Productivity Measurement

Abstract

AbstractIn this chapter we extend our analysis to panel data to allow us to measure productivity changes. We analyze shifts in the frontier with distance functions to measure productivity. The standard decomposition of the Malmquist Productivity Index (MPI) to measure efficiency change, technical change, and scale efficiency change. Following Brennan, Haelermans and Ruggiero (2013), we further decompose the Malmquist productivity index for public sector production characterized by the influence of environmental variables. We derive decomposed measures of technical, efficiency, scale, and environmental change and apply this decomposition to the 2008–2009 and 2009–2010 school years for both primary and secondary Australian public schools. In the next sections, we redefine our technology to be time specific and present our measures of the public sector Malmquist Productivity Index and its components. Much of the modeling and discussion in this chapter is borrowed from Brennan, Haelermans and Ruggiero (2013).KeywordsDistance FunctionTechnical EfficiencyTechnical ChangeProductivity IndexFavorable EnvironmentThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.