Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders

Double auction prediction markets have proven successful in large-scale applications such as elections and sporting events. Consequently, several large corporations have adopted these markets for smaller-scale internal applications where information may be complex and the number of traders is small. Using laboratory experiments, we test the performance of the double auction in complex environments with few traders and compare it to three alternative mechanisms. When information is complex we find that an iterated poll (or Delphi method) outperforms the double auction mechanism. We present five behavioral observations that may explain why the poll performs better in these settings

Experimental studies of arbitration mechanisms and two-sided markets

This dissertation consists of three essays. The first essay is an experimental study that examines a relative new type of arbitration called α-Final Offer Arbitration. The second is a theoretical study that introduces inequality aversion as a new explanatory factor for low agreements rates during disputes under arbitration mechanism. The final essay analyzes the effects of different polices on the price stricter in a two-sided market monopoly. Promising results to improve arbitration used in the field are obtained from Amended Final Offer Arbitration (AFOA), which outperforms Final-Offer Arbitration (FOA) and weakly outperforms Conventional Arbitration (CA). The first essay presents an experiment to evaluate a more general case of AFOA, α-Final Offer Arbitration (α-FOA). This mechanism is similar to a second-price auction, which punishes the loser with a value proportional (α) to the difference between her final offer and the arbitrator\u27s fair settlement. The experiment furthermore divides the pool of subjects within a session into two groups according to their estimated risk preferences in order to assess how the contract zone depends on the relative risk preferences of the subjects involved in negotiation. Although agreement rates overall are low, the results show that α-FOA has a significantly higher agreement rate than both CA and FOA. Contrary to theoretical prediction the more risk-averse group of subjects does not have a higher agreement rate than the less risk-averse group of subjects. The second essay proposes an as yet unstudied factor to explain disagreements between disputants under α-Final Offer Arbitration and Conventional Arbitration. Using a utility function proposed by Fehr & Schmidt (1999) that includes inequality aversion, the model predicts that two risk-neutral disputants will not reach an agreement if one of them has positively biased beliefs about the size of the pie. The third essay investigates the effects of different policies on price structure and consumer surplus in a two-sided market monopoly. In a laboratory environment, most of the monopolists charge a price below cost even if there is no threat of new competitors. A policy that imposes that the monopolist must charge the same price for both sides of the market decreases the total consumer surplus, while a policy that imposes that prices must be above costs decreases the total consumer surplus even more. A tax that increases the cost on one side of the market leads to a decrease in the price that monopolist charges on the other side of the market. These results suggest that the policymakers should distinguish between a one-sided and a two-sided market before they impose different policies

Multi-outcome and Multidimensional Market Scoring Rules

Hanson's market scoring rules allow us to design a prediction market that still gives useful information even if we have an illiquid market with a limited number of budget-constrained agents. Each agent can "move" the current price of a market towards their prediction. While this movement still occurs in multi-outcome or multidimensional markets we show that no market-scoring rule, under reasonable conditions, always moves the price directly towards beliefs of the agents. We present a modified version of a market scoring rule for budget-limited traders, and show that it does have the property that, from any starting position, optimal trade by a budget-limited trader will result in the market being moved towards the trader's true belief. This mechanism also retains several attractive strategic properties of the market scoring rule

Essays in Corporate Prediction Markets

Personal subjective opinions are one of the most important assets in management. Prediction markets are mechanisms that can be deployed to elicit and aggregate a group of people’s opinions regarding the outcome of future events at any point in time. Prediction markets are exchange-traded markets where security values are tied to the outcome of future events. Prediction markets are systematically designed in a way that their market prices capture the crowd’s consensus about the probability of a future event. Corporations harness internal prediction markets for managerial decision making and business forecasting. Prediction markets are traditionally designed for large and diverse populations, two properties that are not often displayed in corporate settings. Therefore special considerations must be given to prediction markets used in corporations. Our first contribution in this thesis is in addressing the issue of diversity, in the sense of risk preferences, in corporate prediction markets. We study prediction markets in the presence of risk averse or risk seeking agents that have unknown risk preferences. We show that such agents’ behavior is not desirable for the purpose of information aggregation. We then characterize the agents’ behavior with respect to prediction market parameters and offer a systematic method to market organizers that fine tunes market parameters so at to best mitigate the impact of a pool agents’ risk-preferences. Our Second contribution in this thesis is in recommending prediction market mechanisms in different settings. There are many prediction market mechanisms with various advantages and weaknesses. The choice of a market mechanism can heavily affect the market accuracy and in turn, the success of a managerial decision, or a forecast based on prediction markets’ prices. Using trade data from two real-world prediction markets, we study the two main types of prediction markets mechanism and provide the much-needed insight as to what market mechanism to choose in various situations

