What’s in a Name? Assessing the Performance of Local Government Classification Systems

Dados Bibliográficos

ID6301666
AutoresJoseph Drew (0000-0003-3579-5758, University of New England), Brian Dollery (0000-0003-2760-865X, University of New England)
Ano2016
Volume42
Fascículo2
Páginas248-266
Data de publicação2016-03-03
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoLocal Government Studies (JOURNAL)
Identificadores do periódicoISSN: 0300-3930 • E-ISSN: 1743-9388
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/03003930.2015.1007132
OpenAlexW2072621109
IdiomaEN
Citações recebidas4
Referências citadas22

Local government classification systems are employed in many countries for regulation, grant transfers and other public policy purposes. Given the pivotal role these classification systems play in public policy, their accuracy is a matter of some importance. Classification systems take several forms typically consisting of groupings of municipalities based on factors such as degree of urbanisation, population size and the like. However, to date none of these classification systems have been tested for homogeneity with respect to environmental constraints or validated against external data. This paper employs the classification system for New South Wales (NSW) local authorities as a representative case study to demonstrate that a wider range of external constraints should be considered for the robust classification of local councils

Economic growth · Economics · Government (linguistics · Homogeneity (statistics · Local government · Machine learning · Political science · Population · Public policy · Sociology · Urbanization · Computer Science · E-Government and Public Services · Law · Local Government Finance and Decentralization · Public Administration · Public Policy and Administration Research