We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the quality of their return forecasts. In the low signal-to-noise environment of a one month horizon, we find that it is preferable to rely on a theory-based approach instead of engaging...

Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of forecast rationality when the measure of...

Releases of key macroeconomic indicators are closely watched by financial markets. We investigate the role of expectation dispersion and economic uncertainty for the stock-market reaction to indicator releases. We find that the strength of the financial market response to news decreases with the...

Global container ship movements may reliably predict global trade flows. Aggregating both movements at sea and port call events produces a wealth of explanatory variables. The machine learning algorithm partial least squares can map these explanatory time series to unilateral imports and...

Christoph Heible evaluiert die gesundheitswirtschaftlichen Effekte des medizinisch-technologischen Fortschritts und des demografischen Wandels auf Basis modellgestützter und szenarienbasierter Analysen. Der Autor belegt u.a., dass von medizinisch-technischem Fortschritt nicht zwangsläufig...

The failure of economists to anticipate the global financial crisis and mitigate the impact of the ensuing recession has spurred a public outcry. Economists are under fire, but questions concerning exactly how to redeem the discipline remain unanswered. In this provocative book, renowned...