IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/675.html
   My bibliography  Save this paper

Macroeconomic shocks and the probability of being employed

Author

Listed:

Abstract

Macroeconomic theories take polar views on the importance of choice versus chance. At the micro level, it seems realistic to assume that both dimensions play a role for individual employment outcomes, although it might be difficult to separate these two effects. Nevertheless the choice and chance dimension are seldom treated symmetrically in models that use micro data. We estimate a logistic model of the probability of being employed among married or cohabitating women that are in the labor force. Besides variables that measure individual characteristics (choice), we allow a full set of indicator variables for observation periods that represent potential effects of aggregate shocks (chance) on job probabilities. To reduce the number of redundant indicator variables as far as possible and in a systematic way, an automatic model selection is used, and we assess the economic interpretation of the statistically significant indicator variables with reference to a theoretical framework that allows for friction in the Norwegian labor market. In addition, we also estimate models that use the aggregate female and male unemployment rates as 'sufficient' variables for the chance element in individual employment outcomes. Data are for Norway and span the period 1988q2-2008q4.

Suggested Citation

  • Tom Kornstad & Ragnar Nymoen & Terje Skjerpen, 2012. "Macroeconomic shocks and the probability of being employed," Discussion Papers 675, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:675
    as

    Download full text from publisher

    File URL: http://www.ssb.no/a/publikasjoner/pdf/DP/dp675.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
    2. Per Krusell & Toshihiko Mukoyama & Richard Rogerson & Ayşegül Şahin, 2010. "Aggregate labor market outcomes: The roles of choice and chance," Quantitative Economics, Econometric Society, vol. 1(1), pages 97-127, July.
    3. Mortensen, Dale & Pissarides, Christopher, 2011. "Job Creation and Job Destruction in the Theory of Unemployment," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 1-19.
    4. Robert E. Hall, 2005. "Job Loss, Job Finding, and Unemployment in the U.S. Economy Over the Past Fifty Years," NBER Working Papers 11678, National Bureau of Economic Research, Inc.
    5. John Dagsvik & Tom Kornstad & Terje Skjerpen, 2013. "Labor force participation and the discouraged worker effect," Empirical Economics, Springer, vol. 45(1), pages 401-433, August.
    6. David F. Hendry & Hans-Martin Krolzig, 1999. "Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 202-219.
    7. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
    8. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages 32-61, March.
    9. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    10. Mortensen, Dale T. & Pissarides, Christopher A., 2016. "Job Matching, Wage Dispersion, and Unemployment," OUP Catalogue, Oxford University Press, number 9780198779995.
    11. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Job probability; Automatic model selection; Random utility modeling;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

    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:ssb:dispap:675. 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: (L Maasø) or (Rebekah McClure). General contact details of provider: http://edirc.repec.org/data/ssbgvno.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.