This study examines the causal effect of housing wealth on labor supply using restricted geographic data from the Survey of Income and Program Participation (SIPP). The analysis employs a novel household-level instrument that measures the duration of homeowners' exposure to housing market booms driven by credit expansion in housing supply-constrained areas, leveraging cross-household variation in both the timing and location (counties) of home purchases. Housing wealth negatively affects women's labor supply, a 1% increase lowers participation by 0.098 pp, but shows no significant effect for men. This negative wealth effectamong female workers is driven primarily by childcare responsibilities and human capital investment, as it is strongest among mothers of young children and those who report child-related reasons for not working. Other potential mechanisms, such as income effects, precautionary saving, or liquidity constraints, do not seem to fully explain the negative association.
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Playing with Matches: An Assessment of Accuracy in Linked Historical Data
June 2016
Working Paper Number:
carra-2016-05
This paper evaluates linkage quality achieved by various record linkage techniques used in historical demography. I create benchmark, or truth, data by linking the 2005 Current Population Survey Annual Social and Economic Supplement to the Social Security Administration's Numeric Identification System by Social Security Number. By comparing simulated linkages to the benchmark data, I examine the value added (in terms of number and quality of links) from incorporating text-string comparators, adjusting age, and using a probabilistic matching algorithm. I find that text-string comparators and probabilistic approaches are useful for increasing the linkage rate, but use of text-string comparators may decrease accuracy in some cases. Overall, probabilistic matching offers the best balance between linkage rates and accuracy.
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Reallocation and Productivity Dynamics in the Appalachian Region
January 2006
Working Paper Number:
CES-06-03
The Appalachian Region has long suffered from poor economic performance as measured over a variety of dimensions. Even as the region has improved over the last few decades, Appalachia still lags behind the nation. A growing body of empirical work has found that reallocation is pervasive in the U.S. economy and is an integral component of economic growth. Productivity growth is improved when resources are shifted from less productive establishments towards more productive establishments either through changes in existing establishments or through the births and deaths of establishments. Establishments that use new products, technologies, and production processes replace establishments that do not in a continual process of creative destruction. Using establishment-level data, this paper examines the reallocation and productivity dynamics of the Appalachian Region. The first part of the paper compares the reallocation dynamics of Appalachia to the rest of the U.S. using a newly developed establishment-level database that covers virtually the entire U.S. economy. From this analysis, it is apparent that establishment birth and death rates and job creation and destruction rates for Appalachia are consistently below those for the rest of the U.S.. The second part of the paper uses data from the Economic Censuses to determine whether the establishment and employment dynamics of the Appalachian Region are also qualitatively different (in terms of their productivity rankings) from their U.S. counterparts. It appears that the North subregion of Appalachia has reallocation and productivity dynamics that are consistent with an impeded creative destruction story.
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Patents, Innovation, and Market Entry
September 2023
Working Paper Number:
CES-23-45
Do patents facilitate market entry and job creation? Using a 2014 Supreme Court decision that limited patent eligibility and natural language processing methods to identify invalid patents, I find that large treated firms reduce job creation and create fewer new establishments in response, with no effect on new firm entry. Moreover, companies shift toward innovation aimed at improving existing products consistent with the view that patents incentivize creative destruction.
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How Does Venture Capital Financing Improve Efficiency in Private Firms? A Look Beneath the Surface
June 2008
Working Paper Number:
CES-08-16
Using a unique sample from the Longitudinal Research Database (LRD) of the U.S. Census Bureau, we study several related questions regarding the efficiency gains generated by venture capital (VC) investment in private firms. First, does VC backing improve the efficiency (total factor productivity, TFP) of private firms, and are certain kinds of VCs (higher reputation versus lower reputation) better at generating such efficiency gains than others? Second, how are such efficiency gains generated: Do venture capitalists invest in more efficient firms to begin with (screening) or do they improve efficiency after investment (monitoring)? Third, how are these efficiency gains spread out over rounds subsequent to VC investment? Fourth, what are the channels through which such efficiency gains are generated: increases in product market performance (sales) or reductions in various costs (labor, materials, total production costs)? Finally, how do such efficiency gains affect the probability of a successful exit (IPO or acquisition)? Our main findings are as follows. First, the overall efficiency of VC backed firms is higher than that of non-VC backed firms. Second, this efficiency advantage of VC backed firms arises from both screening and monitoring: the efficiency of VC backed firms prior to receiving financing is higher than that of non-VC backed firms and further, the growth in efficiency subsequent to receiving VC financing is greater for such firms relative to non-VC backed firms. Third, the above increase in efficiency of VC backed firms relative to non-VC backed firms increases over the first two rounds of VC financing, and remains at the higher level till exit. Fourth, while the TFP of firms prior to VC financing is lower for higher reputation VC backed firms, the increase in TFP subsequent to financing is significantly higher for the former firms, consistent with higher reputation VCs having greater monitoring ability. Fifth, the efficiency gains generated by VC backing arise primarily from improvement in product market performance (sales); however for higher reputation VCs, the additional efficiency gains arise from both an additional improvement in product market performance as well as from reductions in various input costs. Finally, both the level of TFP of VC backed firms prior to receiving financing and the growth in TFP subsequent to VC financing positively affect the probability of a successful exit (IPO or acquisition).
