Luis Monroy-Gómez-Franco

Roberto Vélez Grajales

Luis Felipe López-Calva

Documento de trabajo CEEY no. 08 / 2021

This paper use a new database for Mexico to model the possible long-run effects of the pandemic on learning. First, based on the framework of Neidhöfer et al. (2021), the authors estimate the loss of schooling due to the transition from in-person to remote learning using data from the ESRU Survey on Social Mobility in Mexico 2017 (ESRU-EMOVI-2017), census data and national statistics of COVID-19 incidence. Secondly, the authors estimate the potential long-run consequences of this shock through a calibrated learning profile for five Mexican regions following Kaffenberger and Pritchett (2021). Assuming the distance learning policy adopted by the Mexican government is entirely effective, the 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.