This paper contributes to the empirical research on corruption in three ways. From a methodological viewpoint, it applies partial least squares–structural equation modeling to estimate an index of perceived corruption around the world—hereinafter structural corruption perception index (S-CPI). This approach allows one to estimate corruption as a multidimensional latent variable by complex cause-effect relationships between observed and/or unobserved variables. From a positive viewpoint, it estimates comparable S-CPI scores in 165 countries from 1995 to 2016, using a model specification based on existing theory of and empirics on the causes and consequences of corruption. In terms of policy implications, helpful hints on which are the most effective channels for fighting corruption are provided.
Corruption around the world: an analysis by partial least squares—structural equation modeling
Dell’Anno, Roberto
2020-01-01
Abstract
This paper contributes to the empirical research on corruption in three ways. From a methodological viewpoint, it applies partial least squares–structural equation modeling to estimate an index of perceived corruption around the world—hereinafter structural corruption perception index (S-CPI). This approach allows one to estimate corruption as a multidimensional latent variable by complex cause-effect relationships between observed and/or unobserved variables. From a positive viewpoint, it estimates comparable S-CPI scores in 165 countries from 1995 to 2016, using a model specification based on existing theory of and empirics on the causes and consequences of corruption. In terms of policy implications, helpful hints on which are the most effective channels for fighting corruption are provided.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
