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When Convergence is Crisis-Driven:Evidence From Unemployment Dynamics Across Czech Districts Cover

When Convergence is Crisis-Driven:Evidence From Unemployment Dynamics Across Czech Districts

By:   
Open Access
|May 2026

Figures & Tables

Fig. 1:

The development of unemployment rate across Czech districts (2005–2024, annual averages); author’s elaboration using data from MoLSA (2025)

Fig. 2:

The development of relative unemployment rate across Czech districts (2005–2024, annual averages, national average = 1); author’s elaboration using data from MoLSA (2025)

Fig. 3:

Development of unemployment rates across Czech districts in selected years (annual averages, %);author’s elaboration using data from MoLSA (2025) using shapefile from ČÚZK (2022), own elaboration in QGIS 3.36.0-Maidenhead (QGIS.org, 2024), Mapový podklad – Soubor hranic, 2022 © Český úřad zeměměřický a katastrální, www.cuzk.cz (ČÚZK, 2022)

Fig. 4:

Graphical depiction of absolute β-convergence of unemployment rates across Czech districts, 2005–2024; author’s processing in Stata 15 (StataCorp, 2017) based on data from MoLSA (2025)

Fig. 5:

Graphical depiction of results – unemployment dynamics across Czech districts, 2005–2024; author’s elaboration based on results of econometric analysis and using data from MoLSA (2025)

Fig. 6:

Graphical depiction of absolute β-convergence of unemployment rates across Czech districts, 2008–2013; author’s processing in Stata 15 (StataCorp, 2017) based on data from MoLSA (2025)

Fig. 7:

Change of unemployment rate across Czech districts (2008–2013), comparison of absolute change (percentage points, pp) and relative change (%); author’s elaboration using data from MoLSA (2025)

Absolute β-convergence model for district-level unemployment, OLS estimates (p-values reported in parentheses)

2005–20082008–20132013–20192019–20242005–2024
α (constant)– 0.1242 (0.000)0.2323 (0.000)–0.2384 (0.000)0.0966 (0.000)0.0007 (0.891)
β (initial unemployment)–0.0158 (0.201)–0.0732 (0.000)0.0294 (0.022)–0.0296 (0.000)–0.0156 (0.000)
F test1.67 (0.2005)206.60 (0.0000)5.46 (0.0221)16.11 (0.0001)35.37 (0.0000)
R20.02180.73370.06790.17680.3205
White’s test (heteroskedasticity)1.75 (0.4169)1.25 (0.5359)0.04 (0.9783)5.00 (0.0820)0.26 (0.8787)
Breusch-Pagan/Cook-Weisberg test (heteroskedasticity)0.07 (0.7978)1.37 (0.2410)0.00 (0.9886)4.53 (0.0333)0.18 (0.6693)
Skewness/Kurtosis tests for normality (residuals)8.03 (0.0180)0.85 (0.6526)0.30 (0.8601)1.37 (0.5029)1.53 (0.4655)

Summary of results

2005–20082008–20132013–20192019–20242005–2024
Absolute β-convergence (OLS estimates)
ConclusionUNCERTAINCON***DIV**CON***CON***
R22.18%73.37%6.79%17.68%32.05%
Spatial lag model (ML estimates)
ConclusionUNCERTAINCON***DIV**CON***CON***
Pseudo R23.75%73.37%4.94%14.18%34.91%

Spatial lag β-convergence model for district-level unemployment, Maximum Likelihood estimates (p-values reported in parentheses)

2005–20082008–20132013–20192019–20242005–2024
α (constant)–0.0766 (0.004)0.2335 (0.000)–0.1874 (0.000)0.0759 (0.000)0.0030 (0.537)
β (initial unemployment)–0.0076 (0.516)–0.0734 (0.000)0.0297 (0.013)–0.0304 (0.000)–0.0125 (0.000)
ρ (spatial autoregressive parameter)0.4089 (0.003)–0.0065 (0.952)0.2870 (0.060)0.3178 (0.020)0.2875 (0.028)
Direct effect–0.0079 (0.514)–0.0734 (0.000)0.0303 (0.014)–0.0311 (0.000)–0.0127 (0.000)
Indirect effect–0.0049 (0.507)0.0005 (0.952)0.0114 (0.231)–0.0134 (0.134)–0.0048 (0.067)
Total effect–0.0128 (0.505)–0.0729 (0.000)0.0417 (0.030)–0.0446 (0.001)–0.0175 (0.000)
Wald χ2 test10.55 (0.0051)212.13 (0.0000)9.51 (0.0086)23.40 (0.0000)43.98 (0.0000)
Pseudo R20.03750.73370.04940.14180.3491
Moran test for spatial dependence7.16 (0.0074)0.02 (0.8933)5.54 (0.0186)10.48 (0.0012)1.88 (0.1698)
DOI: https://doi.org/10.2478/revecp-2025-0006 | Journal eISSN: 1804-1663 | Journal ISSN: 1213-2446
Language: English
Page range: 91 - 108
Published on: May 13, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2026 Jan Belardi, published by Mendel University in Brno
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.