Central Bank Transparency, the Accuracy of Professional Forecasts, and Interest Rate Volatility

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Federal Reserve Bank of New York Staff Reports Central Bank Transparency, the Accuracy of Professional Forecasts, and Interest Rate Volatility Menno Middeldorp Staff Report no. 496 May 2011 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the author and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author. Central Bank Transparency, the Accuracy of Professional Forecasts, and Interest Rate Volatility Menno Middeldorp Federal Reserve Bank of New York Staff Reports, no. 496 May 2011 JEL classification: D83, E47, E58, G14 Abstract Central banks worldwide have become more transparent. An important reason is that democratic societies expect more openness from public institutions. Policymakers also see transparency as a way to improve the predictability of monetary policy, thereby lowering interest rate volatility and contributing to economic stability. Most empirical studies support this view. However, there are three reasons why more research is needed. First, some (mostly theoretical) work suggests that transparency has an adverse effect on predictability. Second, empirical studies have mostly focused on average predictability before and after specific reforms in a small set of advanced economies. Third, less is known about the effect on interest rate volatility. To extend the literature, I use the Dincer and Eichengreen (2007) transparency index for twenty-four economies of varying income and examine the impact of transparency on both predictability and market volatility. I find that higher transparency improves the accuracy of interest rate forecasts for three months ahead and reduces rate volatility. Key words: Central bank communication, interest rate forecasts, central bank transparency, financial market efficiency Middeldorp: Federal Reserve Bank of New York and Utrecht University (menno.middeldorp@ny.frb.org). The author gratefully acknowledges the support of the Institute for Monetary Research of the Hong Kong Monetary Authority (HKMA), where most of the research was conducted in the context of a doctoral dissertation for Utrecht University. Thanks also to Qianying Chen, Deborah Perelmuter, Matthew Raskin, Stephanie Rosenkranz, and participants at an HKMA seminar for useful questions and comments. Special thanks to Clemens Kool for extensive comments on several drafts. The views expressed in the paper are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author. 1 Overview Central banks worldwide have become considerably more transparent about monetary policy, including de…ning their goals, explaining decisions, releasing economic forecasts and providing guidance about future policy. Between 1998 and 2005, 89 of the 100 countries in the Dincer and Eichengreen (2007) index show an increase in transparency and none a decline. An important reason is that (the increased number of) democratic societies expect more openness from public institutions. Another motivation for greater transparency is a reduction in monetary policy surprises to thereby reduce accompanying …nancial market and economic volatility. Along these lines, Bernanke (2004) asserts that, “clear communication helps to increase the near-term predictability of [central bank]1 rate decisions, which reduces risk and volatility in …nancial markets and allows for smoother adjustment of the economy to rate changes.” This paper focuses on the bene…ts Bernanke describes, by examining transparency’s impact both on predictability and interest rate volatility. As discussed in the literature review in Section 2, Although straightforward intuition and standard …nancial market theory suggest that transparency should enhance predictability, this has been challenged by some theoretical and experimental research, that shows that under some circumstances transparency can reduce the use of private information and thereby actually damage predictability. Nevertheless, a considerable body of empirical research suggests that transparency improves predictability. The focus in empirical work has largely been on …xed income markets, for at least three reasons. First, they provide a readily available measure of monetary policy expectations. Second, they provide the most immediate avenue through which the central bank’s own interest rates a¤ect the economy. Third, central banks are often concerned with the volatility of interest rates and thus averse to surprising markets, as the quote above illustrates. Three approaches have been used to assess the impact of greater transparency on predictability. First, testing the extent to which market prices react to central bank decisions, second, examining forecast errors of expectations priced into the yield curve or futures and third, studying the accuracy of predictions by professional forecasters. Each approach has its own advantages and disadvantages. In this paper I use private sector forecasts of money market interest rates for four reasons. First, these represent a straightforward measure of expectations. Second, they are available for a broad set of countries. Third, they are available for fore1 Originally “FOMC” for the Federal Open Market Committee, the body that sets US monetary policy; clearly the same reasoning applies to any other central bank. 1 cast horizons out to a year. Fourth and importantly, it is possible to observe individual forecasts. Despite the signi…cant number of papers, there is still room for improvement in the empirical literature. Most studies only examine a limited number of advanced countries. They do this largely by comparing average predictability