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nr 2
251-264
EN
Research background: Brands are considered to be the most valuable asset of a company. Some of them achieve spectacular global results. The significance of global brands is proved by the fact that their value is often greater than the sum of all company's net assets. Purpose of the article: The aim of this article is to highlight that brand value does not only create company's value, but also leverages economies. The Authors claim that even though global brands are sold worldwide and are a part of 'global factories', they strongly relate to the development of economies in the countries where these brands' headquarters are located. Methods: Based on 500 Brandirectory, the Most Valuable Global Brands ranking powered by Brand Finance, an analysis of spatial autocorrelation of brand values, GDP per capita was performed and also the interdependency between them was illustrated with the use of the spatial cross-regressive model (SCM). The SCM approach allowed us to include spatial effects of brand values into the final form of the estimated equation. The empirical analysis was performed for 33 countries in 2014. Findings & Value added: Findings confirm the hypothesis that there is a highly statistically significant relationship between brand value and GDP per capita and, what's more, it is observed that spatial dependencies matter for brand values. The evidence is based on the results of spatial cross-regressive model (SCM).
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tom 43
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nr 2
67-80
EN
Contemporary development policy concentrates predominantly on reducing noticeable economic differences in a spatial system, and an important role in this respect is played by EU Cohesion Policy. Owing to the considerable scale of financial exposure of Cohesion Policy, the assessment of effectiveness of the implemented measures and their greater reliance on evidence are of major significance. Despite numerous attempts to empirically verify the effects of EU funds spending, the problem remains unresolved, and the results of recent studies lead frequently to ambiguous conclusions. The article aims to verify the β-convergence process in EU regions in the years 2007–2015 allowing for the impact of the received EU funds and the spatial effects determining economic growth. In the research, use was made of a covergence approach consisting in the regression modelling of per capita GDP growth. Spatial econometrics methods were applied, by adding variables determining spatial interactions that can influence the economic growth rate to the specification of the estimated models. The estimated econometric models show that in the years 2007–2015 EU funds positively affected economic growth. At the same time, the process of reducing economic disparities between EU regions was observed. Moreover, the existence of spatial effects for a dependent variable was confirmed. The results also show that the value of the EU funds received in the surrounding area generally did not translate into the dynamics of growth in a given location. The research presented is one of the few in which spatial interaction was verified by using weights matrices based on contiguity, distance, flows and affiliation.
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