A common result from altering several fundamental assumptions of the neoclassical investment model with convex adjustment costs is that investment may occur in lumpy episodes. This paper takes a step back and asks "How lumpy is the investment?" We answer this question by documenting the distributions of investment and capital adjustment for a sample of over 33,000 manufacturing plants drawn from over 400 four-digit industries. We find that many plants do undergo large investment episodes, however, there is tremendous variation across plants in their capital accumulation patterns. This paper explores how the variation in capital accumulation patterns vary by observable plant and firm characteristics, and how large investment episodes at the plant level transmit into fluctuations in aggregate investment.
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State and Local Determinants of Employment Outcomes among Individuals with Disabilities
March 2016
Working Paper Number:
CES-16-21
In the United States, employment rates among individuals with disabilities are persistently low but vary substantially. In this study, we examine the relationship between employment outcomes and features of the state and county physical, economic, and policy environment among a national sample of individuals with disabilities. To do so, we merge a set of state- and county-level environmental variables with data from the 2009'2011 American Community Survey accessed in a U.S. Census Research Data Center. We estimate regression models of employment, work hours, and earnings as a function of health conditions, personal characteristics, and these environmental features. We find that certain environmental variables are significantly associated with employment outcomes. Although the estimated importance of environmental variables is small relative to individual health and personal characteristics, our results suggest that these variables may present barriers or facilitators to employment that can explain some geographic variation in employment outcomes across the United States.
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MISCLASSIFICATION IN BINARY CHOICE MODELS
May 2013
Working Paper Number:
CES-13-27
We derive the asymptotic bias from misclassification of the dependent variable in binary choice models. Measurement error is necessarily non-classical in this case, which leads to bias in linear and non-linear models even if only the dependent variable is mismeasured. A Monte Carlo study and an application to food stamp receipt show that the bias formulas are useful to analyze the sensitivity of substantive conclusions, to interpret biased coefficients and imply features of the estimates that are robust to misclassification. Using administrative records linked to survey data as validation data, we examine estimators that are consistent under misclassification. They can improve estimates if their assumptions hold, but can aggravate the problem if the assumptions are invalid. The estimators differ
in their robustness to such violations, which can be improved by incorporating additional information. We propose tests for the presence and nature of misclassification that can help to choose an estimator.
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Growth Through Heterogeneous Innovations
June 2012
Working Paper Number:
CES-12-08
We study how exploration versus exploitation innovations impact economic growth through a tractable endogenous growth framework that contains multiple innovation sizes, multiproduct firms, and entry/exit. Firms invest in exploration R&D to acquire new product lines and exploitation R&D to improve their existing product lines. We model and show empirically that exploration R&D does not scale as strongly with firm size as exploitation R&D. The resulting framework conforms to many regularities regarding innovation and growth differences across the firm size distribution. We also incorporate patent citations into our theoretical framework. The framework generates a simple test using patent citations that indicates that entrants and small firms have relatively higher growth spillover effects.
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Location, Location, Location: The 3L Approach to House Price Determination
May 2004
Working Paper Number:
CES-04-06
The immobility of houses means that their location affects their values. This explains the common belief that three things determine the price of a house: location, location, and location. We use this notion to develop the 3L Approach to house price determination. That is, prices are determined by the Metropolitan Statistical Area (MSA), town, and street where the house is located. This study creates a unique data set based on data from the American Housing Survey (AHS) consisting of small 'clusters' of housing units with information on their housing characteristics and resident characteristics that is merged with census tract-level attributes. We use this data to verify the 3L Approach: we find that all three levels of location are significant when estimating the house price hedonic equation. This indicates that individuals care about their local neighborhood, i.e. the general upkeep of their street and possibly their neighbors' characteristics (cluster variables), a broader area such as the school district and/or the town (tract variables) that account for school quality and crime rates, and the particular amenities found in their MSA.
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Smart Cafe Cities: Testing Human Capital Externalities in the Boston Metropolitan Area
October 2005
Working Paper Number:
CES-05-24
Existing studies have explored either only one or two of the mechanisms that human capital externalities percolate at only macrogeographic levels. This paper uses the 1990 Massachusetts Census data and tests four mechanisms at the microgeographic levels in the Boston metropolitan area labor market. We propose that individual workers can learn from their occupational and industrial peers in the same local labor market through four channels: depth of human capital stock, Marshallian labor market externalities, Jacobs labor market externalities, and thickness of the local labor market. We find that all types of human capital externalities are significant across Census blocks. Different types of externalities attenuate at different speeds over distances. For example, the effect of human capital depth decays rapidly beyond three miles away from block centroid. We conclude that knowledge spillovers are very localized within microgeographic scope in cities that we call Smart Caf' Cities.