before and after speci…c reforms in communication policy. As a result, there is no real understanding of the relationship between varying levels of transparency (across time and space) and corresponding variations in predictability. The research presented in this paper addresses these gaps in the literature by utilizing the Dincer and Eichengreen (2007) index along with professional interest rate forecasts to study varying levels of transparency across 24 countries with di¤ering levels of economic development. Because one goal of improving monetary policy predictability is to reduce …nancial market and economic volatility, this paper also examines the impact of transparency on interest rate volatility. To establish a relationship between transparency, predictability and interest rate volatility requires measures of all three. In Section 3, I give a detailed description of datasets that can be used to do this. To measure transparency I employ the Dincer and Eichengreen (2007) index, which essentially counts the number of transparency enhancing institutions of each central bank. To measure predictability I use the error of professional interest rate forecasts at both three and twelve month horizons. To measure interest rate volatility I use the historic standard deviation of the same interest rates. Section 4 describes formally how public information could impact forecasts of interest rates and interest rate volatility. If an increase in transparency only improves public information then it will result in individual forecasts that become more accurate. However, if transparency has a negative impact on private information, as the theoretical and experimental research discussed below suggests, it could also lead to higher errors. Theoretically, market volatility behaves similarly to predictability, more public information should dampen volatility unless it hampers private information. As shown in Section 5, simple graphs and panel regression results suggest that transparency enhances predictability. Forecast errors decline signi…cantly at the three month horizon, but not at twelve months ahead. Transparency also lowers volatility. Overall the evidence suggests that transparency can indeed serve the goal outlined by Bernanke (2004), i.e. improving predictability helps to foster lower interest rate volatility. 2 2 Review of the literature on predictability The literature on central bank transparency and communication has grown rapidly over the last decade and now consists of hundreds of papers and articles. Di¤erent angles have been pursued. Many papers examine the implications of transparency in theoretical macroeconomic models. Others examine empirically if transparency has in‡uenced in‡ation and other macroeconomic variables. The impact of transparency on the …nancial markets has also been an important theme in the literature. Especially around the turn of the century, many articles examined if central bank communication had some impact on the …nancial markets, generally concluding that it does. The question addressed here goes a step further, asking whether transparency improves the predictability of monetary policy in the …nancial markets. This section reviews the theoretical, experimental and empirical evidence to date and highlights gaps in the literature that are addressed by research described in the remainder of the paper. Blinder, Ehrmann, Fratzscher, de Haan and Jansen (2008) and van der Cruijsen and Eij¢ nger (2007) o¤er broader overviews of the literature on transparency. 2.1 Theory Intuitively, one would expect better public information to improve market functioning, in the sense that …nancial markets become better at predicting the outcome of unrealized fundamentals. This is true in a basic rational expectations asset market model with exogenous public and private information.2 Under di¤erent assumptions or models, however, better public information can hamper market functioning. Probably the best known example is Morris and Shin (2002). They present a model where the pro…ts of individual agents depend not only on fundamental values but also on the expectations of others (clearly an issue in any market where assets can be sold before the realization of their fundamental value). Under these circumstances a su¢ ciently clear signal from the central bank can act as a coordinating point that could distract market participants from their private information and possibly fundamentals. Svensson (2006) argues that this conclusion is only valid for the unlikely situation where public signals are less precise than private information. However, Demertzis and Hoeberichts (2007) add costly information acquisition to Morris and Shin (2002)’s model and …nd that it strengthens their result. Another theoretical model by Dale, Orphanides and Osterholm (2008) demonstrates that if the private sector is not able to learn the precision of the central bank’s information, it may overreact to central bank communication. Kool et al. 2 See Kool, Middeldorp and Rosenkranz (2011), where the case of exogenous private information is equivalent to holding the fraction of informed traders constant. 3 (2011) …nd that public information can crowd out investment in private information, which hampers predictability, a conclusion supported by the experimental work of Middeldorp and Rosenkranz (2011). 