Constructivist and Ecological Rationality in Economics

When we leave our closet, and engage in the common affairs of life, (reason's) conclusions seem to vanish, like the phantoms of the night on the appearance of the morning; and 'tis difficult for us to retain even that conviction, which we had attained with difficulty (Hume, 1739/, p 507). we must constantly adjust our lives, our thoughts and our emotions, in order to live simultaneously within different kinds of orders according to different rules. If we were to apply the unmodified, uncurbed rules (of caring intervention to do visible 'good') of the small band or troop, or our families to the (extended order of cooperation through markets), as our instincts and sentimental yearnings often make us wish to do, we would destroy it. Yet if we were to always apply the (noncooperative) rules of the extended order to our more intimate groupings, we would crush them. (Hayek, 1988, p 18). (Italics are his, parenthetical reductions are mine).behavioral economics; experimental economics

A dynamic mechanism and surplus extraction under ambiguity

We study the question of auction design in an IPV setting characterized by ambiguity. We assume that the preferences of agents exhibit ambiguity aversion; in particular, they are represented by the epsilon-contamination model. We show that a simple variation of a discrete Dutch auction can extract almost all surplus. This contrasts with optimal auctions under IPV without ambiguity as well as with optimal static auctions with ambiguity—in all of these, types other than the lowest participating type obtain a positive surplus. An important point of departure is that the modified Dutch mechanism is dynamic rather than static, establishing that under ambiguity aversion—even when the setting is IPV in all other respects—a dynamic mechanism can have additional bite over its static counterparts. A further general insight is that the standard revelation principle does not automatically extend to environments not characterized by subjective expected utility

The Effects of Beliefs versus Risk Preferences on Bargaining Outcomes

In bargaining environments with uncertain impasse outcomes (e.g., litigation or labor strike outcomes), there is an identification problem that confounds data interpretation. In such environments, the minimally acceptable settlement value from a risk-averse (risk-loving) but unbiased bargainer is empirically indistinguishable from what one could get with risk-neutrality and pessimism (optimism). This paper reports data from a controlled bargaining experiment where risk preferences and beliefs are both measured in order to assess their relative importance in bargaining outcomes. The average lab subject is risk-averse, yet optimistic, which is consistent with existing studies that examine each in isolation. I also find that the effects of optimism dominate those of risk-aversion. Optimistic bargainers are significantly more likely to dispute and have aggressive final bargaining positions. Dispute rates are not statistically affected by risk preferences, but there is some evidence that risk aversion leads to less aggressive bargaining positions and lower payoff outcomes. A key implication is that increased settlement rates are more likely achieved by minimizing impasse uncertainty (to limit the potential for optimism) rather than maximizing uncertainty (to weaken the reservation point of risk-averse bargainers), as has been argued in the dispute resolution literature.risk preference, optimism, bargaining, experiments

A Dynamic Mechanism and Surplus Extraction Under Ambiguity

In the standard independent private values (IPV)model, each bidder’s beliefs about the values of any other bidder is represented by a unique prior. In this paper we relax this assumption and study the question of auction design in an IPV setting characterized by ambiguity: bidders have an imprecise knowledge of the distribution of values of others, and are faced with a set of priors. We also assume that their preferences exhibit ambiguity aversion; in particular, they are represented by the epsilon-contamination model. We show that a simple variation of a discrete Dutch auction can extract almost all surplus. This contrasts with optimal auctions under IPV without ambiguity as well as with optimal static auctions with ambiguity - in all of these, types other than the lowest participating type obtain a positive surplus. An important point of departure is that the modified Dutch mechanism we consider is dynamic rather than static, establishing that under ambiguity aversion – even when the setting is IPV in all other respects – a dynamic mechanism can have additional bite over its static counterparts.Ambiguity Aversion; Epsilon Contamination; Modified Dutch Auction; Dynamic Mechanism; Surplus Extraction

Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization

On top of Smart Grid technologies and new market mechanism design, the further deregulation of retail electricity market at distribution level will play a important role in promoting energy system transformation in a socioeconomic way. In today’s retail electricity market, customers have very limited ”energy choice,” or freedom to choose different types of energy services. Although the installation of distributed energy resources (DERs) has become prevalent in many regions, most customers and prosumers who have local energy generation and possible surplus can still only choose to trade with utility companies.They either purchase energy from or sell energy surplus back to the utilities directly while suffering from some price gap. The key to providing more energy trading freedom and open innovation in the retail electricity market is to develop new consumer-centric business models and possibly a localized energy trading platform. This dissertation is exactly pursuing these ideas and proposing a holistic localized electricity retail market to push the next-generation retail electricity market infrastructure to be a level playing field, where all customers have an equal opportunity to actively participate directly. This dissertation also studied and discussed opportunities of many emerging technologies, such as reinforcement learning and deep reinforcement learning, for intelligent energy system operation. Some improvement suggestion of the modeling framework and methodology are included as well.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145686/1/Tao Chen Final Dissertation.pdfDescription of Tao Chen Final Dissertation.pdf : Dissertatio