On the Road to Making Science of “Art”: Risk Bias in Market Scoring Rules

We study market scoring rule (MSR) prediction markets in the presence of risk-averse or risk-seeking agents that have unknown yet bounded risk preferences. It is well known that if agents can be prescreened, then MSRs can be corrected to elicit agents’ beliefs. However, agents cannot always be screened, and instead, an online MSR mechanism is needed. We show that agents’ submitted reports always deviate from their beliefs, unless their beliefs are identical to the current market estimate. This means, in most cases it is impossible for a MSR prediction market to elicit an individual agent’s exact belief. To analyze this issue, we introduce a measure to calculate the deviation between an agent’s reported belief and personal belief. We further derive the necessary and sufficient conditions for a MSR to yield a lower deviation relative to another MSR. We find that the deviation of a MSR prediction market is related to the liquidity provided in the MSR’s corresponding cost-function prediction market. We use the relation between deviation and liquidity to present a systematic approach to help determine the amount of liquidity required for cost-function prediction markets, an activity that up to this point has been described as “art” in the literature.Natural Sciences and Engineering Research Council of Canad

Information Procurement and Delivery: Robustness in Prediction Markets and Network Routing.

In this dissertation we address current problems in information procurement and delivery. Uncertainty commonly reduces the efficacy of information procurement systems, such as prediction markets, and information delivery systems, such as Internet backbone networks. We address the problems of uncertainty by designing robust algorithms and protocols that function well under uncertainty. Telecommunication backbone networks are used for delivering information across the Internet. Current backbone networks mostly employ protocols that include sender-receiver based congestion control. However, as protocols that do not have congestion control available become more prevalent, the network routers themselves must perform congestion control. In order to maximize network throughput, routing policies for backbone networks that take into account router based congestion control must be devised. We propose a mathematical model that can be used to design improved routing policies, while also taking into account existing flow management methods. Our model incorporates current active congestion control methods, and takes into account demand uncertainty when creating routing policies. The resulting routing policies tended to be at least 20% better than those currently used in a real world network in our experiments. Prediction markets are information aggregation tools in which participants trade on the outcome of a future event. One commonly used form of prediction market, the market scoring rule market, accurately aggregate the beliefs of traders assuming the traders are myopic, meaning they do not consider future payoffs, and are risk neutral. In currently deployed prediction markets neither of these assumptions typically holds. Therefore, in order to analyze the effectiveness of such markets, we look at the impact of non-myopic risk neutral traders, as well as risk averse traders on prediction markets. We identify a setting where non-myopic risk neutral traders may bluff, and propose a modified prediction market to disincentivize such behavior. Current prediction markets do not accurately aggregate all risk averse traders' beliefs. Therefore, we propose a new prediction market that does. The resulting market exponentially reduces the reward given to traders as the number of traders increases; we show that this exponential reduction is necessary for any prediction market that aggregates the beliefs of risk averse traders.Ph.D.Industrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75962/1/sdimitro_1.pd

Unemployment Insurance in Theory and Practice

A hallmark of modern labor economics is the close interplay between the development of theory, data sources and econometric testing. The evolution of the economic analysis of unemployment insurance provides a good illustration. New theoretical approaches, in particular job-search theory, have inspired a large amount of empirical research, some of it methodologically innovative and most of it highly relevant for economic policy. The paper presents a broad survey and an assessment of the economic analysis of unemployment insurance as it has evolved since the 1970s.

Essays in Behavioral Economics

This dissertation aims at continuing and expanding three lines of research prominent in behavioral economics today. The first chapter deals with the role of reciprocity in labor contracts and explores which factors determine whether a payment scheme is perceived as fair. The second chapter studies whether people integrate money from various income sources. This question is related to the notion of fungibility and narrow bracketing. Chapter 3 tests whether people evaluate their outcome in comparison to a reference point. More specifically, it tests whether an individual's rational expectations serve as a reference point. Even though the three chapters cover different areas of behavioral economics, they share the same underlying questions: To which degree are fundamental assumptions of economics in line with real world behavior and where do they need to be refined? And how can we use this new knowledge to design economic institutions serving people that are neither fully rational nor completely selfish? All chapters present empirical analyses of laboratory or field experiments. Experiments provide a maximum of control and allow for a causal interpretation as treatments are assigned exogenously. The results presented in this dissertation are potentially important for many fundamental economic questions, especially in the areas of labor and public economics, but also for the understanding of investment and consumption decisions.</p

Improving Incentives in Unemployment Insurance: A Review of Recent Research

This paper provides a review of the recent literature on how incentives in unemployment insurance (UI) can be improved. We are particularly concerned with three instruments, viz. the duration of benefit payments (or more generally the time sequencing of benefits), monitoring in conjunction with sanctions, and workfare. Our reading of the theoretical literature is that the case for imposing a penalty on less active job search is fairly solid. A growing number of empirical studies, including randomized experiments, are in line with this conclusion.Unemployment insurance; search; monitoring; sactions; workfare

Some Aspects of the Economics of Catastrophe Risk Insurance

The ability to share risk efficiently in the economy is essential to welfare and growth. However, the increased frequency of natural catastrophes over the last decade has raised once again questions associated to the limits of insurability in a free-market economy, and to the relevance of public interventions on risk-sharing markets. In this paper, we explore the potential reasons for the lack of insurance specifically associated to catastrophe environmental risks. Our final aim is to link each source of possible market inefficiency to its possible remedies.