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The Forecasting and Policy System: stochastic simulations of the core model

Uncertainty in applied macroeconomic policy analysis arises from three distinct sources. The first, often referred to as model uncertainty, arises because the models used for policy analysis are simple abstractions of the complex behavioural interactions that occur in an economy. The second source, denoted shock uncertainty, arises from unforeseen events that the analysis cannot explicitly factor in ex ante. Finally, starting-point uncertainty reflects the fact that given data lags and revisions, often it is difficult to assess the current state of the economy. This paper discusses the approach the Reserve Bank has taken to enable its Forecasting and Policy System (FPS) to quantify the implications that the typical level of shock uncertainty might be expected have on the analysis of alternative policy actions designed to achieve the objectives of monetary policy.

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Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number G98/6.

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Length: 27p
Date of creation: Oct 1998
Date of revision:
Handle: RePEc:nzb:nzbdps:1998/06
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  1. Canova, Fabio, 1993. "Detrending and Business Cycle Facts," CEPR Discussion Papers 782, C.E.P.R. Discussion Papers.
  2. Svensson, Lars E. O., 1997. "Inflation forecast targeting: Implementing and monitoring inflation targets," European Economic Review, Elsevier, vol. 41(6), pages 1111-1146, June.
  3. Paul Conway, 1998. "Macroeconomic variability in New Zealand: An SVAR study," New Zealand Economic Papers, Taylor & Francis Journals, vol. 32(2), pages 161-186.
  4. Charles L. Evans & Kenneth N. Kuttner, 1998. "Can VAR's describe monetary policy?," Working Paper Series WP-98-19, Federal Reserve Bank of Chicago.
  5. Robert J. Barro, 1996. "Reflections on Ricardian Equivalence," NBER Working Papers 5502, National Bureau of Economic Research, Inc.
  6. Arthur Grimes & Jason Wong, 1992. "The role of the exchange rate in New Zealand monetary policy," Proceedings, Federal Reserve Bank of San Francisco, pages 176-197.
  7. Drew, Aaron & Hunt, Benjamin, 2000. "Efficient simple policy rules and the implications of potential output uncertainty," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 143-160.
  8. 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.
  9. Paul Conway & Aaron Drew & Ben Hunt & Alasdair Scott, 1998. "Exchange rate effects and inflation targeting in a small open economy: a stochastic analysis using FPS," Reserve Bank of New Zealand Discussion Paper Series G99/4, Reserve Bank of New Zealand.
  10. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
  11. Buiter, Willem H, 1988. "Death, Birth, Productivity Growth and Debt Neutrality," Economic Journal, Royal Economic Society, vol. 98(391), pages 279-93, June.
  12. Weil, Philippe, 1989. "Overlapping families of infinitely-lived agents," Journal of Public Economics, Elsevier, vol. 38(2), pages 183-198, March.
  13. Paul Conway & Ben Hunt, 1997. "Estimating potential output: a semi-structural approach," Reserve Bank of New Zealand Discussion Paper Series G97/9, Reserve Bank of New Zealand.
  14. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
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