantial.

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Economic theory of responses to CV survey questions is developed, set within the framework of the random utility maximization model, which generates statistical models for the survey responses. A number of statistical issues arise in the estimation of economic welfare measures from data on CV responses using the maximum likelihood method. Optimal experimental design procedures are outlined to select the bids to be used in CV surveys. Advanced topics in statistical design and the analysis of discrete choice data are presented.

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Climate change is likely to affect the generation of energy from California's high-elevation hydropower systems. To investigate these impacts, this study formulates a linear programming model of an 11-reservoir hydroelectric system operated by the Sacramento Municipal Utility District in the Upper American River basin. Four sets of hydrologic scenarios are developed using the Variable Infiltration Capacity model combined with climatic output from two general circulation models under two greenhouse-gas emissions scenarios. Power generation and revenues fall under two of the four climate change scenarios, as a consequence of drier hydrologic conditions. Energy generation is primarily limited by annual volume of streamflow, and is affected more than revenues, reflecting the ability of the system to store water when energy prices are low for use when prices are high (July through September). Power generation and revenues increase for two of the scenarios, which predict wetter hydrologic conditions. In this case, power generation increases more than revenues indicating that the system is using most of its available capacity under current hydrologic conditions. Hydroelectric systems located in basins with hydrograph centroids occuring close to summer months (July through September) are likely to be affected by the changes in hydrologic timing associated with climate change (e.g., earlier snowmelts and streamflows) if the systems lack sufficient storage capacity. High Sierra hydroelectric systems with sufficiently large storage capacity should not be affected by climate-induced changes in hydrologic timing.