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Macroeconomic shocks and the probability of being employed

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  • Kornstad, Tom
  • Nymoen, Ragnar
  • Skjerpen, Terje

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 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 female and male unemployment rates as ‘sufficient’ variables for the chance element in individual employment outcomes. Data are for Norway for the period 1988q2–2008q4.

Suggested Citation

  • Kornstad, Tom & Nymoen, Ragnar & Skjerpen, Terje, 2013. "Macroeconomic shocks and the probability of being employed," Economic Modelling, Elsevier, vol. 33(C), pages 572-587.
  • Handle: RePEc:eee:ecmode:v:33:y:2013:i:c:p:572-587
    DOI: 10.1016/j.econmod.2013.04.022
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    1. 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.
    2. Mortensen, Dale & Pissarides, Christopher, 2011. "Job Creation and Job Destruction in the Theory of Unemployment," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 1-19.
    3. Robert E. Hall, 2006. "Job Loss, Job Finding and Unemployment in the US Economy over the Past Fifty Years," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 101-166, National Bureau of Economic Research, Inc.
    4. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5.
    5. 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.
    6. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    7. 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.
    8. 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.
    9. Mortensen, Dale T. & Pissarides, Christopher A., 2016. "Job Matching, Wage Dispersion, and Unemployment," OUP Catalogue, Oxford University Press, number 9780198779995, Decembrie.
    10. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    11. 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.
    12. 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.
    13. Castle, Jennifer & Shephard, Neil (ed.), 2009. "The Methodology and Practice of Econometrics: A Festschrift in Honour of David F. Hendry," OUP Catalogue, Oxford University Press, number 9780199237197, Decembrie.
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    More about this item

    Keywords

    Job probability; Automatic model selection; Random utility modeling;
    All these keywords.

    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

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