Papers written by Author(s): 'Mark J. Kutzbach'
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Viewing papers 1 through 10 of 11
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Working PaperThe Children of HOPE VI Demolitions: National Evidence on Labor Market Outcomes
November 2020
Working Paper Number:
CES-20-39
We combine national administrative data on earnings and participation in subsidized housing to study how the demolition of 160 public housing projects'funded by the HOPE VI program'affected the adult labor market outcomes for 18,500 children. Our empirical strategy compares children exposed to the program to children drawn from thousands of non-demolished projects, adjusting for observable differences using a flexible estimator that combines features of matching and regression. We find that children who resided in HOPE VI projects earn 14% more at age 26 relative to children in comparable non-HOPE VI projects. These earnings gains are strongest for demolitions in large cities, particularly in neighborhoods with higher pre-demolition poverty rates and lower pre-demolition job accessibility. There is no evidence that the labor market gains are driven by improvements in household or neighborhood environments that promote human capital development in children. Rather, subsequent improvements in job accessibility represent a likely pathway for the results.View Full Paper PDF
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Working PaperRecalculating... : How Uncertainty in Local Labor Market Definitions Affects Empirical Findings
January 2017
Working Paper Number:
CES-17-49R
This paper evaluates the use of commuting zones as a local labor market definition. We revisit Tolbert and Sizer (1996) and demonstrate the sensitivity of definitions to two features of the methodology: a cluster dissimilarity cutoff, or the count of clusters, and uncertainty in the input data. We show how these features impact empirical estimates using a standard application of commuting zones and an example from related literature. We conclude with advice to researchers on how to demonstrate the robustness of empirical findings to uncertainty in the definition of commuting zonesView Full Paper PDF
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Working PaperA Comparison of Training Modules for Administrative Records Use in Nonresponse Followup Operations: The 2010 Census and the American Community Survey
January 2017
Working Paper Number:
CES-17-47
While modeling work in preparation for the 2020 Census has shown that administrative records can be predictive of Nonresponse Followup (NRFU) enumeration outcomes, there is scope to examine the robustness of the models by using more recent training data. The models deployed for workload removal from the 2015 and 2016 Census Tests were based on associations of the 2010 Census with administrative records. Training the same models with more recent data from the American Community Survey (ACS) can identify any changes in parameter associations over time that might reduce the accuracy of model predictions. Furthermore, more recent training data would allow for the incorporation of new administrative record sources not available in 2010. However, differences in ACS methodology and the smaller sample size may limit its applicability. This paper replicates earlier results and examines model predictions based on the ACS in comparison with NRFU outcomes. The evaluation consists of a comparison of predicted counts and household compositions with actual 2015 NRFU outcomes. The main findings are an overall validation of the methodology using independent data.View Full Paper PDF
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Working PaperDeveloping a Residence Candidate File for Use With Employer-Employee Matched Data
January 2017
Working Paper Number:
CES-17-40
This paper describes the Longitudinal Employer-Household Dynamics (LEHD) program's ongoing efforts to use administrative records in a predictive model that describes residence locations for workers. This project was motivated by the discontinuation of a residence file produced elsewhere at the U.S. Census Bureau. The goal of the Residence Candidate File (RCF) process is to provide the LEHD Infrastructure Files with residence information that maintains currency with the changing state of administrative sources and represents uncertainty in location as a probability distribution. The discontinued file provided only a single residence per person/year, even when contributing administrative data may have contained multiple residences. This paper describes the motivation for the project, our methodology, the administrative data sources, the model estimation and validation results, and the file specifications. We find that the best prediction of the person-place model provides similar, but superior, accuracy compared with previous methods and performs well for workers in the LEHD jobs frame. We outline possibilities for further improvement in sources and modeling as well as recommendations on how to use the preference weights in downstream processing.View Full Paper PDF
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Working PaperTwo Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files
January 2017
Working Paper Number:
CES-17-34
Commuting flows and workplace employment data have a wide constituency of users including urban and regional planners, social science and transportation researchers, and businesses. The U.S. Census Bureau releases two, national data products that give the magnitude and characteristics of home to work flows. The American Community Survey (ACS) tabulates households' responses on employment, workplace, and commuting behavior. The Longitudinal Employer-Household Dynamics (LEHD) program tabulates administrative records on jobs in the LEHD Origin-Destination Employment Statistics (LODES). Design differences across the datasets lead to divergence in a comparable statistic: county-to-county aggregate commute flows. To understand differences in the public use data, this study compares ACS and LEHD source files, using identifying information and probabilistic matching to join person and job records. In our assessment, we compare commuting statistics for job frames linked on person, employment status, employer, and workplace and we identify person and job characteristics as well as design features of the data frames that explain aggregate differences. We find a lower rate of within-county commuting and farther commutes in LODES. We attribute these greater distances to differences in workplace reporting and to uncertainty of establishment assignments in LEHD for workers at multi-unit employers. Minor contributing factors include differences in residence location and ACS workplace edits. The results of this analysis and the data infrastructure developed will support further work to understand and enhance commuting statistics in both datasets.View Full Paper PDF
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Working PaperLabor Market Networks and Recovery from Mass Layoffs Before, During, and After the Great Recession
June 2015
Working Paper Number:
CES-15-14
