Abstract. Meta-analysis is used to determine if there are factors that systematically affect price elasticity estimates in studies of residential water demand in the United States. An econometric model is estimated, using price elasticity estimates from previous studies as the dependent variable. Explanatory variables include functional form, cross-sectional versus time series, water price specification, rate structure, location, season, and estimation technique. Inclusion of income, rainfall, and evapotranspiration are all found to influence the estimate of the price elasticity. Population density, household size, and temperature do not significantly influence the estimate of the price elasticity. Pricing structure and season are, also found to significantly influence the estimate of the price elasticity.

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Meta-analysis is used to quantitatively summarize previous studies of residential electricity demand to determine if there are factors that systematically affect estimated elasticities. In this study, price and income elasticities of residential demand for electricity from previous studies are used as the dependent variables, with data characteristics, model structure, and estimation technique as independent variables, using both least square estimation of a semilog model and maximum likelihood estimation of a gamma model. The findings of this research can help better inform public policy makers, regulators, and utilities about the responsiveness of residential electricity consumers to price and income changes.

The hedonic price method is used to estimate the relationship between residential property values and airport noise and proximity to the airport in the Reno-Sparks area. Empirical results suggest there is a statistically significant negative relationship between airport noise and residential property values, with the average home in areas where noise levels are 65 decibels or high selling for about $2400 less than equivalent homes in quieter areas. However, in direct contrast to the study by Tomkins et al.(1998) who found proximity to the Manchester airport to be an amenity, this study finds proximity to the Reno-Sparks airport to have a significant negative value. Copyright 2000 Gatton College of Business and Economics, University of Kentucky.

[1] A logistic model is estimated to determine factors that have influenced the formation of bilateral international water treaties over the last 60 years. Results indicate that the larger a water basin is as a percent of a country's size, the more likely the country is to form a treaty regarding its management. On the other hand, the more control over the water basin any given country has, the less likely it will be involved in a treaty. The results also support aspects of two competing theories about the role of country differences, that in some cases they serve as obstacles to treaty formation yet in other cases they encourage treaty formation to formalize management when informal arrangements are not adequate.

Meta-analysis is used to determine if there are factors that systematically affect price and income elasticity estimates in studies of gasoline demand in the United States. Elasticity estimates from previous studies are used as the dependent variable with data characteristics, model structure, and estimation technique as the independent variables. Included among the explanatory variables a rejunctional form, lag structure, time span, and national setting (U.S. versus the U.S. pooled with other countries). Inclusion of vehicle ownership in gasoline demand studies is found to result in lower estimates of income elasticity, data sets which pool U.S. and foreign data result in larger (absolute) estimates of both price and income elasticity, and the small difference between static and dynamic models suggests that lagged responses to price or income changes are relatively short. This study also found that elasticity estimates appear relatively robust across estimation techniques.

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The effect on housing prices of proximity to different types of parks is estimated using a unique data set of single-family homes sold between 1990 and 1999 in Greenville, South Carolina. While the value of park proximity is found to vary with respect to park size and amenities, the estimates from this study are larger than previous studies. The greatest impact on housing values was found with proximity to small neighborhood parks, with the positive impact of proximity to both small and medium-size parks extending to homes as far as 1500 feet from the park.