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GDP data revisions and forward-looking monetary policy in Switzerland

Author

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  • Kugler, Peter
  • Jordan, Thomas J.
  • Lenz, Carlos
  • Savioz, Marcel R.

Abstract

This paper analyzes forward-looking rules for Swiss monetary policy in a small structural VAR model consisting of four variables taking into account data revisions for GDP. First, the paper develops an analytical method to analyze the effect of data revision errors in GDP on the ex ante or conditional inflation-output-growth volatility trade-off and applies it to Swiss data. Second, the effects of different targets in a forward-looking monetary policy on ex post or unconditional volatility of inflation and output growth is explored by a simulation exercise. In general, the results obtained suggest that focusing monetary policy on GDP growth instead on inflation may lead to an inefficient policy with both increased medium term inflation and GDP growth volatility in the presence of GDP data revisions.
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Suggested Citation

  • Kugler, Peter & Jordan, Thomas J. & Lenz, Carlos & Savioz, Marcel R., 2005. "GDP data revisions and forward-looking monetary policy in Switzerland," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 351-372, December.
  • Handle: RePEc:eee:ecofin:v:16:y:2005:i:3:p:351-372
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    References listed on IDEAS

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    1. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
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    4. Jordan, Thomas J. & Kugler, Peter & Lenz, Carlos & Savioz, Marcel R., 2005. "The Analysis of Forward-Looking Monetary Policy in a SVAR Framework," Working papers 2005/10, Faculty of Business and Economics - University of Basel.
    5. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
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    11. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    12. Peter Kugler & Thomas J. Jordan, 2004. "Structural Vector Autoregressions and the Analysis of Monetary Policy Interventions: The Swiss Case," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 140(I), pages 67-87, March.
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    Cited by:

    1. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    2. Katrin Assenmacher-Wesche, 2008. "Modeling Monetary Transmission in Switzerland with a Structural Cointegrated VAR Model," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 197-246, June.
    3. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
    4. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    5. 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.

    More about this item

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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