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Problem indicators and territorial restructuring: do institutional decision rules matter?

Published online by Cambridge University Press:  14 February 2025

Jostein Askim*
Affiliation:
Department of political science, University of Oslo, Oslo, Norway
Adam Gendźwiłł
Affiliation:
Center for Electoral Studies, Department of Sociology, University of Warsaw, Warszawa, Poland
Jan Erling Klausen
Affiliation:
Department of political science, University of Oslo, Oslo, Norway
*
Corresponding author: Jostein Askim; Email: jostein.askim@stv.uio.no
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Abstract

Territorial restructuring through amalgamating local authorities has figured prominently on the agendas of European governments for many decades. Precisely where and when restructuring occurs is poorly understood, although it is broadly assumed to be initiated in response to fiscal stress, urbanization, and functional decentralization. Using a large-N approach with a 30-year time series for 39 European countries, this article demonstrates that associations between these problems and territorial restructuring depend on institutional decision rules, specifically whether the power to decide on local government amalgamations is centralized or dispersed. The findings indicate that policymakers at the local level are particularly attentive to demographic problems, whereas policymakers at the central level pay more attention to problems related to policy delivery. We outline theoretical and practical implications.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Table 1. Incidences of administrative-territorial system (ATS) change in 39 European countries, 1990–2020

Figure 1

Figure 1. Incremental (Iceland, left panel) versus one-off (Denmark, right panel) ATS change. Note: Dashed lines mark observations identified in accordance with the “>5% rule,” i.e. years in which the accumulated decrease in the number of municipalities exceeds 5%.

Figure 2

Table 2. Models explaining the likelihood of administrative-territorial system (ATS) change: random-effects logistic regressions

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Figure 2. Main results of the logistic regression with random effects: estimated marginal effects of recession, urbanization dynamics and increased policy scope on the probability of ATS change. Note: Point estimates are accompanied by 95% confidence intervals. Symbols in the upper part of the graph indicate whether the difference between the estimates for dispersed and centralized settings is statistically significant (*** p < .01). ns: non-significant.

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Figure 3. Supplementary results of the logistic regression with random effects: comparison of the baseline model with models employing alternative definitions of the independent variables. Note: The graph displays the estimated AMEs of recession, urbanization dynamics, and increased policy scope on the probability of ATS change. Point estimates are accompanied by 95% confidence intervals. The differences in AMEs between the centralized and dispersed groups are statistically significant at p < .05 only for urbanization (for the 5%, 6%, and 7% thresholds identifying ATS change) and increased policy scope (for the 3%, 4%, 5%, 6%, and 7% thresholds). Model estimates are presented in the Appendix (Table A3).

Figure 5

Figure 4. Supplementary results of the logistic regression with random effects: comparison of the baseline model with a model employing three-year lags for problem indicators. Note: Point estimates are accompanied by 95% confidence intervals. Symbols in the upper part of the graph indicate whether the differences between estimates for dispersed and centralized settings are statistically significant (*** p < .01; ns: non-significant). Model estimates are presented in the Appendix (Table A4).

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Table A1. Descriptive statistics

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Table A2. Comparison of random effect (RE) and fixed effect (FE) models on a restricted sample of 21 countries

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Table A3. Alternative model specification: models explaining the likelihood of administrative-territorial system (ATS) change, random-effects logistic regressions with different thresholds defining the dependent variable

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Table A4. Alternative model specification: model explaining the likelihood of administrative-territorial system (ATS) change, random-effects logistic regressions with longer lags

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