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PurposeThis study examines the forecasting performance of the professional analysts participating in the Blue Chip Economic Indicators Survey using an alternative methodological research design.Design/methodology/approachThis work employs two methodologies, namely a panel specification, with the cross-section being the forecast horizon (from 1-month to 18-months ahead forecasts) and the time period being the time that the forecast was made and a quantile regression technique, which evaluates the hidden nonmonotonic relations between the forecasts and the target variables being forecasted.FindingsThe empirical findings of this study show that survey-based forecasts of certain key macroeconomic variables are generally biased but still efficient predictors of target variables. In particular, we find that survey participants are more efficient in predicting long-term interest rates in the long-run and short-term interest rates in the short run, while the predictability of medium-term interest rates is the least accurate. Finally, our empirical analysis suggests that currency fluctuations are very hard to predict in the short run, while we show that survey-based forecasts are among the most accurate predictors of GDP deflator and growth.Practical implicationsEvaluating the accuracy of economic forecasts is critical since market participants and policymakers utilize such data (as one of several inputs) for making investment, financial and policy decisions. Therefore, the quality of a decision depends, in part, on the quality of the forecast. Our empirical results should have immediate implications for asset pricing models that use interest rates and inflation forecasts as variables.Originality/valueThe present study marks a methodological departure from existing empirical attempts as it proposes a simpler yet powerful approach in order to investigate the efficiency of professional forecasts. The employed empirical specifications enable market participants to investigate the information content of forecasts over different forecast horizons and the temporal evolution of forecast quality.

The interest rate plays an important role in the economies. It's like a self-regulator of capital allocation. Interest rate changes is a complex mechanism: 1) the economic downturn in the demand for credit decreases and this reduces the cost of credit, 2) economic recession increases credit risk, which is the rate-increasing factor, 3) improving the country's economic situation, growth of gross domestic product and positive direction of change of other macroeconomic variables, interest rates may rise. Factors affecting the rate can be divided into three categories: economic (inflation and the country's economic activity, the degree of foreign influence on financial markets, government securities supply and demand changes), political (control of the money supply, changes in the tax area, the reserve rate) and social (in the age structure of the population employment rate). The financial crisis is a challenge for everyone. In order to reduce stress in the financial sector, to increase the liquidity of the financial system and the implementation of monetary policy incentives measures, the ECB's key interest rate was reduced to a minimum low limit. Negative central bank policy interest rates in history have few examples: Switzerland (foreign currency deposits), Sweden, and Denmark (certificates of deposit), Switzerland, Denmark and Germany (negative short-term bond yields). ECB's cheap and readily available monetary policy can be a deciding factor in lending, businesses moving out of recession in the development phase. Requires detailed studies assessing the risk of interest rate theory implications for financial stability. DOI: https://doi.org/10.15544/ssaf.2012.21