Contract Design for Energy Demand Response

Power companies such as Southern California Edison (SCE) uses Demand Response (DR) contracts to incentivize consumers to reduce their power consumption during periods when demand forecast exceeds supply. Current mechanisms in use offer contracts to consumers independent of one another, do not take into consideration consumers' heterogeneity in consumption profile or reliability, and fail to achieve high participation. We introduce DR-VCG, a new DR mechanism that offers a flexible set of contracts (which may include the standard SCE contracts) and uses VCG pricing. We prove that DR-VCG elicits truthful bids, incentivizes honest preparation efforts, enables efficient computation of allocation and prices. With simple fixed-penalty contracts, the optimization goal of the mechanism is an upper bound on probability that the reduction target is missed. Extensive simulations show that compared to the current mechanism deployed in by SCE, the DR-VCG mechanism achieves higher participation, increased reliability, and significantly reduced total expenses.Comment: full version of paper accepted to IJCAI'1

Vickrey Auctions with Reserve Pricing

We generalize the Vickrey auction to allow for reserve pricing in a multiple item auction with interdependent values. By withholding quantity in some circumstances, the seller can improve revenues or mitigate collusion. In the Vickrey auction with reserve pricing, the seller determines the quantity to be made available as a function of the bidders' private information, and then efficiently allocates this quantity among the bidders. Truthful bidding is a dominant strategy with private values and an ex post equilibrium with interdependent values. If the auction is followed by resale, then truthful bidding remains an equilibrium in the auction-plus-resale game. In settings where resale exhausts all the gains from trade among the bidders, the Vickrey auction with reserve pricing maximizes seller revenues.Auctions, Vickrey Auctions, Multiple Item Auctions, Resale

Complexity Theory, Game Theory, and Economics: The Barbados Lectures

This document collects the lecture notes from my mini-course "Complexity Theory, Game Theory, and Economics," taught at the Bellairs Research Institute of McGill University, Holetown, Barbados, February 19--23, 2017, as the 29th McGill Invitational Workshop on Computational Complexity. The goal of this mini-course is twofold: (i) to explain how complexity theory has helped illuminate several barriers in economics and game theory; and (ii) to illustrate how game-theoretic questions have led to new and interesting complexity theory, including recent several breakthroughs. It consists of two five-lecture sequences: the Solar Lectures, focusing on the communication and computational complexity of computing equilibria; and the Lunar Lectures, focusing on applications of complexity theory in game theory and economics. No background in game theory is assumed.Comment: Revised v2 from December 2019 corrects some errors in and adds some recent citations to v1 Revised v3 corrects a few typos in v

FARMERS' PREFERENCES FOR CROP CONTRACTS

An empirical approach combining elements of principal-agent theory and transaction cost economics is used to determine farmers'Â’ preferences for contract terms in crop production. The approach is tested by asking grain farmers to rank contract choices and specify price premiums in simulated case situations. The statistical results indicate that farmers'Â’ preferences for rates of cost sharing, price premiums, and financing arrangements are significantly influenced by asset specialization and uncertainty associated with the case situations, and by selected business and personal characteristics.Farm Management,

Dynamic pricing models for electronic business

Dynamic pricing is the dynamic adjustment of prices to consumers depending upon the value these customers attribute to a product or service. Today’s digital economy is ready for dynamic pricing; however recent research has shown that the prices will have to be adjusted in fairly sophisticated ways, based on sound mathematical models, to derive the benefits of dynamic pricing. This article attempts to survey different models that have been used in dynamic pricing. We first motivate dynamic pricing and present underlying concepts, with several examples, and explain conditions under which dynamic pricing is likely to succeed. We then bring out the role of models in computing dynamic prices. The models surveyed include inventory-based models, data-driven models, auctions, and machine learning. We present a detailed example of an e-business market to show the use of reinforcement learning in dynamic pricing

Inefficiencies in Digital Advertising Markets

Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

Private Information in Sequential Common-Value Auctions

We study an infinitely-repeated ?rst-price auction with common values. Initially, bid- ders receive independent private signals about the objects' value, which itself does not change over time. Learning occurs only through observation of the bids. Under one-sided incomplete information, this information is eventually revealed and the seller extracts es- sentially the entire rent (for large discount factors). Both players?payo¤s tend to zero as the discount factor tends to one. However, the uninformed bidder does relatively better than the informed bidder. We discuss the case of two-sided incomplete information, and argue that, under a Markovian re?nement, the outcome is pooling: information is revealed only insofar as it does not affect prices. Bidders submit a common, low bid in the tradition of collusion without conspiracy.repeated game with incomplete information; private information; ratchet effect; first-price auction; dynamic auctions