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Abstract: The present paper provides an ample view of employment transitions and their relation to workers' skills in Brazil using a random sample from the universe of formal labor contracts to follow workers between 2003 and 2018. We propose a novel procedure to derive internationally comparable skill measures from occupations' task descriptions in the country under analysis based on machine learning and natural language processing methods, but without usual ad hoc classifications. Our findings confirm that workers who use non-routine cognitive skills intensively experience the highest employment growth rates and wages. Their labor market exit risk is relatively low, occupational and sectoral changes are least common, and in the case of occupational switching, non-routine cognitive workers tend to find closer, higher-paid occupations. In terms of these characteristics, routine and non-routine manual workers are worse off in the labor market. Overall, there are signs of routine biased technological change and employment polarization since the recent recession.

Presenters: Willian Admaczyk; Philipp Ehrl and Leonardo Monasterio
Discussant: Aguinaldo Maciente
Chair: Janine Berg

Bios

Willian Adamczyk:
Willian Adamczyk holds a Ph.D. in Economics from the Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS, Porto Alegre). He works as a research coordinator at Evidence Express in the National School of Public Management (ENAP, Brasília).

Philipp Ehrl:
Philipp is professor of Economics at the Catholic University of Brasília (UCB) since 2016. He is currently research fellow at the Institute of Applied Economic Research (IPEA), the National Research Consil (CNPq) and project consultant at the of Illinois at Chicago. He is editor of the Brazilian Journal of Business Economics (RBEE). He holds a degree and a master's degree and PhD in Economics from the University of Passau, Germany. He worked as a research assistant of International Economics at the Universities of Passau and Würzburg (Germany). His areas of interest are regional economics, labor economics and public policy evaluation. He has publications in economic journals, including Regional Science and Urban Economics, Journal of Regional Science, Oxford Economic Papers, Journal of Economic Behavior and Organization, among others.

Leonardo Monasterio: 
Leonardo Monasterio is a researcher at Ipea (Brazil) and professor at IDP - Brasília. He was a visiting professor at the University of London (2006-2007) and a visiting researcher at UCLA's Department of Economics (2015-2016). Between 2019 and 2022, he was the head of Data Science at the National School of Public Administration (ENAP)