DEA-based yardstick competition: The optimality of best practice regulation

In this paper, we introduce the notion of ''best practice'' or ''minimal extrapolation'' regulation, and we show that cost reimbursement based on best practice norms may be (second best) optimal when the regulated firms have superior technological information and make non-verifiable cost reductions. In particular, we investigate the use of Data Envelopment Analysis (DEA) in regulatory environments with considerable technological uncertainty. A series of DEA models, including the crs, drs, vrs, fdh and frh models, are considered, and it is shown that schemes which reimburse actual costs plus a fraction of DEA estimated cost reductions will (1) induce the firms to minimize costs and (2) minimize the informational rents of the firms.