Estimating Stochastic Malmquist ProductivityIndex

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs. DEA-based Malmquist productivity index measures the productivity change over time. The DEA-based Malmquist productivity index can be decomposed into two components: measuring the technical efficiency change (TEC) and measuring the frontier shift (FS). In the current study, we provide an approach by using stochastic variables for forecasting Malmquist index when progress or regress in the future is a considerable aim.

Keywords:

Data Envelopment Analysis , Malmquist index , Normal distribution