IDEAS home Printed from https://ideas.repec.org/a/bla/buecrs/v71y2019i3p240-256.html
   My bibliography  Save this article

Examining The Stability Of Okun'S Coefficient

Author

Listed:
  • Nektarios A. Michail

Abstract

The stability of Okun's law coefficient in the United States from 1949 to 2015 is examined using a regression with GARCH errors in order to capture the volatility of the series. Rolling estimations suggest that taking the volatility of the series into account yields more stable results compared to the simple OLS estimation, irrespective of the specification (gap or growth model), the data frequency (monthly or quarterly), or the length of the rolling window. The results also suggest that the persistence of shocks became much more important in explaining contemporaneous volatility when data from the recent global financial crisis were incorporated. In contrast, the feedthrough of output shocks in next period's output volatility was more important in the past, and especially during the 1970s stagflation period, but has been declining since.

Suggested Citation

  • Nektarios A. Michail, 2019. "Examining The Stability Of Okun'S Coefficient," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 240-256, July.
  • Handle: RePEc:bla:buecrs:v:71:y:2019:i:3:p:240-256
    DOI: 10.1111/boer.12157
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/boer.12157
    Download Restriction: no

    File URL: https://libkey.io/10.1111/boer.12157?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nicholas Apergis & Anthony Rezitis, 2003. "An examination of Okun's law: evidence from regional areas in Greece," Applied Economics, Taylor & Francis Journals, vol. 35(10), pages 1147-1151.
    2. Michael T. Owyang & Tatevik Sekhposyan, 2012. "Okun’s law over the business cycle: was the great recession all that different?," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 399-418.
    3. 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.
    4. Ball, Laurence & Jalles, João Tovar & Loungani, Prakash, 2015. "Do forecasters believe in Okun’s Law? An assessment of unemployment and output forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 176-184.
    5. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    6. Soosung Hwang & Pedro L. Valls Pereira, 2006. "Small sample properties of GARCH estimates and persistence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 473-494.
    7. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    8. Michelle L. Barnes & Fabia Gumbau-Brisa & Giovanni P. Olivei, 2013. "Do real-time Okun's law errors predict GDP data revisions?," Working Papers 13-3, Federal Reserve Bank of Boston.
    9. Blinder, Alan S, 1997. "Is There a Core of Practical Macroeconomics That We Should All Believe?," American Economic Review, American Economic Association, vol. 87(2), pages 240-243, May.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Valadkhani, Abbas & Smyth, Russell, 2015. "Switching and asymmetric behaviour of the Okun coefficient in the US: Evidence for the 1948–2015 period," Economic Modelling, Elsevier, vol. 50(C), pages 281-290.
    12. Roger Perman & Christophe Tavera, 2005. "A cross-country analysis of the Okun's Law coefficient convergence in Europe," Applied Economics, Taylor & Francis Journals, vol. 37(21), pages 2501-2513.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nektarios A. Michail & Christos S. Savva, 2021. "Public Debt Thresholds: An Analysis for Cyprus," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 15(1), pages 75-85, June.
    2. Shabir Mohsin Hashmi & Ali Gul Khushik & Muhammad Akram Gilal & Zhao Yongliang, 2021. "The Impact of GDP and Its Expenditure Components on Unemployment Within BRICS Countries: Evidence of Okun’s Law From Aggregate and Disaggregated Approaches," SAGE Open, , vol. 11(2), pages 21582440211, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Valadkhani, Abbas & Smyth, Russell, 2015. "Switching and asymmetric behaviour of the Okun coefficient in the US: Evidence for the 1948–2015 period," Economic Modelling, Elsevier, vol. 50(C), pages 281-290.
    2. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    3. Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2023. "The heterogeneity of Okun's law: A metaregression analysis," Economic Modelling, Elsevier, vol. 128(C).
    4. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," Post-Print hal-01943883, HAL.
    5. repec:hal:wpaper:hal-01943883 is not listed on IDEAS
    6. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    7. Bohl, Martin T. & Diesteldorf, Jeanne & Siklos, Pierre L., 2015. "The effect of index futures trading on volatility: Three markets for Chinese stocks," China Economic Review, Elsevier, vol. 34(C), pages 207-224.
    8. N. Antonakakis & J. Darby, 2013. "Forecasting volatility in developing countries' nominal exchange returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(21), pages 1675-1691, November.
    9. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    10. Rossi, Alessandro & Gallo, Giampiero M., 2006. "Volatility estimation via hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 203-230, March.
    11. Timotheos Angelidis & Stavros Degiannakis, 2005. "Modeling risk for long and short trading positions," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 6(3), pages 226-238, July.
    12. Andreas Brunhart, 2014. "Stock Market's Reactions to Revelation of Tax Evasion: An Empirical Assessment," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 161-190, September.
    13. Altaf Muhammad & Zhang Shuguang, 2015. "Impact Of Structural Shifts on Variance Persistence in Asymmetric Garch Models: Evidence From Emerging Asian and European Markets," Romanian Statistical Review, Romanian Statistical Review, vol. 63(1), pages 57-70, March.
    14. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
    15. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    16. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Working Papers 0501, University of Crete, Department of Economics.
    17. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    18. Rui Pereira, 2014. "Okun’s law, asymmetries and regional spillovers: evidence from Virginia metropolitan statistical areas and the District of Columbia," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 583-595, March.
    19. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    20. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    21. Jushan Bai & Serena Ng, 1998. "A Test for Conditional Symmetry in Time Series Models," Boston College Working Papers in Economics 410, Boston College Department of Economics.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

    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:bla:buecrs:v:71:y:2019:i:3:p:240-256. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0307-3378 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.