We test the effects of labor market networks defined by residential neighborhoods on re-employment following mass layoffs. We develop two measures of labor market network strength. One captures the flows of information to job seekers about the availability of job vacancies at employers of workers in the network, and the other captures referrals provided to employers by other network members. These network measures are linked to more rapid re-employment following mass layoffs, and to re-employment at neighbors' employers. We also find evidence that network connections ' especially those that provide information about job vacancies ' became less productive during the Great Recession.View Full Paper PDF
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Working PaperStorms and Jobs: The Effect of Hurricanes on Individuals' Employment and Earnings over the Long Term*
January 2015
Working Paper Number:
CES-15-21R
Hurricanes Katrina and Rita devastated the U.S. Gulf Coast in 2005, destroying homes and businesses and causing mass evacuations. The economic effects of disasters are often studied at a regional level, but little is known about the responsiveness of individuals' employment and earnings to the damages, disruption, and rebuilding'particularly in the longer run. Our analysis is based on data that tracks workers over nine years, including seven years after the storms. We estimate models that compare the evolution of earnings for workers who resided in a storm-affected area with those who resided in a suitable control counties. We find that, on average, the storms reduced the earnings of affected individuals during the first year after the storm. These losses reflect various aspects of the short-run disruption caused by the hurricanes, including job separations, migration to other areas, and business contractions. Starting in the third year after the storms, however, we find that the earnings of affected individuals outpaced the earnings of individuals in the control sample. We provide evidence that the long-term earnings gains were the result of wage growth in the affected areas relative to the control areas, due to reduced labor supply and increased labor demand, especially in sectors related to rebuilding. Despite the short-term earnings losses, we find a net increase in average quarterly earnings among affected individuals over the entire post-storm period. However, those who worked in sectors closely tied to tourism or the size of the local population experienced net earnings losses.View Full Paper PDF
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Working PaperDesign Comparison of LODES and ACS Commuting Data Products
October 2014
Working Paper Number:
CES-14-38
The Census Bureau produces two complementary data products, the American Community Survey (ACS) commuting and workplace data and the Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES), which can be used to answer questions about spatial, economic, and demographic questions relating to workplaces and home-to-work flows. The products are complementary in the sense that they measure similar activities but each has important unique characteristics that provide information that the other measure cannot. As a result of questions from data users, the Census Bureau has created this document to highlight the major design differences between these two data products. This report guides users on the relative advantages of each data product for various analyses and helps explain differences that may arise when using the products.2,3 As an overview, these two data products are sourced from different inputs, cover different populations and time periods, are subject to different sets of edits and imputations, are released under different confidentiality protection mechanisms, and are tabulated at different geographic and characteristic levels. As a general rule, the two data products should not be expected to match exactly for arbitrary queries and may differ substantially for some queries. Within this document, we compare the two data products by the design elements that were deemed most likely to contribute to differences in tabulated data. These elements are: Collection, Coverage, Geographic and Longitudinal Scope, Job Definition and Reference Period, Job and Worker Characteristics, Location Definitions (Workplace and Residence), Completeness of Geographic Information and Edits/Imputations, Geographic Tabulation Levels, Control Totals, Confidentiality Protection and Suppression, and Related Public-Use Data Products. An in-depth data analysis'in aggregate or with the microdata'between the two data products will be the subject of a future technical report. The Census Bureau has begun a pilot project to integrate ACS microdata with LEHD administrative data to develop an enhanced frame of employment status, place of work, and commuting. The Census Bureau will publish quality metrics for person match rates, residence and workplace match rates, and commute distance comparisons.View Full Paper PDF
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Working PaperChildhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing
January 2013
Working Paper Number:
CES-13-48RR
To date, research on the long-term effects of childhood participation in voucher-assisted and public housing has been limited by the lack of data and suitable identification strategies. We create a national level longitudinal data set that enables us to analyze how children's housing experiences affect adult earnings and incarceration rates. While naive estimates suggest there are substantial negative consequences to childhood participation in voucher assisted and public housing, this result appears to be driven largely by selection of households into housing assistance programs. To mitigate this source of bias, we employ household fixed-effects specifications that use only within-household (across-sibling) variation for identification. Compared to naive specifications, household fixed-effects estimates for earnings are universally more positive, and they suggest that there are positive and statistically significant benefits from childhood residence in assisted housing on young adult earnings for nearly all demographic groups. Childhood participation in assisted housing also reduces the likelihood of incarceration across all household race/ethnicity groups. Time spent in voucher-assisted or public housing is especially beneficial for females from non-Hispanic Black households, who experience substantial increases in expected earnings and lower incarceration rates.View Full Paper PDF
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Working PaperDo Labor Market Networks Have An Important Spatial Dimension?
September 2012
Working Paper Number:
CES-12-30
We test for evidence of spatial, residence-based labor market networks. Turnover is lower for workers more connected to their neighbors generally and more connected to neighbors of the same race or ethnic group. Both results are consistent with networks producing better job matches, while the latter could also reflect preferences for working with neighbors of the same race or ethnicity. For earnings, we find a robust positive effect of the overall residence-based network measure, whereas we usually find a negative effect of the same-group measure, suggesting that the overall network measure reflects productivity enhancing positive network effects, while the same-group measure captures a non-wage amenity.View Full Paper PDF
