IDEAS home Printed from https://ideas.repec.org/p/nbb/reswpp/200803-31.html
   My bibliography  Save this paper

Do survey indicators let us see the business cycle ? A frequency decomposition

Author

Listed:
  • Luc Dresse

    (National Bank of Belgium, Research Department)

  • Christophe Van Nieuwenhuyze

    (National Bank of Belgium, Research Department)

Abstract

This paper uses a frequency domain approach to gain insight into the correlation between survey indicators and year-on-year GDP growth. Using the Baxter-King filter, we split up each series into three components: a short-term, a business cycle (oscillations between 18 and 96 months) and a long-term component. We then calculate how much of the variation of the survey series and GDP growth can be ascribed to these different components. Finally, we use this information together with an analysis of the correlation between survey indicators and year-on-year GDP growth at the different frequencies to explain their overall correlation. We show that survey indicators, similar to year-on-year GDP growth, do not perfectly reflect business cycle movements but contain cycles of other frequencies. Long-term cycles, in particular, are a nontrivial part of the series' variance. Furthermore, there exist some clear relations between the weight of these cycles in the survey indicators and their correlation with GDP growth. In general, the larger the business cycle component, the larger the correlation, while the opposite is true for the short-term component. The evidence for the long-term component is mixed: although a long-term component seems necessary as the correlation at this frequency is the highest, strong or weak long-term components are typically idiosyncratic, dragging down the overall correlation between the indicator and year-on-year GDP growth. The paper applies this methodology to the euro area countries (EC survey indicators) and to Belgium separately (NBB business survey indicators). The results are highly comparable

Suggested Citation

  • Luc Dresse & Christophe Van Nieuwenhuyze, 2008. "Do survey indicators let us see the business cycle ? A frequency decomposition," Working Paper Research 131, National Bank of Belgium.
    • Handle: RePEc:nbb:reswpp:200803-31
    as

    Download full text from publisher

    File URL: https://www.nbb.be/doc/ts/publications/wp/wp131en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Massmann & James Mitchell, 2005. "Reconsidering the Evidence: Are Euro Area Business Cycles Converging?," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(3), pages 275-307.
    2. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    3. Rua, Antonio & Nunes, Luis C., 2005. "Coincident and leading indicators for the euro area: A frequency band approach," International Journal of Forecasting, Elsevier, vol. 21(3), pages 503-523.
    4. Raymond E. Owens & Pierre-Daniel G. Sarte, 2005. "How well do diffusion indexes capture business cycles? A spectral analysis," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 91(Fall), pages 23-42.
    5. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    6. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64, Elsevier.
    7. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    8. Michael A. Kouparitsas, 2003. "International business cycles under fixed and flexible exchange rate regimes," Working Paper Series WP-03-28, Federal Reserve Bank of Chicago.
    9. Christian Gayer, 2006. "Forecast Evaluation of European Commission Survey Indicators," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2005(2), pages 157-183.
    10. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, June.
    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. I. De Greef & C. Van Nieuwenhuyze, 2009. "The National Bank of Belgium, Research Department’s new business survey indicator," Economic Review, National Bank of Belgium, issue ii, pages 31-51, 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. Cravo, Túlio A., 2011. "Are small employers more cyclically sensitive? Evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 754-769.
    2. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    3. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department.
    4. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    5. Rua, Antonio & Nunes, Luis C., 2005. "Coincident and leading indicators for the euro area: A frequency band approach," International Journal of Forecasting, Elsevier, vol. 21(3), pages 503-523.
    6. Alessandra Iacobucci & Alain Noullez, 2005. "A Frequency Selective Filter for Short-Length Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 75-102, February.
    7. Michael Funke & Harm Bandholz, 2003. "In search of leading indicators of economic activity in Germany," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 277-297.
    8. Luca Benati, 2001. "Band-pass filtering, cointegration, and business cycle analysis," Bank of England working papers 142, Bank of England.
    9. Robert J. Hodrick, 2020. "An Exploration of Trend-Cycle Decomposition Methodologies in Simulated Data," NBER Working Papers 26750, National Bureau of Economic Research, Inc.
    10. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    11. Konstantakopoulou, Ioanna & Tsionas, Efthymios G., 2014. "Half a century of empirical evidence of business cycles in OECD countries," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 389-409.
    12. Richard Ashley & Randal Verbrugge, 2009. "Frequency Dependence in Regression Model Coefficients: An Alternative Approach for Modeling Nonlinear Dynamic Relationships in Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 4-20.
    13. Efe Can KILINÇ & Cafer Necat BERBEROĞLU, 2019. "The Relationship Between Saving, Profit Rates and Business CyclesAbstract:There are different approaches of economics schools on the sources, causes and determinants of business cycles. These approach," Sosyoekonomi Journal, Sosyoekonomi Society.
    14. Nath, Hiranya K., 2016. "A note on the cyclical behavior of sectoral employment in the U.S," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 52-61.
    15. Aadland, David, 2005. "Detrending time-aggregated data," Economics Letters, Elsevier, vol. 89(3), pages 287-293, December.
    16. Baffes, John & Kabundi, Alain, 2023. "Commodity price shocks: Order within chaos?," Resources Policy, Elsevier, vol. 83(C).
    17. Afonso, António & Furceri, Davide, 2010. "Government size, composition, volatility and economic growth," European Journal of Political Economy, Elsevier, vol. 26(4), pages 517-532, December.
    18. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, July.
    19. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    20. D. S. G. Pollock, 2016. "Econometric Filters," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 669-691, December.

    More about this item

    Keywords

    Baxter-King; spectral analysis; survey indicators; correlation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:nbb:reswpp:200803-31. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bnbgvbe.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.