Mark J. Kutzbach

Do Labor Market Networks Have an Important Spatial Dimension

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 may capture a non-wage amenity.

Job Displacement and the Duration of Joblessness: The Role of Spatial Mismatch

This paper presents a new approach to the measurement of the effects of spatial mismatch that takes advantage of matched employer-employee administrative data integrated with a person-specific job accessibility measure, as well as demographic and neighborhood characteristics. The basic hypothesis is that if spatial mismatch is present, then improved accessibility to appropriate jobs should shorten the duration of unemployment. We focus on lower-income workers with strong labor force attachment searching for employment after being subject to a mass layoff – thereby focusing on a group of job searchers that are plausibly searching for exogenous reasons. We construct person-specific measures of job accessibility based upon an empirical model of transport modal choice and network travel-time data, giving variation both across neighborhoods in nine metropolitan areas, as well as across neighbors. Our results support the spatial mismatch hypothesis. We find that better job accessibility significantly decreases the duration of joblessness among lower-paid displaced workers. Blacks, females, and older workers are more sensitive to job accessibility than other subpopulations.

Childhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing

To date, research on the long-term effects of childhood participation in voucher-assisted and public housing has been limited by the lack of appropriate data and suitable identification strategies. We create a new, national-level longitudinal data set on housing assistance and labor market earnings to explore how children’s housing affects their later earnings. While naive estimates suggest there are substantial negative long-term consequences to childhood participation in voucher-assisted and public housing, these relationships appear to be driven largely by negative selection 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 are more positive for all demographic groups and, for some groups, positive and statistically significant. Black non-Hispanic females, in particular, benefit from time spent in both voucher-assisted and public housing. Exploiting the between sibling variation accounts for unobserved time-invariant family attributes that may influence outcomes but does not address time varying within household factors that may be at work. We use a number of strategies to address these issues and find our results are results are largely robust to these concerns.

Storms and Jobs: The Effect of Hurricanes on Individuals’ Employment and Earnings over the Long Term*

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.

Labor Market Networks and Recovery from Mass Layoffs Before, During, and After the Great Recession

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.