2.2 Empirical studies Many empirical research papers have tried to assess if transparency improves the predictability of monetary policy in the …nancial markets.3 The general approach is to select a watershed communication reform and test the di¤erence between predictability before and afterwards. US studies typically use the …rst announcement of the Federal Open Market Committee’s (FOMC) rate decisions in February 1994, while for other countries the introduction of an in‡ation target, with its accompanying communication tools, is used. One can measure predictability in at least three ways. The …rst is to ascertain how surprised markets are by policy decisions. The second extracts expectations from the yield curve or futures to see how accurate they are. The third uses professional forecasts of interest rates. Taken together the evidence to date suggests that transparency improves predictability. The …rst approach to assessing the predictability of monetary policy involves examining market movements close to policy decisions. Little reaction in money market rates following a policy rate change suggests that it has been priced in and that policy is predictable. Money market movements prior to the decision in the same direction as the rate change can be interpreted as anticipating the move. Swanson (2006) …nds that US interest rates show less reaction to Fed decisions over the period where the Fed reformed its communication policy. Holmsen, Qvigstad, Øistein Røisland and Solberg-Johansen (2008) …nd lower volatility on the days the Norges Bank announced its decisions after it started to release forecasts of its own interest rates. Murdzhev and Tomljanovich (2006) and Coppel and Connolly (2003) show that policy changes are better anticipated in, respectively, six and eight advanced economies. Although such an approach is fairly intuitive and clear cut, its disadvantage is that it only provides a measure of market expectations between meetings and at the time of rate announcements. Communication reforms that allow market interest rates to anticipate monetary policy earlier than one meeting ahead can’t be identi…ed. A second method is to measure market expectations of monetary policy and examine how accurate these are. Typically expectations are either extracted from the yield curve or futures data. Here too, …ndings suggest that 3 A related strand of the literature does not address predictability in the …nancial markets but examines the usefulness of central bank communication in contructing forecasts of monetary policy. Some studies have simply asked if communications contain predictive power in itself; examples include Mizen (2009) and Jansen and de Haan (2009). Other studies examine if communication is useful in improving models that forecast monetary policy, such as the Taylor rule; recent examples are Sturm and de Haan (2009) for the ECB and Hayo and Neuenkirch (2009) for the FOMC. 4 transparency improves predictability. Ra¤erty and Tomljanovich (2002) and Lange, Sack and Whitesell (2003) …nd better accuracy for the US Treasury yield curve. Lildholdt and Wetherilt (2004) use a term structure model to show an improvement in the predictability of UK monetary policy. Similarly, Tomljanovich (2004) extracts expectations from bond yield curves and …nds that forecast errors decline in seven advanced economies after transparency reforms. Regarding futures rates, Swanson (2006) and Carlson, Craig, Higgins and Melick (2006) …nd that the Fed funds futures are better able to predict US monetary policy after communication reforms. Kwan (2007) concludes that forward looking language or guidance, introduced in 2003, has helped to lower the average error between the Fed funds futures and the actual outcome of the Fed funds rate. The disadvantage of using bond market expectations, is that such estimates are likely to be biased. The failure of the expectations hypothesis for the Treasury yield curve is a well-documented empirical result (e.g. Cochrane and Piazzesi (2005), Campbell and Shiller (1991), Stambaugh (1988), Fama and Bliss (1987)). Risk premiums on interest rates are positive on average and timevarying. Sack (2004) and Piazzesi and Swanson (2008) show that Fed funds futures rates also include risk premiums, particularly at longer maturities. Piazzesi and Swanson (2008) demonstrate how to adjust Fed funds futures rates for time-varying risk premiums using business cycle data. Middeldorp (2011) contributes to the literature on transparency by applying their correction to the question of the accuracy of the Fed funds futures. A third approach is to use predictions by professional forecasters. These are a direct measure of expectations, without risk premiums, and also allow one to observe individual forecasts. There are several studies that look at US interest rates. Swanson (2006) …nds an improvement in the accuracy of private sector interest rate forecasts. Berger, Ehrmann and Fratzscher (2006) …nd that communication reduces the disparity of Fed funds target rate predictions produced by forecasters from di¤erent locations. Hayford and Malliaris (2007) and Bauer, Eisenbeis, Waggoner and Zha (2006) …nd declining dispersion in US T-bill forecasts. Regarding other central banks, Mariscal and Howells (2006b) …nd a growing dispersion of private sector forecasts of Bundesbank and ECB monetary policy up to 2005, a result which runs counter to that for most others studies, including that of their own (2006b) research for the Bank of England. Several multi-country studies use professional forecasts, but they generally focus on economic rather than interest rate forecasts. Johnson (2002) shows a decline in in‡ation forecasts, but not in errors or variance, in an eleven country panel. Crowe (2006) …nds a convergence of in‡ation forecasts for eleven in‡ation targeters. Crowe and Meade (2008) demonstrate a convergence of in‡ation forecasts in line with increasing transparency as measured by an index. Cecchetti and Hakkio (2009), on the other hand, do not …nd convincing evidence of a reduction in the dispersion of in‡ation forecasts in a sample of 15 countries. 