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CES-WP-02-27

Human Capital Spillovers in Manufacturing: Evidence from Plant-Level Production Functions

Enrico Moretti

November 01, 2002

I assess the magnitude of human capital spillovers in US cities by estimating plant level production functions. I use a unique firm-worker matched dataset, obtained by combining the Census of Manufacturers with the Census of Population. After controlling for a plant’s own human capital, plant fixed effects, industry-specific and state-specific transitory shocks, I find that the output of plants located in cities that experience large increases in the share of college graduates rises more than the output of similar plants located in cities that experience small increases in the share of college graduates. Several specification tests indicate that the estimated effect is not completely spurious. First, within a city, the spillover between plants that are geographically and economically close is positive, while spillovers between plants that are geographically close but economically distant is zero. Second, most of the estimated spillover comes from hi-tech plants. For non hi-tech productions, the spillover is virtually zero. When I stratify the sample by the percentage of employees who are college educated, I find that the spillover is larger the larger the percentage of college educated workers in the plant. Third, density of physical capital in a city outside a plant has no effect on a plant’s productivity. Consistent with a model that includes both standard and general equilibrium forces and spillovers, the estimated productivity differences between cities with high and low levels of human capital match remarkably well differences in labor costs that are typically observed between cities with high and low levels of human capital. This is important because, in equilibrium, any productivity gain generated by human capital spillover should be offset by increased costs.

View Paper   49 Pages 500953 Bytes

CES-WP-02-26

What Drives Racial Segregation? New Evidence Using Census Microdata

Patrick Bayer, Robert McMillan, Kim Rueben

October 01, 2002

Residential segregation on the basis of race is widespread and has important welfare consequences. This paper sheds new light on the forces that drive observed segregation patterns. Making use of restricted micro-Census data from the San Francisco Bay Area and a new measurement framework, it assesses the extent to which the correlation of race with other household characteristics, such as income, education and immigration status, can explain a significant portion of observed racial segregation. In contrast to the findings of the previous literature, which has been hampered by serious data limitations, our analysis indicates that individual household characteristics can explain a considerable fraction of segregation by race. Taken together, we find that the correlation of race with other household attributes can explain almost 95 percent of segregation for Hispanic households, over 50 percent for Asian households, and approximately 30 percent for White and Black households. Our analysis also indicates that different factors drive the segregation of different races. Language explains a substantial proportion - more than 30 percent - of Asian and Hispanic segregation, education explains a further 20 percent of Hispanic segregation, while income is the most important non-race household characteristic for Black households, explaining around 10 percent of Black segregation.

View Paper   44 Pages 666593 Bytes

CES-WP-02-25

The Survival of Industrial Plants

Michael Gort, J. Bradford Jensen, Seong-Hoon Lee

October 01, 2002

The study seeks to explain the attrition rate of new manufacturing plants in the United States in terms of three vectors of variables. The first explains how survival of the fittest proceeds through learning by firms (plants) about their own relative efficiency. The second explains how efficiency systematically changes over time and what augments or diminishes it. The third captures the opportunity cost of resources employed in a plant. The model is tested using maximum-likelihood probit analysis with very large samples for successive census years in the 1967-97 period. One sample consists of an unbalanced panel of about three-fourths of a million plants of single and multi-unit firms, or alternatively of about 300,000 plants if only the most reliable data are considered. The second is restricted to the plants of multi-unit firms in the same time span and consists of an unbalanced panel of more than 100,000 plants. The empirical analysis strongly confirms the predictions of the model.

View Paper   26 Pages 153497 Bytes

CES-WP-02-24

Analysis of Young Small Firms That Have Closed: Delineating Successful from Unsuccessful Closures

Timothy Bates

October 01, 2002

This study of small businesses created between 1989 and 1992, and then closed down between 1993 and 1996, reveals that owners often described their firms as “successful” when the disclosure decision was made. . Theoretical explanations consistent with this pattern are explored in this study. One view describes successful closures as rational outcomes of learning processes undertaken by entrepreneurs opening firms amidst considerable uncertainty. Another approach sees the seeming paradox of successful closure in terms of alternative opportunities: if something better comes along, the entrepreneur may close down. Empirically, successful closure owners are found to be moving on to more attractive alternatives.

View Paper   26 Pages 109728 Bytes

CES-WP-02-23

The 1990 Decennial Employer-Employee Dataset

Kimberly Bayard, Joel Elvery, Judith Hellerstein, David Neumark

October 01, 2002

We describe the construction and assessment of a new matched employer-employee data set, the 1990 Decennial Employer-Employee Dataset (1990 DEED). By using place of work name and address, we link workers from the 1990 Long Form Sample to their place of work in the 1990 Standard Statistical Establishment List. The resulting data set is much larger and more representative across regional and industry dimensions than previous matched data sets for the United States. The known strengths and limitations of the data set are discussed in detail.

