Do Municipal Mergers Improve Technical Efficiency? An Empirical Analysis of the 2008 Queensland Municipal Merger Program

Abstract

Municipal mergers remain an important instrument of local government policy in numerous countries, including Australia, despite some concerns surrounding its efficacy. We consider the claim that amalgamations enhance the technical efficiency of the merged entities by examining the 2008 Queensland compulsory consolidation program that reduced the number of local authorities from 157 to 73 councils. To test the claim, we conduct locally intertemporal data envelopment analysis over the period 2003-2013 inclusive. Our evidence suggests that (1) in the financial year preceding the mergers, there was no statistically significant difference in the typical efficiency scores of amalgamated and non-amalgamated councils and (2) 2 years following the mergers, the typical technical efficiency score of the amalgamated councils was well below the non-amalgamated cohort. We argue this may be attributed to increased spending on staffing expenses, although comparatively larger operational expenditure also served to diminish efficiency.

Local Government Capacity and Land Use Planning for Natural Hazards: A Comparative Evaluation of Australian Local Government Areas

“…The history of State politics in Australia suggests that governance arrangements and funding mechanisms for differential State size and degrees of remoteness can assist in equalising the capacity of local governments for hazards planning (Vardon, 2007). However, notions of efficiency are often applied to rationalise local government structural settings, leading to amalgamations or policy standardisations that in hindsight have proven unpopular with local communities (Farid Uddin, 2018), reduced council independence (Costar & Economou, 1999) or were detrimental to service delivery capacity, including in planning (Boyle, 2001;Drew et al, 2013;McQuestin et al, 2017). Addressing the varied geography of council capacity for planning policy provision should focus on strengthening local council factors such as internal resources, professional planning skills and balancing compliance with State mandates with appropriate emphasis on localised, place-oriented activities such as community engagement, risk identification and plan-making (Frazier et al, 2013;Berke et al, 2014).…”

Efficiency, Conflicting Goals and Trade-Offs: A Nonparametric Analysis of the Water and Wastewater Service Industry in Italy

“…Since its introduction, DEA has been extensively employed in economic analysis to calculate measures of efficiencies in various situations and industries, such as transportation [29,31,32], government and public sector [33][34][35], public utilities [21,22,[36][37][38], healthcare [39][40][41], education [42,43], banking and finance [44,45], energy and environmental studies [46][47][48][49][50][51][52], manufacturing and information technology [53][54][55][56].…”

The Influence of Excellence on Municipal Performance: Quasi-Experimental Evidence From the Czech Republic

“…The final recommendation of the Delphi panel was to choose the current expenditures as the main input variable. This option has justification in the literature (Aiello et al, 2017;McQuestin et al, 2018;Narbón-Perpina et al, 2019) and was also applied in previous research dealing with the Czech Republic (Plaček et al, 2019). There are also legal arguments based on Act on Municipalities 182/200 Coll and Act about Financial Control 320/2001.…”

“…According to the recommendations of McQuestin et al (2018) and lo Storto (2016), the Delphi panel focused special attention on the output side of indicator selection to reduce the complexity of municipal services delivered (Plaček et al, 2020a), to deal with the lack of available data (Plaček et al, 2020a), to avoid inconsistent results (lo Storto, 2016), and to eliminate the association with factors that cannot be influenced by municipalities. In this case, McQuestin et al (2018) and lo Storto (2016) favor the argument for utilizing proxy variables as output indicators. "Proxy variables serve as an indirect approximation for the demand for public services and the data for them is more available" (Plaček et al, 2020a).…”