Compensating Differentials in Emerging Labor and Housing Markets: Estimates of Quality of Life in Russian Cities

The existence of compensating differentials in Russian labor and housing markets is examined using data from the Russian Longitudinal Monitoring Survey (RLMS) augmented by city and regional-specific characteristics from other sources. While Russia is undergoing transition to a market economy, we find ample evidence that compensating differentials for location-specific amenities exist in the labor and housing markets. Our estimated wage and housing value equations suggest that workers are compensated for differences in climate, environmental conditions, ethnic conflicts, crime rates, and health conditions, after controlling for worker characteristics, occupation, industry, and economic conditions, and various housing characteristics. Moreover, we find evidence that these compensating differentials exist even after controlling for the regional pay differences (“regional coefficients”) used by the Russian government to compensate workers for living in regions that are designated as less desirable. We rank 953 Russian cities by quality of life as measured by a group of eleven amenities. Sizable variation in the estimated quality of life across cities exists. The highest ranked cities tend to be in relatively warm areas and areas in the western, European part of the country. In addition, our quality of life index is positively correlated with net migration into a region, suggesting workers are attracted to amenity-rich locations. Overall, we find that sufficient market equilibrium exists and a model of compensating differentials with controls for disequilibrium yields useful information about values of location-specific amenities and quality of life in this large transition economy.http://deepblue.lib.umich.edu/bitstream/2027.42/40006/2/wp620.pd

Estimating the Social Value of Higher Education: Willingness to Pay for Community and Technical Colleges

Much is known about private returns to education in the form of higher earnings. Less is known about social value, over and above the private, market value. Associations between education and socially-desirable outcomes are strong, but disentangling the effect of education from other causal factors is challenging. The purpose of this paper is to estimate the social value of one form of higher education. We elicit willingness to pay for the Kentucky Community and Technical College System directly through a stated-preferences survey and compare our estimate of total social value to our estimates of private value in the form of increased earnings. Our earnings estimates are based on two distinct data sets, one administrative and one from the U.S. Census. The difference between the total social value and the increase in earnings is our measure of the education externality. Our work differs from previous research by eliciting values directly in a way that yields a total value including any external benefits and by focusing on education at the community college level. Our preferred estimate indicates the social value of expanding the system substantially exceeds private value by approximately 50 percent.social returns, education externalities, contingent valuation, earnings

Task III Report: Water Use Estimation and Forecasting for the Kentucky River Basin

We estimate aggregate monthly water use for summer, peak demand and nonsummer off-peak demand periods for the Kentucky River Basin. Using Kentucky Division of Water use data, U.S. Census data for county demographic and economic conditions, and U.S. Weather Service data for weather conditions we estimate use for the 1970-1993 period. Our model allows for idiosyncratic effects of each of the 27 counties in the sample. We find factors such as population and manufacturing employment affect use and temperature and rainfall in current and preceding months effect use during the summer, peak period. The model predicts well within the sample period. Population forecasts, both moderate and high growth series, from the Kentucky Data Center are used along with manufacturing employment forecasts for water use forecasts. Water use forecasts are made for years out to 2020 under 1930 drought conditions for comparison with water supply estimates. The use estimates are made assuming pricing and other demand estimate policies remain constant. For Pool 9 under 1930 weather conditions and high (moderate) population growth, water use is forecast to be 70 (55) MGD which is 220 gallons per person per day. For the Basin aggregate water use is forecast to be 129 (110) MGD. An Excel 5.0 spreadsheet was developed to make forecasts for various assumptions concerning: population, growth, and employment the degree to which new users come on line to water and sewer systems, and weather conditions

Water Use Estimation and Forecasting for the Kentucky River Basin: A Preliminary Draft Report

We estimate aggregate monthly water use for summer, peak demand and nonsummer off-peak demand periods for the Kentucky River Basin. Using Kentucky Division of Water use data, U.S. Census data for county demographic and economic conditions, and U.S. Weather Service data for weather conditions we estimate use for the 1970-1993 period. Our model allows for idiosyncratic effects of each of the 27 counties in the sample. We find factors such as population and manufacturing employment effect use and temperature and rainfall in current and preceding months effect use during the summer, peak period. The model predicts well within the sample period Population forecasts. both moderate and high growth series, from the Kentucky Data Center are used along with the manufacturing employment forecasts for water use forecasts. Water use forecasts are made for years out to 2020 under 1930 drought conditions for comparison with water supply estimates. The use estimates are made assuming pricing and other demand management policies remain constant