IDEAS home Printed from https://ideas.repec.org/p/hhs/osloec/2013_008.html
   My bibliography  Save this paper

Identifying Age-Cohort-Time Effects, Their Curvature and Interactions from Polynomials: Examples Related to Sickness Absence

Author

Listed:
  • Biørn, Erik

    () (Dept. of Economics, University of Oslo)

Abstract

In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including additive polynomials, are explored. The cohort+time=age identity makes the treatment of interactions important. If no interactions between the three variables are included, only the coefficients of the linear terms remain unidentified unless additional information is available. Illustrations using a large data set for individual long-term sickness absence in Norway are given. The sensitivity to the estimated marginal effects of cohort and age at the samplemean, as well as conclusions about the equations’ curvature, are illustrated. We find notable differences in this respect between linear and quadratic equations on the one hand and cubic and fourth-order polynomials on the other.

Suggested Citation

  • Biørn, Erik, 2013. "Identifying Age-Cohort-Time Effects, Their Curvature and Interactions from Polynomials: Examples Related to Sickness Absence," Memorandum 08/2013, Oslo University, Department of Economics.
  • Handle: RePEc:hhs:osloec:2013_008
    as

    Download full text from publisher

    File URL: https://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2013/memo-08-2013.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Erik Biørn & Simen Gaure & Simen Markussen & Knut Røed, 2013. "The rise in absenteeism: disentangling the impacts of cohort, age and time," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(4), pages 1585-1608, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    AGe cohort-time problem; Identification; Polynomial regression; Interaction; Age-cohort curvature; Panel data; Sickness absence;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

    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:hhs:osloec:2013_008. 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: (Mari Strønstad Øverås). General contact details of provider: http://edirc.repec.org/data/souiono.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.