Judgmental Forecast

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Judgmental Forecast

A forecast made on subjective information. A judgmental forecast is made by a person thought to be knowledgeable about the company or market about which the forecast is being made. It may consider quantitative information, but it relies on a great deal of subjective feeling.
References in periodicals archive ?
Second, a wide body of literature suggests that judgmental forecasts are likely to be of dubious accuracy.
In other words, greater expertise does not lead to better judgmental forecasts.
When evaluating DSGE models on an absolute basis, however, we find that the benchmark estimated mediumscale DSGE model forecasts inflation and GDP growth very poorly, although statistical and judgmental forecasts do equally poorly.
Section V considers robustness analysis and extensions, showing in particular that judgmental forecasts have adjusted faster than the others to capture developments during the Great Recession.
They found that these judgmental forecasts were not, in most cases, more accurate than the naive forecast, and the forecasts suffered from both inefficiency and bias.
In general, they found the judgmental forecasts to be less than optimal.
Armstrong and Collopy (1998) demonstrated how to integrate objective forecasts with judgmental forecasts to gain more confidence in future forecasts.
Future research related to the PMI should explore the use of combining judgmental forecasts with the quantitative forecasting of the PMI.
Econometric and judgmental forecasts were obtained from commercial forecasting agencies.
Also, Makridakis (1987) indicated that managers should prepare a separate judgmental forecast, and then objectively combine it with quantitative forecasts, rather than use judgment for the blending process itself.
The advantages and limitations of economic models and judgmental forecasts are reviewed, and a process that incorporates features of both is recommended.
If the linkages among policy, the economy, and prices were well enough understood, reasonably stable over time, and mostly free from noise, they might be captured by a reliable empirical model or perhaps by judgmental forecasts.