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A FIRST STEP TOWARDS A GERMAN SYNLBD: CONSTRUCTING A GERMAN LONGITUDINAL BUSINESS DATABASE
February 2014
Working Paper Number:
CES-14-13
One major criticism against the use of synthetic data has been that the efforts necessary to generate useful synthetic data are so in- tense that many statistical agencies cannot afford them. We argue many lessons in this evolving field have been learned in the early years of synthetic data generation, and can be used in the development of new synthetic data products, considerably reducing the required in- vestments. The final goal of the project described in this paper will be to evaluate whether synthetic data algorithms developed in the U.S. to generate a synthetic version of the Longitudinal Business Database (LBD) can easily be transferred to generate a similar data product for other countries. We construct a German data product with infor- mation comparable to the LBD - the German Longitudinal Business Database (GLBD) - that is generated from different administrative sources at the Institute for Employment Research, Germany. In a fu- ture step, the algorithms developed for the synthesis of the LBD will be applied to the GLBD. Extensive evaluations will illustrate whether the algorithms provide useful synthetic data without further adjustment. The ultimate goal of the project is to provide access to multiple synthetic datasets similar to the SynLBD at Cornell to enable comparative studies between countries. The Synthetic GLBD is a first step towards that goal.
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LOOKING BACK ON THREE YEARS OF USING THE SYNTHETIC LBD BETA
February 2014
Working Paper Number:
CES-14-11
Distributions of business data are typically much more skewed than those for household or individual data and public knowledge of the underlying units is greater. As a results, national statistical offices (NSOs) rarely release establishment or firm-level business microdata due to the risk to respondent confidentiality. One potential approach for overcoming these risks is to release synthetic data where the establishment data are simulated from statistical models designed to mimic the distributions of the real underlying microdata. The US Census Bureau's Center for Economic Studies in collaboration with Duke University, the National Institute of Statistical Sciences, and Cornell University made available a synthetic public use file for the Longitudinal Business Database (LBD) comprising more than 20 million records for all business establishment with paid employees dating back to 1976. The resulting product, dubbed the SynLBD, was released in 2010 and is the first-ever comprehensive business microdata set publicly released in the United States including data on establishments employment and payroll, birth and death years, and industrial classification. This pa- per documents the scope of projects that have requested and used the SynLBD.
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RANDOMIZED SAFETY INSPECTIONS AND RISK EXPOSURE ON THE JOB: QUASI-EXPERIMENTAL ESTIMATES OF THE VALUE OF A STATISTICAL LIFE
January 2014
Working Paper Number:
CES-14-05
Compensating wages for workplace fatality and accident risks are used to infer the value of a statistical life (VSL), which in turn is used to assess the benefits of human health and safety regulations. The estimation of these wage differentials, however, has been plagued by measurement error and omitted variables. This paper employs the first quasi-experimental design within a labor market setting to overcome such limitations in the ex-tant literature. Specifically, randomly assigned, exogenous federal safety inspections are used to instrument for plant-level risks and combined with confidential U.S. Census data on manufacturing employment to estimate the VSL using a difference-in-differences framework. The VSL is estimated to be between $2 and $4 million ($2011), suggesting prior studies may substantially overstate the value workers place on safety, and therefore, the benefits of health and safety regulations.
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HUMAN CAPITAL LOSS IN CORPORATE BANKRUPTCY
July 2013
Working Paper Number:
CES-13-37
This paper quantifies the 'human costs of bankruptcy' by estimating employee wage losses induced by the bankruptcy filing of employers using employee-employer matched data from the U.S. Census Bureau's LEHD program. We find that employee wages begin to deteriorate one year prior to bankruptcy. One year after bankruptcy, the magnitude of the decline in annual wages is 30% of pre-bankruptcy wages. The decrease in wages persists (at least) for five years post-bankruptcy. The present value of wage losses summed up to five years after bankruptcy amounts to 29-49% of the average pre-bankruptcy market value of firm. Furthermore, we find that the ex-ante wage premium to compensate for the ex-post wage loss due to bankruptcy can be of similar magnitude with that of the tax benefits of debt.
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WHY IMMIGRANTS LEAVE NEW DESTINATIONS AND WHERE DO THEY GO?
June 2013
Working Paper Number:
CES-13-32
Immigrants have a markedly higher likelihood of migrating internally if they live in new estinations. This paper looks at why that pattern occurs and at how immigrants' out-migration to new versus traditional destinations responds to their labor market economic and industrial structure, nativity origins and concentration, geographic region, and 1995 labor market type. Confidential data from the 2000 and 1990 decennial censuses are used for the analysis. Metropolitan and non-metropolitan areas are categorized into 741 local labor markets and classified as new or traditional based on their nativity concentrations of immigrants from the largest Asian, Caribbean and Latin American origins. The analysis showed that immigrants were less likely to migrate to new destinations if they lived in areas of higher nativity concentration, foreign-born population growth, and wages but more likely to make that move if they were professionals, agricultural or blue collar workers, highly educated, fluent in English, and lived in other new destinations. While most immigrants are more likely to migrate to new rather than traditional destinations that outcome differs sharply for immigrants from different origins and for some immigrants, particularly those from the Caribbean, the dispersal process to new destinations has barely started.
