Sergio Scippacercola

Estimating the Relative Efficiency of Secondary Schools by Stochastic Frontier Analysis

Abstract This study has the aim of evaluating the efficiency of schools of secondary education. We used the first data (pilot survey) gathered from an official survey, in progress, performed by the school management of the Campania Region. The survey covers attributes regarding the environment, territorial context and economic resources. We adopted the Stochastic Frontier Analysis to estimate the efficiency and a Tobit regression model in order to discuss which factors might affect the efficiency.

Ordinal principal component analysis for a common ranking of stochastic frontiers

ABSTRACT The Stochastic Frontier Analysis (SFA) is a model to evaluate the Technical Efficiency (TE) for Production Units (PU). When SFA is applied on different output variables with same input, the analysis estimates different TEs for the PU. We refer to these TEs as the Multiple Technical Efficiency (MTE) of the PU. In this work, we present a method to unify the MTE in one ranking, in order to compute a synthetic index of the TE based on a parametric model. Our approach transforms the measures of efficiency into values on an ordinal scale. Then, using the Ordinal Principal Component Analysis and a genetic algorithm, we merge the multiple rankings.

Evaluating the Current Evolution of GDP towards Quality

Abstract A new nowcasting technique is coupled with a quality-oriented analysis of GDP to provide a tracking tool for policies and innovations introduced by policymakers. GDP is split into quality and non-quality components in a certain reference year, then nowcasting techniques are employed to provide an estimation of the current evolution. As new monthly data are available, re-estimation can be performed, with policy-makers being given timely feedback on their actions. Data on Italy and an educated guess for Euro-zone are produced.