Using monthly GDP forecasts from Consensus Economics Inc. for 18 developed countries reported over 24 different forecast horizons during 1989-2004, we find that the survey forecasts do not have much value when the horizon goes beyond 18 months. Using two alternative approaches to measure the flow of new information in fixed-target survey forecasts, we found that the biggest improvement in forecasting performance comes when the forecast horizon is around 14 months. The dynamics of information accumulation over forecast horizons can provide both the forecasters and their clients with an important clue in their selection of the timing and frequency in the use of forecasting services. The limits to forecasting that these private market forecast...
This paper discusses how forecasts are affected by the use of real-time data rather than latest-avai...
We present a novel approach to assessing the attentiveness of professional forecasters to news about...
We estimate a Bayesian learning model with heterogeneity aimed at explaining the evolution of expert...
For stationary transformations of variables, there exists a maximum horizon beyond which forecasts c...
For stationary transformations of variables, there exists a maximum horizon beyond which forecasts c...
We develop an unobserved components approach to study surveys of forecasts containing multiple forec...
We develop an unobserved components approach to study surveys of forecasts containing multiple forec...
We develop tests for the null hypothesis that forecasts become uninformative beyond some maximum for...
We develop an econometric framework for understanding how agents form expectations about economic va...
For quantities that are approximately stationary, the information content of statistical forecasts t...
In this paper, we use survey data to analyze the accuracy, unbiasedness and efficiency of profession...
In economic forecasting, it is important that the forecasts be based on data that is both reliable a...
We present a novel approach to assessing the attentiveness of professional forecasters to news about...
We document information rigidity in forecasts for real GDP growth in 46 countries over the past two ...
How often should we update predictions for economic activity? Gross domestic product is a quarterly ...
This paper discusses how forecasts are affected by the use of real-time data rather than latest-avai...
We present a novel approach to assessing the attentiveness of professional forecasters to news about...
We estimate a Bayesian learning model with heterogeneity aimed at explaining the evolution of expert...
For stationary transformations of variables, there exists a maximum horizon beyond which forecasts c...
For stationary transformations of variables, there exists a maximum horizon beyond which forecasts c...
We develop an unobserved components approach to study surveys of forecasts containing multiple forec...
We develop an unobserved components approach to study surveys of forecasts containing multiple forec...
We develop tests for the null hypothesis that forecasts become uninformative beyond some maximum for...
We develop an econometric framework for understanding how agents form expectations about economic va...
For quantities that are approximately stationary, the information content of statistical forecasts t...
In this paper, we use survey data to analyze the accuracy, unbiasedness and efficiency of profession...
In economic forecasting, it is important that the forecasts be based on data that is both reliable a...
We present a novel approach to assessing the attentiveness of professional forecasters to news about...
We document information rigidity in forecasts for real GDP growth in 46 countries over the past two ...
How often should we update predictions for economic activity? Gross domestic product is a quarterly ...
This paper discusses how forecasts are affected by the use of real-time data rather than latest-avai...
We present a novel approach to assessing the attentiveness of professional forecasters to news about...
We estimate a Bayesian learning model with heterogeneity aimed at explaining the evolution of expert...