Communication channels and induced behavior

This paper reports recent findings on the effects of cheap talk communication on behavior. It exemplifies how different communication channels influence decisions in various games and information environments and addresses possible consequences for the design of real-world economic environments.communication, economic experiment, bargaining, public good

Vertical competition between manufacturers and retailers and upstream incentives to innovate and differentiate

Vertical competition, namely competition between retailers' store brands (or private labels) and manufacturers' brands has become a crucial factor of change of the competitive environment in several industries, particularly in the grocery and food industries. Despite the growing literature on the determinants of the phenomenon, one topic area regarding the impact of vertical competition on the upstream incentives to adopt non-price strategies such as product innovation as well as horizontal and vertical product differentiation has so far received little attention. An idea often put forward is that the increasing bargaining power of retailers and higher vertical competitive pressures can have negative effects on such incentives by lowering manufacturers' profits. On the other hand, there is a significant empirical evidence supporting the view that non-price strategies of product innovation and differentiation continue to play a key role and remain a crucial source of competitive advantages for several manufacturers. In this paper, we present a simple conceptual framework which allows us to focus on two hypotheses which interacting explain why the disincentive effects are not so obvious. The first hypothesis regards the existence of an inverse relationship between the strength of a given brand and the retail margin as suggested by Robert Steiner. Through a two-stage model in which manufacturers do not sell directly to final consumers and the retail industry is not perfectly competitive, Steiner argued persuasively that in such models leading brands in a product category yield lower retail margins than less strong brands. Retailers are forced to stock strong brands and therefore have relatively less bargaining power in negotiating wholesale prices. In addition, price competition among retailers is more intense on strong brands since consumers select these brands to form their perceptions of stores' price competitiveness and are ready to shift to lower price stores if retail price of these brands is not perceived as competitive. Thus, intensive intrabrand competitive pressures discipline retailers pricing policy on stronger manufacturer brands much more than on weaker brands. A key prediction of Steiner's two-stage model is that, since manufacturers' non-price strategies have a margin depressing impact which is additional to their direct demand - creating effect, manufacturers face greater incentives to invest in advertising and R&D. The second central hypothesis in our framework is that in a world of asymmetric brands and intense vertical competition there is a further mechanism at work due to retailers' delisting decisions. Given that retailers have to make room for their store brands at the point of sale, they have to readjust their assortments delisting some manufacturer brands. Retailers would like delisting strong brands given that the retailer's margin on these brands is lower. The problem is that strong brands can contrast vertical pressures better than weaker brands and cannot be delisted. In making shelf - space decisions, rational retailers will recognise that they can delist only the brands whose brand loyalty is lower than their store loyalty. On the contrary, retailers cannot delist brands for which brand loyalty is greater than store loyalty. This implies that manufacturer brands operate in a two- region environment. We call these two regions, respectively, the 'delisting' and 'no-delisting' region and show that the demarcation point between them is given by the level of retailer's store loyalty. By combining the Steiner's hypothesis with the mechanism of delisting, we argue that in a competitive environment characterized by vertical competition is at work a threshold effect which increases optimal 2 R&D and advertising expenditures. The intuition is that it is vital for manufacturers willing to remain sellers of branded products to keep brand loyalty of their brands at a level higher than retailer's store loyalty. And the only way to pursue this goal and avoid to be involved into the risk of being delisted is to boost brands. We also show that vertical competitive pressures are particularly strong on second- tier brands. A brief review of some recent patterns and stylised facts in the food industries and grocery channels consistent with these predictions conclude the paper.vertical competition, store brands, delisting, optimal advertising, Industrial Organization,

Peer-to-Peer Energy Trading in Smart Residential Environment with User Behavioral Modeling

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid. Trading energy among users in a decentralized fashion has been referred to as Peer- to-Peer (P2P) Energy Trading, which has attracted significant attention from the research and industry communities in recent times. However, previous research has mostly focused on engineering aspects of P2P energy trading systems, often neglecting the central role of users in such systems. P2P trading mechanisms require active participation from users to decide factors such as selling prices, storing versus trading energy, and selection of energy sources among others. The complexity of these tasks, paired with the limited cognitive and time capabilities of human users, can result sub-optimal decisions or even abandonment of such systems if performance is not satisfactory. Therefore, it is of paramount importance for P2P energy trading systems to incorporate user behavioral modeling that captures users’ individual trading behaviors, preferences, and perceived utility in a realistic and accurate manner. Often, such user behavioral models are not known a priori in real-world settings, and therefore need to be learned online as the P2P system is operating. In this thesis, we design novel algorithms for P2P energy trading. By exploiting a variety of statistical, algorithmic, machine learning, and behavioral economics tools, we propose solutions that are able to jointly optimize the system performance while taking into account and learning realistic model of user behavior. The results in this dissertation has been published in IEEE Transactions on Green Communications and Networking 2021, Proceedings of IEEE Global Communication Conference 2022, Proceedings of IEEE Conference on Pervasive Computing and Communications 2023 and ACM Transactions on Evolutionary Learning and Optimization 2023