In this paper, we use a new database for Mexico to model the possible long-run effects of the pandemic on learning. First, based on the framework of Neidhöffer, Lustig, and Tommasi (2021), we estimate the loss of schooling due to the transition from in-person to remote learning using data from the National Survey on Social Mobility (ESRU-EMOVI-2017), census data, and national statistics of COVID-19 incidence. In this estimation, we account for the attenuation capacity of households by considering the parental educational attainment and the economic resources available to the household in the calculation of the short-run cost. Secondly, we estimate the potential long-run consequences of this shock through a calibrated learning profile for five Mexican regions following Kaffenberger and Pritchett (2020). Assuming the distance learning policy adopted by the Mexican government is entirely effective, our results indicate that a learning loss equivalent to the learning during a third of a school year in the short run translates into a learning loss equivalent to an entire school year further up the educational career of students. On the other hand, if the policy was ineffective, the short-run loss increases to an entire school year and becomes a loss of two years of learning in the long run. Our results suggest substantial variation at the regional level, with the most affected region, the South experiencing a loss thrice as large as that of the least affected region, the Centre region
