Intermunicipal cooperation, public spending and service levels

Abstract

Local governments can increase size in particular policy fields through cooperation with other local governments. This is often thought to improve efficiency, but there is little empirical evidence supporting this hypothesis. We study the case of the Netherlands, which has been a veritable laboratory of intermunicipal cooperation (IMC), using panel data for 2005-2013. We find no evidence that IMC reduces total spending of the average municipality. Indeed, IMC seems to increase spending in small and large municipalities, leaving spending in mid-sized municipalities unaffected. In one specific field, tax collection, spending may be reduced through IMC. Spending in this field is low, which may explain why total spending is unaffected. Instead of lowering spending, municipalities may have used possible cost savings as a result of IMC to improve public service levels. We do not find evidence substantiating this hypothesis, however.

Privatisation, contracting-out and inter-municipal cooperation: new developments in local public service delivery

“…Even in the case of tax collection, where due to its capital-intensive nature savings are expected from IMC, total spending is unaffected, although the size of spending is relatively small. For Dutch waste collection, the outcome reported by Allers and De Greef (2018) is similar to that found by Gradus, Schoute, and Dijkgraaf (2018), who, for the years 2002, 2006 and 2010, show there to be no (significant) cost advantage for implementing IMC. Interestingly, however, in the case of 2014, Gradus, Schoute, and Dijkgraaf (2018) found a significant positive cost-advantage effect of cooperation of 17%.…”

“…Likewise, Blaeschke and Haug (2018) reported enhanced efficiency as a result of IMC, again for small municipalities, in this case in the Hessian (Germany) sewage sector. In contrast, Allers and De Greef (2018) found that IMC does not, in general, seem to be an effective method for reducing local government spending. Even in the case of tax collection, where due to its capital-intensive nature savings are expected from IMC, total spending is unaffected, although the size of spending is relatively small.…”

Does intermunicipal cooperation promote efficiency gains? Evidence from Italian municipal unions

“…Finally, our data set contains annual information at municipal level on some public service indicators, which we use to directly test the efficiency in the provision of local services. This is an important advantage compared to similar studies (e.g., Allers & de Greef, ). We find that spending cuts are not associated with a downsizing of local services, and municipal cooperation might (marginally) reduce local tax revenues.…”

“…In particular, relevant factors in favor of intermunicipal cooperation appear to be the size of municipalities (Brasington, ; Carr, Gerber, & Lupher, ), regional characteristics (Feiock, ; LeRoux & Carr, ), geographic factors (Morgan & Hirlinger, ; Post, ), fiscal revenue (Di Porto, Merlin, & Paty, ), and spatial proximity of municipalities (Di Porto, Parenti, Paty, & Abidi, ). However, few studies have analyzed the impact of intermunicipal cooperation on socioeconomic variables, focusing, instead, either on specific services (see Bel, Fageda, & Mur, ) and (Brasington, , ) for the case of solid waste services and public schooling, respectively, or on a particular spending field (e.g., Allers & de Greef, use the share of tax collection spending). Thus, to the best of our knowledge, no one has empirically explored the ex post local impact of intermunicipal cooperation, by considering both financial and service outcomes…”

“…(), who rely on cross‐sectional variations, we are able to exploit the panel dimension of our data, more precisely the different timing in entering/forming municipal unions and the permanence in a union. Furthermore, while the existing literature has employed maximum likelihood (Brasington, , ), probit (Bel et al., ) and system‐generalized method of moments estimators (Allers & de Greef, ) to identify the impact of municipal cooperation on public outcomes, in our work we employ counterfactual impact evaluation methods, such as difference‐in‐differences (DiD). Yet, to control for the different sources of biases that may arise due to the heterogeneity of the municipalities in the sample, we adopt parametric and nonparametric DiD matching models.…”