How informative are interest rate survey-based forecasts?
| Autor | Feitosa, Mateus A. |
INTRODUCTION
The dynamics of interest rates have important implications for the economy and their forecasts are necessary for almost all economic activities. Participants in the financial markets require accurate forecasts of interest rates to make economic and financial decisions. These decisions have a heavy influence on aggregate-spending, which, in turn, affects real output and inflation.
In mid-1999, after moving to a floating exchange rate system, Inflation Targeting [IT] was implemented in Brazil. This new monetary framework proved to be fundamental in enhancing transparency and in guiding expectations. Additionally, evidence suggests a positive relationship between inflation targets and the credibility of monetary policy (2).
Other studies (see Minella, 2003) indicate that the Central Bank of Brazil is concerned exclusively with inflation control, thereby avoiding the inflation-output trade-off to enhance short-term production in Brazil. This behavior is an important aspect towards the construction of credibility.
In an IT framework the main goal of the Central Bank is to provide guidance to the economy to anchor expectations regarding the future path of inflation. Therefore, it is crucial to assess market expectations in a timely fashion and check whether they are in line with the conduct of monetary policy.
With the implementation of the IT regime in Brazil the Central Bank of Brazil began to collect information from market participants using surveys, which provide information regarding market expectations on relevant economic and financial variables such as short-term interest rates (SELIC) (3), inflation, exchange rates, GDP growth, and others. However, very little is known regarding the informational content of these survey-based market predictions. If the information content embedded in such predictions is relevant and meaningful then these surveys may be used to assess Central Bank credibility and eventually to calibrate the conduct of monetary policy.
In this paper, we study the dynamic relationship of interest rate based-survey forecasts and spot interest rates. Our results suggest that these market expectations contain useful information regarding the future evolution of interest rates and also that they may be used to gauge Central Bank credibility.
The rest of the paper will be structured as follows: in section Brief Literature Review a brief literature review is presented; section Data Description describes the data used in our estimates; section Methodology contains the methodology; in section Empirical Results we present the empirical results; in section Policy Implications the policy implications are discussed and, finally, section Final Considerations concludes.
BRIEF LITERATURE REVIEW
The market predictions for the interest rate are an important issue that has been studied for a long time, mainly in the case of the United States financial system. The studies analyze many questions, such as the directional accuracy of the predictions, the rationality of the forecasts and the quality of the methods used to forecast interest rates.
Friedman (1980) and Baghestani (2006) make an evaluation of the interest rates in the USA and both test the rationality of the forecasts. They both arrived at the same conclusion that the forecasts are not rational, i.e., they are unbiased and, in some cases, do not fully incorporate the information contained in past actual rates. Using Friedman's sample, Mishkin (1981) also tests the rationality of the forecasts and reached the opposite conclusion. The author argues that there is very little evidence in bond market data in support of the irrationality of interest rate forecasts. Jones and Roley (1983) rejected the joint hypotheses that forecasters form their expectations rationally and the expectations model of the term structure accurately represents equilibrium yields. However, because a joint hypothesis is tested, the precise cause of rejection cannot be determined.
Dua (1991) tests various hypotheses concerning the determinants of the three, six, and nine-month horizon term premia. He uses data on the three-month Treasury bill rate from the survey conducted by the American Statistical Association in collaboration with the National Bureau of Economic Research. His conclusion is that the term premia vary over time and are negative in some periods. They are heavily influenced by the level of interest rates and cyclical factors in addition to the level of rates. They are also influenced by Government economic policy.
Hafer, Hein and McDonald (1992) compare four different one-quarter ahead forecasts of the three-month U.S. Treasury-bill rate from the 12-year period 1977/88. The forecasts considered are: a prediction from the futures market, a forecast derived from an implicit forward rate calculation, a survey-gathered forecast and a no-change forecast. Their main conclusion is that the futures market rate statistically dominates the other three forecasts. Another comparison of forecasting methods is made by Fauvel, Paquet and Zimmermann (1999), which concludes that despite their apparent simplicity, univariate models tend to do pretty well in practice for forecasting purposes. Similarly, their natural extension to a multivariate setting (i.e. VAR and VECM) constitutes an interesting approach for an integrated treatment of various interest rates, including both their short-term dynamics and any existing long-run relationships.
Kolb and Stekler (1998) examine three issues: is there a general agreement among analysts about the level of interest rates six months in the future; are all the forecasters equally good; are the forecasts valuable to prospective users? They conclude that there is a consensus among financial analysts and there is no significant difference in the ability of these financial analysts to predict short-term interest rates. For the last issue, the conclusion is that the forecasts were not significantly better than random walk forecasts.
Greer (2003) tests the directional accuracy of long-term interest rate forecasts. The tests are applied to the 1-year long-term bond yield issued by The Wall Street Journal's panel of economic forecasters. The author affirms that the forecasts performed modestly better than flipping a fair coin to predict the direction of change in long-term interest rates. The forecast of movements in long-term interest rates were also studied by Pesando (1981), who concluded that economic agents are not likely to succeed in forecasting short-term movements in long-term interest rates.
Following the results found by previous studies, Mitchell and Pearce (2007) concluded that market forecasts for the Treasury bill rate had a performance very similar to the random walk model, even though they found no evidence that these forecasts are biased.
Overall, we have a poor understanding of the role of market expectations (implied in surveys) on the determination of interest rates. Do forecasts collected in surveys correctly predict changes in future interest rates? How do interest rates survey based forecasts interact with spot interest rates? This paper attempts to answer these questions by focusing on the Brazilian economy, which has had an inflation-targeting framework in operation since 1999, and has collected information on market expectations employing surveys since 2001.
DATA DESCRIPTION
Data from Selic and the market forecasts in the one, three and six-month horizon were used in this paper. The data consists of the period from November, 2001 to August, 2006. Selic series were taken from Bloomberg, and the market predictions series were taken from the Central Bank of Brazil, which has been monitoring market consensus for the most important economic variables since 2001. In this study, we use average forecasts, and our sample has 57 observations.
Table 1 presents the descriptive statistics of the series and it shows that Selic and the forecasts for all time horizons reject the null hypothesis of following a normal distribution, despite the low values of the skewness.
To test if the series are stationary, we employ the Augmented Dickey-Fuller [ADF] and the Kwiatkowski-Phillips-Schmidt-Shin [KPSS] tests. The results for Selic and the average of the Selic forecasts are shown in Table 2 and they indicate that all series are stationary. Consequently, the use of a VAR model is the appropriate method to study the dynamic relationship between these series.
The relationship between Selic and the three-month horizon forecast is presented in Figure 1. It indicates that the movements of the series over time are very similar, and it appears that the...
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