We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

A solution method is derived in this paper for solving a system of linear rationalexpectations equation with lagged expectations (e.g., models incorporating sticky information) using the method of undetermined coefficients for the infinite MA representation. The method applies a combination of a...

In this note we establish the existence of the first two moments of the asymptotic tracestatistic, which appears as weak limit of the likelihood ratio statistic for testing the cointe-gration rank in a vector autoregressive model and whose moments may be used to developpanel cointegration tests....

Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of the...

Exploratory factor analysis (EFA) is an important tool in data analyses,particularly in social science. Usually four steps are carried out which contain alarge number of options. One important option is the number of factors and theassociation of variables with a factor. Our tools aim to...

Independent component analysis (ICA) is a modern factor analysis tool developed in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then...

Teaching statistics to students in our area of economics and educationalscience often brings about the problem that students have either forgottentheir statistical knowledge, or have taken different classes than the ones weoffer in basic statistics. We therefore need some kind of statistical...

We introduce new stylometry tools based on the sliced conditional compression complexity of literary texts which are inspired by the nearly optimal application of the incomputable Kolmogorov conditional complexity (and presumably approximates it). Whereas other stylometry tools can occasionally...

Linear Methods are often used to compute approximate solutions to dynamic models, as these models often cannot be solved analytically. Linear methods are very popular, as they can easily be implemented. Also, they provide a useful starting point for understanding more elaborate numerical...