There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a...

This paper considers estimation methods and inference for linear dynamic panel data models with unit-specific heterogeneity and a short time dimension. In particular, we focus on the identification of the coefficients of time-invariant variables in a dynamic version of the Hausman and Taylor...

This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979) twostep estimator for estimating a selection model. It shows that exploratory work to check for collinearity problems is strongly recommended before deciding on which estimator to apply. In the...

A decade ago, the German Advisory Council to the Federal Government on Global Environmental Change (Wissenschaftlichen Beirats der Bundesregierung für Globale Umweltveränderungen - WBGU) published its main report. This attempt to take stock in 2011 made an impact and provided orientation on...

Vor einem Jahrzehnt wurde das Hauptgutachten des Wissenschaftlichen Beirats der Bundesregierung für Globale Umweltveränderungen (WBGU) veröffentlicht. Dieser Versuch einer Bestandsaufnahme im Jahre 2011 hat national und international Impulse gesetzt und Orientierung gegeben. Der WBGU ging...

We develop a new Bayesian estimator that is able to deal with multivariate panel data structure in the presence of spatial correlation. The analysis of panel data introduced here allows us to analyze not only the fixed effect but also the random effect model. This work extends the previous study...

This paper describes the inference procedures required to perform Bayesian inference to some multivariate econometric models. These models have a spatial component built into commonly used multivariate models. In particular, the seemingly unrelated regression and vector autoregressive models are...

We analyze Granger causality testing in a mixed-frequency VAR, where the difference in sampling frequencies of the variables is large. Given a realistic sample size, the number of high-frequency observations per low-frequency period leads to parameter proliferation problems in case we attempt to...