RT Report
T1 Are Forecast Updates Progressive?
A1 Chang, Chia-Lin
A1 Franses, Philip Hans
A1 McAleer, Michael
AB Many macro-economic forecasts and forecast updates, such as those from the IMF and OECD, typically involve both a model component, which is replicable, as well as intuition (namely, expert knowledge possessed by a forecaster), which is non-replicable. . Learning from previous mistakes can affect both the replicable component of a model as well as intuition. If learning, and hence forecast updates, are progressive, forecast updates should generally become more accurate as the actual value is approached. Otherwise, learning and forecast updates would be neutral. The paper proposes a methodology to test whether macro-economic forecast updates are progressive, where the interaction between model and intuition is explicitly taken into account. The data set for the empirical analysis is for Taiwan, where we have three decades of quarterly data available of forecasts and their updates of two economic fundamentals, namely the inflation rate and real GDP growth rate. The empirical results suggest that the forecast updates for Taiwan are progressive, and that progress can be explained predominantly by improved intuition.
PB Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid
YR 2011
FD 2011-03
LK https://hdl.handle.net/20.500.14352/48971
UL https://hdl.handle.net/20.500.14352/48971
LA eng
NO JEL Classifications: C53, C22, E27, E37.
NO National Science Council, Taiwan
NO Australian Research Council
NO Japan Society for the Promotion of Science
DS Docta Complutense
RD 6 abr 2025