Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia
This paper focuses on the analysis of unemployment data in Czechia on a very detailed spatial structure and yearly, extended time series (2002–2019). The main goal of the study was to examine the spatial dimension of disparities in regional unemployment and its evolutionary tendencies on a municipal...
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Online Access: | https://www.mdpi.com/2220-9964/9/6/401 |
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doaj-29238f10b75c4958909550e23e0149e12020-11-25T02:25:06ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-06-01940140110.3390/ijgi9060401Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in CzechiaPavlína Netrdová0Vojtěch Nosek1Department of Social Geography and Regional Development, Faculty of Science, Charles University, 128 43 Prague, Czech RepublicDepartment of Social Geography and Regional Development, Faculty of Science, Charles University, 128 43 Prague, Czech RepublicThis paper focuses on the analysis of unemployment data in Czechia on a very detailed spatial structure and yearly, extended time series (2002–2019). The main goal of the study was to examine the spatial dimension of disparities in regional unemployment and its evolutionary tendencies on a municipal level. To achieve this goal, global and local spatial autocorrelation methods were used. Besides spatial and space-time analyses, special attention was given to spatial weight matrix selection. The spatial weights were created according to real-time accessibilities between the municipalities based on the Czech road network. The results of spatial autocorrelation analyses based on network spatial weights were compared to the traditional distance-based spatial weights. Despite significant methodological differences between applied spatial weights, the resulting spatial pattern of unemployment proved to be very similar. Empirically, relative stability of spatial patterns of unemployment with only slow shift of differentiation from macro- to microlevels could be observed.https://www.mdpi.com/2220-9964/9/6/401socioeconomic disparitiesunemploymentCzechiaspace–time analysisreal-time accessibilityspatial weights |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pavlína Netrdová Vojtěch Nosek |
spellingShingle |
Pavlína Netrdová Vojtěch Nosek Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia ISPRS International Journal of Geo-Information socioeconomic disparities unemployment Czechia space–time analysis real-time accessibility spatial weights |
author_facet |
Pavlína Netrdová Vojtěch Nosek |
author_sort |
Pavlína Netrdová |
title |
Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia |
title_short |
Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia |
title_full |
Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia |
title_fullStr |
Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia |
title_full_unstemmed |
Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia |
title_sort |
spatial dimension of unemployment: space-time analysis using real-time accessibility in czechia |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2020-06-01 |
description |
This paper focuses on the analysis of unemployment data in Czechia on a very detailed spatial structure and yearly, extended time series (2002–2019). The main goal of the study was to examine the spatial dimension of disparities in regional unemployment and its evolutionary tendencies on a municipal level. To achieve this goal, global and local spatial autocorrelation methods were used. Besides spatial and space-time analyses, special attention was given to spatial weight matrix selection. The spatial weights were created according to real-time accessibilities between the municipalities based on the Czech road network. The results of spatial autocorrelation analyses based on network spatial weights were compared to the traditional distance-based spatial weights. Despite significant methodological differences between applied spatial weights, the resulting spatial pattern of unemployment proved to be very similar. Empirically, relative stability of spatial patterns of unemployment with only slow shift of differentiation from macro- to microlevels could be observed. |
topic |
socioeconomic disparities unemployment Czechia space–time analysis real-time accessibility spatial weights |
url |
https://www.mdpi.com/2220-9964/9/6/401 |
work_keys_str_mv |
AT pavlinanetrdova spatialdimensionofunemploymentspacetimeanalysisusingrealtimeaccessibilityinczechia AT vojtechnosek spatialdimensionofunemploymentspacetimeanalysisusingrealtimeaccessibilityinczechia |
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