JUDGEMENTAL FORECASTING

Judgmental Forecasting

Judgmental Forecasting

Judgmental Forecasting

There are other forecasting methods that forecasters can use apart from time series forecasting methods and casual methods. Forecasters can use the judgmental forecasting method. Judgmental forecasting is the most common method of forecasting. The method has been used in different areas including business, technology and even weather forecasting. Judgmental forecasting is used when the decision being made is critical (Andreassen, & Kraus, 1990, pp.347 - 372). In this case, the forecaster has to make a judgmental method to forecast the value of the variables. In addition, the judgmental forecasting is used when the data needed for forecasting the value of a variable is not available.

Andreassen and Kraus (1990) and Lawrence and O'Connor (1992, 1995) demonstrated that judgmental forecasting can be modeled as single exponential smoothing, or alternatively as anchor and adjustment, where the anchor point is the average of recent time series values and the adjustment is the proportion of deviation of the most recent value from this average. When modeled as exponential smoothing, the judgmental forecaster appears to use a value of the smoothing constant dependent on the characteristics of the series. As the forecast horizon increases, less emphasis is placed on the last observation. Each of these characteristics is appropriate for achieving accuracy. Thus one can conclude that judgmental forecasting accuracy is the product of a good subjective model being applied.

However, these results again depend on the characteristics of the series and the presentation of the task. But as Goodwin and Wright (1993) pointed out, although a good fit was obtained, a wide range of alternative models was not investigated. Highlighting the contingent nature of the time series and the task presentation, Harvey, Bolger and McClelland (1991), using a strongly cyclical series with low levels of noise and a tabular presentation of information ...