IDEAS home Printed from https://ideas.repec.org/a/nbb/ecrart/y2009mjuneiiip31-51.html

The National Bank of Belgium, Research Department’s new business survey indicator

Author

Listed:
  • I. De Greef

    (National Bank of Belgium, Statistics Department)

  • C. Van Nieuwenhuyze

    (National Bank of Belgium, Research Department)

Abstract

The business survey indicator is one of the most valuable statistics that the Bank publishes every month. Its reputation is due to the reliability it has demonstrated over several decades in reflecting the pattern of economic activity in the country and in the euro area every month. The indicator is compiled on the basis of the responses to the monthly business survey that the Bank has arranged with enterprises in Belgium since 1954. Almost twenty years after the last methodological revision of the indicator in 1990, the Bank decided that it was now desirable to review its method of calculation again. This article presents the key characteristics of the business survey indicator, its practical applications and the new method of calculation applied since April 2009. This methodological revision gradually became necessary owing to the extension of the survey in 1994 to business-related services, the results of which were not included in the general business survey indicator until this methodological change. The old business survey indicator had also exhibited some undesirable short-term fluctuations. The methodological changes have been kept to a minimum and only concern the calculation of the synthetic curves, with an amended selection of questions that are included in the synthetic curves for each industry and by incorporating the business-related services curve into the overall synthetic business indicator. These changes aim to strengthen the correlation between the indicator and GDP growth, to reduce the undesirable short-term volatility and to maintain its early response.

Suggested Citation

  • 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.
    • Handle: RePEc:nbb:ecrart:y:2009:m:june:i:ii:p:31-51
    as

    Download full text from publisher

    File URL: https://www.nbb.be/en/articles/national-bank-belgium-economics-and-research-departments-new-business-survey-indicator
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. King, Robert G. & Plosser, Charles I., 1994. "Real business cycles and the test of the Adelmans," Journal of Monetary Economics, Elsevier, vol. 33(2), pages 405-438, April.
    4. Andreas Jonsson & Staffan Lindén, 2009. "The quest for the best consumer confidence indicator," European Economy - Economic Papers 2008 - 2015 372, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    5. Ilse Mintz, 1969. "Dating Postwar Business Cycles: Methods and Their Application to Western Germany, 1950–67," NBER Books, National Bureau of Economic Research, Inc, number mint69-1, August.
    6. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, August.
    7. 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.
    8. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    9. Ilse Mintz, 1969. "Summary to "Dating Postwar Business Cycles: Methods and Their Application to Western Germany, 1950–67"," NBER Chapters, in: Dating Postwar Business Cycles: Methods and Their Application to Western Germany, 1950–67, pages 53-54, National Bureau of Economic Research, Inc.
    10. Luc Aucremanne & Marianne Collin & Thomas Stragier, 2007. "Assessing the Gap between Observed and Perceived Inflation in the Euro Area : Is the Credibility of the HICP at Stake ?," Working Paper Research 112, National Bank of Belgium.
    11. 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.
    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. Cockx, Bart & Desiere, Sam, 2024. "Labour costs and the decision to hire the first employee," European Economic Review, Elsevier, vol. 170(C).
    2. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    3. Ferrari, Stijn & Van Roy, Patrick & Vespro, Cristina, 2021. "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Journal of Financial Stability, Elsevier, vol. 52(C).

    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. Robert Pater, 2014. "Are there two types of business cycles? a note on crisis detection," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(3), pages 1-28, December.
    2. Adél Bosch & Steven F. Koch, 2020. "The South African Financial Cycle and its Relation to Household Deleveraging," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 145-173, June.
    3. Everts, Martin, 2006. "Duration of Business Cycles," MPRA Paper 1219, University Library of Munich, Germany.
    4. Marco Gallegati, 2019. "A system for dating long wave phases in economic development," Journal of Evolutionary Economics, Springer, vol. 29(3), pages 803-822, July.
    5. Luca Benati, 2001. "Band-pass filtering, cointegration, and business cycle analysis," Bank of England working papers 142, Bank of England.
    6. 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.
    7. 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.
    8. Emel Siklar & Ilyas Siklar, 2021. "Measuring and Analyzing the Common and Idiosyncratic Cycles: An Application for Turkish Manufacturing Industry," Business and Economic Research, Macrothink Institute, vol. 11(2), pages 279-300, June.
    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. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007, Elsevier.
    11. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    12. Cravo, Túlio A., 2011. "Are small employers more cyclically sensitive? Evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 754-769.
    13. Meller, Barbara & Metiu, Norbert, 2015. "The synchronization of European credit cycles," Discussion Papers 20/2015, Deutsche Bundesbank.
    14. 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.
    15. Laurent Ferrara & Olivier Vigna, 2009. "Cyclical relationships between GDP and housing market in France: Facts and factors at play," Working papers 268, Banque de France.
    16. Lars-H. R. Siemers, 2024. "On the Hamilton-HP Filter Controversy: Evidence from German Business Cycles," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 367-409, November.
    17. Yılmaz Akdi & Serdar Varlik & Hakan Berument, 2018. "Cycle Duration in Production with Periodicity - Evidence from Turkey," International Econometric Review (IER), Econometric Research Association, vol. 10(2), pages 24-32, September.
    18. Hilde Bjørnland & Leif Brubakk & Anne Jore, 2008. "Forecasting inflation with an uncertain output gap," Empirical Economics, Springer, vol. 35(3), pages 413-436, November.
    19. 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.
    20. Mashabela, Juliet & Raputsoane, Leroi, 2018. "The behaviour of disaggregated output over the economic cycle," MPRA Paper 121912, University Library of Munich, Germany.

    More about this item

    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
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:ecrart:y:2009:m:june:i:ii:p:31-51. 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.