IDEAS home Printed from https://ideas.repec.org/p/nbb/docwpp/200011-12.html
   My bibliography  Save this paper

The Belgian industrial confidence indicator: leading indicator of economic activity in the euro area ?

Author

Listed:
  • Jean-Jacques Vanhaelen

    (National Bank of Belgium, Statistics Department)

  • Luc Dresse

    (National Bank of Belgium, Research Department)

  • Jan De Mulder

    (National Bank of Belgium, Research Department)

Abstract

The international press has recently reported on the widely-held view in the financial markets that the movement of the Belgian industrial confidence indicator might precede the euro area business cycles. The initial purpose of this paper is to assess whether this market perception is more than a simple optical illusion, resulting from the inspection of graphical representations of the data. For that, explicitly formalised methods are used to identify the timing of turning points in the industrial confidence indicators for Belgium and for the euro area, and the statistical significance of the differences in timing has been assessed using the Randomization Test proposed by Banerji. We conclude that the turning points in Belgium do in fact significantly lead turning points in the euro area from 1993 onwards. The leading nature of the Belgian industrial confidence indicator is not really surprising, as changes in the business cycle stages in Belgium seem to have been ahead of changes in the euro area during the period from 1985 to the first quarter of 2000. Among the three different reference series used to compare the business cycle movements in Belgium and in the euro area, the null hypothesis that turning points in Belgium do not lead those in the euro area is rejected at a confidence level above 90 p.c. in the case of GDP and of the degree of utilisation of production capacity in manufacturing industry. The leading nature is more pronounced for the sub-period beginning with the first quarter of 1993, especially in the case of GDP. However, the comparison of the movements of the industrial production indices does not confirm these conclusions. Due to the lack of sufficiently long time series for the euro area it was not possible to check whether differences in the economic structure could explain the leading nature of the activity in Belgium. However, using partial industrial confidence indicators, three factors (specialisation in intermediate goods, openness and high representation of small and medium-sized enterprises) that might explain why the Belgian business indicator and Belgian activity seem to lead their euro area counterparts were investigated, but could not be validated by the data. As it seems to be impossible to identify one or more sectors or groups of enterprises accounting for the leading nature of Belgian economic activity when looking at turning points, at least when using the business survey data, it looks as if this leading nature is a kind of general feature of the Belgian economy.

Suggested Citation

  • Jean-Jacques Vanhaelen & Luc Dresse & Jan De Mulder, 2000. "The Belgian industrial confidence indicator: leading indicator of economic activity in the euro area ?," Working Paper Document 12, National Bank of Belgium.
  • Handle: RePEc:nbb:docwpp:200011-12
    as

    Download full text from publisher

    File URL: https://www.nbb.be/doc/ts/publications/wp/wp12en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    2. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, March.
    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. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    2. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    3. Klaus Weyerstrass & Bas Aarle & Marcus Kappler & Atilim Seymen, 2011. "Business Cycle Synchronisation with(in) the Euro Area: in Search of a ‘Euro Effect’," Open Economies Review, Springer, vol. 22(3), pages 427-446, July.
    4. Maria Antoinette Silgoner, 2005. "An Overview of European Economic Indicators: Great Variety of Data on the Euro Area, Need for More Extensive Coverage of the New EU Member States," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 66-89.
    5. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    6. Monica Billio & Jacques Anas & Laurent Ferrara & Marco Lo Duca, 2007. "A turning point chronology for the Euro-zone," Working Papers 2007_33, Department of Economics, University of Venice "Ca' Foscari".
    7. Patrick Bisciari & Alain Durré & Alain Nyssens, 2003. "Stock market valuation in the United States," Working Paper Document 41, National Bank of Belgium.
    8. Ivo Maes, 2002. "On the origins of the Franco-German EMU controversies," Working Paper Research 34, National Bank of Belgium.
    9. Ch. Piette & G. Langenus, 2014. "Using BREL to nowcast the Belgian business cycle: the role of survey data," Economic Review, National Bank of Belgium, issue i, pages 75-98, June.
    10. Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
    11. Bruneau, C. & De Bandt, O. & Flageollet, A., 2003. "Forecasting Inflation in the Euro Area," Working papers 102, Banque de France.
    12. Gagea Mariana, 2012. "Study of Industrial Conjuncture Balances in Romania, Using Logit Model with Heteroscedasticity," Scientific Annals of Economics and Business, Sciendo, vol. 59(1), pages 337-349, July.
    13. Alžbeta Suhányiová & Ladislav Suhányi & Michaela Kočišová, 2023. "Business Confidence in the Sustainable Manufacturing Sector in the Context of Production, Production Prices, and Interest Rates," Sustainability, MDPI, vol. 16(1), pages 1-20, December.
    14. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.
    15. Geert Langenus, 2006. "Fiscal sustainability indicators and policy design in the face of ageing," Working Paper Research 102, National Bank of Belgium.
    16. Christophe Van Nieuwenhuyze, 2006. "A generalised dynamic factor model for the Belgian economy - Useful business cycle indicators and GDP growth forecasts," Working Paper Research 80, National Bank of Belgium.
    17. Luc Aucremann & David Cornille, 2001. "Attractive prices and euro-rounding effects on inflation," Working Paper Document 17, National Bank of Belgium.
    18. Gagea Mariana, 2012. "The Contribution Of Business Confidence Indicators In Short-Term Forecasting Of Economic Development," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 617-623, July.
    19. Elena Doina Dascălu & Nicu Marcu & Ştefan Pete & Maria-Lenuţa Ulici & Vadim Dumitraşcu, 2016. "Dependent Business Climate. A Network-Based Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 138-152, March.

