A Logistic Regression Analysis to Assist Welfare Recipients Attaining Employment

Jorge Zumaeta

The Journal of Social Sciences Research, 2021, vol. 7, issue 2, 75-91

Abstract: This study reports on an experiment using logistic regression to uncover the preponderant factors influencing the likelihood of attaining employment by a welfare recipient in Broward County, Florida. Our study considers whether profiling the participants and tailoring the workforce development services based on their respective profiles can increase their likelihood of finding employment (Black et al., 2003). The study finds that our econometric model predicted the probability of employment with reasonably strong reliability. This finding is in alignment with the Welfare Profiling Model of Michigan’s (Barnow et al., 2012; Eberts, 1997;2002) and the Factors Influencing AFDC Duration and Labor Market Outcomes Research Study of Texas (Schexnayder et al., 1991). More specifically, the results indicate that education and prior employment history are significant factors increasing the likelihood of departing from welfare and achieving employment. Furthermore, the study concludes that the number of children, participant’s age, and the ethnicity of the welfare recipient also play a role in breaking away from welfare.  The results from the experiment show that using the econometric model to assign services to individuals increases the likelihood of finding employment from 11% to 24% on average. This is a very encouraging finding since it motivates researchers to perform further research in this area of study.

Keywords: Demographics; Labor economics; Labor policy; Workforce development; Welfare policy. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:arp:tjssrr:2021:p:75-91

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