The Market Web
If prediction markets were to become commonplace, decision makers might link to them in their own analyses. For example, suppose that a corporation is deciding whether to build a new factory in a particular area. That decision might depend on such variables as future interest rates and geographic patterns. And so a decision maker might build a spreadsheet containing live links to prediction markets that are assessing these issues. That way, as the market predictions change, the spreadsheet’s bottom line would change as well. Forecasts in many prediction markets may be interrelated, and so participants in one prediction market will often have incentives to take into account developments in others. Prediction markets thus can affect one another indirectly. Sometimes, however, it might be desirable to construct links among prediction markets so that changes in one automatically lead to changes in another. Consider, for example, the possibility of a market-based alternative to class-action litigation. In Chapter 8, each adjudicated case represented a separate prediction market, but often different cases have issues in common. Many thousands of cases may depend in part on some common factual issues, as well as on some distinct issues. Legal issues also may be the same or different across cases. Someone who improves the analysis of any common factual or legal issue can thus profit on that only by changing predictions in a very large number of cases. A better system might allow someone to make a change across a single market and have that change take effect automatically in individual cases. The critical step needed to facilitate creation of the market web is to allow a market participant to propose a mathematical formula to be used for some particular prediction market. Some of the variables in that formula could be references to other prediction markets, sometimes new ones. For example, in a market for determining the level of damages the plaintiff should receive, a participant might propose a formula that is dependent on variables such as the probability that the plaintiff states a cause of action, the probability that the plaintiff was in fact injured, the probability given injury that the defendant caused the injury, the probability given a cause of action that the defendant is subject to strict liability, the probability (given no strict liability) that the defendant was negligent, and the damages that the plaintiff should be awarded if liability is proved. This formula, for example, presumably would allow for no damages where the plaintiff probably does not state a cause of action. Each of the components of this formula might be assessed with a separate prediction market. We can easily build the market web by combining three tools that have already been described. The first is a text-authoring market. The relevant text would be the formula itself, including specifications of other prediction markets that would be used to calculate specific variables. As with any text-authoring market, a timing market would determine when a proposal to change the text should be resolved. Other markets might become live only once proposals to take them into account were approved. Ex post decision makers would assess the wisdom of these markets’ recommendations in some fraction of cases in order to discipline the market’s functioning. The second tool would be a simple normative prediction market corresponding to the text-authoring market. It might also be possible to have computer software that automatically parses the formula and consults various sources, but the market sponsor need not build this tool. Rather, ex post decision makers will assess the appropriate value for the normative prediction market using the formula. An advantage of this approach is that it would make it easy to use complicated formulas, as well as formulas that depend in part on numbers from sources other than prediction markets or from prediction markets of other types. In addition, this approach makes it easy to collapse a formula into a single prediction market, if that should prove desirable. The formula text simply would be changed to a description of the market to be created, such as “adjudication of plaintiff’s liability in a particular case.” The third tool is a mechanism for determining the market subsidy. A separate subsidy would be needed for the text-authoring market and the normative prediction market. Each of these subsidies could be determined by additional normative prediction markets, perhaps with fixed subsidies. The subsidy for the text-authoring market would be distributed by that market to individuals who have proposed particular amendments and to individuals who have participated in the assessment of particular amendments. This also could allocate a subsidy to the first individual who creates the market and proposes some text for it. When the text-authoring market produces a new formula reflecting additional prediction markets, the subsidy for the main prediction market would fall (since calculating a formula based on other prediction markets will often be relatively easy). A single node in the market web would thus consist of a text-authoring market describing the node and providing a formula for calculating it, a normative prediction market, and a set of additional prediction markets for determining how to distribute a subsidy to contributors to the different components of the node. The nodes collectively create a web because the formulas link to other nodes; software, of course, could easily make these links clickable. At the same time, a mechanism is needed to determine what portion of the market subsidy each node should receive. A prediction market could simply be used for every link to determine the portion of the subsidy for each node that should be allocated to each node linked to it. The total should add up to a figure less than one so that a portion of the subsidy is left for the node itself. Once these markets are established, software could easily distribute a single subsidy for the market as a whole to market participants who have traded on individual nodes when the market closes. Market participants working on one portion of the web, meanwhile, would not have to assess the relative importance of one node to nodes that are only distantly related. It would also be straightforward to have a continuously open market, periodically collecting and distributing money in accordance with individual participants’ success on the market. This assumes that the market web would be arranged on a single server. It is possible, though, that a node on one market web might link to a node on another market web. Allowing such links could promote competition among prediction market providers. It also answers in part one potential criticism of using prediction markets for decision making: that a software engineer might hijack the government by falsifying some prediction market results. Market participants at least will have incentives to identify false prediction markets and not link to them. In principle, it is possible to have government decisions based entirely on decentralized prediction markets, although the government might want to subsidize individual market web providers, and it might use centralized prediction markets to do so. Whether or not the markets are decentralized, they would allow participants to make it easier to assess the basis for market predictions. Indeed, the market web is in some ways a substitute for deliberative prediction markets, because both provide means of helping observers understand the basis for the market’s predictions. An observer could look at any individual node of the market web and understand how it has been calculated, though inevitably there must be some “leaf” nodes that themselves do not contain any formulas. At the same time, software might allow an observer to find all of the nodes that link to a particular node. So a market participant addressing a factual issue that is relevant to many cases could link to all of the cases represented by that factual issue. As a particular issue becomes increasingly important, the subsidy for that node should rise, and market participants can profit on their analysis of the issues relevant to that node without worrying about details of individual cases.
Leave a Reply