IDEAS home Printed from https://ideas.repec.org/p/aep/anales/4661.html
   My bibliography  Save this paper

Trabajadores a tiempo completo en situación de pobreza en Argentina

Author

Listed:
  • Iparraguirre José
  • Carena Bruno
  • Stratta Nicolás

Abstract

Este trabajo presenta un análisis econométrico de la pobreza laboral en Argentina en base a la encuesta permanente de hogares entre 2017 y 2022 dentro de un grupo particular de trabajadores -los trabajadores que trabajan al menos 35 horas por semana. Se ha encontrado que, a nivel nacional, a mayor nivel de educación se reduce la probabilidad de vivir en situación de pobreza, y lo mismo ocurre con el acceso a determinadas categorías ocupacionales. Además, es menor el riesgo entre trabajadoras mujeres y entre trabajadores registrados. La edad presenta una relación en forma de U invertida con respecto a la probabilidad de percibir con ingresos por debajo de la línea de pobreza, y lo mismo sucede con la cantidad de menores de 10 años en el hogar. Finalmente, es mayor la probabilidad de vivir en situación de pobreza entre parejas casadas, comparado con personas separadas, divorciadas o solteras -aunque el riesgo es menor entre mujeres casadas que trabajan a tiempo completo y mayor entre mujeres separadas/divorciadas y mujeres solteras con el mismo nivel de intensidad laboral. Se reportan diferencias significativas por región geográfica.

Suggested Citation

  • Iparraguirre José & Carena Bruno & Stratta Nicolás, 2023. "Trabajadores a tiempo completo en situación de pobreza en Argentina," Asociación Argentina de Economía Política: Working Papers 4661, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4661
    as

    Download full text from publisher

    File URL: https://aaep.org.ar/works/works2023/4661.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Zachary Van Winkle & Emanuela Struffolino, 2018. "When working isn’t enough: Family demographic processes and in-work poverty across the life course in the United States," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(12), pages 365-380.
    3. Leonardo Gasparini & Pablo Gluzmann & Leopoldo Tornarolli, 2019. "Pobreza Crónica en Datos de Corte Transversal: Estimaciones para Argentina," CEDLAS, Working Papers 0252, CEDLAS, Universidad Nacional de La Plata.
    4. Van Winkle, Zachary & Struffolino, Emanuela, 2018. "When working isn’t enough: Family demographic processes and in-work poverty across the life course in the United States," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39, pages 365-380.
    5. Polizzi, Antonino & Struffolino, Emanuela & Van Winkle, Zachary, 2022. "Family demographic processes and in-work poverty: A systematic review," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52, pages 1-1.
    6. Stammann, Amrei & Heiß, Florian & McFadden, Daniel, 2016. "Estimating Fixed Effects Logit Models with Large Panel Data," VfS Annual Conference 2016 (Augsburg): Demographic Change 145837, Verein für Socialpolitik / German Economic Association.
    7. Filandri, Marianna & Struffolino, Emanuela, 2019. "Individual and household in-work poverty in Europe: understanding the role of labor market characteristics," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 21(1), pages 130-157.
    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. Denton R. Vaughan & Barbara A. Haley & Aref N. Dajani, 2021. "Ten years later: Self‐sufficiency of welfare mothers before the Great Recession," Poverty & Public Policy, John Wiley & Sons, vol. 13(2), pages 184-223, June.
    2. Struffolino, Emanuela & Van Winkle, Zachary, 2019. "Is there only one way out of in-work poverty? Difference by gender and race in the US," Discussion Papers, Research Group Demography and Inequality SP I 2019-601, WZB Berlin Social Science Center.
    3. Jo M. Hale & Christian Dudel & Angelo Lorenti, 2020. "Cumulative disparities in the dynamics of working poverty for later-career U.S. workers (2002-2012)," MPIDR Working Papers WP-2020-028, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. 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.
    5. Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
    6. Hou, Yanxi & Leng, Xuan & Peng, Liang & Zhou, Yinggang, 2024. "Panel quantile regression for extreme risk," Journal of Econometrics, Elsevier, vol. 240(1).
    7. Chung‐Hua Shen & Hsing‐Hua Hsu, 2022. "The determinants of Asian banking crises—Application of the panel threshold logit model," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 248-277, March.
    8. Abdulaziz Alsultan & Khaled Hussainey, 2024. "The Moderating Effect of Ownership Structure on the Relationship between Related Party Transactions and Earnings Quality: Evidence from Saudi Arabia," IJFS, MDPI, vol. 12(3), pages 1-25, June.
    9. Cristina Herghelegiu & Evgenii Monastyrenko, 2020. "Risk and Cost Sharing in Firm-to-Firm Trade," DEM Discussion Paper Series 20-24, Department of Economics at the University of Luxembourg.
    10. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2021. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian model averaging techniques," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(4), pages 881-926, November.
    11. Chernozhukov, Victor & Fernández-Val, Iván & Weidner, Martin, 2024. "Network and panel quantile effects via distribution regression," Journal of Econometrics, Elsevier, vol. 240(2).
    12. Chiara Mussida & Dario Sciulli, 2023. "Low pay and household poverty in Italy," Working Papers 635, ECINEQ, Society for the Study of Economic Inequality.
    13. Rüttenauer, Tobias & Kapelle, Nicole, 2024. "Panel Data Analysis," SocArXiv 3mfzq, Center for Open Science.
    14. Koen Jochmans, 2023. "Modified-likelihood estimation of fixed-effect models for dyadic data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(3), pages 417-433, December.
    15. Yugang He, 2024. "E-commerce and foreign direct investment: pioneering a new era of trade strategies," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    16. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    17. Francesco Bartolucci & Claudia Pigini, 2018. "Partial effects estimation for fixed-effects logit panel data models," Working Papers 431, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    18. Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
    19. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities," Papers 2305.03134, arXiv.org, revised Nov 2024.
    20. Matias D Cattaneo & Michael Jansson & Xinwei Ma, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(3), pages 1095-1122.

    More about this item

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    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:aep:anales:4661. 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: Juan Manuel Quintero (email available below). General contact details of provider: https://edirc.repec.org/data/aaeppea.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.