The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model...

Since the end of the 2000s, the question of the decline of French medium-sized towns has become central within the scientific and public debate. More specifically, two processes are underlined: the devitalisation of city centres on the one hand, and urban shrinkage on the other hand. The...

The study concentrates on an analysis of the Czech stock market performed by an application of DCC MV GARCH model of Engle (2002). Data sample including years from 1994 to 2009 is represented by daily returns of Prague Stock Exchange index and other 11 major stock indices. There is found an...

In this paper, the profitability indicators are analysed for the first hundred companies of the Croatian market, which are classified according to the net profit. The profitability indicators included in the analysis are the following: EBIT margin, EBITDA margin, net profit margin, return on...

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

This paper discusses a large-scale factor model for the German economy. Following the recent literature, a data set of 121 time series is used via principal component analysis to determine the factors, which enter a dynamic model for German GDP. The model is compared with alternative univariate...

We propose a dynamic factor model for the analysis of multivariate time series count data. Our model allows for idiosyncratic as well as common serially correlated latent factors in order to account for potentially complex dynamic interdependence between series of counts. The model is estimated...

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between...

Comparing groups with respect to hypothetical constructs requires that the measurement models are equal across groups. Otherwise conclusions drawn from the observed indicators regarding differences at the latent level (mean differences, differences in the structural relations) might be severly...

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