Incentive Regulation for Electricity Networks

Elektrizitätswirtschaft, Anreizregulierung, Electric utility industry, Incentive regulation

Online Pricing with Offline Data: Phase Transition and Inverse Square Law

This paper investigates the impact of pre-existing offline data on online learning, in the context of dynamic pricing. We study a single-product dynamic pricing problem over a selling horizon of $T$ periods. The demand in each period is determined by the price of the product according to a linear demand model with unknown parameters. We assume that before the start of the selling horizon, the seller already has some pre-existing offline data. The offline data set contains $n$ samples, each of which is an input-output pair consisting of a historical price and an associated demand observation. The seller wants to utilize both the pre-existing offline data and the sequential online data to minimize the regret of the online learning process. We characterize the joint effect of the size, location and dispersion of the offline data on the optimal regret of the online learning process. Specifically, the size, location and dispersion of the offline data are measured by the number of historical samples $n$, the distance between the average historical price and the optimal price $\delta$, and the standard deviation of the historical prices $\sigma$, respectively. We show that the optimal regret is $\widetilde \Theta\left(\sqrt{T}\wedge \frac{T}{(n\wedge T)\delta^2+n\sigma^2}\right)$, and design a learning algorithm based on the "optimism in the face of uncertainty" principle, whose regret is optimal up to a logarithmic factor. Our results reveal surprising transformations of the optimal regret rate with respect to the size of the offline data, which we refer to as phase transitions. In addition, our results demonstrate that the location and dispersion of the offline data also have an intrinsic effect on the optimal regret, and we quantify this effect via the inverse-square law.Comment: Forthcoming in Management Scienc

Incentive Regulation in Theory and Practice: Electricity Distribution and Transmission Networks

Modern theoretical principles to govern the design of incentive regulation mechanisms are reviewed and discussed. General issues associated with applying these principles in practice are identified. Examples of the actual application of incentive regulation mechanisms to the regulation of prices and service quality for 'unbundled' transmission and distribution networks are presented and discussed. Evidence regarding the performance of incentive regulation in practice for electric distribution and transmission networks is reviewed. Issues for future research are identified.

Regulation, competition, and liberalization

In many countries throughout the world, regulators are struggling to determine whether and how to introduce competition into regulated industries. This essay examines the complexities involved in the liberalization process. While stressing the importance of case-specific analyses, this essay distinguishes liberalization policies that generally are pro-competitive from corresponding anti-competitive liberalization policies

MILK PRICING IN THE UNITED STATES

This report provides a primer on the complex pricing system that has evolved in the United States to deal with milk production, its assembly (collection), and its distribution to alternative users. All the various government and private institutions making up the system are expected to work together to ensure that the public gets the milk it wants, while dairy farmers get the economic returns needed to provide the milk. The major institutions are the Federal milk price support program and milk marketing orders, the Northeast Interstate Dairy Compact, State regulations, dairy cooperatives, and milk and dairy product futures and options markets. Our goal is to provide a primer on milk pricing that can serve as a steppingstone to other, more detailed works for those so inclined.Dairy, milk pricing, Demand and Price Analysis, Livestock Production/Industries,

WARNING: Physics Envy May Be Hazardous To Your Wealth!

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.Comment: v3 adds 2 reference