IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v118y2013i3p482-484.html
   My bibliography  Save this article

Earnings persistence and schooling returns

Author

Listed:
  • Andini, Corrado

Abstract

The standard approach to the estimation of schooling returns disregards earnings persistence. Using longitudinal data for Belgian male workers (ECHP, 1994–2001), we show that earnings persistence matters.

Suggested Citation

  • Andini, Corrado, 2013. "Earnings persistence and schooling returns," Economics Letters, Elsevier, vol. 118(3), pages 482-484.
  • Handle: RePEc:eee:ecolet:v:118:y:2013:i:3:p:482-484
    DOI: 10.1016/j.econlet.2012.12.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512006611
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2012.12.025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fatih Guvenen, 2009. "An Empirical Investigation of Labor Income Processes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(1), pages 58-79, January.
    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. Flannery, Mark J. & Rangan, Kasturi P., 2006. "Partial adjustment toward target capital structures," Journal of Financial Economics, Elsevier, vol. 79(3), pages 469-506, March.
    4. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    5. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    6. Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    7. Corrado Andini, 2013. "How well does a dynamic Mincer equation fit NLSY data? Evidence based on a simple wage-bargaining model," Empirical Economics, Springer, vol. 44(3), pages 1519-1543, June.
    8. Jacob A. Mincer, 1974. "Schooling and Earnings," NBER Chapters, in: Schooling, Experience, and Earnings, pages 41-63, National Bureau of Economic Research, Inc.
    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. Frieder Kropfhäußer & Marco Sunder, 2014. "A Weighty Issue Revisited: The Dynamic Effect of Body Weight on Earnings and Satisfaction in Germany," SOEPpapers on Multidisciplinary Panel Data Research 635, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Kropfhäußer, Frieder & Sunder, Marco, 2013. "A weighty issue revisited: the dynamic effect of body weight on earnings and satisfaction in Germany," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79895, Verein für Socialpolitik / German Economic Association.
    3. Andini, Corrado, 2013. "Persistence Bias and the Wage-Schooling Model," IZA Discussion Papers 7186, Institute of Labor Economics (IZA).
    4. Karlis Vilerts & Olegs Krasnopjorovs & Edgars Brekis, 2015. "Does Education Affect Wages During and After Economic Crisis? Evidence from Latvia (2006–2012)," Working Papers 2015/03, Latvijas Banka.
    5. Massimiliano Agovino & Antonio Garofalo, 2016. "The Impact of Education on Wage Determination between Workers in Southern and Central-Northern Italy," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(1), pages 25-43, March.
    6. Andini, Corrado, 2014. "Persistence Bias and Schooling Returns," IZA Discussion Papers 8143, Institute of Labor Economics (IZA).
    7. Marconi, Gabriele, 2015. "Dynamic returns to schooling by work experience," MPRA Paper 88073, University Library of Munich, Germany.
    8. Mirko Felchner, 2015. "Einkommensdynamik bei Selbständigen als Freie Berufe und abhängig Beschäftigte Eine dynamische Paneldatenschätzung mit Daten des Sozio-oekonomischen Panels," FFB-Discussionpaper 101, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
    9. Moczall, Andreas, 2015. "The effect of hiring subsidies on regular wages," IAB-Discussion Paper 201501, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    10. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.
    11. Moczall, Andreas, 2015. "The effect of hiring subsidies on regular wages," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113225, Verein für Socialpolitik / German Economic Association.

    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. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    2. Andini, Corrado, 2009. "How Fast Do Wages Adjust to Human-Capital Productivity? Dynamic Panel-Data Evidence from Belgium, Denmark and Finland," IZA Discussion Papers 4583, Institute of Labor Economics (IZA).
    3. Corrado Andini, 2013. "How well does a dynamic Mincer equation fit NLSY data? Evidence based on a simple wage-bargaining model," Empirical Economics, Springer, vol. 44(3), pages 1519-1543, June.
    4. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.
    5. 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.
    6. Mirko Felchner, 2015. "Einkommensdynamik bei Selbständigen als Freie Berufe und abhängig Beschäftigte Eine dynamische Paneldatenschätzung mit Daten des Sozio-oekonomischen Panels," FFB-Discussionpaper 101, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
    7. Jozef Konings & Stijn Vanormelingen, 2015. "The Impact of Training on Productivity and Wages: Firm-Level Evidence," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 485-497, May.
    8. Giesecke, Matthias & Bönke, Timm & Lüthen, Holger, 2011. "The Dynamics of Earnings in Germany: Evidence from Social Security Records," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48692, Verein für Socialpolitik / German Economic Association.
    9. Blundell, Richard & Graber, Michael & Mogstad, Magne, 2015. "Labor income dynamics and the insurance from taxes, transfers, and the family," Journal of Public Economics, Elsevier, vol. 127(C), pages 58-73.
    10. Yang, Guanyi, 2018. "Endogenous Skills and Labor Income Inequality," MPRA Paper 89638, University Library of Munich, Germany.
    11. Stimpfle, Alexander & Stadelmann, David, 2015. "The Impact of Fundamental Development Factors on Different Income Groups: International Evidence," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113128, Verein für Socialpolitik / German Economic Association.
    12. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post schooling human capital investments and the life cycle variance of earnings," IDEI Working Papers 765, Institut d'Économie Industrielle (IDEI), Toulouse.
    13. Yamarik Steven J, 2008. "Estimating Returns to Schooling from State-Level Data: A Macro-Mincerian Approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-16, August.
    14. Marcelo Soto, 2006. "Estimating the Social Return on Schooling," Papers of the Annual IUE-SUNY Cortland Conference in Economics, in: Oguz Esen & Ayla Ogus (ed.), Proceedings of the Conference on Human and Economic Resources, pages 43-65, Izmir University of Economics.
    15. Gustavsson, Magnus & Österholm, Pär, 2014. "Does the labor-income process contain a unit root? Evidence from individual-specific time series," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 152-167.
    16. Jones, A. M. & Laporte, A. & Rice, N. & Zucchelli, E., 2014. "A synthesis of the Grossman and Becker-Murphy models of health and addiction: theoretical and empirical implications," Health, Econometrics and Data Group (HEDG) Working Papers 14/07, HEDG, c/o Department of Economics, University of York.
    17. François Rycx & Yves Saks & Ilan Tojerow, 2015. "Does Education Raise Productivity and Wages Equally? The Moderating Roles of Age, Gender and Industry," Working Paper Research 281, National Bank of Belgium.
    18. Chu, Lan Khanh & Hoang, Dung Phuong, 2020. "How does economic complexity influence income inequality? New evidence from international data," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 44-57.
    19. Bayer, Christian & Kuhn, Moritz, 2018. "Which Ladder to Climb? Wages of Workers by Job, Plant, and Education," IZA Discussion Papers 11827, Institute of Labor Economics (IZA).
    20. Kyoung-Youn Na & Chirok Han & Chang-Ho Yoon, 2013. "Network effect of transportation infrastructure: a dynamic panel evidence," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(1), pages 265-274, February.

    More about this item

    Keywords

    Mincer equation; Wages; Human capital; Dynamic panel-data models;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:eee:ecolet:v:118:y:2013:i:3:p:482-484. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.