This paper studies how increasing teacher compensation at hard-to-staff schools can reduce inequality in access to qualified teachers. Leveraging an unconditional change in the structure of teacher compensation in Per ́u, we first show causal evidence that increasing salaries at less desirable locations attracts teachers who score 0.45 standard deviations higher in standardized competency tests, leading to an average increase in student test scores of 0.33-0.38 standard deviations. 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. A policy that sets compensation at each job posting taking into account teacher preferences is more cost-effective than the actual policy in terms of reducing structural inequality in access to learning opportunities, and it possibly enhances the efficiency of the education system.