ABSTRACT
We analyse the way in which spending efficiency of French departments evolved from 2007 to 2019. We use the time-dependent conditional order-m approach , which allows to account for the heterogeneity among departments, characterized by contextual variables, and to evaluate the effect of these variables. The results reveal a continuous improvement in their performance (management of total expenditures) over time and show that departments have much more room for improvement in the management of investment expenditures than in the management of operating costs. Moreover, the time variable has a positive effect on performance (shape of the frontier and catch-up) for both the operating and the investment specific models.
Acknowledgements
We would like to thank Kristoff De Witte for providing his R code. We adapt and use parts of this code in our setting.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
Data will be made available: https://github.com/ayoubakassoum/local_gvt
Ethical Approval
This article does not contain any studies with human participants or animals performed by any of the authors.
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All authors of this paper have consented to its submission and its publication.
Notes
1 This figure and those in the rest of the introduction come from the report by the Finance and Local Public Management Observatory (Observatoire des Finances et de la Gestion publique locales, Citation2021).
2 The decentralization process in France is characterized by several stages known as ‘Act I’, ‘Act II’ and ‘Act III’. Competencies regarding social aid were mainly transferred from central government to departments’ responsibilities after the law of July 22, 1983. The competencies of departments were gradually extended later with other laws, such as the law of December 18, 2003 and the law of December 1, 2008.
3 The appendix contains a discussion on convexity.
4 This characteristic in the evolution of French departments’ spending over these years is extensively commented on and analysed in Duboz, Le Gallo, and Houser (Citation2021).
5 This is confirmed by average growth rates of efficiency scores ().
6 Descriptive statistics on optimal estimated bandwidth confirm this observation (). Indeed, the median values of bandwidth estimates have reasonable (narrow) values, predicting significant influence on the production process. High maximum values can be a result of smoothing out, for some departments, of an insignificant variable.
7 Large (positive) value of ‘pure efficiency’ indicates a department which has poor performance, and small (negative) value indicates very good performance.