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ABSTRACT
This study examines the early impact of a Local Self-Sufficiency (LSS) program of the Housing Authority of Champaign County (HACC), Illinois, on recipients’ total annual household income and earnings, and employment. In 2013, HACC, through LSS, mandated work requirements for households with working-age, able-bodied adult members and imposed sanctions on those who did not meet the program requirements. We find that, between 2012 and 2014, the LSS program led to an average increase of $2,283 in earnings for an individual household. In aggregate, this allowed HACC to serve an additional 98 (9%) LSS-eligible households for a year. Also, LSS-eligible households experienced an increase in the employment–adult ratio by 11.6 percentage points. The LSS program also had a larger impact for more economically disadvantaged households with no prior work history.
Disclosure Statement
No potential conflict of interest was reported by the authors.
Notes
1. Exiters are FSS program participants who exited before graduating, forfeiting their escrow. Silva et al. (Citation2011) find that nearly one fourth of the participants graduated from the FSS program whereas more than one third left the program without completing their FSS contracts.
2. We carefully determine pretreatment control covariates through iterating PSM estimations and matching results. First, there exists no consensus on neighborhood characteristics that should be included in the estimation to control for heterogeneous regional effects. Studies subjectively choose the types and number of characteristics. On the other hand, including too many extraneous variables would create issues of overparameterization in the PSM estimation, which exacerbates the common support problem as well as increases variance of the estimates (Bryson, Dorsett, & Purdon, Citation2002; Caliendo & Kopeinig, Citation2008). Initially, we run the PSM regressions, using a set of neighborhood characteristics in addition to household characteristics and lagged variables, and observe that the model’s matching quality falls outside of the acceptable range when adding more than two neighborhood characteristics. Also, even though the matching results are acceptable, many intervention group observations are dropped because of the common support condition. Based on the data and matching estimation, we decided to include the poverty rates variable that represents the region’s overall characteristics. Additionally, although we acknowledge that the type of housing assistance can be an important factor affecting recipients’ labor-market outcomes, we did not include the variable in the matching estimation, for the same reason as above. The key difference between the HCV program and public housing is the former’s flexibility in mobility. Specifically, during the analysis period, the HCV recipients could move to another location if rent affordability and housing quality standards were met, whereas public housing residents could not. We attempt to control for the effect of changing neighborhoods over time by adding census-tract level dummy variables in regressions reported in .
3. We first run a mixed-effects probit model with the dependent variable of a nonattrition dummy on a set of preintervention covariates and predict the fitted probabilities, using the full sample in the baseline year. We then invert the fitted values. Sample weights from PSM are applied to the regressions.
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Notes on contributors
Han Bum Lee
Dr. Han Bum Lee is a postdoctoral research fellow, conducting an evaluation of the impact of economic self-sufficiency programs that HACC has implemented under the MTW demonstration on a wide range of outcomes including residential locations, economic outcomes, educational attainment, physical and mental health, social capital, and food security. He holds a PhD from the Department of Agricultural and Consumer Economics at the University of Illinois at Urbana-Champaign. His research interests include impact evaluation, public policy, and rural development.
Paul E. McNamara
Dr. Paul E. McNamara is an associate professor in the Department of Agricultural and Consumer Economics at the University of Illinois, and the principal investigator of the evaluation of the Housing Authority of Champaign County’s Moving to Work program. He holds a master’s degree in public policy from the Harvard Kennedy School and a PhD from the Department of Applied Economics at the University of Minnesota. His research interests include consumer economics and health economics, the economics of development, and public program management and evaluation.