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On the Determinants of the Okun’s Law: New Evidence from Time-Varying Estimates

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Abstract

This paper revisits, by means of both time series and panel data analyses, the empirical regularity identified by Okun’s (in: Proceedings of the business and economics statistics section, American Statistical Association, Washington, DC, 98–103, 1962) seminal paper. Based on a sample of 85 advanced and developing economies between 1978 and 2014, we confirm the existence of an average negative and statistically significant Okun’s relationship. At the same time, results suggest that the relation varies substantially across countries and times. Finally, we identify several factors affecting the variation in Okun’s coefficient across and within countries. Across countries, the relationship is stronger in countries with higher average unemployment, a larger share of public employment, lower informality and smaller agricultural sectors, and one that is more diversified. Within countries, in addition to some of these factors, we find that deregulation in labor and product markets and recessions have strengthened the response of unemployment to the business cycle.

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Fig. 1

Source: Authors’ calculations

Fig. 2

Source: Authors’ calculations

Fig. 3

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Fig. 4

Source: Authors’ calculations

Fig. 5

Source: Authors’ calculations

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Notes

  1. For the USA, many authors posit that a 1% deviation of output from potential causes an opposite change in unemployment of half a percentage point (Mankiw 2012).

  2. For the McKinsey Global Institute (2011) the Okun’s law has broken down because of problems in the labor market, such as mismatch between workers and jobs.

  3. These can be constructed using any filtering method. Ball et al. (2019) rely on the Hodrick–Prescott (1981, 1997) filter and take 2 values of the smoothness parameter, 100 and 12 [the latter for developing countries as suggested by Rand and Tarp (2002)].

  4. The approach proposed by Schlicht (2003) is very similar to that used by Aghion and Marinescu (2008). The main difference is in the computation of the variances \(\sigma_{i}^{2}\). Aghion and Marinescu (2008) use the Markov chain Monte Carlo (MCMC) method to approximate these variances, while Schlicht (2003) uses a method-of-moments estimator.

  5. The correlation matrices for unemployment and GDP using alternative filters are displayed in Table 10 in “Appendix.”

  6. Labor market regulations are composed of the following sub-indicators: hiring regulations and minimum wage, hiring and firing regulations, centralized collected bargaining, hours regulations, mandated costs of worker dismissal and conscription. As far as product market sub-indicators are concerned, we consider: administrative requirements, bureaucracy costs, starting a business, extra payments/bribes/favoritism, licensing restrictions and cost of tax compliance.

  7. While the migration process along with urbanization is almost completed in advanced economies, rural-to-urban migrant flows are still very significant in developing countries.

  8. https://www.imf.org/external/np/res/dfidimf/diversification.htm.

  9. The list includes: Venezuela, Trinidad and Tobago, Iran, Kuwait, Brunei, Algeria and Kazakhstan.

  10. Country results using the changes version instead are available from the authors upon request.

  11. Rescaling each factor with weights corresponding to the inverse of the standard deviations of the TVC estimates does not qualitatively change the scatter results.

  12. Results using the changes versions yield qualitatively similar conclusions and are available upon request.

  13. Results using the changes versions yield qualitatively similar conclusions and are available in Appendix Tables’ 12 and 13.

  14. In Appendix Table 14 we re-run Table 7 with both country and time effects for robustness purposes. We can observe that our previous conclusions remain qualitatively valid. The results in Table 15 also show that similar results are obtained when we exclude the Global Financial Crisis (years 2008 and 2009) and when we consider recessions identified as: (i) episodes with a negative output gap—computed with an HP filter with smoothness parameter equal to 100—below the 10th percentile of output gap distribution; and (ii) those produced by the Harding and Pagan (2002) algorithm to identify economic turning points.

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Acknowledgements

The authors are grateful to the editor and one anonymous referee for comments and suggestions Thanks also go to Younghun Kim and Jun Ge for research assistance. The opinions expressed herein are those of the authors and do not necessarily reflect those of the IMF, its member countries or its policy.

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Authors and Affiliations

  1. Research Department, International Monetary Fund, 700 19th Street NW, Washington, DC, 20431, USA

    Davide Furceri

  2. Portuguese Public Finance Council, Praca de Alvalade 6, 1700-036, Lisbon, Portugal

    João Tovar Jalles

  3. REM/UECE, Rua Miguel Lupi 20, 1249-078, Lisbon, Portugal

    João Tovar Jalles

  4. Centre for Globalization and Governance and Economics for Policy, Nova School of Business and Economics, Rua da Holanda 1, 2775, Carcavelos, Portugal

    João Tovar Jalles

  5. Independent Evaluation Office, International Monetary Fund, 700 19th Street NW, Washington, DC, 20431, USA

    Prakash Loungani

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  1. Davide Furceri
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Correspondence to João Tovar Jalles.

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Appendix

Appendix

See Figs. 6, 7 and Tables 9, 10, 11, 12, 13, 14, 15.

Fig. 6
figure 6

Source: Authors’ calculations

Okun’s changes version: histograms of static \(\beta\). Note: Histograms using the changes version of the Okun’s law.

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Fig. 7
figure 7

Behavior of time-varying Okun’s coefficients during recessions. Note: Using the gap version of the Okun’s law. “t” denotes the year of the recession. “t − 2,” “t − 1,” “t + 1,” “t + 2” denote 2 or 1 years, prior or after the recession year. The figure displays the average TVC for the gap version of the unemployment–output relationships

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Table 9 Correlation matrices
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Table 10 Summary statistics
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Table 11 Okun’s coefficient in oil-exporting countries
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Table 12 Country effect OLS regressions of time-varying Okun’s coefficients on main determinants—changes version
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Table 13 Country effect WLS regressions of time-varying Okun’s coefficients on main determinants—changes version
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Table 14 Country and time effect WLS regressions of time-varying Okun’s coefficients on main determinants—gap version
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Table 15 Country effect OLS regressions of time-varying Okun’s coefficients on main determinants—gap version, alternative recession definitions
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Furceri, D., Jalles, J.T. & Loungani, P. On the Determinants of the Okun’s Law: New Evidence from Time-Varying Estimates. Comp Econ Stud 62, 661–700 (2020). https://doi.org/10.1057/s41294-019-00111-1

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