Adaptive learning and survey data
This paper investigates the ability of the adaptive learning approach to replicate the expectations of professional forecasters. For a range of macroeconomic and financial variables, we compare constant and decreasing gain learning models to simple, yet powerful benchmark models. We find that constant gain models provide a better fit for the expectations of professional forecasters. For macroeconomic series they usually perform significantly better than a naïve random walk forecast. In contrast, we find it difficult to beat the no-change benchmark using the adaptive learning models to forecast financial variables.
|Adaptive learning, Bounded rationality, Expectations, Survey of professional forecasters|
|ERIM Top-Core Articles|
|Journal of Economic Behavior & Organization|
|Organisation||Erasmus School of Economics|
Markiewicz, A, & Pick, A. (2014). Adaptive learning and survey data. Journal of Economic Behavior & Organization. doi:10.1016/j.jebo.2014.04.005