IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Multiple Time-Serie3 Models Applied to Panel Data

Listed author(s):
  • Thomas E. MaCurdy
Registered author(s):

    This study presents a general methodology for fitting multiple time series models to panel data. The basic statistical framework considered here consists of a dynamic simultaneous equation model where disturbances follow a permanent-transitory scheme with transitory components generated by a multivariate autoregressive-moving average process. This error scheme admits a wide variety of autocovariance patterns and provides a flexible framework for describing the dynamic characteristics of longitudinal data with a minimal number of parameters. It is possible within this framework to consider generally specified rational distributed lag structures involving both exogenous and endogenous variables which includes infinite order lag relationships. This paper outlines the generalizations of standard time series models that are possible when using panel data, and it identifies those instances in which procedures found in the time series literature cannot be directly applied to analyze longitudinal data. Data analysis techniques in the tine series literature are adapted for panel data analysis. These techniques aid in the choice of a time series model and prevent one from choosing a specification that is broadly inconsistent with the data. Several estimation procedures are proposed that can be used to estimate all the parameters of a multiple tine series model including both regression coefficients and parameters of the covariance matrix. The techniques developed here are robust in the sense that they do not rely on any specific distributional assumptions for their asymptotic properties, and in many cases their implementation requires only standard computer packages.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 0646.

    in new window

    Date of creation: Mar 1981
    Handle: RePEc:nbr:nberwo:0646
    Note: LS
    Contact details of provider: Postal:
    National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

    Phone: 617-868-3900
    Web page:

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. Lillard, Lee A & Willis, Robert J, 1978. "Dynamic Aspects of Earning Mobility," Econometrica, Econometric Society, vol. 46(5), pages 985-1012, September.
    2. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
    3. John C. Hause, 1977. "The Covariance Structure of Earnings and the On-The-Job Training Hypothesis," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 6, number 4, pages 335-365 National Bureau of Economic Research, Inc.
    4. Milton Friedman & Simon Kuznets, 1954. "Income from Independent Professional Practice," NBER Books, National Bureau of Economic Research, Inc, number frie54-1, November.
    5. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:0646. 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: ()

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.