We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectation-formation process in the U.S. stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectation-formation process in the U.S. stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time...

Survey data of forecasts of the housing market may provide a particularly rich data nvironment for researchers and policymakers to study developments in housing markets. Based on the approach advanced by Elliott et al. (Rev. Ec. Studies. 72, 1197-1125, 2005), we studied the properties of a large...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectationformation process in the US stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time as...

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report three results. 1) Real-time macroeconomic data did not contribute much to ex ante...

We used a recursive modeling approach to study whether investors could, in real time, have used information on the comovement of stock markets to forecast stock returns in European stock markets for high-technology firms. We used weekly data on returns in the Neuer Markt, the Nouveau Marché,...