Unobservable factors and panel data sets: an investigation in the labour market

This paper investigates the effects of unobservable factors that, as is well-known, contaminate two of the variables most used in labour market research, namely the stock of unemployment and the stock of vacancies. Using a matching function framework, we compare different panel data estimators using a number of appropriate Hausman tests robust to deviations from the classical errors assumptions. The relevance of the choice of the model specification is underlined. It is shown to what extent conclusions lacking a rigorous statistical analysis may be misleading.

Continuum-plasma solution surrounding nonemitting spherical bodies

The classical problem of the interaction of a nonemitting spherical body with a zero mean-free-path continuum plasma is solved numerically in the full range of physically allowed free parameters (electron Debye length to body radius ratio, ion to electron temperature ratio, and body bias), and analytically in rigorously defined asymptotic regimes (weak and strong bias, weak and strong shielding, thin and thick sheath). Results include current-voltage characteristics as well as floating potential and capacitance, for both continuum and collisionless electrons. Our numerical computations show that for most combinations of physical parameters, there exists a closest asymptotic regime whose analytic solutions are accurate to 15% or better

An urban sprawl index based on multivariate and Bayesian factor analysis with application at the municipality level in Valencia

[EN] Urban sprawl is now a common and threatening phenomenon in Europe, severely affecting environmental and economic sustainability. An analytical characterization and measurement of urban sprawl are required to gain a better understanding of the phenomenon and to propose the possible solutions. Traditional factor analysis techniques, especially Principal Component Analysis and Factor Analysis, have been commonly used. In this paper, we additionally test Independent Component Analysis with the aim to obtain a multidimensional characterization of the sprawl phenomenon. We also use Bayesian Factor Analysis to obtain a single (unidimensional) measuring index of sprawl, which also allows us to obtain the uncertainty of the inferred index, in contrast to traditional approaches. All these techniques have been applied to study the phenomenon of urban sprawl at the municipality level in Valencia, Spain using a wide set of variables related to the characteristics and patterns of urban land use.Gielen, E.; Riutort-Mayol, G.; Palencia Jiménez, JS.; Cantarino-Martí, I. (2017). An urban sprawl index based on multivariate and Bayesian factor analysis with application at the municipality level in Valencia. Environment and Planning B Planning and Design. 1-27. doi:10.1177/2399808317690148S12

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need accurate forecasts of the unemployment evolution in order to design short- or long-run local welfare policies. These predictions should then consider the spatial interrelations and dynamics of regional unemployment. In addition, a number of papers have demonstrated the improvement in the reliability of long-run forecasts when spatial dependence is accounted for. We estimate a heterogeneouscoefficients dynamic panel model employing a spatial filter in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment, as well as a spatial vector-autoregressive (SVAR) model. We compare the short-run forecasting performance of these methods, and in particular, we carry out a sensitivity analysis in order to investigate if different number and size of the administrative regions influence their relative forecasting performance. We compute short-run unemployment forecasts in two countries with different administrative territorial divisions and data frequency: Switzerland (26 regions, monthly data for 34 years) and Spain (47 regions, quarterly data for 32 years)

Regional age structure, human capital and innovation - is demographic ageing increasing regional disparities?

Demographic change is expected to affect labour markets in very different ways on a regional scale. The objective of this paper is to explore the spatio-temporal patterns of recent distributional changes in the workers age structure, innovation output and skill composition for German regions by conducting an Exploratory Space-Time Data Analysis (ESTDA). Beside commonly used tools, we apply newly developed approaches which allow investigating the space-time dynamics of the spatial distributions. We include an analysis of the joint distributional dynamics of the patenting variable with the remaining interest variables. Overall, we find strong clustering tendencies for the demographic variables and innovation that constitute a great divide across German regions. The detected clusters partly evolve over time and suggest a demographic polarization trend among regions that may further reinforce the observed innovation divide in the future