View Paper   39 Pages 88170 Bytes

CES-WP-02-22

Survival of the Best Fit: Competition from Low Wage Countries and the (Uneven) Growth of U.S. Manufacturing Plants

Andrew Bernard, J. Bradford Jensen, Peter Schott

October 01, 2002

We examine the relationship between import competition from low wage countries and the reallocation of US manufacturing from 1977 to 1997. Both employment and output growth are slower for plants that face higher levels of low wage import competition in their industry. As a result, US manufacturing is reallocated over time towards industries that are more capital and skill intensive. Differential growth is driven by a combination of increased plant failure rates and slower growth of surviving plants. Within industries, low wage import competition has the strongest effects on the least capital and skill intensive plants. Surviving plants that switch industries move into more capital and skill intensive sectors when they face low wage competition.

View Paper   36 Pages 440821 Bytes

CES-WP-02-21

The Measurement of Medicaid Coverage in the SIPP: Evidence from California, 1990-1996

David Card, Andrew Hildreth, Lara Shore-Sheppard

September 01, 2002

This paper studies the accuracy of reported Medicaid coverage in the Survey of Income and Program Participation (SIPP) using a unique data set formed by matching SIPP survey responses to administrative records from the State of California. Overall, we estimate that the SIPP underestimates Medicaid coverage in the California populaton by about 10 percent. Among SIPP respondents who can be matched to administrative records, we estimate that the probability someone reports Medicaid coverage in a month when they are actually covered is around 85 percent. The corresponding probability for low-income children is even higher – at least 90 percent. These estimates suggest that the SIPP provides reasonably accurate coverage reports for those who are actually in the Medicaid system. On the other hand, our estimate of the false positive rate (the rate of reported coverage for those who are not covered in the administrative records) is relatively high: 2.5 percent for the sample as a whole, and up to 20 percent for poor children. Some of this is due to errors in the recording of Social Security numbers in the administrative system, rather than to problems in the SIPP.

View Paper   41 Pages 204857 Bytes

CES-WP-02-20

The Relationship of Personal and Neighborhood Characteristics to Immigrant Fertility

Laura Hill, Hans Johnson

August 01, 2002

We find that fertility varies by immigrant generation, with significant declines between the first and subsequent generations for groups with large immigrant population. However, we find that personal characteristics--such as educational attainment, marital status, and income levels--are much more important than immigrant generation in understanding fertility outcomes. In fact, generations are not independently important once these personal characteristics are controlled for. We maintain that declining fertility levels among the descendants of Mexican and Central American immigrants are primarily the result of higher educational attainment levels, lower rates of marriage, and lower poverty. For example, a four-year increase in educational attainment decreases children ever born (CEB) by half a child. We conclude that immigrant generation serves as a proxy for changes in other personal characteristics that decrease fertility. Neighborhood characteristics have some bearing on fertility, but the correlations are relatively weak. Among Mexican and Central American immigrants and their descendants, the most consistent predictor of children ever born (CEB) at the neighborhood level is the percentage of Hispanic adults. However, no neighborhood characteristics bear any statistical relationship to current fertility, the measure that emphasizes recent births. This pattern of evidence suggests that the observed relationships between neighborhood characteristics and fertility are based on selection into the neighborhood rather than on neighborhood influences as such.

View Paper   69 Pages 905190 Bytes

CES-WP-02-19

Interactions, Neighborhood Selection, and Housing Demand

Yannis Ioannides, Jeffrey Zabel

August 01, 2002

This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e®ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di®erent levels (“scales”) of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects.

View Paper   38 Pages 328673 Bytes

CES-WP-02-18

The Link Between Aggregate and Micro Productivity Growth: Evidence from Retail Trade

C.J. Krizan, John Haltiwanger, Lucia Foster

August 01, 2002

Understanding the nature and magnitude of resource reallocation, particularly as it relates to productivity growth, is important both because it affects how we model and interpret aggregate productivity dynamics, and also because market structure and institutions may affect the reallocation’s magnitude and efficiency. Most evidence to date on the connection between reallocation and productivity dynamics for the U.S. and other countries comes from a single industry: manufacturing. Building upon a unique establishment-level data set of U.S. retail trade businesses, we provide some of the first evidence on the connection between reallocation and productivity dynamics in a non-manufacturing sector. Retail trade is a particularly appropriate subject for such a study since this large industry lies at the heart of many recent technological advances, such as E-commerce and advanced inventory controls. Our results show that virtually all of the productivity growth in the U.S. retail trade sector over the 1990s is accounted for by more productive entering establishments displacing much less productive exiting establishments. Interestingly, much of the between-establishment reallocation is a within, rather than betweenfirm phenomenon.

View Paper   44 Pages 381471 Bytes

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