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HUMAN CAPITAL TRAPS? ENCLAVE EFFECTS USING LINKED EMPLOYER-HOUSEHOLD DATA
June 2013
Working Paper Number:
CES-13-29
This study uses linked employer-household data to measure the impact of immigrant social networks, as identified via neighborhood and workplace affiliation, on immigrant earnings. Though ethnic enclaves can provide economic opportunities through job creation and job matching, they can also stifle the assimilation process by limiting interactions between enclave members and non-members. I find that higher residential and workplace ethnic clustering among immigrants is consistently correlated with lower earnings. For immigrants with a high school education or less, these correlations are primarily due to negative self-selection. On the other hand, self-selection fails to explain the lower earnings associated with higher ethnic clustering for immigrants with post-secondary schooling. The evidence suggests that co-ethnic clustering has no discernible effect on the earnings of immigrants with lower education, but may be leading to human capital traps for immigrants who have more than a high school education.
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COMMUNITY DETERMINANTS OF IMMIGRANT SELF-EMPLOYMENT: HUMAN CAPITAL SPILLOVERS AND ETHNIC ENCLAVES
April 2013
Working Paper Number:
CES-13-21
I find evidence that human capital spillovers have positive effects on the proclivity of low human capital immigrants to self-employ. Human capital spillovers within an ethnic community can increase the self-employment propensity of its members by decreasing the costs associated with starting and running a business (especially, transaction costs and information costs). Immigrants who do not speak English and those with little formal education are more likely to be self-employed if they reside in an ethnic community boasting higher human capital. On the other hand, the educational attainment of co-ethnics does not appear to affect the self-employment choices of immigrants with a post-secondary education to become self-employed. Further analysis suggests that immigrants in communities with more human capital choose industries that are more capital-intensive. Overall, the results suggest that the communities in which immigrants reside influences their self-employment decisions. For low-skilled immigrants who face high costs to learning English and/or acquiring more education, these human capital spillovers may serve as an alternative resource of information and labor mobility.
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Dynamically Consistent Noise Infusion and Partially Synthetic Data as Confidentiality Protection Measures for Related Time Series
July 2012
Working Paper Number:
CES-12-13
The Census Bureau's Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job flows, tabulated by worker characteristics in various combinations. The data are released for several levels of NAICS industries and geography, the lowest aggregation of the latter being counties. Disclosure avoidance methods are required to protect the information about individuals and businesses that contribute to the underlying data. The QWI disclosure avoidance mechanism we describe here relies heavily on the use of noise infusion through a permanent multiplicative noise distortion factor, used for magnitudes, counts, differences and ratios. There is minimal suppression and no complementary suppressions. To our knowledge, the release in 2003 of the QWI was the first large-scale use of noise infusion in any official statistical product. We show that the released statistics are analytically valid along several critical dimensions { measures are unbiased and time series properties are preserved. We provide an analysis of the degree to which confidentiality is protected. Furthermore, we show how the judicious use of synthetic data, injected into the tabulation process, can completely eliminate suppressions, maintain analytical validity, and increase the protection of the underlying confidential data.
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LEHD Data Documentation LEHD-OVERVIEW-S2008-rev1
December 2011
Working Paper Number:
CES-11-43
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Firm Market Power and the Earnings Distribution
December 2011
Working Paper Number:
CES-11-41
Using the Longitudinal Employer Household Dynamics (LEHD) data from the United States Census Bureau, I compute firm-level measures of labor market (monopsony) power. To generate these measures, I extend the dynamic model proposed by Manning (2003) and estimate the labor supply elasticity facing each private non-farm firm in the US. While a link between monopsony power and earnings has traditionally been assumed, I provide the first direct evidence of the positive relationship between a firm\'s labor supply elasticity and the earnings of its workers. I also contrast the semistructural method with the more traditional use of concentration ratios to measure a firm\'s labor market power. In addition, I provide several alternative measures of labor market power which account for potential threats to identification such as endogenous mobility. Finally, I construct a counterfactual earnings distribution which allows the effects of firm market power to vary across the earnings distribution. I estimate the average firm\'s labor supply elasticity to be 1.08, however my findings suggest there to be significant variability in the distribution of firm market power across US firms, and that dynamic monopsony models are superior to the use of concentration ratios in evaluating a firm\'s labor market power. I find that a one-unit increase in the labor supply elasticity to the firm is associated with wage gains of between 5 and 18 percent. While nontrivial, these estimates imply that firms do not fully exercise their labor market power over their workers. Furthermore, I find that the negative earnings impact of a firm\'s market power is strongest in the lower half of the earnings distribution, and that a one standard deviation increase in firms\' labor supply elasticities reduces the variance of the earnings distribution by 9 percent.
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