How Automation Affects Allocation of Talent?

• Grant number: 24/06763-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: September 01, 2024
• Status: Discontinued
• Field of knowledge: Applied Social Sciences - Economics - Growth, Fluctuations and Economic Planning
• Principal Investigator: Fernando Antônio de Barros Júnior
• Grantee: Marcos Júnio Ribeiro
• Host Institution: Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto (FEARP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated scholarship(s): 25/03416-0 - How does Automation Affect the Allocation of Talent?, BE.EP.PD

Abstract

Automation, which involves replacing human workers with machines programmed bysoftware, is expanding in several sectors, such as banking, transport, industry andagriculture, often integrating artificial intelligence (AI) to improve the precision oftasks. The joint use of AI with human work can result in a significant increase inproductivity, automating routine tasks and allowing humans to focus on more complexand creative activities, thus driving technological advances. However, the advancementof AI also raises fears among workers about the possibility of job loss, raising importantquestions about possible negative impacts of automation on the labor market, forexample, high unemployment rates, pay inequality and talent reallocation. In thiscontext, we will develop a general equilibrium model, calibrate this model and carryout a series of counterfactual exercises to understand how AI affects the labor market.Our specific objective is to understand the impacts of automation on the demand fornew skills and qualifications, on workers' decisions to acquire new skills, on income andeconomic growth.

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

BARROS JR, FERNANDO; LEITE, WILLIAM; RIBEIRO, MARCOS. Non-linear Incentives and Intertemporal Consistency in Inflation Targeting Regimes. INTERNATIONAL ECONOMIC JOURNAL, v. N/A, p. 10-pg., 2025-03-26. (24/06763-0)