IDEAS home Printed from https://ideas.repec.org/p/rug/rugwps/15-914.html
   My bibliography  Save this paper

Demographics And Business Cycle Volatility A Spurious Relationship?

Author

Listed:
  • Gerdie Everaert
  • Hauke Vierke

Abstract

This paper replicates the estimation results of three studies on the impact of the age composition of the labor force on business cycle volatility and investigates whether they signal a meaningful long-run relationship. We show that both the volatile-age labor force share variable and the business cycle volatility measure exhibit non-stationary behavior but find no robust evidence of cointegration. Hence, the estimation results reported in the literature may be spurious. This conclusion is further supported by the finding that the strong relationship (i) disappears when cross-sectional dependence is accounted for using the CCEP estimator and (ii) is highly sensitive to small changes in the composition of the sample, to data revisions, and to the exact definition of the volatile-age labor share.

Suggested Citation

  • Gerdie Everaert & Hauke Vierke, 2015. "Demographics And Business Cycle Volatility A Spurious Relationship?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/914, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:15/914
    as

    Download full text from publisher

    File URL: http://wps-feb.ugent.be/Papers/wp_15_914.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Everaert, Gerdie, 2014. "A panel analysis of the fisher effect with an unobserved I(1) world real interest rate," Economic Modelling, Elsevier, vol. 41(C), pages 198-210.
    2. Ai Deng, 2014. "Understanding Spurious Regression in Financial Economics," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(1), pages 122-150.
    3. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    4. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    5. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    6. Antonio E. Noriega & Daniel Ventosa‐Santaulària, 2006. "Spurious Regression Under Broken‐Trend Stationarity," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 671-684, September.
    7. Karlsson, Sune & Lothgren, Mickael, 2000. "On the power and interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 66(3), pages 249-255, March.
    8. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    9. James H. Stock & Mark W. Watson, 2005. "Understanding Changes In International Business Cycle Dynamics," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 968-1006, September.
    10. Maddala, G S & Wu, Shaowen, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
    11. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    12. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    13. Antonio E. Noriega & Daniel Ventosa‐Santaulària, 2007. "Spurious Regression and Trending Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(3), pages 439-444, June.
    14. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    15. Nir Jaimovich & Seth Pruitt & Henry E. Siu, 2013. "The Demand for Youth: Explaining Age Differences in the Volatility of Hours," American Economic Review, American Economic Association, vol. 103(7), pages 3022-3044, December.
    16. Jean‐Pierre Urbain & Joakim Westerlund, 2011. "Least Squares Asymptotics in Spurious and Cointegrated Panel Regressions with Common and Idiosyncratic Stochastic Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(1), pages 119-139, February.
    17. Chu Ba & Kozhan Roman, 2010. "Spurious Regressions of Stationary AR(p) Processes with Structural Breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-25, December.
    18. Nir Jaimovich & Henry E. Siu, 2009. "The Young, the Old, and the Restless: Demographics and Business Cycle Volatility," American Economic Review, American Economic Association, vol. 99(3), pages 804-826, June.
    19. Nicolau, João, 2002. "Stationary Processes That Look Like Random Walks— The Bounded Random Walk Process In Discrete And Continuous Time," Econometric Theory, Cambridge University Press, vol. 18(1), pages 99-118, February.
    20. Mark Gertler & Kenneth Rogoff, 2003. "NBER Macroeconomics Annual 2002, Volume 17," NBER Books, National Bureau of Economic Research, Inc, number gert03-1, February.
    21. Steven Lugauer, 2012. "Estimating the Effect of the Age Distribution on Cyclical Output Volatility Across the United States," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 896-902, November.
    22. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    23. Lugauer, Steven & Redmond, Michael, 2012. "The age distribution and business cycle volatility: International evidence," Economics Letters, Elsevier, vol. 117(3), pages 694-696.
    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. Martin Iseringhausen & Hauke Vierke, 2019. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 849-867, August.
    2. Lorenzo Carbonari & Vincenzo Atella & Paola Samà, 2018. "Hours worked in selected OECD countries: an empirical assessment," International Review of Applied Economics, Taylor & Francis Journals, vol. 32(4), pages 525-545, July.
    3. Milanez Ana, 2020. "Workforce Ageing and Labour Productivity Dynamics," Naše gospodarstvo/Our economy, Sciendo, vol. 66(3), pages 1-13, September.
    4. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2023. "Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects," Empirical Economics, Springer, vol. 64(6), pages 2611-2659, June.
    5. Mario Holzner & Stefan Jestl & David Pichler, 2022. "Public and private pension systems and macroeconomic volatility in OECD countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 131-168, May.

