IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2006.09007.html

Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective

Author

Listed:
  • Andreas Dibiasi
  • Samad Sarferaz

Abstract

This paper constructs internationally consistent measures of macroeconomic uncertainty. Our econometric framework extracts uncertainty from revisions in data obtained from standardized national accounts. Applying our model to post-WWII real-time data, we estimate macroeconomic uncertainty for 39 countries. The cross-country dimension of our uncertainty data allows us to study the impact of uncertainty shocks under different employment protection legislation. Our empirical findings suggest that the effects of uncertainty shocks are stronger and more persistent in countries with low employment protection compared to countries with high employment protection. These empirical findings are in line with a theoretical model under varying firing cost.

Suggested Citation

  • Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
  • Handle: RePEc:arx:papers:2006.09007
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2006.09007
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Redl, Chris, 2020. "Uncertainty matters: Evidence from close elections," Journal of International Economics, Elsevier, vol. 124(C).
    2. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
    4. Berger, Tino & Grabert, Sibylle & Kempa, Bernd, 2017. "Global macroeconomic uncertainty," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 42-56.
    5. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    6. Elisa Guglielminetti, 2016. "The labor market channel of macroeconomic uncertainty," Temi di discussione (Economic working papers) 1068, Bank of Italy, Economic Research and International Relations Area.
    7. Kevin Lee & Nilss Olekalns & Kalvinder Shields & Zheng Wang, 2012. "Australian Real-Time Database: An Overview and an Illustration of its Use in Business Cycle Analysis," The Economic Record, The Economic Society of Australia, vol. 88(283), pages 495-516, December.
    8. Nicholas Bloom & Max Floetotto & Nir Jaimovich & Itay Saporta†Eksten & Stephen J. Terry, 2018. "Really Uncertain Business Cycles," Econometrica, Econometric Society, vol. 86(3), pages 1031-1065, May.
    9. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    10. McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
    11. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    12. Adriana Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization Institute Working Papers 96, Federal Reserve Bank of Dallas.
    13. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    14. Cath Sleeman, 2006. "Analysis of revisions to quarterly GDP - a real-time database," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 69, pages 1-44., March.
    15. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    16. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    17. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    18. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    19. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-287, April.
    20. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    21. Matteo Cacciatore, 2015. "Uncertainty and the Business Cycle," 2015 Meeting Papers 1440, Society for Economic Dynamics.
    22. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW Kiel).
    23. repec:taf:jnlbes:v:30:y:2012:i:2:p:181-190 is not listed on IDEAS
    24. Chris Redl, 2017. "The impact of uncertainty shocks in the United Kingdom," Bank of England working papers 695, Bank of England.
    25. Christian Grund, 2006. "Severance payments for dismissed employees in Germany," European Journal of Law and Economics, Springer, vol. 22(1), pages 49-71, July.
    26. de Jong, Piet, 1987. "Rational Economic Data Revisions," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 539-548, October.
    27. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    28. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    Full references (including those not matched with items on IDEAS)

    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. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    2. Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
    3. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2025. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Springer Books, in: Stepan Mazur & Pär Österholm (ed.), Recent Developments in Bayesian Econometrics and Their Applications, pages 89-115, Springer.
    4. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    5. Redl, Chris, 2020. "Uncertainty matters: Evidence from close elections," Journal of International Economics, Elsevier, vol. 124(C).
    6. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    7. Kovalenko, Tim, 2021. "Uncertainty shocks and employment fluctuations in Germany: The role of establishment size," Discussion Papers 119, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    8. Tim Kovalenko, 2021. "Uncertainty shocks and employment fluctuations in Germany: the role of establishment size," Working Papers 212, Bavarian Graduate Program in Economics (BGPE).
    9. Rivolta, Giulia & Trecroci, Carmine, 2020. "Measuring the effects of U.S. uncertainty and monetary conditions on EMEs' macroeconomic dynamics," MPRA Paper 99403, University Library of Munich, Germany.
    10. Dong, Ding & Liu, Zheng & Wang, Pengfei, 2025. "Turbulent business cycles," Journal of Monetary Economics, Elsevier, vol. 155(C).
    11. Ahmed Ali & Granberg Mark & Troster Victor & Uddin Gazi Salah, 2022. "Asymmetric dynamics between uncertainty and unemployment flows in the United States," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 155-172, February.
    12. Bhanu Pratap & Nalin Priyaranjan, 2023. "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, vol. 65(4), pages 1599-1625, October.
    13. Gabriel P. Mathy, 2020. "How much did uncertainty shocks matter in the Great Depression?," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 14(2), pages 283-323, May.
    14. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2022. "Uncertainty in an emerging market economy: evidence from Thailand," Empirical Economics, Springer, vol. 62(3), pages 933-989, March.
    15. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    16. Shen, Yifan & He, Jia & Shi, Xunpeng & Zeng, Ting, 2025. "Uncertainty, macroeconomic activity and commodity price: A global analysis," International Review of Financial Analysis, Elsevier, vol. 101(C).
    17. Den Haan, Wouter J. & Freund, Lukas B. & Rendahl, Pontus, 2021. "Volatile hiring: uncertainty in search and matching models," Journal of Monetary Economics, Elsevier, vol. 123(C), pages 1-18.
    18. Lee, Kiryoung & Jeon, Yoontae, 2020. "Measuring Chinese consumers’ perceived uncertainty," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 51-70.
    19. Caggiano, Giovanni & Castelnuovo, Efrem & Delrio, Silvia & Kima, Richard, 2021. "Financial uncertainty and real activity: The good, the bad, and the ugly," European Economic Review, Elsevier, vol. 136(C).
    20. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.

    More about this item

    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:arx:papers:2006.09007. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.