[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/ucp/ecdecc/v56y2007p125-161.html
   My bibliography  Save this article

Earnings Mobility and Measurement Error: A Pseudo-Panel Approach

Author

Listed:
  • Francisca Antman
  • David J. McKenzie
Abstract
The degree of mobility in incomes is often seen as an important measure of the equality of opportunity in a society and of the flexibility and freedom of its labor market. However, estimation of mobility using panel data is biased by the presence of measurement error and nonrandom attrition from the panel. This study shows that dynamic pseudo-panel methods can be used to consistently estimate measures of absolute and conditional mobility when genuine panels are not available and in the presence of nonclassical measurement errors. These methods are applied to data on earnings from a Mexican quarterly rotating panel. Absolute mobility in earnings is found to be very low in Mexico, suggesting that the high level of inequality found in the cross-section will persist over time. However, the study finds conditional mobility to be high, so that households are able to recover quickly from earnings shocks. These findings suggest a role for policies that address underlying inequalities in earnings opportunities.

Suggested Citation

  • Francisca Antman & David J. McKenzie, 2007. "Earnings Mobility and Measurement Error: A Pseudo-Panel Approach," Economic Development and Cultural Change, University of Chicago Press, vol. 56(1), pages 125-161, October.
  • Handle: RePEc:ucp:ecdecc:v:56:y:2007:p:125-161
    DOI: 10.1086/520561
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/520561
    Download Restriction: Access to the online full text or PDF requires a subscription.

