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How Forward-looking are Central Banks? Some Evidence from their Forecasts* Michał Brzoza-Brzezina, Jacek Kotłowski, Agata Miśkowiec Summary prepared for „Warsztaty doktorskie z zakresu ekonometrii i statystyki” * This is a preliminary summary of the paper. Please do not recirculate. April 30, 2011 Key words: Taylor rule, forward-looking monetary policy, feedback horizon JEL classification: C25, E52, E58 Main objective of the research The main aim of this paper is to determine whether central banks adopt forward-looking approach in their conduct of monetary policy, and if so - what length of horizon they take into account. Introduction and related literature According to both central banks and academics, efficient monetary policy should be forward-looking. Such monetary policy is able to better stabilize output and inflation fluctuations (see inter alia Rudebusch (1998), Bernanke et al. (1999), Orphanides (2001), Clarida et al. (2001), Mishkin (2007)). This observation has even led to suggestions that central banks should explicitly adjust interest rates to deviations of forecasted output and inflation from targets (Svensson (1997)). Central banks have claimed for many years that they conduct monetary policy in a forward-looking way. In order to convince the public that this is the case they publish inflation reports, minutes of decision-makers Strona 1 z 7 meetings and, in particular, macroeconomic projections (including inflation, GDP and sometimes even interest rate path). Especially publishing inflation forecasts - which often are de facto intermediate targets for monetary policy - has become a common practice (Fracasso et al. 2003). Mishkin and Schmidt-Hebbel (2001) listed central banks that failed to fulfill that unwritten rule. Today, each bank from their list publishes an inflation forecast in order to increase transparency and be in line with the best practices. Things become less clear when it comes to decide how forward-looking central banks should be and how far they look indeed into the future. As to the first question, regarding the optimal targeting horizon, the literature is vast. Several theoretical studies have been conducted, analyzing the performance of monetary policy rules with various horizons. Batini and Haldane (1999) estimated the optimal forecast horizon (according to their definition - one that is securing as good inflation as any other, while at the same time delivering significantly lower output variability) to be between three and six quarters ahead. They also noticed that the greater the degree of forward-lookingness by the private sector, the less the compensating need for forward-looking behaviour on the part of the central bank. At the same time however, Batini and Pearlman (2002) illustrated analytically using a New Keynesian closed economy model that long inflation feedback horizons (with or without additional output gap feedbacks) can lead to indeterminacy. The same was later proved for open economy models (Batini et al. (2004)). However, in spite of the numerous studies in the subject, no consensus over the question how forward-looking central banks should be has been reached. Commenting on the literature on optimal policy horizons, it may be worth citing Goodhart (2001), who suggested that the selection of monetary policy horizons is so model specific that little advance can be made unless such studies apply the context of monetary policy as found in practice. In line with this argumentation, several authors tried to determine optimal targeting horizons for specific economies. For instance, Batini and Nelson (2000) found that for the Bank of England the best feedback horizon to focus can range from 2 quarters if agents other than the central bank are assumed to be forwardlooking, up to 15 quarters in models with no forward-looking behaviour in the economy. In case of the Czech Republic, Strasky (2005) observed a trade-off between the inflation and output variability that accompanied the policy horizon increase. At longer horizons the inflation variability augmented (it was the smallest for two quarters horizon), while the output gap variability was gradually reduced (reached minimum for nine quarters horizon). The simulation results suggested the Czech National Bank's optimal targeting horizon was three quarters. As to the second question, i.e. how far in practice central banks look into the future while setting interest rates, there is substantially less evidence. Central banks themselves usually avoid pointing at particular dates at which they target inflation or output. They prefer to provide this information indirectly, e.g. stating that they intend to bring inflation to target in the medium term. The medium-term orientation of the European Strona 2 z 7 Central Bank's monetary policy was emphasized at the start of Stage Three of European Monetary Union. As explained by Trichet (2003), the medium-term orientation clarifies that there is no fixed time horizon over which price stability has to be re-established. It gives ECB the possibility to vary the appropriate monetary policy horizon