IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/117269.html
   My bibliography  Save this paper

Impacto del Covid-19 en el mercado laboral en América del Norte en 2019-2020 por sectores económicos, nivel de instrucción, género y edad: un modelo de datos panel 2013-2020
[Impact of Covid-19 on the labor market in North America in 2019-2020 by economic sectors, educational level, gender and age: a panel data model 2013-2020]

Author

Listed:
  • Colin-Romero, Alexis David
  • Venegas-Martínez, Francisco

Abstract

La presente investigación evalúa el impacto que tuvo la pandemia de COVID-19 en 2019-2020 en el mercado laboral de México, Estados Unidos y Canadá. Se consideran los tres sectores económicos (primario, secundario y terciario), y a su vez cada sector económico se divide en 3 grupos, Sexo, Edad y Nivel de Instrucción. Se propone un modelo de datos panel que considera 24 periodos que van del primer trimestre del 2013 al cuarto trimestre del 2018, además de los trimestres de 2019 y 2020. Los resultados empíricos encontrados sugieren que el menor nivel de desempleo para los tres países se dio en el cuarto trimestre de 2019 y el mayor nivel se dio en el segundo trimestre de 2020. Asimismo, el mayor nivel de desempleo durante el periodo de estudio (T1-2013 a T4-2020) se dio en Estados Unidos y el menor nivel se dio en Canadá. Por otro lado, previo a la pandemia de COVID-19, los sectores de la población con mayor nivel de desempleo en el sector primario fueron las mujeres, las personas con edad de 20 a 39 años y las personas con un nivel de educación básica; en el sector secundario fueron las personas con un nivel de educación menor a la básica; y en el sector terciario fueron los hombres, las personas con edad de 15 a 19 años y de 60 años y más, y las personas con un nivel de educación menor a la básica y de educación superior. De manera general, previo a la pandemia el sector con menor población desempleada fue el secundario y el de mayor fue el terciario. Asimismo, durante la pandemia de COVID-19, en el sector primario no se establece un grupo especifico que haya sido mayormente afectado en cuestión de desempleo; en el secundario los grupos con mayor nivel de desempleo fueron las personas con un nivel de educación menor a la básica, básica y media; y en el terciario las personas con mayor nivel de desempleo fueron los hombres, las personas con edad de 20 a 39 años y de 50 a 59 años, y las personas con un nivel de educación menor a la básica, básica y media. De manera general en Norte América, durante la pandemia de COVID-19, el sector con menor población desempleada fue el primario y el de mayor población desempleada fue el terciario. / This research assesses the impact of the COVID-19 pandemic in 2019-2020 on the labor market in Mexico, the United States, and Canada. We consider the three economic sectors (primary, secondary and tertiary), and in turn each economic sector is divided into 3 groups, Gender, Age and Education Level. A panel data model is proposed that considers 24 periods ranging from the first quarter of 2013 to the fourth quarter of 2018, in addition to the quarters of 2019 and 2020. The empirical results found suggest that, for the three countries, the lowest level of unemployment occurred in the fourth quarter of 2019 and the highest level occurred in the second quarter of 2020. Likewise, the highest level of unemployment during the study period (Q1-2013 to Q4-2020) occurred in the United States and the lowest level occurred in Canada. On the other hand, prior to the COVID-19 pandemic, the sectors of the population with the highest level of unemployment in the primary sector were women, people between the ages of 20 and 39, and people with a basic educational level; in the secondary sector there were people with a level of education below basic; and in the tertiary sector they were men, people aged 15 to 19 and 60 years and over, and people with less than basic and higher education. In general, before the pandemic, the sector with the lowest unemployed population was the secondary and the sector with the largest level was the tertiary. Likewise, during the COVID-19 pandemic, in the primary sector there is no specific group that has been more affected in terms of unemployment; in secondary, the groups with the highest level of unemployment were people with a level of education below basic, basic and secondary; and in the tertiary, the people with the highest level of unemployment were men, people from 20 to 39 years old and from 50 to 59 years old, and people with an educational level below basic, basic and medium. In general, in North America, during the COVID-19 pandemic, the sector with the lowest unemployed population was the primary sector and the sector with the highest unemployed population was the tertiary sector.

