Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

We propose a dynamic factor model which we use to analyze the relationship between education participation and national unemployment, as well as to forecast the number of students across the many different types of education. By clustering the factor loadings associated with the dynamic...

Systems of civil service reflect specific needs, traditions and institutional fundamentals of every state. The paper provides an outline of the European context of civil service, characteristics of basic features of civil service in EU countries, and evaluation of selected determinants of civil...

Child birth leads to a break in a woman's employment history and is considered one reason for the relatively poor labor market outcomes observed for women compared to men. However, the time spent at home after child birth varies significantly across mothers and is likely driven by observed and,...

This paper presents a variance decomposition method - factor analysis with Procrustes rotation - that is capable of separating the global, regional and idiosyncratic components of various financial market indicators. The method is applied to indicators of five key financial markets: sovereign...

The paper addresses the topic of an overall long-term productivity slowdown in labor productivity for a panel of 25 developed countries. Besides studying individual long-term trends of single countries using filtering techniques we also test for multiple structural breakpoints in the long-term...

High dimensional composite index makes experts' preferences in setting weights a hard task. In the literature, one of the approaches to derive weights from a data set is Principal Component or Factor Analysis that, although conceptually different, they are similar in results when FA is based on...

The paper presents forecasts of headline and core inflation in Estonia with factor models in a recursive pseudo out-of-sample framework. The factors are constructed with a principal component analysis and are then incorporated into vector autoregressive (VAR) forecasting models. The analyses...

Which type of work do Italians perform? In this contribution we aim at detecting the anatomy of the Italian occupational structure by taking stock of a micro-level dataset registering the task content, the execution of procedures, the knowledge embedded in the work itself, called ICP (Indagine...