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FORECASTING IN CENTRAL BANKS David G Mayes University of Auckland Bank of Finland.

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Presentation on theme: "FORECASTING IN CENTRAL BANKS David G Mayes University of Auckland Bank of Finland."— Presentation transcript:

1 FORECASTING IN CENTRAL BANKS David G Mayes University of Auckland Bank of Finland

2 OUTLINE Why do central banks forecast? Forecasting and Policy Systems –Data, assumptions Distributed forecasts –Risks, simulations Publication

3 WHY DO CENTRAL BANKS FORECAST? Monetary policy is forward-looking because it acts with a lag –Forecasts narrow, target focused Want to affect expectations, so show policy working –Requires firm model basis and publication Need to advise private and public sectors to help their decisions and ease adjustment of economy –These last two require forecasting even if a country does not have its own money, or a currency board

4 FORECASTING AND POLICY SYSTEMS Need to simulate as well to explore policy choices System normally adds a great deal of information to the model – often bottom up meeting top down But normally informing a policy making board all of whom have different opinions/like different models –How to combine and present information? –Too much is confusing; a single articulated view usurps the policy maker? State of the art – Norway? Sweden? Canada too secretive –‘Inflation Report’ is summary of evidence leading to decision

5 FORECASTING AND POLICY SYSTEMS Starting at the bottom –Need data often not normally available – strong emphasis on expectations and intentions, components of leading indicators – firm visits, panels etc –Need detailed data on prices and the working of the price index – EU inflation persistence network –Close relationship with statistical authorities –Let the data speak – simple statistical models, indicators, Stock and Watson

6 FORECASTING AND POLICY SYSTEMS The basis for a forecast –As realistic as possible – endogenous monetary policy –Market expectations or model driven not constant rates –What about fiscal policy? –Commodity prices, exchange rates? – consensus forecasts –Semantics on assumptions, projections and forecasts cut no ice Key importance of being methodical – forecast must be reproducible - learning

7 FORECASTING AND POLICY SYSTEMS Top down –Need a core model with strong theory – DGSE very popular. Transition strategy –Fashion is for small models, can understand how they work – often problems with estimation – calibration controversial –Must include policy

8 DISTRIBUTED FORECASTS Point estimates spurious precision –Some show range (ECB) –Some show variety of view (FOMC) –Some show probabilities – Bank of England Rivers of blood –Some look at risks to inputs – Bank of Portugal –Uncertainty vs. risks Scenario simulation more valuable – cannot just vary some parameters/values must be complete

9 PUBLICATION Under inflation targeting the explanation of the outlook gives the policy decision credibility Under other regimes the information is designed to inform market participants Traditional annual and other reports were backward looking There is enormous variety in practice

10 Length of forecast documents Bank No of pages ECB 4 NBB 9 DNB 9 OENB 20 BdP 24 RBNZ 40 CNB 40* BoE 50* SI 60 SR 60+ NB 61+ CBI 64 SP 75

11 Chart 1.4 Policy rates and estimated forward rates on 25 October 2007 and 10 March ) Per cent. Daily and quarterly figures. 2 Jan 06 – 31 Dec 11 UK Euro area US 1) Dotted lines show forward rates on 25 October Broken lines show forward rates at 10 March Forward rates are based on money market rates and interest rate swaps. Sources: Reuters (EcoWin) and Norges Bank

12 Chart 1.7a Projected key policy rate in the baseline scenario with fan chart. Per cent. Quarterly figures. 06 Q1 – 11 Q4 Source: Norges Bank 30%50%70%90%

13 Chart 1.7b Estimated output gap in the baseline scenario with fan chart. Per cent. Quarterly figures. 06 Q1 – 11 Q4 Sources: Statistics Norway and Norges Bank 30%50%70%90%

14 Chart 1.7c Projected CPI in the baseline scenario with fan chart. 4-quarter change. Per cent. Quarterly figures. 06 Q1 – 11 Q4 Sources: Statistics Norway and Norges Bank 30%50%70%90%

15 Chart 1.8 Key policy rate in the baseline scenario in MPR 2/07, MPR 3/07 and MPR 1/08. Per cent. Quarterly figures. 06 Q1 – 11 Q4 Source: Norges Bank MPR 3/07 MPR 2/07 MPR 1/08

16 Source: Norges Bank Chart 1.13a Key policy rate in the baseline scenario and in the alternatives with higher and lower inflation. Per cent. Quarterly figures. 06 Q1 – 11 Q4 Higher inflation Lower inflation 30%50%70%90%

17 Chart 1.14 Key policy rate, Taylor rule, growth rule and rule with external interest rates. Per cent. Quarterly figures. 06 Q1 – 08 Q1 Taylor rule (blue line) Key policy rate (red line) Growth rule (yellow line) Rule with external interest rates (green line) Sources: Statistics Norway and Norges Bank

18 Chart 2 Factors behind changes in the interest rate path since MPR3/07. Percentage points. Quarterly figures. 07 Q4 – 10 Q4 1) Reflects effects of unexpectedly high output growth in ) Reflects effects of higher inflation in Norway over and above the effects of changes in projections for capacity utilisation. 3) Reflects effects of lower expected growth in the global economy. 4) Reflects effects of expectations of lower key policy rates among trading partners, through effects on the krone exchange rate. Source: Norges Bank

19 BIBLIOGRAPHY Norges Bank Monetary Policy Report 1/2008 Coats, W., D. Laxton, and D. Rose (2003): The Czech National Bank’s Forecasting and Policy Analysis System. Czech National Bank (available at J Kontulainen, D G Mayes and J Tarkka 'Monetary Policy Assumptions in Central Bank Forecasts', Bank of Finland Bulletin, vol.78(4), pp.28-35, 2004 D Mayes and J Tarkka, ‘Transparency in European Central Banks: The Role of Forecasts’, Contemporary Politics and Economics of Europe, vol.11(3), pp D Mayes and J Tarkka ‘The Value of Publishing Official Central Bank Forecasts’, Bank of Finland Bulletin, vol.74 (1) 2000, pp Black, R, V Cassino, A Drew, E Hansen, B Hunt, D. Rose and A. Scott (1997), “The Forecasting and Policy System: the core model”, Reserve Bank of New Zealand Research Paper No. 43.


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