In this study, data envelopment analysis (DEA) is used to compute efficiency scores for a sample of Italian schools by employing OECD-PISA2006 data aggregated at school level. Efficiency has been defined as the ability to transform inputs (resources, student background, etc.) into outputs (student achievement). Different versions of the DEA models were estimated to test result robustness, including a DEA bootstrapping procedure. In a second-stage analysis, the factors affecting school efficiency are investigated through a Tobit regression. Among these factors, alternative indicators of competition were included. The results show that at least one indicator of competition is statistically associated with higher performances of schools, suggesting that there is a potential role for improving school results by increasing the number of schools competing each other. These findings are consistent with a previous analysis conducted on the same dataset by estimating an educational production function. Policy implications are presented in the last part of the study.