Spatial Autocorrelation Method for Local Analysis of the EU

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86090733" target="_blank" >RIV/61989100:27510/15:86090733 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/S2212-5671(15)00484-0" target="_blank" >http://dx.doi.org/10.1016/S2212-5671(15)00484-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/S2212-5671(15)00484-0" target="_blank" >10.1016/S2212-5671(15)00484-0</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Spatial Autocorrelation Method for Local Analysis of the EU

Popis výsledku v původním jazyce

Polarization and differentiation among EU countries and their regions are the result of close interaction among economic, social and territorial dimension, which is reflected not only in disparities between territories, but also along with a wide range of other different factors. The aim of this paper is to identify the relevant variables in specified EU territory and time, which contributed to detection of territorial disparities, and its consequences within the structural constraints of the analysed area. This problematic of classifying territories is solved with using of spatial autocorrelation method, which plays an important role in spatial statistics and spatial econometrics. Spatial autocorrelation statistics detect the presence of interdependence between the values of data at neighbouring locations. Local form of spatial autocorrelation is based on the premise that the presence of spatial autocorrelation can vary across the study area, and it is fully in line with contemporary

Název v anglickém jazyce

Spatial Autocorrelation Method for Local Analysis of the EU

Popis výsledku anglicky

Polarization and differentiation among EU countries and their regions are the result of close interaction among economic, social and territorial dimension, which is reflected not only in disparities between territories, but also along with a wide range of other different factors. The aim of this paper is to identify the relevant variables in specified EU territory and time, which contributed to detection of territorial disparities, and its consequences within the structural constraints of the analysed area. This problematic of classifying territories is solved with using of spatial autocorrelation method, which plays an important role in spatial statistics and spatial econometrics. Spatial autocorrelation statistics detect the presence of interdependence between the values of data at neighbouring locations. Local form of spatial autocorrelation is based on the premise that the presence of spatial autocorrelation can vary across the study area, and it is fully in line with contemporary

Druh

D - Stať ve sborníku

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/EE2.3.20.0296" target="_blank" >EE2.3.20.0296: Výzkumný tým pro modelování ekonomických a finančních procesů na VŠB-TU Ostrava</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Procedia Economics and Finance. Volume 23

ISBN

—

ISSN

2212-5671

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1102-1109

Název nakladatele

Elsevier

Místo vydání

Amsterdam

Místo konání akce

Praha

Datum konání akce

29. 10. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000360103600170