Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations

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Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. / Bhatti, Yosef; Hansen, Kasper Møller.

I: European Journal of Political Research, Bind 50, Nr. 2, 2011, s. 212-238 .

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Bhatti, Y & Hansen, KM 2011, 'Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations', European Journal of Political Research, bind 50, nr. 2, s. 212-238 . https://doi.org/10.1111/j.1475-6765.2010.01928.x

APA

Bhatti, Y., & Hansen, K. M. (2011). Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. European Journal of Political Research, 50(2), 212-238 . https://doi.org/10.1111/j.1475-6765.2010.01928.x

Vancouver

Bhatti Y, Hansen KM. Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. European Journal of Political Research. 2011;50(2):212-238 . https://doi.org/10.1111/j.1475-6765.2010.01928.x

Author

Bhatti, Yosef ; Hansen, Kasper Møller. / Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. I: European Journal of Political Research. 2011 ; Bind 50, Nr. 2. s. 212-238 .

Bibtex

@article{7c0b25c0b35d11df825b000ea68e967b,
title = "Who {\textquoteleft}marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations",
abstract = "For decades, political scientists have been asking how political jurisdictions are formed and reshaped. Nevertheless, studies of local government jurisdictional formation are few and often plagued with endogeneity since the formation of jurisdictions cannot be separated from sorting effects. In this article, the unique case of the Danish structural reform is utilised to overcome endogeneity due to migration-related sorting by studying patterns of municipal amalgamations. In the recent Danish reform, 239 of 271 municipal entities were forced to amalgamate simultaneously, while who actually amalgamated with whom was left entirely to negotiations between the respective municipalities. Applying logistical regression to a dataset where the unit of analysis is dyads of municipalities allows the construction of a relational model for estimating the effect of different political and societal variables on the likelihood of amalgamation. Societal connectedness, population size and geography are important predictors of amalgamation patterns, while political and economic homogeneity between municipalities does not appear to matter much",
author = "Yosef Bhatti and Hansen, {Kasper M{\o}ller}",
year = "2011",
doi = "10.1111/j.1475-6765.2010.01928.x",
language = "English",
volume = "50",
pages = "212--238 ",
journal = "European Journal of Political Research",
issn = "0304-4130",
publisher = "Wiley-Blackwell",
number = "2",

}

RIS

TY - JOUR

T1 - Who ‘marries' whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations

AU - Bhatti, Yosef

AU - Hansen, Kasper Møller

PY - 2011

Y1 - 2011

N2 - For decades, political scientists have been asking how political jurisdictions are formed and reshaped. Nevertheless, studies of local government jurisdictional formation are few and often plagued with endogeneity since the formation of jurisdictions cannot be separated from sorting effects. In this article, the unique case of the Danish structural reform is utilised to overcome endogeneity due to migration-related sorting by studying patterns of municipal amalgamations. In the recent Danish reform, 239 of 271 municipal entities were forced to amalgamate simultaneously, while who actually amalgamated with whom was left entirely to negotiations between the respective municipalities. Applying logistical regression to a dataset where the unit of analysis is dyads of municipalities allows the construction of a relational model for estimating the effect of different political and societal variables on the likelihood of amalgamation. Societal connectedness, population size and geography are important predictors of amalgamation patterns, while political and economic homogeneity between municipalities does not appear to matter much

AB - For decades, political scientists have been asking how political jurisdictions are formed and reshaped. Nevertheless, studies of local government jurisdictional formation are few and often plagued with endogeneity since the formation of jurisdictions cannot be separated from sorting effects. In this article, the unique case of the Danish structural reform is utilised to overcome endogeneity due to migration-related sorting by studying patterns of municipal amalgamations. In the recent Danish reform, 239 of 271 municipal entities were forced to amalgamate simultaneously, while who actually amalgamated with whom was left entirely to negotiations between the respective municipalities. Applying logistical regression to a dataset where the unit of analysis is dyads of municipalities allows the construction of a relational model for estimating the effect of different political and societal variables on the likelihood of amalgamation. Societal connectedness, population size and geography are important predictors of amalgamation patterns, while political and economic homogeneity between municipalities does not appear to matter much

U2 - 10.1111/j.1475-6765.2010.01928.x

DO - 10.1111/j.1475-6765.2010.01928.x

M3 - Journal article

VL - 50

SP - 212

EP - 238

JO - European Journal of Political Research

JF - European Journal of Political Research

SN - 0304-4130

IS - 2

ER -

ID: 21633327