We propose a new approach to test the full-information rational expectations hypothesis which can identify whether rejections of the arise from information rigidities. This approach quantifies the economic significance of departures from the and the underlying degree of information rigidity. Applying this approach to U.S. and international data of professional forecasters and other agents yields pervasive evidence consistent with the presence of information rigidities. These results therefore provide a set of stylized facts which can be used to calibrate imperfect information models. Finally, we document evidence of state-dependence in the expectations formation process.
External headwinds, together with domestic vulnerabilities, have loomed over the prospects of
emerging markets in recent years. We propose an empirical toolbox to quantify the impact of external
macro-financial shocks on domestic economies in parsimonious way. Our model is a Bayesian VAR
consisting of two blocks representing home and foreign factors, which is particularly useful for small
open economies. By exploiting the mixed-frequency nature of the model, we show how the toolbox
can be used for “nowcasting” the output growth. The conditional forecast results illustrate that regular
updates of external information, as well as domestic leading indicators, would significantly enhance
the accuracy of forecasts. Moreover, the analysis of variance decompositions shows that external
shocks are important drivers of the domestic business cycle.