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 ?

As with most judgmental forecasts, the maximum projection horizon for the Greenbook forecast is not constant across vintages but varies from 6 to 10 quarters, depending on the forecast round.

The DSGE model and the BVAR produce continuous (and in very recent periods negative) interest rate forecasts, whereas the judgmental forecasts obviously factor in the discrete nature of interest rate setting and the zero nominal bound.

Here we adjust the DSGE model and BVAR forecasts using the realized future population growth numbers to make them comparable to announced GDP growth rates and judgmental forecasts, but we again note that this is an imperfect adjustment, which likely reduces the forecasting ability of the DSGE model and the BVAR.

It is not very surprising that judgmental forecasts fare better in capturing such regime switches.

How useful are estimated DSGE model forecasts for central bankers?

Judgmental forecasts of time series affected by special events: does providing a statistical forecast improve accuracy.

An overview of forecasting error among international manufacturers

Judgmental forecasts should be another tool as well.

Future research related to the PMI should explore the use of combining judgmental forecasts with the quantitative forecasting of the PMI.

As the PMI turns: a tool for supply chain managers

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.

Forecasting foreign exchange rates using objective composite models

In other words, greater expertise does not lead to better judgmental forecasts.

Research suggests that judgmental forecasts can also be improved by simply averaging the results of multiple independent forecasts.

Cognitive biases do much to explain the limitations of judgmental forecasts, but Tetlock's work suggests an additional explanation.

In cases where expert judgment is an appropriate method of forecasting, this article has identified a number of strategies for mitigating the weaknesses of judgmental forecasts, including documenting forecasts, not relying on a single forecaster, understanding cognitive biases and taking steps to mitigate them, and using some type of algorithm.