5 Ehrmann, Eij¢ nger and Fratzscher (2010) use various measures of central bank transparency to show a convergence of professional forecasts of both economic variables and interest rates in twelve advanced economies. To my knowledge, there are no studies like the one presented in this paper, that focus on interest rate forecasts using multi-country panel data. A disadvantage of professional forecasts versus the expectations embedded in interest rates is that it is not obvious that they are relevant to the transmission of monetary policy. It is, nevertheless, likely that they both re‡ect and in‡uence monetary policy expectations. Large …nancial institutions are the most common employers of professional forecasters and their views are actively dispersed to market participants and widely reported on in the press. Although there is a signi…cant number of empirical studies, they are limited in scope, both in their measure of transparency and geography. The vast majority of the empirical research discussed above only shows that the average predictability was higher after a particular communication reform than it was before. This provides only a binary measure of transparency that gives little sense of how much transparency has improved. Regarding geographic scope, studies have been conducted for a limited number of advanced economies, typically one country at a time. To address these issues I use a measure of transparency with a higher resolution, namely the Dincer and Eichengreen (2007) index, which uses a 15 point scale. Combined with the available data on interest rate forecasts, this produces a panel of 24 countries of varying levels of income, which provides much greater geographic scope than earlier research. 6 3 Data To establish the connection of transparency to interest rate predictability and volatility, one needs adequate measures of all three. I use the Dincer and Eichengreen (2007) index to measure transparency. It grades central banks according to the di¤erent types of information disclosed. Its main advantage is that it covers a larger set of countries and periods than earlier measures. Predictability is measured by the absolute error between private sector money market forecasts reported by Consensus Economics and realized market rates. The advantages and disadvantages of using professional forecasts were discussed in the literature review. To examine if transparency also impacts the volatility of interest rates, I also incorporate the standard deviation of interest rates into the dataset. Transparency is unlikely to be the only determinant of either predictability or volatility. Therefore, to control for overall perceptions of risk I utilize the commonly used …nancial risk indices of the PRS Group. 3.1 Transparency index Di¤erent measures of transparency have been assembled and corresponding data collected by various researchers. The approach was pioneered by Eij¢ nger and Geraats (2006), who measure transparency by scoring central banks on a checklist of 15 di¤erent types of disclosure, which are grouped into …ve categories: political, economic, procedural, policy and operational (see the Appendix). Their measure of transparency is based on the simple idea that more types of disclosure represent greater transparency. A disadvantage is that the quality of the information provided is neglected. On the other hand, precisely by avoiding additional interpretation it is possible to create an objective measure of transparency over a wide variety of central banks. Eij¢ nger and Geraats (2006) only have data available for nine advanced economies and for just the years 1998 and 2002. Crowe and Meade (2008) assemble data for 37 countries, following the same approach. Their data, however, is only available for 1998 and 2006, but not in between. Dincer and Eichengreen (2007) also employ the same method but gather data for a hundred countries for every year between 1998 and 2005. The scope of their dataset clearly surpasses other data sources, which is why it is used in this paper. However, due to the necessary availability of both the transparency data and the surveys of professional forecasts discussed below, only 24 of the hundred countries studied by Dincer and Eichengreen (2007) can be used. 7 Dincer and Eichengreen (2007) compare the disclosure checklist to the practice of central banks as documented on their websites and in their statutes, annual reports and other published documents. For some items half points are awarded. The approach followed results in a score for each central bank of between 0 and 15 for each year. Where reforms were introduced during the year, the score is based on the disclosures that existed during most of the year. Levels of transparency vary greatly over the sample studied in this paper, both over space and time. India only scores a 2 on the index compared to 13.5 for New Zealand in 2005 (see Figure 1 and Table 1). In between there is no concentration at any particular level of transparency. Lower-income economies tend to have lower levels of transparency, but this is not a hard-and-fast rule; the Czech Republic and Hungary are more transparent than the US while Norway is as transparent as Indonesia. Transparency has increased substantially over the majority of the countries studied and no country saw a decrease in transparency (see Figure 1 and Table 1). Although the three nations that show the largest increase in transparency are lower-income economies, the rates of improvement do not seem to be strongly associated with income levels. 8
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