This paper studies how increasing teacher compensation at hard-to-staff schools can reduce inequality in access to qualifed teachers. Leveraging an unconditional change in the teacher compensation structure in Perú, we first show causal evidence that increasing salaries at less desirable locations attracts better quality applicants and improves student test scores. We then estimate a model of teacher preferences over local amenities, school characteristics, and wages using geocoded job postings and rich application data from the nationwide centralized teacher assignment system. Our estimated model suggests that the current policy is both inefficient and not large enough to effectively undo the inequality of initial conditions that hard-to-staff schools and their communities face. Counterfactual analyses that incorporate equilibrium sorting effects characterize alternative wage schedules and quantify the cost of reducing structural inequality in the allocation of teacher talent across schools.
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