Edward L. Glaeser

Growth in Cities

Recent theories of economic growth, including those of Romer, Porter, and Jacobs, have stressed the role of technological spillovers in generating growth. Because such knowledge spillovers are particularly effective in cities, where communication between people is more extensive, data on the growth of industries in different cities allow us to test some of these theories. Using a new data set on the growth of large industries in 170 U.S. cities between 1956 and 1987, we find that local competition and urban variety, but not regional specialization, encourage employment growth in industries. The evidence suggests that important knowledge spillovers might occur between rather than within industries, consistent with the theories of Jacobs.

Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach

This paper discusses the prevalence of Silicon Valley‐style localizations of individual manufacturing industries in the United States. A model in which localized industry‐specific spillovers, natural advantages, and pure random chance all contribute to geographic concentration is used to develop a test for whether observed levels of concentration are greater than would be expected to arise randomly and to motivate new indices of geographic concentration and of coagglomeration. The proposed indices control for differences in the size distribution of plants and for differences in the size of the geographic areas for which data are available. As a consequence, comparisons of the degree of geographic concentration across industries can be made with more confidence. Our empirical results provide a strong reaffirmation of the previous wisdom in that we find almost all industries to be somewhat localized. In many industries, however, the degree of localization is slight. We explore the nature of agglomerative forces in describing patterns of concentration, the geographic scope of localization, and the coagglomeration of related industries and of industries with strong upstream‐downstream ties.

Crime and Social Interactions

The high degree of variance of crime rates across space (and across time) is one of the oldest puzzles in the social sciences (see Quetelet (1835)). Our empirical work strongly suggests that this variance is not the result of observed or unobserved geographic attributes. This paper presents a model where social interactions create enough covariance across individuals to explain the high cross- city variance of crime rates. This model provides a natural index of social interactions which can compare the degree of social interaction across crimes, across geographic 1units and across time. Our index gives similar results for different data samples and suggests that the amount of social interactions are highest in petty crimes (such as larceny and auto theft), moderate in more serious crimes (assault, burglary and robbery) and almost negligible in murder and rape. The index of social interactions is also applied to non-criminal choices and we find that there is substantial interaction in schooling choice.

An Economic Approach to Social Capital

To identify the determinants of social capital formation, it is necessary to understand the social capital investment decision of individuals. Individual social capital should then be aggregated to measure the social capital of a community. This paper assembles the evidence that supports the individual-based model of social capital formation, including seven facts: (l) the relationship between social capital and age is first increasing and then decreasing, (2) social capital declines with expected mobility, (3) social capital investment is higher in occupations with greater returns to social skills, (4) social capital is higher among homeowners, (5) social connections fall sharply with physical distance, (6) people who invest in human capital also invest in social capital, and (7) social capital appears to have interpersonal complementarities.

The Rise and Decline of the American Ghetto

This paper examines segregation in American cities from 1890 to 1990. From 1890 to 1940, ghettos were born as blacks migrated to urban areas and cities developed vast expanses filled with almost entirely black housing. From 1940 to 1970, black migration continued and the physical areas of the ghettos expanded. Since 1970, there has been a decline in segregation as blacks have moved into previously all‐white areas of cities and suburbs. Across all these time periods there is a strong positive relation between urban population or density and segregation. Data on house prices and attitudes toward integration suggest that in the mid‐twentieth century, segregation was a product of collective actions taken by whites to exclude blacks from their neighborhoods. By 1990, the legal barriers enforcing segregation had been replaced by decentralized racism, where whites pay more than blacks to live in predominantly white areas.

What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns

Many industries are geographically concentrated. Many mechanisms that could account for such agglomeration have been proposed. We note that these theories make different predictions about which pairs of industries should be coagglomerated. We discuss the measurement of coagglomeration and use data from the Census Bureaus Longitudinal Research Database from 1972 to 1997 to compute pairwise coagglomeration measurements for U.S. manufacturing industries. Industry attributes are used to construct measures of the relevance of each of Marshalls three theories of industry agglomeration to each industry pair: (1) agglomeration saves transport costs by proximity to input suppliers or final consumers, (2) agglomeration allows for labor market pooling, and (3) agglomeration facilitates intellectual spillovers. We assess the importance of the theories via regressions of coagglomeration indices on these measures. Data on characteristics of corresponding industries in the United Kingdom are used as instruments. We find evidence to support each mechanism. Our results suggest that input-output dependencies are the most important factor, followed by labor pooling.

Trade and Circuses: Explaining Urban Giants

Using theory, case studies, and cross-country evidence, we investigate the factors behind the concentration of a nations urban population in a single city. High tariffs, high costs of internal trade, and low levels of international trade increase the degree of concentration. Even more clearly, politics (such as the degree of instability) determines urban primacy. Dictatorships have central cities that are, on average, 50 percent larger than their democratic counterparts. Using information about the timing of city growth, and a series of instruments, we conclude that the predominant causality is from political factors to urban concentration, not from concentration to political change.

Why Is There More Crime in Cities

Crime rates are much higher in big cities than in either small cities or rural areas. This paper explains this connection by using victimization data, evidence from the NLSY on criminal behavior, and the Uniform Crime Reports. Higher pecuniary benefits for crime in large cities can explain at most one‐quarter of the connection between city size and crime rates. Lower probabilities of arrest and a lower probability of recognition are features of urban life, but these factors seem to explain at most one‐fifth of the urban crime oeffect. Between one‐third and one‐half of the urban effect on crime can be explained by the presence of more famale‐headed households in cities.

Why Doesn't the United States Have a European-Style Welfare State?

European countries are much more generous to the poor relative to the US level of generosity. Economic models suggest that redistribution is a function of the variance and skewness of the pre-tax income distribution, the volatility of income (perhaps because of trade shocks), the social costs of taxation and the expected income mobility of the median voter. None of these factors appear to explain the differences between the US and Europe. Instead, the differences appear to be the result of racial heterogeneity in the US and American political institutions. Racial animosity in the US makes redistribution to the poor, who are disproportionately black, unappealing to many voters. American political institutions limited the growth of a socialist party, and more generally limited the political power of the poor.

The Rise of the Skilled City

For more than a century, educated cities have grown more quickly than comparable cities with less human capital. This fact survives a battery of other control variables, metropolitan area fixed effects and tests for reverse causality. We also find that skilled cities are growing because they are becoming more economically productive (relative to less skilled cities), not because these cities are becoming more attractive places to live. Most surprisingly, we find evidence suggesting that the skills-city growth connection occurs mainly in declining areas and occurs in large part because skilled cities are better at adapting to economic shocks. As in Schultz (1964), skills appear to permit adaptation.