Optimization clustering techniques on register unemployment data

An important strategy for data classification consists in organising data points in clusters. The k-means is a traditional optimisation method applied to cluster data points. Using a labour market database, aiming the segmentation of this market taking into account the heterogeneity resulting from different unemployment characteristics observed along the Portuguese geographical space, we suggest the application of an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. This approach presents results consistent with the results obtained by the k-means.info:eu-repo/semantics/publishedVersio

Technological Diffusion, Spatial Spillovers And Regional Convergence In Europe

In this paper we study two closely related issues. First, the role of technology heterogeneity and diffusion in the convergence of GDP per worker observed across the European regions, in the absence of data on regional TFP. Second, the spatial pattern of the observed regional heterogeneity in technology and the relevance of this pattern for the econometric analysis of regional convergence in Europe. As for the first issue, our aim is to assess whether the convergence observed across European regions is due to convergence in technology as well as to convergence in capital-labor ratios. We first develop a growth model where technology accumulation in lagging regions depends on their own propensity to innovate and on technology diffusion from the leading region, and convergence in GDP per worker is due to both capital deepening and catch-up. We use data (1978-97) on 131 European regions. Propensities to innovate are computed by assigning each patent collected by the European Patent Office to its region of origin. Our findings are consistent with the hypothesis that technology differs across regions and that convergence is partly due to technological catch-up. As for the second empirical issue, we study to what extent each region's propensity to innovate is correlated with that of the surrounding regions. Our results show, first, that the performance of each region does depend on that of the surrounding areas. Second, that the intensity of such spillovers fades with distance. Taken together, these findings suggest the existence of significant localized spillovers of technological knowledge. Finally, we show that these spillovers are strong enough to play a role that cannot be ignored in the econometric analysis of the convergence process in Europe

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)

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Precision Measurement of the Boron to Carbon Flux Ratio in Cosmic Rays from 1.9 GV to 2.6 TV with the Alpha Magnetic Spectrometer on the International Space Station

Knowledge of the rigidity dependence of the boron to carbon flux ratio (B/C) is important in understanding the propagation of cosmic rays. The precise measurement of the B/C ratio from 1.9 GV to 2.6 TV, based on 2.3 million boron and 8.3 million carbon nuclei collected by AMS during the first 5 years of operation, is presented. The detailed variation with rigidity of the B/C spectral index is reported for the first time. The B/C ratio does not show any significant structures in contrast to many cosmic ray models that require such structures at high rigidities. Remarkably, above 65 GV, the B/C ratio is well described by a single power law R[superscript Δ] with index Δ=-0.333±0.014(fit)±0.005(syst), in good agreement with the Kolmogorov theory of turbulence which predicts Δ=-1/3 asymptotically.National Science Foundation (U.S.) (Grants 1455202 and 1551980)Wyle Research (Firm) (Grant 2014/T72497)United States. National Aeronautics and Space Administration (NASA Earth and Space Science Fellowship Grant HELIO15F-0005

Electron and positron fluxes in primary cosmic rays measured with the alpha magnetic spectrometer on the international space station

Precision measurements by the Alpha Magnetic Spectrometer on the International Space Station of the primary cosmic-ray electron flux in the range 0.5 to 700 GeV and the positron flux in the range 0.5 to 500 GeV are presented. The electron flux and the positron flux each require a description beyond a single power-law spectrum. Both the electron flux and the positron flux change their behavior at &sim;30GeV but the fluxes are significantly different in their magnitude and energy dependence. Between 20 and 200 GeV the positron spectral index is significantly harder than the electron spectral index. The determination of the differing behavior of the spectral indices versus energy is a new observation and provides important information on the origins of cosmic-ray electrons and positrons.</p

High statistics measurement of the positron fraction in primary cosmic rays of 0.5-500 GeV with the alpha magnetic spectrometer on the international space station

A precision measurement by AMS of the positron fraction in primary cosmic rays in the energy range from 0.5 to 500 GeV based on 10.9 million positron and electron events is presented. This measurement extends the energy range of our previous observation and increases its precision. The new results show, for the first time, that above &sim;200GeV the positron fraction no longer exhibits an increase with energy.</p