section_path: Microeconomics/Uncertainty and game theory
section_name: Uncertainty and game theory
paragraph_text: Uncertainty and game theory
  
  Uncertainty in economics is an unknown prospect of gain or loss, whether quantifiable as risk or not. Without it, household behaviour would be unaffected by uncertain employment and income prospects, financial and capital markets would reduce to exchange of a single instrument in each market period, and there would be no communications industry. Given its different forms, there are various ways of representing uncertainty and modelling economic agents' responses to it.
  
  Game theory is a branch of applied mathematics that considers strategic interactions between agents, one kind of uncertainty. It provides a mathematical foundation of industrial organisation, discussed above, to model different types of firm behaviour, for example in a solipsistic industry (few sellers), but equally applicable to wage negotiations, bargaining, contract design, and any situation where individual agents are few enough to have perceptible effects on each other. In behavioural economics, it has been used to model the strategies agents choose when interacting with others whose interests are at least partially adverse to their own.
  
  In this, it generalises maximisation approaches developed to analyse market actors such as in the supply and demand model and allows for incomplete information of actors. The field dates from the 1944 classic Theory of Games and Economic Behavior by John von Neumann and Oskar Morgenstern. It has significant applications seemingly outside of economics in such diverse subjects as the formulation of nuclear strategies, ethics, political science, and evolutionary biology.
  
  Risk aversion may stimulate activity that in well-functioning markets smooths out risk and communicates information about risk, as in markets for insurance, commodity futures contracts, and financial instruments. Financial economics or simply finance describes the allocation of financial resources. It also analyses the pricing of financial instruments, the financial structure of companies, the efficiency and fragility of financial markets, financial crises, and related government policy or regulation.
  
  Some market organisations may give rise to inefficiencies associated with uncertainty. Based on George Akerlof 's " Market for Lemons " article, the paradigm example is of a dodgy second-hand car market. Customers without knowledge of whether a car is a "lemon" depress its price below what a quality second-hand car would be. Information asymmetry arises here, if the seller has more relevant information than the buyer but no incentive to disclose it. Related problems in insurance are adverse selection, such that those at most risk are most likely to insure (say reckless drivers), and moral hazard, such that insurance results in riskier behaviour (say more reckless driving).
  
  Both problems may raise insurance costs and reduce efficiency by driving otherwise willing transactors from the market (" incomplete markets "). Moreover, attempting to reduce one problem, say adverse selection by mandating insurance, may add to another, say moral hazard. Information economics, which studies such problems, has relevance in subjects such as insurance, contract law, mechanism design, monetary economics, and health care. Applied subjects include market and legal remedies to spread or reduce risk, such as warranties, government-mandated partial insurance, restructuring or bankruptcy law, inspection, and regulation for quality and information disclosure.