This work aims at characterising Italian municipalities according to what has been accomplished in terms of corruption prevention. The recent “anti-corruption law” of 2012 establishes a new plan for corruption prevention. It introduces a new figure, the prevention-of-corruption supervisor who reports if and how preventive measures are implemented within the public institution he/she represents, by filling in a standardised form, which has to be published in the institution website. We rely on these data – downloaded from each single municipality website – to apply a Latent Class model allowing us to identify groups of municipalities with a similar behaviour. Further, we qualify such classes on account of several covariates. First results show that i. there is a general tendency among municipalities to fulfil the prevention-of-corruption law and ii. virtuous municipalities are large municipalities experiencing at least one corruption event.

Characterising Italian municipalities according to the annual report of the prevention-of-corruption supervisor: a Latent Class approach

michela gnaldi;simone del sarto
2017

Abstract

This work aims at characterising Italian municipalities according to what has been accomplished in terms of corruption prevention. The recent “anti-corruption law” of 2012 establishes a new plan for corruption prevention. It introduces a new figure, the prevention-of-corruption supervisor who reports if and how preventive measures are implemented within the public institution he/she represents, by filling in a standardised form, which has to be published in the institution website. We rely on these data – downloaded from each single municipality website – to apply a Latent Class model allowing us to identify groups of municipalities with a similar behaviour. Further, we qualify such classes on account of several covariates. First results show that i. there is a general tendency among municipalities to fulfil the prevention-of-corruption law and ii. virtuous municipalities are large municipalities experiencing at least one corruption event.
2017
9788864535210
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1424374
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