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Who Leaves, Where to, and Why Worrry? Employee Mobility, Employee Entrepreneurship, and Effects on Source Firm Performance
September 2009
Working Paper Number:
CES-09-32
We theorize that differences in human assets' ability to generate value are linked to exit decisions and their effects on firm performance. Using linked employee-employer data from the U.S. Census Bureau on legal services, we find that employees with higher earnings are less likely to leave relative to employees with lower earnings, but if they do leave, they are more likely to move to a spin-out instead of an incumbent firm. Employee entrepreneurship has a larger adverse impact on source firm performance than moves to established firms, even controlling for observable employee quality. Findings suggest that the transfer of human capital, complementary assets, and opportunities all affect mobility decisions and their impact on source firms.
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What Has Been Capitalized into Property Values: Human Capital, Social Capital, or Cultural Capital?
October 2005
Working Paper Number:
CES-05-25
Urban amenities can be capitalized into land values or property values. However, little attention has been paid to the capitalization of social amenities. This paper classifies three types of social-interaction-based social amenities: human capital, social capital, and cultural capital at residential neighborhood levels. We use the restricted version of the 1990 Massachusetts Census data and estimate hedonic housing models with social amenities. The findings are as follows: (1) Human capital has significant positive effects on property values. This tests the Lucas conjecture. (2) Different types of social capital have different effects on property values: an increase in the percentage of new residents has significant positive effects on property values, probably due to the strength of weak ties. However, an increase in the percentage of single-parent households has negative effects on property values. An increase in the home ownership rate has positive effects at large geographic levels. (3) Cultural capital effects vary from high to low geographic levels, the effects of English proficiency and racial homogeneity are positive at and beyond the tract level, but insignificant at the block level. This may imply that cultural capital is more important in social interactions at large geographic scale.
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Startup Dynamics: Transitioning from Nonemployer Firms to Employer Firms, Survival, and Job Creation
April 2025
Working Paper Number:
CES-25-26
Understanding the dynamics of startup businesses' growth, exit, and survival is crucial for fostering entrepreneurship. Among the nearly 30 million registered businesses in the United States, fewer than six million have employees beyond the business owners. This research addresses the gap in understanding which companies transition to employer businesses and the mechanisms behind this process. Job creation remains a critical concern for policymakers, researchers, and advocacy groups. This study aims to illuminate the transition from non-employer businesses to employer businesses and explore job creation by new startups. Leveraging newly available microdata from the U.S. Census Bureau, we seek to gain deeper insights into firm survival, job creation by startups, and the transition from non-employer to employer status.
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Buyer-Seller Relationships in International Trade: Do Your Neighbors Matter?
October 2014
Working Paper Number:
CES-14-44
Using confidential U.S. customs data on trade transactions between U.S. importers and Bangladeshi exporters between 2002 and 2009, and information on the geographic location of Bangladeshi exporters, we show that the presence of neighboring exporters that previously transacted with a U.S. importer is associated with a greater likelihood of matching with the same U.S. importer for the first time. This suggests a role for business networks among trading firms in generating exporter-importer matches. Our research design also allows us to isolate potential gains from neighborhood exporter presence that are partner-specific, from overall gains previously documented in the literature.
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Interactions, Neighborhood Selection, and Housing Demand
August 2002
Working Paper Number:
CES-02-19
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.
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The Two-Income Trap:
Are Two-Earner Households More Financially Vulnerable?
June 2019
Working Paper Number:
CES-19-19
We test whether two-earner married couples are more likely to file for consumer bankruptcy in the future than similar married couples. Since two-earner households are unable to adjust their income on the extensive margin, they are more vulnerable to income shocks, and thus at risk of bankruptcy in the future. We find that two-earner married couples in 1999 are more likely to file for bankruptcy from 2002-2004 compared to other married couples. Additionally, we present supporting information that suggests that two-earner households have a higher average propensity to consume.
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Output Price And Markup Dispersion In Micro Data: The Roles Of Producer And Heterogeneity And Noise
August 1997
Working Paper Number:
CES-97-10
This paper provides empirical evidence on the extent of producer heterogeneity in the output market by analyzing output price and price-marginal cost markups at the plant level for thirteen homogeneous manufactured goods. It relies on micro data from the U.S. Census of Manufactures over the 1963-1987 period. The amount of price heterogeneity varies substantially across products. Over time, plant transition patterns indicate more persistence in the pricing of individual plants than would be generated by purely random movements. High-price and low-price plants remain in the same part of the price distribution with high frequency, suggesting that underlying time-invariant structural factors contribute to the price dispersion. For all but two products, large producers have lower output prices. Marginal cost and the markups are estimated for each plant. The markup remains unchanged or increases with plant size for all but four of the products and declining marginal costs play an important role in generating this pattern. The lower production costs for large producers are, at least partially, passed on to purchasers as lower output prices. Plants with the highest and lowest markups tend to remain so over time, although overall the persistence in markups is less than for output price, suggesting a larger role for idiosyncratic shocks in generating markup variation.
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Taking the Leap: The Determinants of Entrepreneurs Hiring their First Employee
January 2016
Working Paper Number:
CES-16-48
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.
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How Businesses Use Information Technology: Insights for Measuring Technology and Productivity
June 2006
Working Paper Number:
CES-06-15
Business use of computers in the United States dates back fifty years. Simply investing in information technology is unlikely to offer a competitive advantage today. Differences in how businesses use that technology should drive differences in economic performance. Our previous research found that one business use ' computers linked into networks ' is associated with significantly higher labor productivity. In this paper, we extend our analysis with new information about the ways that businesses use their networks. Those data show that businesses conduct a variety of general processes over computer networks, such as order taking, inventory monitoring, and logistics tracking, with considerable heterogeneity among businesses. We find corresponding empirical diversity in the relationship between these on-line processes and productivity, supporting the heterogeneity hypothesis. On-line supply chain activities such as order tracking and logistics have positive and statistically significant productivity impacts, but not processes associated with production, sales, or human resources. The productivity impacts differ by plant age, with higher impacts in new plants. This new information about the ways businesses use information technology yields vital raw material for understanding how using information technology improves economic performance.
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The Role of Technological and Industrial Heterogeneity In Technology Diffusion: a Markovian Approach
February 2003
Working Paper Number:
CES-03-07
Recent empirical studies have established the importance of intra and inter-industry heterogeneity in investment in innovation and other outcomes. This paper examines the role of industry and technology heterogeneity in the diffusion of advanced manufacturing technologies from a simple Markovian approach. Using the Maximum Entropy estimator, I estimate transition probabilities and corresponding half-lives, look for outliers in technology and industry diffusion patterns, and try to find explanations of their unusual behavior in idiosyncratic technology and industry characteristics. A consistent industry-level pattern that emerged is one that relates consumer demand and production processes. It seems that in industries where hand-made products are a sign of quality to the customer, technology spreads very slowly. On the other hand, in industries where demand for sophisticated, high-precision goods is high or in industries where demand-driven product specifications vary quite rapidly over relatively short periods of time, advanced technologies diffuse much more rapidly.
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