The idea of this study is to employ the Data Envelopment Analysis (DEA) to assess the relative efficiency of European (EU) countries in order to compare their performances while dealing with the Shadow Economy (SE). The results can be interpreted in terms of encouraging the interventions as regards to taxation and regulation when referring to the indicators proposed in the model. The features of the well-known SE are widely debated. The impact of the SE varies considerably from country to country and there are a number of studies which have investigated the size of the SE in European countries (Schneider and Colin, 2013), the influence of public institutions on the SE (Schneider and Enste, 2007; Schneider, 2010), the relationship between the SE and the measurements of governance and institutional credibility (Perry et al., 2007; Hazans, 2011), etc. The DEA has been extensively studied and applied in various areas for thirty years, since Charnes et al. (1978) first proposed it. The DEA is a nonparametric method for measuring the efficiency of a set of decision making units (DMUs) such as firms or public sector agencies. In this paper, each DMU can be identified as a country and the DEA refers to the SE output obtained by performing a Structural Equation Model (SEM). Thus, the DEA efficiency scores compare the relative performance to the considered sample of countries. In the present contribution, the SE needs several assumptions related to its scale to make the results coherent with the DEA assumptions. To the authors’ knowledge, studies in the literature have only focused on SEM and DEA approaches, but not on the combination of the two or the different forms they can take, especially referring to the SE. The nonparametric frontier can be used to interpret the taxation and regulation differentials in the countries considered.
A comparative analysis in the EU shadow economy using a DEA model,
Quintano Claudio
2014-01-01
Abstract
The idea of this study is to employ the Data Envelopment Analysis (DEA) to assess the relative efficiency of European (EU) countries in order to compare their performances while dealing with the Shadow Economy (SE). The results can be interpreted in terms of encouraging the interventions as regards to taxation and regulation when referring to the indicators proposed in the model. The features of the well-known SE are widely debated. The impact of the SE varies considerably from country to country and there are a number of studies which have investigated the size of the SE in European countries (Schneider and Colin, 2013), the influence of public institutions on the SE (Schneider and Enste, 2007; Schneider, 2010), the relationship between the SE and the measurements of governance and institutional credibility (Perry et al., 2007; Hazans, 2011), etc. The DEA has been extensively studied and applied in various areas for thirty years, since Charnes et al. (1978) first proposed it. The DEA is a nonparametric method for measuring the efficiency of a set of decision making units (DMUs) such as firms or public sector agencies. In this paper, each DMU can be identified as a country and the DEA refers to the SE output obtained by performing a Structural Equation Model (SEM). Thus, the DEA efficiency scores compare the relative performance to the considered sample of countries. In the present contribution, the SE needs several assumptions related to its scale to make the results coherent with the DEA assumptions. To the authors’ knowledge, studies in the literature have only focused on SEM and DEA approaches, but not on the combination of the two or the different forms they can take, especially referring to the SE. The nonparametric frontier can be used to interpret the taxation and regulation differentials in the countries considered.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.