IDEAS home Printed from https://ideas.repec.org/p/ifs/ifsewp/15-24.html
   My bibliography  Save this paper

Earnings and consumption dynamics: a nonlinear panel data framework

Author

Listed:
  • Manuel Arellano

    () (Institute for Fiscal Studies and CEMFI)

  • Richard Blundell

    () (Institute for Fiscal Studies and Institute for Fiscal Studies and University College London)

  • Stéphane Bonhomme

    () (Institute for Fiscal Studies and University of Chicago)

Abstract

We develop a new quantile-based panel data framework to study the nature of income persistence and the transmission of income shocks to consumption. Log-earnings are the sum of a general Markovian persistent component and a transitory innovation. The persistence of past shocks to earnings is allowed to vary according to the size and sign of the current shock. Consumption is modeled as an age-dependent nonlinear function of assets and the two earnings components. We establish the nonparametric identification of the nonlinear earnings process and the consumption policy rule. Exploiting the enhanced consumption and asset data in recent waves of the Panel Study of Income Dynamics, we find nonlinear persistence and conditional skewness to be key features of the earnings process. We show that the impact of earnings shocks varies substantially across earnings histories, and that this nonlinearity drives heterogeneous consumption responses. The transmission of shocks is found to vary systematically with assets.

Suggested Citation

  • Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2015. "Earnings and consumption dynamics: a nonlinear panel data framework," IFS Working Papers W15/24, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:15/24
    as

    Download full text from publisher

    File URL: https://www.ifs.org.uk/uploads/publications/wps/WP201524.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Botosaru, Irene & Sasaki, Yuya, 2018. "Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics," Journal of Econometrics, Elsevier, vol. 203(2), pages 283-296.
    2. Fatih Guvenen, 2007. "Learning Your Earning: Are Labor Income Shocks Really Very Persistent?," American Economic Review, American Economic Association, vol. 97(3), pages 687-712, June.
    3. Lance Lochner & Youngki Shin, 2014. "Understanding Earnings Dynamics: Identifying and Estimating the Changing Roles of Unobserved Ability, Permanent and Transitory Shocks," NBER Working Papers 20068, National Bureau of Economic Research, Inc.
    4. Fabien Postel-Vinay & Hélène Turon, 2010. "On-The-Job Search, Productivity Shocks, And The Individual Earnings Process," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(3), pages 599-629, August.
    5. Hu, Yingyao & Shum, Matthew, 2012. "Nonparametric identification of dynamic models with unobserved state variables," Journal of Econometrics, Elsevier, vol. 171(1), pages 32-44.
    6. 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.
    7. Jonathan Heathcote & Kjetil Storesletten & Giovanni L. Violante, 2014. "Consumption and Labor Supply with Partial Insurance: An Analytical Framework," American Economic Review, American Economic Association, vol. 104(7), pages 2075-2126, July.
    8. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    9. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Greg Kaplan & Giovanni L. Violante, 2014. "A Model of the Consumption Response to Fiscal Stimulus Payments," Econometrica, Econometric Society, vol. 82(4), pages 1199-1239, July.
    11. Meghir, Costas & Pistaferri, Luigi, 2011. "Earnings, Consumption and Life Cycle Choices," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 9, pages 773-854, Elsevier.
    12. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    13. Hall, Robert E & Mishkin, Frederic S, 1982. "The Sensitivity of Consumption to Transitory Income: Estimates from Panel Data on Households," Econometrica, Econometric Society, vol. 50(2), pages 461-481, March.
    14. Geweke, John & Keane, Michael, 2000. "An empirical analysis of earnings dynamics among men in the PSID: 1968-1989," Journal of Econometrics, Elsevier, vol. 96(2), pages 293-356, June.
    15. Fatih Guvenen & Fatih Karahan & Serdar Ozkan & Jae Song, 2015. "What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Dynamics?," Staff Reports 710, Federal Reserve Bank of New York.
    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. Manuel Arellano & Richard Blundell & Stéphane Bonhomme, 2017. "Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework," Econometrica, Econometric Society, vol. 85, pages 693-734, May.
    2. Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
    3. Lance Lochner & Youngki Shin, 2014. "Understanding Earnings Dynamics: Identifying and Estimating the Changing Roles of Unobserved Ability, Permanent and Transitory Shocks," NBER Working Papers 20068, National Bureau of Economic Research, Inc.
    4. Hospido, Laura, 2015. "Wage dynamics in the presence of unobserved individual and job heterogeneity," Labour Economics, Elsevier, vol. 33(C), pages 81-93.
    5. Yang, Guanyi, 2018. "Endogenous Skills and Labor Income Inequality," MPRA Paper 89638, University Library of Munich, Germany.
    6. Neele Balke & Thibaut Lamadon, 2020. "Productivity Shocks, Long-Term Contracts and Earnings Dynamics," NBER Working Papers 28060, National Bureau of Economic Research, Inc.
    7. Richard Blundell & Luigi Pistaferri & Itay Saporta-Eksten, 2016. "Consumption Inequality and Family Labor Supply," American Economic Review, American Economic Association, vol. 106(2), pages 387-435, February.
    8. Greg Kaplan & Giovanni L. Violante, 2010. "How Much Consumption Insurance beyond Self-Insurance?," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(4), pages 53-87, October.
    9. Joseph G. Altonji & Anthony A. Smith Jr. & Ivan Vidangos, 2013. "Modeling Earnings Dynamics," Econometrica, Econometric Society, vol. 81(4), pages 1395-1454, July.
    10. Estelle Dauchy & Francisco Navarro-Sanchez & Nathan Seegert, . "Taxation and Inequality: Active and Passive Channels," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics.
    11. 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.
    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. THELOUDIS Alexandros, 2017. "Consumption Inequality across Heterogeneous Families," LISER Working Paper Series 2017-18, LISER.
    14. Mariacristina De Nardi & Giulio Fella, 2017. "Saving and Wealth Inequality," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 26, pages 280-300, October.
    15. Wang, Chong & Wang, Neng & Yang, Jinqiang, 2016. "Optimal consumption and savings with stochastic income and recursive utility," Journal of Economic Theory, Elsevier, vol. 165(C), pages 292-331.
    16. Manuel Sanchez & Felix Wellschmied, 2020. "Modeling Life-Cycle Earnings Risk with Positive and Negative Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 103-126, July.
    17. Stéphane Bonhomme & Jean-Marc Robin, 2010. "Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 491-533.
    18. Ivan Vidangos, 2009. "Household welfare, precautionary saving, and social insurance under multiple sources of risk," Finance and Economics Discussion Series 2009-14, Board of Governors of the Federal Reserve System (U.S.).
    19. Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2018_1703, CEMFI.
    20. Joachim Hubmer, 2018. "The Job Ladder and its Implications for Earnings Risk," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 172-194, July.

    More about this item

    Keywords

    Earnings dynamics; consumption; panel data; quantile regression; latent variables.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:ifs:ifsewp:15/24. 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: (Emma Hyman). General contact details of provider: https://edirc.repec.org/data/ifsssuk.html .

    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.