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The pyramid of Okun’s coefficient for Italy

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  • Luca Zanin

    (Prometeia)

Abstract

Our aim is to propose a pyramid of Okun’s coefficient by age and gender in the Italian labour force using a varying-coefficient model. The unemployment rate by age and gender—useful information for estimating Okun’s relationship—is not available for Italy from official statistics. Therefore, we provide an estimation of the indicator using microdata for the 2005–2014 period from ISTAT, the Italian labour force survey. Okun’s law is investigated using two measures of the unemployment rate: a traditional measure based on a labour force with and without work experience, and a new measure restricted to the labour force with experience. When Okun’s relationship is estimated using the unemployment rate restricted to the labour force with experience, the young population is less sensitive to business cycles. As the workforce ages, this gap in sensitivity tends to shrink. We also found that there are no significant differences by gender in the magnitude of Okun’s coefficient among the youngest population when considering the unemployment rate restricted to the labour force with experience.

Suggested Citation

  • Luca Zanin, 2018. "The pyramid of Okun’s coefficient for Italy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 17-28, February.
    • Handle: RePEc:kap:empiri:v:45:y:2018:i:1:d:10.1007_s10663-016-9343-5
    DOI: 10.1007/s10663-016-9343-5
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    References listed on IDEAS

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    1. Viren, Matti, 2001. "The Okun curve is non-linear," Economics Letters, Elsevier, vol. 70(2), pages 253-257, February.
    2. Luca Zanin & Giampiero Marra, 2012. "Rolling Regression Versus Time‐Varying Coefficient Modelling: An Empirical Investigation Of The Okun'S Law In Some Euro Area Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 91-108, January.
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    7. Julien Fouquau, 2008. "Threshold effects in Okun's Law: a panel data analysis," Economics Bulletin, AccessEcon, vol. 5(33), pages 1-14.
    8. Roger Perman & Christophe Tavera, 2007. "Testing for convergence of the Okun’s Law coefficient in Europe," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(1), pages 45-61, March.
    9. King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
    10. Raffaella Calabrese & Silvia Angela Osmetti, 2013. "Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1172-1188, June.
    11. Zanin, Luca, 2014. "On Okun’s law in OECD countries: An analysis by age cohorts," Economics Letters, Elsevier, vol. 125(2), pages 243-248.
    12. Holmes, Mark J. & Silverstone, Brian, 2006. "Okun's law, asymmetries and jobless recoveries in the United States: A Markov-switching approach," Economics Letters, Elsevier, vol. 92(2), pages 293-299, August.
    13. Raffaella Calabrese & Giampiero Marra & Silvia Angela Osmetti, 2016. "Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 604-615, April.
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    Cited by:

    1. de Mendonça, Helder Ferreira & de Oliveira, Diego S.P., 2019. "Firms' confidence and Okun's law in OECD countries," Economic Modelling, Elsevier, vol. 78(C), pages 98-107.
    2. Mindaugas Butkus & Janina Seputiene, 2019. "The Output Gap and Youth Unemployment: An Analysis Based on Okun’s Law," Economies, MDPI, vol. 7(4), pages 1-17, November.
    3. Luca Zanin, 2021. "On the estimation of Okun’s coefficient in some countries in Latin America: a comparison between OLS and GME estimators," Empirical Economics, Springer, vol. 60(3), pages 1575-1592, March.
    4. Mindaugas Butkus & Kristina Matuzeviciute & Dovile Rupliene & Janina Seputiene, 2020. "Does Unemployment Responsiveness to Output Change Depend on Age, Gender, Education, and the Phase of the Business Cycle?," Economies, MDPI, vol. 8(4), pages 1-29, November.
    5. Chiara Mussida & Luca Zanin, 2020. "I found a better job opportunity! Voluntary job mobility of employees and temporary contracts before and after the great recession in France, Italy and Spain," Empirical Economics, Springer, vol. 59(1), pages 47-98, July.

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    More about this item

    Keywords

    Binary generalised extreme value additive model; Economic growth; Okun’s coefficient; Unemployment rate; Varying-coefficient model;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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