IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y1999i55-56p211-242.html
   My bibliography  Save this article

Predictive Distributions based on Longitudinal Earnings Data

Author

Listed:
  • Gary Chamberlain
  • Keisuke Hirano

Abstract

Consider an individual trying to forecast his future earnings, in order to guide savings and other decisions. We envision an individual seeking advice from a financial planner. The individual provides data on his earnings history and on various personal characteristics such as age and education. The planner has access to longitudinal data sets that provide data on earnings histories and personal characteristics for samples of individuals. We devise optimal ways to combine the individual's information with the survey data in order to provide the individual with a conditional distribution for his future earnings. We work with data from the Panel Study of Income Dynamics, and our main modification of previous models is to allow for heterogeneity in volatility. This has important consequences, in that the spread of the predictive distribution becomes sensitive to the variability in the earnings history.

Suggested Citation

  • Gary Chamberlain & Keisuke Hirano, 1999. "Predictive Distributions based on Longitudinal Earnings Data," Annals of Economics and Statistics, GENES, issue 55-56, pages 211-242.
  • Handle: RePEc:adr:anecst:y:1999:i:55-56:p:211-242
    as

    Download full text from publisher

    File URL: http://www.jstor.org/stable/20076197
    Download Restriction: no

    Citations

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


    Cited by:

    1. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, January.

    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:adr:anecst:y:1999:i:55-56:p:211-242. 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: (Laurent Linnemer). General contact details of provider: http://edirc.repec.org/data/ensaefr.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.

    We have no references for this item. You can help adding them by using 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.