Spatial Dimension of Unemployment: Space-Time Analysis Using Real-Time Accessibility in Czechia

Pavlína Netrdová,Vojtěch Nosek

doi:10.3390/ijgi9060401

Abstract

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.

Highlights

Many economists have recently emphasized space and spatial effects in their research [1,2]
We focused on the spatial dimension of unemployment, which is connected with regional unemployment and regional disparities in general
Authors who have studied unemployment have all found quite stable regional patterns that oscillate around national unemployment means yet often have some specific outliers, as shown in [8,10,11,12,13] as well as [14], which studied Czechia

Summary

Introduction

Many economists have recently emphasized space and spatial effects in their research [1,2]. Authors who have studied unemployment have all found quite stable regional patterns that oscillate around national unemployment means yet often have some specific outliers, as shown in [8,10,11,12,13] as well as [14], which studied Czechia. This has consistently been found on an international level as well [15,16,17,18]. Even though the explanations behind the high inertia of spatial patterns of unemployment differ by author, the relative stability of these patterns is generally agreed upon

Objectives

Methods