Declining city productivity and the growth of rural regions: a test of alternative explanations

Article Abstract:

Using data compiled from County Business Patterns and an aggregate standard metropolitan statistical area production function, changes in employment patterns between urban and rural areas are measured. An improvement in employment opportunities in rural areas, led by the manufacturing sector and preceding population urban-to-urban migrations, is substantiated. Changes in age group preferences and technological innovations that promote decentralization seem to account for this shift. The data analysis suggests that nonmetropolitan areas are growing more rapidly than metropolitan areas, refuting the predicted development of huge megalopoles (as for example, the extension of Chicago to Pittsburgh or Boston to Washington, D.C. as single metropolitan areas). It is also suggested that smaller metropolitan areas are growing more rapidly than large city centers.

Job vacancies

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A note on the size distribution of cities over time

Article Abstract:

An analysis of interurban concentration is 12 countries (Egypt, India, Nigeria, Turkey, Brazil, Japan, Spain, the USSR, Austria, France, Sweden and the U.S.) since 1900, using the Pareto coefficient as a measure of concentration, indicates that the pattern of interurban concentration is U-shaped. Conformity to this conclusion is stronger among more economically developed nations. The U-shaped conclusion is verifiable when countries' urbanization levels and city sizes are studied individually (country by country); however, the U-shaped pattern of interurban concentration may not be as readily discernible if countries are analyzed in a cross-sectional manner.

Residential mobility

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Estimating generalized urban density functions

Article Abstract:

Estimations of urban population density and density gradients from city centers have largely suffered from sampling bias, produced by a reliance on census data and the phenomenon of heteroskedasticity. Both biases tend to limit transformation parameters in the estimates, although the effect of heteroskedasticity is especially pronounced. Correcting for both these biases produces fundamentally different population density estimations. Population density estimates for 30 U.S. cities are evaluated for bias and heteroskedasticity.

Models

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