IDEAS home Printed from https://ideas.repec.org/p/dls/wpaper/0013.html
   My bibliography  Save this paper

Caracterización de los Cambios en la Desigualdad y la Pobreza en Argentina Haciendo Uso de Técnicas de Descomposiciones Microeconometricas (1992-2001)

Author

Listed:
  • Monserrat Bustelo

    (Centro de Estudios Distributivos, Laborales y Sociales (CEDLAS) FCE - UNLP)

Abstract

La pobreza y la desigualdad de los ingresos laborales y familiares en Argentina han experimentado un sostenido incremento a lo largo de la última década. Como es sabido el ingreso laboral es el producto entre el salario y las horas trabajadas. Si bien importantes resultados han surgido al analizar los cambios producidos en los determinantes del salario, las horas trabajadas han recibido menor atención por parte de la literatura. Es por ello que este trabajo busca caracterizar el impacto en la desigualdad del ingreso y en la pobreza que surge de los cambios experimentados por los determinantes de las horas trabajadas haciendo uso de técnicas de descomposiciones microeconométricas. Adicionalmente se persigue profundizar los estudios previos de medición del efecto distributivo que surge de cambios en los determinantes de los salarios por medio de la metodología de Quantile Regression.

Suggested Citation

  • Monserrat Bustelo, 2004. "Caracterización de los Cambios en la Desigualdad y la Pobreza en Argentina Haciendo Uso de Técnicas de Descomposiciones Microeconometricas (1992-2001)," CEDLAS, Working Papers 0013, CEDLAS, Universidad Nacional de La Plata.
  • Handle: RePEc:dls:wpaper:0013
    as

    Download full text from publisher

    File URL: http://cedlas.econo.unlp.edu.ar/archivos_upload/doc_cedlas13.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mariana Marchionni & Leonardo Gasparini, 2007. "Tracing out the effects of demographic changes on the income distribution," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(1), pages 97-114, April.
    2. Mariana Marchionni & Leonardo Gasparini, 2003. "Tracing out the Effects of Demographic Changes on the Income Distribution. The Case of Greater Buenos Aires 1980-2000," CEDLAS, Working Papers 0004, CEDLAS, Universidad Nacional de La Plata.
    3. Leonardo Gasparini, 2005. "Protección Social y Empleo en América Latina: Estudio sobre la Base de Encuestas de Hogares," CEDLAS, Working Papers 0017, CEDLAS, Universidad Nacional de La Plata.
    4. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
    5. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    6. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    7. Leonardo Gasparini & Mariana Marchionni & Walter Sosa Escudero, 2000. "Characterization of inequality changes through microeconometric decompositions. The case of Greater Buenos Aires," IIE, Working Papers 025, IIE, Universidad Nacional de La Plata.
    8. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    9. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    10. Leonardo Gasparini & Walter Sosa, 2001. "Assessing Aggregate Welfare: Growth and Inequality in Argentina," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 38(113), pages 49-71.
    11. José A. F. Machado & José Mata, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465, May.
    12. Moshe Buchinsky, 2001. "Quantile regression with sample selection: Estimating women's return to education in the U.S," Empirical Economics, Springer, vol. 26(1), pages 87-113.
    13. Cesar Patricio Bouillon & Arianna Legovini & Nora Lustig, 2003. "Rising Inequality in Mexico: Household Characteristics and Regional Effects," Journal of Development Studies, Taylor & Francis Journals, vol. 39(4), pages 112-133.
    14. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
    15. Leonardo Gasparini & Mariana Marchionni & Federico Gutierrez, 2004. "Simulating Income Distribution Changes in Bolivia: a Microeconometric Approach," CEDLAS, Working Papers 0012, CEDLAS, Universidad Nacional de La Plata.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ricardo Bebczuk, 2009. "SME Access to Credit in Guatemala and Nicaragua: Challenging Conventional Wisdom with New Evidence," CEDLAS, Working Papers 0080, CEDLAS, Universidad Nacional de La Plata.

    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. McMillen, Daniel P., 2008. "Changes in the distribution of house prices over time: Structural characteristics, neighborhood, or coefficients?," Journal of Urban Economics, Elsevier, vol. 64(3), pages 573-589, November.
    2. Juan Manuel del Pozo Segura, 2017. "Has the Gender Wage Gap been Reduced during the 'Peruvian Growth Miracle?' A Distributional Approach," Documentos de Trabajo / Working Papers 2017-442, Departamento de Economía - Pontificia Universidad Católica del Perú.
    3. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    4. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    5. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    6. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    7. Azam, Mehtabul, 2012. "Changes in Wage Structure in Urban India, 1983–2004: A Quantile Regression Decomposition," World Development, Elsevier, vol. 40(6), pages 1135-1150.
    8. Joanna Małgorzata Landmesser, 2019. "Decomposition Of Gender Wage Gap In Poland Using Counterfactual Distribution With Sample Selection," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 171-186, September.
    9. Töpfer, Marina, 2017. "Detailed RIF Decomposition with Selection - The Gender Pay Gap in Italy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168422, Verein für Socialpolitik / German Economic Association.
    10. Christopher Bollinger & James P. Ziliak & Kenneth R. Troske, 2011. "Down from the Mountain: Skill Upgrading and Wages in Appalachia," Journal of Labor Economics, University of Chicago Press, vol. 29(4), pages 819-857.
    11. Paolo Naticchioni & Andrea Ricci & Emiliano Rustichelli, 2007. "Wage Structure, Inequality And Skill-Biased Change: Is Italy An Outlier?," Quaderni del Dipartimento di Economia, Finanza e Statistica 38/2007, Università di Perugia, Dipartimento Economia.
    12. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    13. Nicodemo, Catia & Raya, Josep Maria, 2012. "Change in the distribution of house prices across Spanish cities," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 739-748.
    14. Corrado Andini, 2022. "Tertiary education for all and wage inequality: policy insights from quantile regression," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(6), pages 1281-1296, November.
    15. Nicolás Badaracco, 2014. "Fecundidad y Cambios Distributivos en América Latina," CEDLAS, Working Papers 0173, CEDLAS, Universidad Nacional de La Plata.
    16. Patrizia Ordine & Giuseppe Rose, 2015. "The effect of family background, university quality and educational mismatch on wage: an analysis using a young cohort of Italian graduates," Education Economics, Taylor & Francis Journals, vol. 23(2), pages 213-237, April.
    17. Bartelsman, Eric & Dobbelaere, Sabien & Peters, Bettina, 2013. "Allocation of Human Capital and Innovation at the Frontier: Firm-Level Evidence on Germany and the Netherlands," IZA Discussion Papers 7540, Institute of Labor Economics (IZA).
    18. Manuel Arellano & Stéphane Bonhomme, 2017. "Sample Selection in Quantile Regression: A Survey," Working Papers wp2018_1702, CEMFI.
    19. Manuel Arellano & Stéphane Bonhomme, 2017. "Sample Selection in Quantile Regression: A Survey," Working Papers wp2017_1702, CEMFI.
    20. Carla Canelas & Silvia Salazar, 2014. "Gender and ethnic inequalities in LAC countries," IZA Journal of Labor & Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 3(1), pages 1-15, December.

    More about this item

    Keywords

    pobreza; desigualdad del ingreso; descomposiciones; horas trabajadas; salario; Quantile Regression; Argentina.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:dls:wpaper:0013. 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: Ana Pacheco (email available below). General contact details of provider: https://edirc.repec.org/data/funlpar.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.