This paper delevops a tools to analyse the ordering of concordance of random vectors.

This papfer deals with distributional free inference to test for positive quadrant dependence, i.e. for the probability that two variables are simultaneously small (or large) being at least as great as it would be were they dependent.

Partial-least squares regression (PLS) is a statistical tool specifically designed to cope with problems like small datasets, missing values and the presence of multicollinearity . The paper proceeds first with a concise review of the PLS method.

In this paper we want to discuss macroscopic and microscopicproperties of financial markets. By analyzing quantitatively a database consisting of 13 minute per minute recorded financial time series, we identify some macroscopic statistical properties of the corresponding markets, with a special...

The varieties of capitalism approach (VoC) and the related research assume that German firms adopt an internal flexibility profile that corresponds with the national institutional framework. Recent empirical studies, however, have found substantial diversity in realized firm-level strategies....

The aim of this article is to analyse the technical efficiency of Hungarian crop farms between 2001 and 2009 using panel data. We employ both standard stochastic frontier analysis and latent class model (LCM) to estimate technical efficiency. Our results suggest that technological heterogeneity...

Using two different measures of immigrant labour-market integration (the ratio between immigrant unemployment to native unemployment, and the ratio of employment rate among natives and immigrants) this paper tests six suggested explanations of why immigrants are less likely than natives to be...

This paper deals with the identification of treatment effects when the outcome variable is ordered. If outcomes are measured ordinally, previously developed methods to investigate the impact of an endogenous binary regressor on average outcomes cannot be applied as the expectation of an ordered...

We analyze macroeconomic data using univariate and multivariate forecast combining techniques. We simulate forecast errors with different variance-covariance structures. The simulations are used to compare the performance of univariate and multivariate combining techniques.