Shaw, W. Douglass

December, 2000

By: Lambert, David K.; Shaw, W. Douglass
Nevada ranks third in the world in gold production. In order to operate the massive open pit gold mines, the State of Nevada granted mining companies a temporary permit to pump groundwater from near the open pits and dispose of it. Certain instream flows have nearly doubled relative to average historical flows in recent years. Following pit closure, surface flows will likely decline from historical levels. This study measures the impacts of these changing water supplies on downstream agricultural and recreational users. We argue that the creation of temporary changes in water rights for the downstream users would likely mitigate future losses both groups are expected to experience.

December, 1996

By: Shonkwiler, John Scott; Shaw, W. Douglass
When a sample of recreators is drawn from the general population using a survey, many in the sample will not recreate at a recreation site of interest. This study focuses on nonparticipation in recreation demand modeling and the use of modified count-data models. We clarify the meaning of the single-hurdle Poisson (SHP) model and derive the double-hurdle Poisson (DHP) model. The latter is contrasted with the SHP and we show the DHP is consistent with Johnson and Kotz's zero-modified Poisson model.

July, 1996

By: Cameron, Trudy Ann; Shaw, W. Douglass; Ragland, Shannon E.; Callaway, J. Mac; Keefe, Sally
A model of recreation demand is developed to determine the role of water levels in determining participation at and frequency of trips taken to various federal reservoirs and rivers in the Columbia River Basin. Contingent behavior data are required to break the near-perfect multicollinearities among water levels at some waters. We combine demand data for each survey respondent at different levels of time aggregation (summer months, rest of year, and annual), and our empirical models accommodate the natural heteroskedasticity that results. Our empirical results show it to be quite important to control carefully for survey nonresponse bias.