    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. Tim Buyse & Freddy Heylen & Ruben Schoonackers, 2015. "On The Role Of Public Policies And Wage Formation For Private Investment In R&D: A Long-Run Panel Analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/911, Ghent University, Faculty of Economics and Business Administration.
    2. Everaert, Gerdie, 2014. "A panel analysis of the fisher effect with an unobserved I(1) world real interest rate," Economic Modelling, Elsevier, vol. 41(C), pages 198-210.
    3. Gerdie Everaert & Freddy Heylen & Ruben Schoonackers, 2015. "Fiscal policy and TFP in the OECD: measuring direct and indirect effects," Empirical Economics, Springer, vol. 49(2), pages 605-640, September.
    4. Martin Iseringhausen & Hauke Vierke, 2019. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 849-867, August.
    5. Selien De Schryder and Gert Peersman, 2015. "The U.S. Dollar Exchange Rate and the Demand for Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. In Choi, 2013. "Panel Cointegration," Working Papers 1208, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    7. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    8. Markus Eberhardt & Francis Teal, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," CSAE Working Paper Series 2008-12, Centre for the Study of African Economies, University of Oxford.
    9. Dina Azhgaliyeva, 2013. "What Makes Oil Revenue Funds Effective," International Conference on Energy, Regional Integration and Socio-economic Development 6023, EcoMod.
    10. Buyse, Tim & Heylen, Freddy & Schoonackers, Ruben, 2020. "On the impact of public policies and wage formation on business investment in research and development," Economic Modelling, Elsevier, vol. 88(C), pages 188-199.
    11. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
    12. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    13. Cem Ertur & Antonio Musolesi, 2014. "Dépendance individuelle forte et faible : une analyse en données de panel de la diffusion internationale de la technologie," Working Papers halshs-01015208, HAL.
    14. Anindya Banerjee & Josep Lluís Carrion-i-Silvestre, 2017. "Testing for Panel Cointegration Using Common Correlated Effects Estimators," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 610-636, July.
    15. Dobnik, Frauke, 2011. "Energy Consumption and Economic Growth Revisited: Structural Breaks and Cross-section Dependence," Ruhr Economic Papers 303, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    16. Mamun, Md. Al & Sohag, Kazi & Uddin, Gazi Salah & Shahbaz, Muhammad, 2015. "Remittance and domestic labor productivity: Evidence from remittance recipient countries," Economic Modelling, Elsevier, vol. 47(C), pages 207-218.
    17. Shingal, ANIRUDH, 2010. "Services growth and convergence: Getting India’s states together," MPRA Paper 32813, University Library of Munich, Germany.
    18. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2022. "Which are the long-run determinants of US outward FDI? Evidence using large long-memory panels," Working Papers 2022.08, International Network for Economic Research - INFER.
    19. R. Golinelli & I. Mammi & A. Musolesi, 2018. "Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area," Working Papers wp1120, Dipartimento Scienze Economiche, Universita' di Bologna.

    More about this item

    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:rug:rugwps:15/914. 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: Nathalie Verhaeghe (email available below). General contact details of provider: https://edirc.repec.org/data/ferugbe.html .

    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.