Disagreement Amongst Forecasters has Predictive Value

Forecasts from various experts are often used in macroeconomic forecasting models. Usually the focus is on the mean or median of the survey data. In a new study researchers adopt a different perspective on the survey data as they examine the predictive power of disagreement amongst forecasters.  

The premise is that this variable could signal upcoming structural or temporal changes in an economic process or in the predictive power of the survey forecasts. In their empirical work, the researchers haved examined a variety of macroeconomic variables and uses different measurements for the degree of disagreement, together with measures for location of the survey data and autoregressive components.

Forecasts from simple linear models and forecasts from Markov regime-switching models with constant and with time-varying transition probabilities were constructed in real-time and compared on forecast accuracy. They found that disagreement has predictive power indeed and that this variable can be used to improve forecasts when used in Markov regime-switching models.

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