IDEAS home Printed from https://ideas.repec.org/a/spr/jbuscr/v12y2016i1d10.1007_s41549-016-0004-3.html
   My bibliography  Save this article

Does a Survey Based Capacity Utilization Measure Help Predicting Brazilian Output Gap in Real-Time?

Author

Listed:
  • Sarah Lima

    (FGV/IBRE)

  • Marco Malgarini

    (FGV/IBRE
    ANVUR)

Abstract

The aim of the paper is to assess the informational content of a survey-based measure of the Brazilian manufacturing capacity utilization rate produced by the Brazilian Institute of Economics from Getulio Vargas Foundation. From a theoretical point of view, the survey-based capacity measure should provide meaningful information with respect to the Brazilian business cycle. In this work, we choose to use the output gap as the most comprehensive and convincing proxy of the cyclical situation (Graff and Sturm in CESifo Econ Stud 58(1):220–251, 2012). More specifically, we will refer to a real-time version of the output gap, using an existing real-time GDP data set produced by the Central Bank of Brazil (Cusinato et al. in Empir Econ, 2012). The information efficiency of the real-time output gap estimates is tested checking whether survey data can help producing real-time estimates that are significantly closer to the latest releases. In this sense, the paper provides a significant contribution to the existing literature, extending analysis already available for OECD countries to the Brazilian economy. Our main result is that survey data can indeed help to produce more efficient estimates of the output gap in real time.

Suggested Citation

  • Sarah Lima & Marco Malgarini, 2016. "Does a Survey Based Capacity Utilization Measure Help Predicting Brazilian Output Gap in Real-Time?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 119-139, September.
    • Handle: RePEc:spr:jbuscr:v:12:y:2016:i:1:d:10.1007_s41549-016-0004-3
    DOI: 10.1007/s41549-016-0004-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41549-016-0004-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s41549-016-0004-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. Michael Graff & Jan-Egbert Sturm, 2010. "The information content of capacity utilisation rates for output gap estimates," KOF Working papers 10-269, KOF Swiss Economic Institute, ETH Zurich.
    3. 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.
    4. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    5. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    6. Marco Malgarini & Antonio Paradiso, 2012. "Measuring capacity utilisation in the italian manufacturing sector: a comparison between time series and survey estimates," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 5-19.
    7. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    8. Tom Stark, 2002. "A summary of the conference on real-time data analysis," Business Review, Federal Reserve Bank of Philadelphia, issue Q 1, pages 5-11.
    9. 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.
    10. 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.
    11. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    12. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
    13. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    14. Rafael Tiecher Cusinato & André Minella & Sabino da Silva Pôrto Júnior, 2010. "Hiato do Produto e PIB no Brasil: uma Análise de Dados em Tempo Real," Working Papers Series 203, Central Bank of Brazil, Research Department.
    15. 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.
    16. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    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. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    3. Cayen, Jean-Philippe & van Norden, Simon, 2005. "The reliability of Canadian output-gap estimates," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 373-393, December.
    4. Döpke, Jörg, 2004. "Real-time data and business cycle analysis in Germany," Discussion Paper Series 1: Economic Studies 2004,11, Deutsche Bundesbank.
    5. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    6. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
    7. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    8. Van Norden, Simon, 2004. "Filtres pour l’analyse courante," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 523-546, Juin-Sept.
    9. Athanasios Orphanides & John C. Williams, 2002. "Robust Monetary Policy Rules with Unknown Natural Rates," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 63-146.
    10. Yýlmaz 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.
    11. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    12. Hilde Bjørnland & Leif Brubakk & Anne Jore, 2008. "Forecasting inflation with an uncertain output gap," Empirical Economics, Springer, vol. 35(3), pages 413-436, November.
    13. Ard den Reijer, 2006. "The Dutch business cycle: which indicators should we monitor?," DNB Working Papers 100, Netherlands Central Bank, Research Department.
    14. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    15. Bernhardsen, Tom & Eitrheim, Oyvind & Jore, Anne Sofie & Roisland, Oistein, 2005. "Real-time data for Norway: Challenges for monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 333-349, December.
    16. Everts, Martin, 2006. "Duration of Business Cycles," MPRA Paper 1219, University Library of Munich, Germany.
    17. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
    18. Tom Bernhardsen & ØYvind Eitrheim, 2005. "Real-time data for Norway: Output gap revisions and challenges for monetary policy," Computing in Economics and Finance 2005 274, Society for Computational Economics.
    19. Simon van Norden, 2002. "Filtering for Current Analysis," Staff Working Papers 02-28, Bank of Canada.
    20. Fukuda, Kosei, 2012. "Illustrating extraordinary shocks causing trend breaks," Economic Modelling, Elsevier, vol. 29(4), pages 1045-1052.

    More about this item

    Keywords

    Capacity utilization; Output gap; Real-time analysis; Survey data;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    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:spr:jbuscr:v:12:y:2016:i:1:d:10.1007_s41549-016-0004-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.