and adapt it to the nature of a shock the bank responds to. Moreover, this approach is believed by Trichet to be superior over central banks that adopted a fixed horizon, as it gives more flexibility and limits scope for short-sighted reactions. However, some central banks commit (in an explicit or implicit way) to specific targeting horizons. For example, the Reserve Bank of New Zealand (after serious problems with hitting the inflation target in 1998 and 1999) has modified its inflation-targeting regime to lengthen the horizon over which it tries to achieve its inflation target to 6-8 quarters (Drew and Orr (1999)). The Bank of England has the policy horizon of two years, which means that the Monetary Policy Committee tends to put weight on the inflation projection around two years ahead (King (1997)).1 Even less is said about the horizon at which monetary authorities care about output fluctuations. As to the academic literature, it is often limited to the statement that in case of a nonzero weight put on output fluctuations, a longer policy horizon should be implemented in order to avoid major output fluctuations (Mishkin (2002)). In empirical papers gauging optimal policy horizons, focus tends to be on inflation forecasts horizons, while output values are limited to current ones (like in the framework presented by Rudebusch and Svensson (1998)). In particular, to our best knowledge, no paper has tried to exploit the evidence implicit in central banks' own macroeconomic forecasts. This study tries to fill this gap. Data and model We collect data on macroeconomic projections of three important central banks - the Bank of England (BoE), Schweizerische Nationalbank (Swiss National Bank, SNB) and Sveriges Riksbank (SR) and use it to recover the horizon at which these banks look at future inflation and output. The choice of central banks is determined by the availability of a sufficient number of projections based on the assumption of constant interest rates during the projection horizon (conditional forecasts). These seem best suited to conduct our study, since they show explicitly the consequences of not changing the interest rate. If following such a forecast the central bank changes the interest rate it is relatively easy, from the econometric point of view, to 1 However, some economists argue, that in current circumstances there might be a case for considering a longer-term policy horizon. One reason for this would be that quantitative easing may have longer lags before it reaches maximum effect than do changes in bank rate (and part of the reason for focusing around two years ahead is that it is believed to be the point of maximum policy effect). It might also be useful to reconsider the merits of looking to inflation prospects beyond the normal forecast horizon, to ensure any future risks to economic stability are taken fully into account (see Barker (2010)). Strona 3 z 7 figure out which forecast horizon triggered this decision. Following Orphanides critics (2001), only real time data is employed. Model uses information available at the time the forecasts are made, moreover - only from central banks' own projections. Yet - as opposed to the BoE or SR - the Swiss National Bank does not publish its own projection of GDP. Therefore, VAR model with three variables (GDP growth, inflation and unemployment rate) was used to estimate the projected value of the output gap. For the estimation we used an ordered probit model. This econometric approach has been widely used in the literature to estimate monetary policy rules. Even though it was employed in a model describing Fed's discrete interest rate policy in the 50s of the twentieth century (see Rosett (1959)), it became commonly employed not until a paper by Eichengreen et al. (1985). Currently, it is often used in papers which address the Taylor's reaction function. The method is based on the fact that the movements of the central bank reference interest rates take the form of a multiple of some value (typically 0.25 percentage point). As a result, it is the sign of interest rate change, not its magnitude, that is examined. In our framework the dependent variable in the Taylor reaction function - change of the bank rate - can take values (-1, 0, 1). We assume that the central banks' decisions about interest rates depend on the variables presented in the form of an anticipatory Taylor function presented below: ∆BRt = f (E(πt+k |Ωt ) − πt ) + g(E(xt+l |Ωt )), where ∆BRt - central bank reference rate change; πt+k - inflation in time t + k (in %); πt - inflation target in time t (in %); xt+l output gap in time t + l (i.e. deviation of GDP growth from the potential growth rate, in %); k and l - forecast horizons; Ω - information available in time t; f, g – Gaussian functions. One important technical issue that must be discussed here, is the way we include future explanatory variables into the model. Central bank forecasts extend over several quarters, which means that in practice we have to deal with a large amount of explanatory variables: two for each forecast horizon (one for inflation and one for output). Given the limited data