This paper argues that forecast estimators should minimise the loss function in a statistical, rather than deterministic, way. We introduce two new elements into the classical econometric analysis: a subjective guess on the variable to be forecasted and a probability reflecting the confidence...

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...

This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

Eine große Herausforderung der multivariablen Analyse mit bilanziellen Kennzahlen besteht in der Identifikation derjenigen Kennzahlen, die zur besten Modellperformance führen und dabei möglichst leicht interpretierbar und intuitiv bleiben. Die Menge der in Frage kommenden Kennzahlen ist in...

We develop a method for directly modeling cointegrated multivariate time series that are observed in mixed frequencies. We regard lower-frequency data as regularly (or irregularly) missing and treat them with higher-frequency data by adopting a state-space model. This utilizes the structure of...

This paper proposes a new method of forecasting euro area quarterly real GDP that uses area-wide indicators, which are derived by optimally pooling the information contained in national indicator series. Following the ideas of predictive modeling, we construct the area-wide indicators by...

This paper empirically analyzes whether the character-based approach, which is based on the personality structure and the human capital of business founders, allows prediction of entrepreneurial success. A unique data set is used consisting of 414 previously unemployed persons whose personal...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...