Structure, trends and determinants of growth and welfare indices:Cluster analysis of time-dependent and multivariate data

点击翻译按钮获取中文摘要

The analysis of monetary and nonmonetary empirical welfare distributions is of central importance both to the theory of welfare as well as to economic growth theory. Basic aspects are the occurrence of subgroups in the welfare distribution, the inter-temporal dynamics as well as the discovery of relevant determinants. To investigate these issues empirically, switching-regime models are basic econometric tools. A major goal of the project Ho 3260/3-1 was to further develop the statistical machinery of regime-switching models which is required for the analysis of welfare distributions. The actual analysis was conducted together with the projects Kl 1260/9-1 and Vo 1592/3-1. A major focus of interdisciplinary applications within the current grant request for extension is on joint modeling and analysis of subgroups within monetary and nonmonetary welfare indices like life expectancy, education or the Human Development Index (HDI). In case of such multivariate data, the form of the mixture component (mainly the multivariate normal distribution) often does not correspond well to the shape of potential clusters which may represent groups in the data. Therefore, the major new methodological goal is to further develop merging methods, i.e. methods which allow to objectively merge components of the mixture or hidden Markov model into joint clusters. A further applied emphasis is on regional convergence, in particular within the context of the eastern expansion of the EU. Here, the time-inhomogeneous hidden Markov models which were developed within the project Ho 3260/3-1 shall be applied. Finally, the developed methodology shall be used for the analysis of the distribution and determinants of growth-rates.