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Swiss GDP revisions: A monetary policy perspective

Author

Listed:
  • Nicolas Cuche-Curti
  • Pamela Hall
  • Attilio Zanetti

Abstract

This paper focuses on Swiss GDP revisions and the uncertainty they generate from the point of view of monetary policy. After a description of the revisions features, we use GDP vintages to compute real-time output gaps using a production function approach. Then, with a nominal feedback rule, we assess the impact of GDP – and hence output gap – on revisions monetary policy. The main results are threefold. First, Swiss GDP revisions – similarly to those of other small economies – are large, and estimates converge slowly to their final value. Second, GDP mismeasurements clearly exacerbate the difficulty in estimating output gaps. Third, the impact of revisions on monetary policy varies over time. Via its effect on output gaps, ceteris paribus, the inaccuracy of GDP estimates risks introducing a procyclical bias in monetary policy decisions.

Suggested Citation

  • Nicolas Cuche-Curti & Pamela Hall & Attilio Zanetti, 2009. "Swiss GDP revisions: A monetary policy perspective," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 183-213.
  • Handle: RePEc:oec:stdkab:5ksnlh30lx41
    DOI: 10.1787/jbcma-v2008-art10-en
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    Citations

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    Cited by:

    1. Boriss Siliverstovs, 2012. "Are GDP Revisions Predictable? Evidence for Switzerland," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 58(4), pages 299-326.
    2. Boriss Siliverstovs, 2016. "The franc shock and Swiss GDP: how long does it take to start feeling the pain?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3432-3441, August.
    3. Ronald Indergand & Stefan Leist, 2014. "A Real-Time Data Set for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(IV), pages 331-352, December.
    4. Severin Bernhard, 2016. "A real-time GDP data set for Switzerland," Economic Studies 2016-09, Swiss National Bank.
    5. Dr. Nikolay Markov & Dr. Thomas Nitschka, 2013. "Estimating Taylor Rules for Switzerland: Evidence from 2000 to 2012," Working Papers 2013-08, Swiss National Bank.
    6. Michael Graff & Jan-Egbert Sturm, 2010. "The Information Content of Capacity Utilisation Rates for Output Gap Estimates," CESifo Working Paper Series 3276, CESifo.
    7. Boriss Siliverstovs, 2011. "The Real-Time Predictive Content of the KOF Economic Barometer," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(III), pages 353-375, September.
    8. Döhrn, Roland, 2018. "Revisionen der Volkswirtschaftlichen Gesamtrechnungen: Revisionspraxis des Statistischen Bundesamtes und ihre Auswirkungen auf Prognosen," RWI Materialien 127, RWI - Leibniz-Institut für Wirtschaftsforschung.
    9. Mario Meichle & Angelo Ranaldo & Attilio Zanetti, 2011. "Do financial variables help predict the state of the business cycle in small open economies? Evidence from Switzerland," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 435-453, December.
    10. Roland Döhrn, 2019. "Revisionen der Volkswirtschaftlichen Gesamtrechnungen und ihre Auswirkungen auf Prognosen [Revisions of national accounts data and their impact on forecasts]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 13(2), pages 99-123, September.
    11. Eva M. Köberl & Sarah M. Lein, 2011. "The NIRCU and the Phillips curve: an approach based on micro data," Canadian Journal of Economics, Canadian Economics Association, vol. 44(2), pages 673-694, May.
    12. Siliverstovs Boriss, 2013. "Dating Business Cycles in Historical Perspective: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 661-679, October.

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