Regulation of Natural Gas Distribution Using Policy Benchmarks

32 Pages Posted: 6 Dec 2005 Last revised: 12 Apr 2015

See all articles by Kumar Muthuraman

Kumar Muthuraman

University of Texas at Austin - Red McCombs School of Business; Information, Risk and Operations Management

Tarik Aouam

Purdue University - College of Industrial Engineering

Ronald Rardin

Purdue University - College of Industrial Engineering

Date Written: January 25, 2006

Abstract

Local Distribution Companies (LDCs) play the role of purchasing and delivering natural gas to their consumers and state regulators oversee the pricing of natural gas to consumers. The common method of regulation, based on the cost of service, provides arguably little incentive for the LDC to optimally manage their procurement activities. In the light of recent deregulation and other changes, benchmarking based regulatory schemes are being increasingly perceived as the right direction to pursue. Various states are experimenting with simple benchmark mechanisms that have inherent deficiencies and are often criticized. In this paper we propose and characterize a new kind of benchmark that we call policy benchmark as a mechanism for regulation. Using variance as the measure of risk we formulate the regulator's and the LDC's problems as multiple ob jective optimizations. We provide rigorous characterizations of the dominance frontiers for a two-stage model. We also provide multi-stage formulations that take into account various natural gas market microstructures. We compute solutions under parameters estimated from relevant real world data and illustrate that the structures of the dominance frontiers remain unaltered from the characterizations provided by stylized two-stage model.

Keywords: Natural Gas, Regulation, Benchmarks, Linear incentive contracts, Policy Benchmarks

JEL Classification: G18, G28, Q48, G11

Suggested Citation

Muthuraman, Kumar and Muthuraman, Kumar and Aouam, Tarik and Rardin, Ronald, Regulation of Natural Gas Distribution Using Policy Benchmarks (January 25, 2006). Available at SSRN: https://ssrn.com/abstract=861341 or http://dx.doi.org/10.2139/ssrn.861341

Kumar Muthuraman (Contact Author)

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

Information, Risk and Operations Management ( email )

Austin, TX 78712
United States

Tarik Aouam

Purdue University - College of Industrial Engineering ( email )

2455, Kestral Blvd., Apt E,
315 N. Grant Street
West Lafayette, IN 47906
United States

Ronald Rardin

Purdue University - College of Industrial Engineering ( email )

2455, Kestral Blvd., Apt E,
315 N. Grant Street
West Lafayette, IN 47906
United States

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