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...

Full description

Bibliographic Details
Main Authors: Pavlína Netrdová, Vojtěch Nosek
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/9/6/401
id doaj-29238f10b75c4958909550e23e0149e1
record_format Article
spelling 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
_version_ 1724852717997785088