In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

Structural VARs have been extensively used in empirical macroeconomics during the last two decades, particularly in analyses of monetary policy. Existing Bayesian procedures for structural VARs are at best confined to a severly limited handling of cointegration restrictions. This paper extends...

We use a Vector Auto Regression (VAR) analysis to explore the (spill-over) effects of fiscal policy shocks in Europe. To enhance comparability with the existing literature, we first analyse the effects of these shocks at the national level. Here, we employ identification based on Choleski...

This paper explores the behavior of profits in the four largest euro area countries (Germany, France, Italy and Spain) and the euro area as a whole, while at the same time considering three main sectors (manufacturing, construction and services) in each economy over the period 1988–2010. The...

Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-ofsample forecasts, particularly for models with many variables. A...

In this paper we develop empirical measures for the strength of spillover effects. Modifying and extending the framework by Diebold and Yilmaz (2011), we quantify spillovers between sovereign credit markets and banks in the euro area. Spillovers are estimated recursively from a vector...

In this paper we apply statistical inference techniques to build neural network models which are able to explain the prices of call options written on the German stock index DAX. By testing for the explanatory power of several input variables serving as network inputs, some insight into the...