IDEAS home Printed from
   My bibliography  Save this article

Imputación de ingresos laborales. Una aplicación con encuestas de empleo en México


  • Rodríguez-Oreggia, Eduardo

    (fue profesor-investigador titular en la EGAP Gobierno y Política Pública, del Tecnológico de Monterrey. EL TRIMESTREECONÓMICO lamenta su fallecimiento, sucedido en el curso de la publicación del artículo)

  • López-Videla, Bruno

    (Banco de México)


The aim of this paper is to make imputation of earnings in observations with missing values in the Encuesta Nacional de Ocupaciones y Empleo (ENOE), and also to analyze a possible bias in human capital estimations from ignoring such missing observations. We present imputations by two methods, and also a correction for estimations by reweighting observations with reported earnings. The results show differences in human capital estimations on wages and factors related to labor poverty when missing values of earnings are ignored. Differences are acute when measuring labor poverty.// El objetivo de este artículo es realizar una imputación de ingresos a observaciones con ingresos faltantes en la Encuesta Nacional de Ocupaciones y Empleo (ENOE) y, posteriormente, analizar el posible sesgo en estimaciones de capital humano derivadas de ignorar esas observaciones. Se presenta una imputación por dos métodos y también una corrección de estimaciones por remuestreo para observaciones de ingreso reportado. Los resultados muestran diferencias en parámetros de capital humano sobre salarios y determinantes de pobreza laboral al no considerar las observaciones con ingreso faltante. Las diferencias son más significativas cuando se mide pobreza laboral

Suggested Citation

  • Rodríguez-Oreggia, Eduardo & López-Videla, Bruno, 2015. "Imputación de ingresos laborales. Una aplicación con encuestas de empleo en México," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(325), pages .117-146, enero-mar.
  • Handle: RePEc:elt:journl:v:82:y:2015:i:325:p:117-146

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
    2. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    3. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    4. Christopher R. Bollinger & Barry T. Hirsch, 2006. "Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 483-520, July.
    5. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, Juni.
    6. Barry T. Hirsch & Edward J. Schumacher, 2004. "Match Bias in Wage Gap Estimates Due to Earnings Imputation," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 689-722, July.
    7. Lopez-Acevedo, Gladys, 2001. "Evolution of earnings and rates of returns to education in Mexico," Policy Research Working Paper Series 2691, The World Bank.
    Full references (including those not matched with items on IDEAS)

    More about this item


    imputación; ingreso; capital humano; pobreza laboral; matching;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D10 - Microeconomics - - Household Behavior - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity


    Access and download statistics


    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:elt:journl:v:82:y:2015:i:325:p:117-146. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nuria Pliego Vinageras). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.