set and the potential high correlation of forecasts at different horizons, the approach of treating inflation and output at each horizon as a separate explanatory variable seemed unrealistic. We decided to assume a specific functional form that would combine forecasts at all horizons into one value for inflation and one for output and estimate the parameters of this function. Our choice of functional form was a Gaussian function. In our view this function is well suited to describe realistic ways of aggregating forecasts at various horizons. By varying the mean parameter we can control the forecast horizon with the highest weight in the central Strona 4 z 7 banks rule. By varying the standard deviation we can control the weight of the peak horizon relative to the other horizons. Additionally, this function leaves only two parameters to estimate, which, given our limited amount of data, is a big advantage. Results Our findings are the following. First, all analysed banks are forward looking with respect to inflation. The BoE and SNB look at the last quarter of their forecasts (respectively 8th and 12th) while the SR takes into account the middle point of the forecast (4th quarter). The case of output is more nuanced. Results for Riksbank do not give an unequivocal response as to the forecast horizon for output employed in the process of interest rate setting. In case of the Bank of England the forward-looking approach as to output gap is undisputed and the lead amounts to 2 quarters. Nevertheless, for these analyzed central banks the lead of inflation forecasts is consistently bigger than the lead of output. Finally, to our surprise we find little evidence that monetary authorities take into account (albeit with varying weights) their whole forecasts. In contrary, the evidence speaks mostly for concentrating strongly on one particular horizon, especially when output is concerned. The paper will be organised as follows. In section two, after the introduction and related literature, the data and the econometric approach will be described. In section three the results followed by some critical remarks will be presented. Conclusions will be given in section four. Strona 5 z 7 References Barker, K. (2010): “Monetary Policy - from stability to financial crisis and back?,” speech given at the National Institute of Economic and Social Research, London, 8 March 2010 Batini, N. and A. Haldane (1999): “Forward-looking rules for monetary policy,” NBER Chapters in: Monetary policy Rules, pp. 157–202 Batini, N., P. Levine, and J. Pearlman (2004): “Indeterminacy with inflation-forecast-based rules in a twobloc model,” International Finance Discussion Papers, 797 Batini, N., and E. Nelson (2000): “Optimal horizons for inflation targeting,” Bank of England, Working paper Batini, N., and J. Pearlman (2002): “Too much too soon: Instability and indeterminacy with forward-looking rules,” External MPC Unit Discussion Paper, Bank of England, 8 Bernanke, B., T. Labauch, and F. Mishkin (1999): Inflation targeting: lessons from the international experience. Princeton University Press, Princeton Clarida, R., J. Gali, and M. Gertler (2001): “Optimal Monetary Policy in Open versus Closed Economies: An Integrated Approach,” American Economic Review, 91(2), 248–252 Drew, A., and A. Orr (1999): “The Reserve Bank’s Role in the recent business cycle: actions and evolution,” Reserve Bank of New Zealand Bulletin, 62, No.1 Eichengreen, B., M. Watson, and R. Grossman (1985): “Bank rate policy under the interwar gold standard: A dynamic probit model,” Economic Journal, 95, 752–745 Fracasso, A., H. Genberg, and C. Wyplosz (2003): How do Central Banks Write? An Evaluation of Inflation Reports by Inflation Targeting Central Banks. Geneva Reports on the World Economy Special Report 2 Goodhart, C. A. E. (2001): “Monetary transmission lags and the formulation of the policy decision on interest rates,” Federal Reserve Bank of St Louis Review, (July/August), 165–181 King, M. (1997): “The inflation target five years on,” Bank of England Quarterly Bulletin, 37, 434–42 Strona 6 z 7 Mishkin, F. (2002): “Overview: Rethinking stabilization policy,” Proceedings, Federal Reserve Bank of Kansas City, pp. 439–446 – (2007): Monetary policy strategy. The MIT Press, 1st edition Mishkin, F., and K. Schmidt-Hebbel (2001): “One decade of inflation targeting in the world: What do we know and what do we need to know?,” Central Bank of Chile, Working Papers, 101 Orphanides, A. (2001): “Monetary Policy Rules Based on Real-Time Data,” American Economic Review, 91, 964–985 Rosett, R. (1959): “A statistical model of friction in economics”, Econometrica, 26, 263–267 Rudebusch, G., and L. Svensson (1998): “Policy rules for inflation targeting,” Seminar Papers 637, Stockholm University, Institute for International Economic Studies Strasky, J. (2005): “Optimal forward-looking policy rules in the quarterly projection model of the Czech National Bank,” Research and Policy Notes, Czech National Bank, 5 Svensson, L. E. (1997): “Inflation forecast targeting: Implementation and monitoring inflation targets,” European Economic Review, 41, 111–146 Strona 7 z 7