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Local Industrial Conditions and Entrepreneurship: How Much of the Spatial Distribution Can We Explain?
October 2008
Working Paper Number:
CES-08-37
Why are some places more entrepreneurial than others? We use Census Bureau data to study local determinants of manufacturing startups across cities and industries. Demo- graphics have limited explanatory power. Overall levels of local customers and suppliers are only modestly important, but new entrants seem particularly drawn to areas with many smaller suppliers, as suggested by Chinitz (1961). Abundant workers in relevant occupations also strongly predict entry. These forces plus city and industry fixed effects explain between sixty and eighty percent of manufacturing entry. We use spatial distributions of natural cost advantages to address partially endogeneity concerns.
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Connected and Uncooperative: The Effects of Homogenous and Exclusive Social Networks on Survey Response Rates and Nonresponse Bias
January 2024
Working Paper Number:
CES-24-01
Social capital, the strength of people's friendship networks and community ties, has been hypothesized as an important determinant of survey participation. Investigating this hypothesis has been difficult given data constraints. In this paper, we provide insights by investigating how response rates and nonresponse bias in the American Community Survey are correlated with county-level social network data from Facebook. We find that areas of the United States where people have more exclusive and homogenous social networks have higher nonresponse bias and lower response rates. These results provide further evidence that the effects of social capital may not be simply a matter of whether people are socially isolated or not, but also what types of social connections people have and the sociodemographic heterogeneity of their social networks.
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Urban Immigrant Diversity and Inclusive Institutions
January 2016
Working Paper Number:
CES-16-07
Recent evidence suggests that rising immigrant diversity in cities offers economic benefits, including improved innovation, entrepreneurship and productivity. One potentially important but underexplored dimension of this relationship is how local institutional context shapes the benefits firms and workers receive from the diversity in their midst. Theory suggests that institutions can make it less costly for diverse workers to transact, thereby catalyzing the latent bene ts of heterogeneity. This paper tests the hypothesis that the effects of immigrant diversity on productivity will be stronger in locations featuring more 'inclusive" institutions. It leverages comprehensive longitudinal linked employer-employee data for the U.S. and two distinct measures of inclusive institutions at the metropolitan area level: social capital and pro- or anti-immigrant ordinances. Findings confirm the importance of institutional context: in cities with low levels of inclusive institutions, the benefits of diversity are modest and in some cases statistically insignificant; in cities with high levels of inclusive institutions, the benefits of immigrant diversity are positive, significant, and substantial. Moreover, natives residing in cities that have enacted laws restricting immigrants enjoy no diversity spillovers whatsoever, while immigrants in these cities continue to receive a diversity bonus. These results confirm the economic significance of urban immigrant diversity, while suggesting the importance of local social and economic institutions.
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Eviction and Poverty in American Cities
July 2023
Working Paper Number:
CES-23-37
More than two million U.S. households have an eviction case filed against them each year.
Policymakers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two major urban areas: Cook County (which includes Chicago) and New York City. We document that prior to housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre-trends pose a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness and hospital visits and reduces earnings, durable goods consumption, and access to credit in the first two years. Effects on housing and labor market outcomes are driven by impacts for female and Black tenants. In the longer-run, eviction increases indebtedness and reduces credit scores.
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A Formal Test of Assortative Matching in the Labor Market
November 2009
Working Paper Number:
CES-09-40
We estimate a structural model of job assignment in the presence of coordination frictions due to Shimer (2005). The coordination friction model places restrictions on the joint distribution of worker and firm effects from a linear decomposition of log labor earnings. These restrictions permit estimation of the unobservable ability and productivity differences between workers and their employers as well as the way workers sort into jobs on the basis of these unobservable factors. The estimation is performed on matched employer-employee data from the LEHD program of the U.S. Census Bureau. The estimated correlation between worker and firm effects from the earnings decomposition is close to zero, a finding that is often interpreted as evidence that there is no sorting by comparative advantage in the labor market. Our estimates suggest that his finding actually results from a lack of sufficient heterogeneity in the workforce and available jobs. Workers do sort into jobs on the basis of productive differences, but the effects of sorting are not visible because of the composition of workers and employers.
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