Suggested Citation

  • Colin-Romero, Alexis David & Venegas-Martínez, Francisco, 2023. "Impacto del Covid-19 en el mercado laboral en América del Norte en 2019-2020 por sectores económicos, nivel de instrucción, género y edad: un modelo de datos panel 2013-2020 [Impact of Covid-19 on ," MPRA Paper 117269, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:117269
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/117269/1/ALEXIS%20venegas%20paper.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghazala Azmat & Maia Güell & Alan Manning, 2006. "Gender Gaps in Unemployment Rates in OECD Countries," Journal of Labor Economics, University of Chicago Press, vol. 24(1), pages 1-38, January.
    2. Riddell, W. Craig & Song, Xueda, 2011. "The impact of education on unemployment incidence and re-employment success: Evidence from the U.S. labour market," Labour Economics, Elsevier, vol. 18(4), pages 453-463, August.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Morales, Marina, 2018. "Can the composition of the family during adolescence influence their future unemployment situation? Evidence for Spain," MPRA Paper 86770, University Library of Munich, Germany.
    2. Ahmed SALAMA, 2017. "How Literacy Affects Unemployment Among Different Age Groups In Palestine," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 15, pages 363-371, December.
    3. Pompei, Fabrizio & Selezneva, Ekaterina, 2021. "Unemployment and education mismatch in the EU before and after the financial crisis," Journal of Policy Modeling, Elsevier, vol. 43(2), pages 448-473.
    4. Fabrizio Pompei & Ekaterina Selezneva, 2015. "Education Mismatch, Human Capital and Labour Status of Young People across European Union Countries," Working Papers 347, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    5. Daouli, Joan & Demoussis, Michael & Giannakopoulos, Nicholas & Lambropoulou, Nikolitsa, 2015. "The ins and outs of Greek unemployment in the Great Depression," MPRA Paper 66299, University Library of Munich, Germany.
    6. Joan Daouli & Michael Demoussis & Nicholas Giannakopoulos & Nikolitsa Lampropoulou, 2015. "The Ins and Outs of Unemployment in the Current Greek Economic Crisis," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(2), pages 177-196.
    7. Daniel Ştefan Armeanu & Georgeta Vintilă & Ştefan Cristian Gherghina, 2017. "Empirical Study towards the Drivers of Sustainable Economic Growth in EU-28 Countries," Sustainability, MDPI, vol. 10(1), pages 1-22, December.
    8. Mengyuan Zhou, 2022. "Does the Source of Inheritance Matter in Bequest Attitudes? Evidence from Japan," Journal of Family and Economic Issues, Springer, vol. 43(4), pages 867-887, December.
    9. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    10. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    11. Ilona Babenko & Benjamin Bennett & John M Bizjak & Jeffrey L Coles & Jason J Sandvik, 2023. "Clawback Provisions and Firm Risk," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 12(2), pages 191-239.
    12. Şahan, Duygu & Tuna, Okan, 2018. "Environmental innovation of transportation sector in OECD countries," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management. Proceedings of the Hamburg International C, volume 25, pages 157-170, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    13. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    14. Alison L. Booth, 2006. "The Glass Ceiling in Europe: Why Are Women Doing Badly in the Labour Market?," CEPR Discussion Papers 542, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    15. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    16. Shaikh M. S. U. Eskander & Sam Fankhauser, 2022. "Income Diversification and Income Inequality: Household Responses to the 2013 Floods in Pakistan," Sustainability, MDPI, vol. 14(1), pages 1-12, January.
    17. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    18. Peter Harasztosi & Attila Lindner, 2019. "Who Pays for the Minimum Wage?," American Economic Review, American Economic Association, vol. 109(8), pages 2693-2727, August.
    19. Cho, Seong-Hoon & Kim, Heeho & Roberts, Roland K. & Kim, Taeyoung & Lee, Daegoon, 2014. "Effects of changes in forestland ownership on deforestation and urbanization and the resulting effects on greenhouse gas emissions," Journal of Forest Economics, Elsevier, vol. 20(1), pages 93-109.
    20. Kazuki Onji & John P. Tang, 2015. "A nation without a corporate income tax: Evidence from nineteenth century Japan," Discussion Papers in Economics and Business 15-12, Osaka University, Graduate School of Economics.

    More about this item

    Keywords

    América del Norte; mercado laboral; desempleo; Covid-19; sectores económicos; nivel de educación; edad laboral; género. / North America; labor market; unemployment; Covid-19; economic sectors; educational level; working age; gender.;
    All these keywords.

    JEL classification:

    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:117269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.