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Forecasting Monetary Rules in South Africa

  • Ruthira Naraidoo

    ()

    (Department of Economics, University of Pretoria)

  • Ivan Paya

    ()

    (Department of Economics, Lancaster University)

This paper is the ?rst one to analyze the ability of linear and nonlinear monetary policy rule specifications as well as nonparametric and semiparametric models in forecasting the nominal interest rate setting that describes the South African Reserve Bank (SARB) policy decisions. We augment the traditional Taylor rule with indicators of asset prices in order to account for potential financial stability targets implicitly considered by the SARB. Using an in-sample period of 1986:01 to 2004:12, we compare the out-of-sample forecasting ability of the models over the period 2005:01 to 2008:12. Our results indicate that the semiparametric models perform particularly well relative to the Taylor rule models currently dominating the monetary policy literature, and that nonlinear Taylor rules improve their performance under the new monetary regime.

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Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201007.

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Length: 20 pages
Date of creation: Mar 2010
Date of revision:
Handle: RePEc:pre:wpaper:201007
Contact details of provider: Postal: PRETORIA, 0002
Phone: (+2712) 420 2413
Fax: (+2712) 362-5207
Web page: http://www.up.ac.za/economics

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  1. Christopher Martin & Costas Milas, 2004. "Modelling Monetary Policy: Inflation Targeting in Practice," Economica, London School of Economics and Political Science, vol. 71(281), pages 209-221, 05.
  2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules And Macroeconomic Stability: Evidence And Some Theory," The Quarterly Journal of Economics, MIT Press, vol. 115(1), pages 147-180, February.
  3. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-84, September.
  4. Castro, Vítor, 2008. "Are Central Banks following a linear or nonlinear (augmented) Taylor rule?," The Warwick Economics Research Paper Series (TWERPS) 872, University of Warwick, Department of Economics.
  5. Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
  6. Schaling, Eric, 2004. "The Nonlinear Phillips Curve and Inflation Forecast Targeting: Symmetric versus Asymmetric Monetary Policy Rules," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(3), pages 361-86, June.
  7. Aksoy, Yunus & Orphanides, Athanasios & Small, David & Wieland, Volker & Wilcox, David, 2003. "A Quantitative Exploration of the Opportunistic Approach to Disinflation," CEPR Discussion Papers 4073, C.E.P.R. Discussion Papers.
  8. Dolado, Juan J. & Maria-Dolores, Ramon & Naveira, Manuel, 2005. "Are monetary-policy reaction functions asymmetric?: The role of nonlinearity in the Phillips curve," European Economic Review, Elsevier, vol. 49(2), pages 485-503, February.
  9. Antulio N. Bomfim & Glenn D. Rudebusch, 1998. "Opportunistic and deliberate disinflation under imperfect credibility," Finance and Economics Discussion Series 1998-01, Board of Governors of the Federal Reserve System (U.S.).
  10. Mishkin, F S., 2008. "How should we respond to asset price bubbles?," Financial Stability Review, Banque de France, issue 12, pages 65-74, October.
  11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  12. Ben S. Bernanke & Mark Gertler, 2001. "Should Central Banks Respond to Movements in Asset Prices?," American Economic Review, American Economic Association, vol. 91(2), pages 253-257, May.
  13. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
  14. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  15. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
  16. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
  17. Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
  18. By Gunnar Jonsson, 2001. "Inflation, Money Demand, and Purchasing Power Parity in South Africa," IMF Staff Papers, Palgrave Macmillan, vol. 48(2), pages 2.
  19. Bec Frédérique & Ben Salem Mélika & Collard Fabrice, 2002. "Asymmetries in Monetary Policy Reaction Function: Evidence for U.S. French and German Central Banks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
  20. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, Elsevier.
  21. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
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