    File URL: https://libkey.io/10.1086/520561?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Neil McCulloch & Bob Baulch, 2000. "Simulating the impact of policy upon chronic and transitory poverty in rural Pakistan," Journal of Development Studies, Taylor & Francis Journals, vol. 36(6), pages 100-130.
    2. Peter Gottschalk & Enrico Spolaore, 2002. "On the Evaluation of Economic Mobility," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(1), pages 191-208.
    3. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    4. repec:bla:revinw:v:48:y:2002:i:4:p:443-69 is not listed on IDEAS
    5. Duncan Thomas & Elizabeth Frankenberg & James P. Smith, 2001. "Lost but Not Forgotten: Attrition and Follow-up in the Indonesia Family Life Survey," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 556-592.
    6. Michael Carter & Christopher Barrett, 2006. "The economics of poverty traps and persistent poverty: An asset-based approach," Journal of Development Studies, Taylor & Francis Journals, vol. 42(2), pages 178-199.
    7. Moffitt, Robert, 1993. "Identification and estimation of dynamic models with a time series of repeated cross-sections," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 99-123, September.
    8. repec:dau:papers:123456789/1560 is not listed on IDEAS
    9. Peter Gottschalk, 1997. "Inequality, Income Growth, and Mobility: The Basic Facts," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 21-40, Spring.
    10. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    11. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
    12. Francisca Antman & David McKenzie, 2007. "Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity," Journal of Development Studies, Taylor & Francis Journals, vol. 43(6), pages 1057-1083.
    13. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    14. Bob Baulch & John Hoddinott, 2000. "Economic mobility and poverty dynamics in developing countries," Journal of Development Studies, Taylor & Francis Journals, vol. 36(6), pages 1-24.
    15. Chang, Yoosoon, 2002. "Nonlinear IV unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 110(2), pages 261-292, October.
    16. Rolf Aaberge & Anders Björklund & Markus Jäntti & Mårten Palme & Peder J. Pedersen & Nina Smith & Tom Wennemo, 2002. "Income Inequality and Income Mobility in the Scandinavian Countries Compared to the United States," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(4), pages 443-469, December.
    17. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 278-287, July.
    18. McKenzie, David, 2001. "Consumption Growth in a Booming Economy: Taiwan 1976-96," Center Discussion Papers 28398, Yale University, Economic Growth Center.
    19. Arellano, Manuel, 1989. "A note on the Anderson-Hsiao estimator for panel data," Economics Letters, Elsevier, vol. 31(4), pages 337-341, December.
    20. Gary Fields & Paul Cichello & Samuel Freije & Marta Menéndez & David Newhouse, 2003. "For Richer or for Poorer? Evidence from Indonesia, South Africa, Spain, and Venezuela," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 1(1), pages 67-99, April.
    21. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
    22. Dolores Collado, M., 1997. "Estimating dynamic models from time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 82(1), pages 37-62.
    23. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    24. Piketty, Thomas, 2000. "Theories of persistent inequality and intergenerational mobility," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 8, pages 429-476, Elsevier.
    25. Jarvis, Sarah & Jenkins, Stephen P, 1998. "How Much Income Mobility Is There in Britain?," Economic Journal, Royal Economic Society, vol. 108(447), pages 428-443, March.
    26. Nazrul Islam, 1995. "Growth Empirics: A Panel Data Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(4), pages 1127-1170.
    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. Francisca Antman & David McKenzie, 2007. "Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity," Journal of Development Studies, Taylor & Francis Journals, vol. 43(6), pages 1057-1083.
    2. Aart Kraay & Roy Weide, 2022. "Measuring intragenerational mobility using aggregate data," Journal of Economic Growth, Springer, vol. 27(2), pages 273-314, June.
    3. Luis Casanova, 2008. "Trampas de Pobreza en Argentina: Evidencia Empírica a Partir de un Pseudo Panel," CEDLAS, Working Papers 0064, CEDLAS, Universidad Nacional de La Plata.
    4. Jose Cuesta & Hugo Ñopo & Georgina Pizzolitto, 2011. "Using Pseudo‐Panels To Measure Income Mobility In Latin America," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 57(2), pages 224-246, June.
    5. Markus Jäntti & Stephen P. Jenkins, 2013. "Income Mobility," SOEPpapers on Multidisciplinary Panel Data Research 607, DIW Berlin, The German Socio-Economic Panel (SOEP).
    6. Rumman Khan, 2021. "Assessing Sampling Error in Pseudo‐Panel Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 742-769, June.
    7. d'Errico, Marco & Letta, Marco & Montalbano, Pierluigi & Pietrelli, Rebecca, 2019. "Resilience Thresholds to Temperature Anomalies: A Long-run Test for Rural Tanzania," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    8. Ingrid Woolard & Stephan Klasen, 2005. "Determinants of Income Mobility and Household Poverty Dynamics in South Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 41(5), pages 865-897.
    9. Inoue, Atsushi, 2008. "Efficient estimation and inference in linear pseudo-panel data models," Journal of Econometrics, Elsevier, vol. 142(1), pages 449-466, January.
    10. Nayoung Lee & Geert Ridder & John Strauss, 2017. "Estimation of Poverty Transition Matrices with Noisy Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 37-55, January.
    11. Hugo Ñopo & Giorgina Pizzolitto & José Cuesta, 2007. "Usando pseudopaneles para medir la movilidad del ingreso en América," Research Department Publications 4558, Inter-American Development Bank, Research Department.
    12. Chiara Comolli & Fabrizio Bernardi, 2015. "The causal effect of the great recession on childlessness of white American women," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-24, December.
    13. Rumman Khan, 2018. "Assessing cohort aggregation to minimise bias in pseudo-panels," Discussion Papers 2018-01, University of Nottingham, CREDIT.
    14. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
    15. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2018. "Territorial and individual educational inequality: A Capability Approach analysis for Italy," Economic Modelling, Elsevier, vol. 71(C), pages 247-262.
    16. Marco d'Errico & Marco Letta & Pierluigi Montalbano & Rebecca Pietrelli, 2018. "Resilience thresholds to temperature shocks in rural Tanzania: a long-run assessment," Working Papers 2/18, Sapienza University of Rome, DISS.
    17. Jeffrey Prince & Shane Greenstein, 2014. "Does Service Bundling Reduce Churn?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 23(4), pages 839-875, December.
    18. Temesgen Woldamanuel Wajebo, 2024. "Determinants of Labour Demand in Manufacturing Sector in Ethiopia," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 67(3), pages 751-782, September.
    19. Ortiz, Rodrigo & Fernandez, Viviana, 2022. "Business perception of obstacles to innovate: Evidence from Chile with pseudo-panel data analysis," Research in International Business and Finance, Elsevier, vol. 59(C).
    20. Frethey-Bentham, Catherine, 2011. "Pseudo panels as an alternative study design," Australasian marketing journal, Elsevier, vol. 19(4), pages 281-292.

    More about this item

    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:ucp:ecdecc:v:56:y:2007:p:125-161. 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: Journals Division (email available below). General contact details of provider: https://www.journals.uchicago.edu/EDCC .

    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.