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Establishment and Employment Dynamics in Appalachia: Evidence from the Longitudinal Business Database
December 2003
Working Paper Number:
CES-03-19
One indicator of the general economic health of a region is the rate at which new jobs are created. The newly developed Longitudinal Business Database has been used in this paper to develop a detailed portrait of establishment formation and attrition and job creation and destruction in the Appalachian Region. The foremost finding is that the pace of reallocation in Appalachia is lower than it is for the U.S.. This is evident in Appalachia's relatively lower establishment birth and death rates and job creation and destruction rates. For example, on average over the study time period, the U.S. job creation rate exceeds 45 percent, while the Appalachian job creation rate is 43 percent. Similarly, the U.S. job destruction rate is about 35 percent, while the Appalachian job destruction rate is about 33 percent. Even when controlling for other differences, job creation rates are 1.2 percentage points lower and job destruction rates are 3.4 percentage points lower in Appalachia relative to the rest of the U.S. Another indicator of the general economic health of a region is the quality of its jobs. The quality of jobs is measured in this paper by the average wage paid at the establishment. Here too there is cause for concern about the economic health of Appalachia. The analysis shows that wages are about 10 percent lower in Appalachia than in the U.S. even when controlling for differences in other characteristics across the two areas. This wage discrepancy has not narrowed over the time of the study. Moreover, new establishments have a similar wage gap. Employees at new establishments earn wages 10 percent less than at new establishments in the rest of the U.S.
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Estimating the Distribution of Plant-Level Manufacturing Energy Efficiency with Stochastic Frontier Regression
March 2007
Working Paper Number:
CES-07-07
A feature commonly used to distinguish between parametric/statistical models and engineering models is that engineering models explicitly represent best practice technologies while the parametric/statistical models are typically based on average practice. Measures of energy intensity based on average practice are less useful in the corporate management of energy or for public policy goal setting. In the context of company or plant level energy management, it is more useful to have a measure of energy intensity capable of representing where a company or plant lies within a distribution of performance. In other words, is the performance close (or far) from the industry best practice? This paper presents a parametric/statistical approach that can be used to measure best practice, thereby providing a measure of the difference, or 'efficiency gap' at a plant, company or overall industry level. The approach requires plant level data and applies a stochastic frontier regression analysis to energy use. Stochastic frontier regression analysis separates the energy intensity into three components, systematic effects, inefficiency, and statistical (random) error. The stochastic frontier can be viewed as a sub-vector input distance function. One advantage of this approach is that physical product mix can be included in the distance function, avoiding the problem of aggregating output to define a single energy/output ratio to measure energy intensity. The paper outlines the methods and gives an example of the analysis conducted for a non-public micro-dataset of wet corn refining plants.
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Examining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.
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Changing Opportunity: Sociological Mechanisms Underlying Growing Class Gaps and Shrinking Race Gaps in Economic Mobility
July 2024
Working Paper Number:
CES-24-38
We show that intergenerational mobility changed rapidly by race and class in recent decades and use these trends to study the causal mechanisms underlying changes in economic mobility. For white children in the U.S. born between 1978 and 1992, earnings increased for children from high-income families but decreased for children from low-income families, increasing earnings gaps by parental income ('class') by 30%. Earnings increased for Black children at all parental income levels, reducing white- Black earnings gaps for children from low-income families by 30%. Class gaps grew and race gaps shrank similarly for non-monetary outcomes such as educational attainment, standardized test scores, and mortality rates. Using a quasi-experimental design, we show that the divergent trends in economic mobility were caused by differential changes in childhood environments, as proxied by parental employment rates, within local communities defined by race, class, and childhood county. Outcomes improve across birth cohorts for children who grow up in communities with increasing parental employment rates, with larger effects for children who move to such communities at younger ages. Children's outcomes are most strongly related to the parental employment rates of peers they are more likely to interact with, such as those in their own birth cohort, suggesting that the relationship between children's outcomes and parental employment rates is mediated by social interaction. Our findings imply that community-level changes in one generation can propagate to the next generation and thereby generate rapid changes in economic mobility.
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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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Residual Claims and Incentives in Restaurant Chains
July 2006
Working Paper Number:
CES-06-18
I examine the relationship between ownership and production activities using a new dataset of restaurant chains. Production in restaurant chains provides an opportunity to examine the effects of residual claims on incentives because production is decentralized and fairly uniform across restaurants in the same chain. Yet the allocation of residual claims varies between company-owned and franchised units, affecting the strength of incentives for restaurantlevel activities. The decision to own or franchise each restaurant reflects the value of either withholding or allocating residual claims for performing these activities. I find that more complex production activities are systematically correlated with company ownership. Onsite food production raises the likelihood of company ownership by 28% relative to offsite food production. Table service raises the likelihood of company ownership by 26% relative to counter service. The results are not consistent with straightforward effort-promoting effects of residual claims in simple principal agent models. They are consistent with the view that residual claims can generate unbalanced incentives across diverse tasks.
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