In the current literature uncertainty about the future course of the economy is identified as a possible driver of business cycle fluctuations. In fact, uncertainty surrounds the movements of all economic variables which gives rise to a monitoring problem. We identify the different dimensions of...

Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively...

The aim of this paper is to assess the dimension of factors and shocks that drive financial conditions, and in particular financial stress in the euro area. A second aim is to construct summary indices on the conditions and level of stress in financial markets with the aid of a dynamic factor...

In 1950, Latin American countries capabilities were promising, and the subcontinent was thought to have a big potential for convergence. In order to understand why this prediction was not fulfilled, we apply in this paper the framework set by Fagerberg and Srholec (2008(24)). Our study of the...

Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals...

This paper presents an econometric mediation analysis. It considers identification of production functions and the sources of output effects (treatment effects) from experimental interventions when some inputs are mismeasured and others are entirely omitted.

Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...

The MDGs are interlinked: acceleration in one goal is likely to speed up progress in others. Nevertheless, these synergies are not always visible, and may differ across countries. Using bivariate cluster analysis, this paper investigates whether distinct groups of developing countries can be...

The segregation indices measure how uneven is the distribution of a certain group within a geographical area. This article deals with segregation indices and presents the methodology of how they are derived and functionality of each. Then an application is made for the formal labor income for...

Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal processing, mechanical engineering, psychometrics, and other fields under different names. It still bears the same mathematical idea: the...