Texas informal housing communities and human capital : school-to-work and wage dynamics of colonia student populations
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In the urban periphery of Texas border cities, many families reside in informal housing in developments known as colonias. The low value lots and lax regulatory standards that exist in such exurban jurisdictions foster incremental and self-help homebuilding, thus attracting large numbers of poor Hispanics who face affordability and discriminatory constraints in the traditional housing market. This flexible building pattern provides a practical means of affordable homeownership, but often leads to substandard housing especially during the early stages of lot acquisition. Residents face a multitude of economic and social challenges, yet investigations of human capital have largely escaped the literature. This mixed-methods research fills this void. First, through survey fieldwork, I document the current socioeconomic conditions faced by residents living under self-help housing. Second, I link Texas education and industry administrative records over a span of 19 years to retrospectively assess colonia students’ high school, higher education and labor market outcomes, and whether residential disconnection adversely impacts their postsecondary transitions and peak wages. The fieldwork demonstrates that the most apparent constraint facing colonia families is the shortage of income which is inexorably linked to little parental formal education, severe housing and health problems, and high levels of job, income and food insecurity. Summary statistics and sequential logit models highlight the importance of high school technical training and community colleges as a stepping stone into employment for colonia students. The education models also provide insight that the negative effects of living in the fringes of cities are nullified when a priori differences are minimized, a surprising yet encouraging result. The converse is true for labor – residential isolation has an adverse effect on earnings, even when compared to Texas students with similar characteristics. However, when the lasso regression is applied to isolate the parsimonious set of variables that best explains the variation in peak wages, geographic disconnection is a statistically significant but relatively weak factor. The lasso instead finds that labor market experience, the start wage, sector employment (i.e., in oil & gas), education, and gender are much more influential variables, and suggests a strong gender wage gap that grows over time.