This study focuses on the relative importance of amenity and productivity differences in determining wage differentials across urban areas. The approach developed takes advantage of the connection between land and labor market clearing conditions required for locational equilibrium of households and firms. Data on recent movers are used to estimate equilibrium wages and rents for a sample of metropolitan areas. This information is then used to identify amenity and productivity components of wages for each city in the sample. Using national estimates of the relative share of land in consumption and production, differences in productivity and amenities are found to be roughly equal sources of wage variation across the sample.

We examine the location and growth of the U.S. population using county-level census data from 1840 and 1990. Counties are described by natural and produced characteristics they possessed in 1840. Natural characteristics include climate, mineral resources and access to natural transportation networks. Produced characteristics include industry mix, educational infrastructure, literacy rates, and access to man-made transportation systems. We investigate how natural characteristics influenced settlement patterns in 1840, and how natural and produced characteristics influenced population growth over the subsequent 150 years. We find that natural characteristics heavily influenced where populations located in 1840. We also that educational infrastructure, literacy rates, industry mix, and access to transportation networks had a significant influence on growth. There is little evidence of population convergence among our full sample of counties; such evidence appears only when the most-heavily-populated counties in 1840 are excluded from the sample. Moreover, when counties located on the western frontier are excluded from the full sample, on the assumption that they were relatively far from their steady state populations, there is evidence of population divergence.We thank Van Beck Hall for help identifying data sources; Carol Kraker and Steve Lehrer for research assistance; and

This paper uses a stochastic frontier production-function model to measure and compare productivity efficiency in the manufacturing sector of states in the United States over the period [1959][1960][1961][1962][1963][1964][1965][1966][1967][1968][1969][1970][1971][1972]. Based on this model we find considerable variations in productive efficiency across states. A large portion of the variation is found to be related to regional differences in labor-force characteristics, levels of urbanization and industrial structure. We also examine the relationship between productive efficiency and the subsequent growth of manufacturing and find some evidence of a weak relationship between efficiency and the growth of employment.

This paper investigates the determinants of productivity growth in the manufacturing sector of states over the period [1959][1960][1961][1962][1963][1964][1965][1966][1967][1968][1969][1970][1971][1972][1973]. Special emphasis is placed on isolating the effects of a state's urbanization characteristics on productivity growth. Urbanization characteristics considered include the spatial arrangement of cities along with the standard measures of urbanization. The results indicate that while both scale economies and technical change are related to urbanization characteristics the effects tend to be offsetting; no relationship is found between urbanization and overall productivity growth as measured by total factor productivity growth.

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SDespite the presence of anecdotal evidence linking regional economic growth and the presence of quality universities in such areas as the Silicon Valley in California and Route 128 in Boston, there have been few systematic studies of the relationship between universities and local economies. In this paper we examined the relationship between four measures of the quality or extent of activities of colleges and universities in an area and various measures of the local labor market activity, including employment, income and migration.We could not reject the hypothesis that there is no relationship between our measures of university activity and the overall employment rate in an SMSA.We did, however, find evidence that colleges and universities affect the composition of employment in an SMSA. The probability of being employed as a scientist or engineer and the probability of being employed in a high-tech industry were both found to increase with the amount of R&D funding at local universities. The probability of being employed in a high-tech industry was also found to be positively related to the number of graduates from local universities. We also found evidence that employment growth rates and earnings are higher in areas with good universities. Finally, the data can not reject the hypothesis that net migration is unrelated to universities.

No abstract

Despite the presence of anecdotal evidence linking regional economic growth and the presence of quality universities in such areas as the Silicon Valley in California and Route 128 in Boston, there have been few systematic studies of the relationship between universities and local economies. In this paper we examined the relationship between four measures of the quality or extent of activities of colleges and universities in an area and various measures of the local labor market activity, including employment, income and migration. We could not reject the hypothesis that there is no relationship between our measures of university activity and the overall employment rate in an SMSA. We did, however, find evidence that colleges and universities affect the composition of employment in an SMSA. The probability of being employed as a scientist or engineer and the probability of being employed in a high-tech industry were both found to increase with the amount of R&D funding at local universities. The probability of being employed in a high-tech industry was also found to be positively related to the number of graduates from local universities. We also found evidence that employment growth rates and earnings are higher in areas with good universities. Finally, the data can not reject the hypothesis that net migration is unrelated to universities.