    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. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    2. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    3. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    4. Chun-Chang Lee & Chih-Min Liang & Hsing-Jung Chou, 2013. "Identifying Taiwan real estate cycle turning points- An application of the multivariate Markov-switching autoregressive Model," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 3(2), pages 1-1.
    5. Agnello, Luca & Nerlich, Carolin, 2012. "On the severity of economic downturns: Lessons from cross-country evidence," Economics Letters, Elsevier, vol. 117(1), pages 149-155.
    6. Mr. Thomas Helbling & Mr. Tamim Bayoumi, 2003. "Are they All in the Same Boat? the 2000-2001 Growth Slowdown and the G-7 Business Cycle Linkages," IMF Working Papers 2003/046, International Monetary Fund.
    7. Ghoshray, Atanu, 2021. "Are coffee farmers worse off in the long run?," 95th Annual Conference, March 29-30, 2021, Warwick, UK (Hybrid) 311084, Agricultural Economics Society - AES.
    8. Theobald, Thomas, 2013. "Markov Switching with Endogenous Number of Regimes and Leading Indicators in a Real-Time Business Cycle Forecast," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79911, Verein für Socialpolitik / German Economic Association.
    9. M.S.Rafiq, 2006. "Business Cycle Moderation - Good Policies or Good Luck: Evidence and Explanations for the Euro Area," Discussion Paper Series 2006_21, Department of Economics, Loughborough University.
    10. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    11. Pablo García S. & Camilo Pérez N., 2017. "Desigualdad, inflación, ciclos y crisis en Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 44(2 Year 20), pages 185-221, December.
    12. Viviana Alejandra Alfonso & Luis Eduardo Arango Thomas & Fernando Arias & José David Pulido, 2011. "Ciclos de negocios en Colombia: 1980-2010," Borradores de Economia 8328, Banco de la Republica.
    13. Grigoraş, Veaceslav & Stanciu, Irina Eusignia, 2016. "New evidence on the (de)synchronisation of business cycles: Reshaping the European business cycle," International Economics, Elsevier, vol. 147(C), pages 27-52.
    14. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
    15. Rachel Male, 2010. "Developing Country Business Cycles: Characterising the Cycle," Working Papers 663, Queen Mary University of London, School of Economics and Finance.
    16. Avouyi-Dovi, S. & Matheron, J., 2003. "Interactions between business cycles, stock market cycles and interest rates: the stylised facts," Financial Stability Review, Banque de France, issue 3, pages 80-99, November.
    17. Yongsung Chang & Sunoong Hwang, 2015. "Asymmetric Phase Shifts in U.S. Industrial Production Cycles," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 116-133, March.
    18. Pami Dua & Anirvan Banerji, 2011. "Predicting Recessions and Slowdowns: A Robust Approach," Working Papers id:4391, eSocialSciences.
    19. Fatma Erdem & Erdal Özmen, 2015. "Exchange Rate Regimes and Business Cycles: An Empirical Investigation," Open Economies Review, Springer, vol. 26(5), pages 1041-1058, November.
    20. Calderón, César & Fuentes, J. Rodrigo, 2014. "Have business cycles changed over the last two decades? An empirical investigation," Journal of Development Economics, Elsevier, vol. 109(C), pages 98-123.

    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:nbb:docwpp:200011-12. 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.