Although discrete hours choice models have become the workhorse in labor supply analyses. Yet, they are often criticized for being a black box due to their numerous underlying modeling assumptions, with respect to, e.g., the functional form, unobserved error components or several exogeneity...

The paper considers two rival models referring to the new macroeconomic consensus: a standard three-equations model of the New-Keynesian variety and dynamic adjustments of a business and an inflation climate in an `Old-Keynesian' tradition. Over the two subperiods of the Great Inflation and...

The paper considers an elementary New-Keynesian three equation model and compares its Bayesian estimation to the results from the method of moments (MM), which seeks to match a finite set of the model-generated second moments of in ation, output and the interest rate to their empirical...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

This study analyzes the performance of the IMF World Economic Outlook forecasts for world output and the aggregates of both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current and the next year, we examine whether IMF forecasts can be...

We propose a monitoring procedure to detect a structural change from stationary to integrated behavior. When the procedure is applied to the errors of a relationship between integrated series it thus monitors a structural change from a cointegrating relationship to a spurious regression. The...

We model credit rating histories as continuous-time discrete-state Markov processes. Infrequent monitoring of the debtors' solvency will result in erroneous observations of the rating transition times, and consequently in biased parameter estimates. We develop a score test against such...

We investigate the accuracy of ex ante assessments of vulnerability to poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a household as...

Seasonally adjusted gross domestic product (GDP) data are inevitably surrounded by uncertainty. Disregarding methodological improvements, two main sources of revisions can be distinguished: First, revisions that reflect the incorporation of more comprehensive or more representative, but...

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....