This thesis addresses questions in the Economics of Crime regarding the effect of crime on GDP per capita and its growth rate, and criminal choices. The first part of the thesis presents evidence concerning the effect of crime on economic outcomes in Italy. Using an Instrumental Variables (IV) strategy and a system GMM approach, the empirical exercise identifies the effect of different crimes on GDP per capita and its growth rate in Italian regions. Results indicate that crime related to organised crime has a substantial negative effect on the economic performance of Italian regions, with the southern regions of Italy driving the outcome. The second part of this thesis sheds further light on the understanding of criminal choices using a dynamic discrete choice model able to replicate trends observed in the National Longitudinal Survey of Youth 1997 (NLSY97). The model offers a unifying framework of the literature, presented in economics of crime, studying the factors leading to criminal success. Its development accounts for criminal and/or human capital accumulation and its impact on legal and illegal earnings. Estimation of the parameters of the model is accomplished by the simulated method of moments. Results show a strong role for social criminal capital in defining successful criminal activity. In addition, the estimated returns to experience in illegal activities are larger compared to legal ones, but the percentage of young men committing offences decreases when the opportunity cost of crime increases. The counterfactual policy exercise suggests that policies aimed at increasing human capital for previous offenders can have a significant effect over short and long-term.