4 resultados para national incomes

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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How immigration affects the labor market of the host country is a topic of major concern for many immigrant-receiving nations. Spain is no exception following the rapid increase in immigrant flows experienced over the past decade. We assess the impact of immigration on Spanish natives’ income by estimating the net immigration surplus accruing at the national level and at high immigrant-receiving regions while taking into account the imperfect substitutability of immigrant and native labor. Specifically, using information on the occupational densities of immigrants and natives of different skill levels, we develop a mapping of immigrant-to-native self-reported skills that reveals the combination of natives across skills that would be equivalent to an immigrant of a given self-reported skill level, which we use to account for any differences between immigrant self-reported skill levels and their effective skills according to the Spanish labor market. We find that the immigrant surplus amounts to 0.04 percent of GDP at the national level and it is even higher for some of the main immigrant-receiving regions, such as Cataluña, Valencia, Madrid, and Murcia.

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[EN] Enforcement of rural policy measures within National Parks may have a particular importance as they may contribute to reach socioeconomic objectives devised for such areas. So this paper approaches as case study the application of a relevant rural development measure in the Northumberland National Park (NNP) –England, North East— over the period 2000-2008 in order to explore whether NNP makes any difference in terms of enforcing rural policy measures. The main research findings indicate that NNP may have some sort of positive impact on rural development, but support relying on tourism monoculture may be a background reason for undesired negative consequences.

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In the ashes of political and socio-economic collapse, social movements sometimes rise like a phoenix. Little more than a year has passed since the Tunisian uprisings, the spark that ignited a series of “mobilizations of the indignant” that spread like wildfire around the world. Many observers have reported on these unprecedented global protests. They have portrayed citizens who declare feeling marginalized if not scapegoated, and who reject the increasing inequalities between rich and poor, the declining mobility of most, and the “disclassment” of many. They have shown, as well, massive protests against governments and politicians that are perceived as indifferent at best, duplicitous at worst, and in any event as blatantly closed to popular concerns. Many journalists have indeed asked what took so long for people to protest given this fatal combination. For the social scientist, however, the questions of who, why and how mobilizes are not so simple. There are specific problematics of mediation between structure, culture and individual or collective agency that need to be addressed.

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Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams.