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Intensity of labor shocks behind the changes in Brazilian hours worked during the pandemic

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  • da Silva, Nelson
  • Caetano, Sidney

Abstract

COVID-19 has impacted the labor market in multiple ways, including by reducing the number of hours effectively worked. A study on the US economy found that two-thirds of the drop in the aggregate growth rate of hours worked was due to a labor supply shock. This paper quantifies the role of labor supply and labor demand shocks in Brazil’s labor market behavior during the COVID-19 period by estimating a Bayesian Structural Vector Autoregression (BVAR) with sign restrictions on the slopes of the labor supply and labor demand curves. Our results show that labor demand shocks were more important than labor supply shocks in explaining the decline in hours effectively worked. The prominence of labor demand shocks in Brazil is an exciting result that demonstrates the heterogeneous impacts of similar shocks on high- and middle-income economies.

Suggested Citation

  • da Silva, Nelson & Caetano, Sidney, 2024. "Intensity of labor shocks behind the changes in Brazilian hours worked during the pandemic," Economic Modelling, Elsevier, vol. 131(C).
    • Handle: RePEc:eee:ecmode:v:131:y:2024:i:c:s0264999323004352
    DOI: 10.1016/j.econmod.2023.106623
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    References listed on IDEAS

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    1. Baumeister, Christiane & Hamilton, James D., 2018. "Inference in structural vector autoregressions when the identifying assumptions are not fully believed: Re-evaluating the role of monetary policy in economic fluctuations," Journal of Monetary Economics, Elsevier, vol. 100(C), pages 48-65.
    2. Laura Alfaro & Oscar Becerra & Marcela Eslava, 2020. "EMEs and COVID-19: Shutting Down in a World of Informal and Tiny Firms," NBER Working Papers 27360, National Bureau of Economic Research, Inc.
    3. Valentina Flamini & Mr. Frederik G Toscani, 2021. "The Short-Term Impact of COVID-19 on Labor Markets, Poverty and Inequality in Brazil," IMF Working Papers 2021/066, International Monetary Fund.
    4. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    5. Ricardo Paes de Barros & Carlos Henrique Corseuil & Gustavo Gonzaga, 1999. "Labor market regulations and the demand for labor in Brazil," Textos para discussão 398, Department of Economics PUC-Rio (Brazil).
    6. Angelini, Elena & Damjanović, Milan & Darracq Pariès, Matthieu & Zimic, Srečko, 2023. "Modelling pandemic risks for policy analysis and forecasting," Economic Modelling, Elsevier, vol. 120(C).
    7. repec:zbw:bofrdp:2018_014 is not listed on IDEAS
    8. Brandon Vick, 2017. "Measuring links between labor monopsony and the gender pay gap in Brazil," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-28, December.
    9. Gustavo Leyva & Carlos Urrutia, 2023. "Informal Labor Markets in Times of Pandemic," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 47, pages 158-185, January.
    10. Baumeister, Christiane & Hamilton, James, 2018. "Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role," CEPR Discussion Papers 12911, C.E.P.R. Discussion Papers.
    11. Christiane Baumeister & James D. Hamilton, 2015. "Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information," Econometrica, Econometric Society, vol. 83(5), pages 1963-1999, September.
    12. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    13. Menezes, Flavio & Figer, Vivian & Jardim, Fernanda & Medeiros, Pedro, 2022. "A near real-time economic activity tracker for the Brazilian economy during the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 112(C).
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    More about this item

    Keywords

    Labor market; Covid-19; Bayesian SVAR; Structural shocks;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General

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