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Information asymmetry

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In contract theory and economics, information asymmetry deals with the study of decisions in transactions where one party has more or better information than the other. This creates an imbalance of power in transactions, which can sometimes cause the transactions to go awry, a kind of market failure in the worst case. Examples of this problem are adverse selection,[1] moral hazard, and information monopoly.[2]

Most commonly, information asymmetries are studied in the context of principal–agent problems. Information asymmetry causes misinforming and is essential in every communication process.[3] Information asymmetry is in contrast to perfect information, which is a key assumption in neo-classical economics.[4] In 2001 the The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was awarded to George Akerlof, Michael Spence, and Joseph E. Stiglitz for their "analyses of markets with asymmetric information".[5]

Information asymmetry models

Information asymmetry models assume that at least one party to a transaction has relevant information, whereas the other(s) do not. Some asymmetric information models can also be used in situations where at least one party can enforce, or effectively retaliate for breaches of, certain parts of an agreement, whereas the other(s) cannot.

In adverse selection models, the ignorant party lacks information while negotiating an agreed understanding of or contract to the transaction, whereas in moral hazard the ignorant party lacks information about performance of the agreed-upon transaction or lacks the ability to retaliate for a breach of the agreement. An example of adverse selection is when people who are high-risk are more likely to buy insurance because the insurance company cannot effectively discriminate against them, usually due to lack of information about the particular individual's risk but also sometimes by force of law or other constraints. An example of moral hazard is when people are more likely to behave recklessly after becoming insured, either because the insurer cannot observe this behavior or cannot effectively retaliate against it, for example by failing to renew the insurance.

Adverse selection

The classic paper on adverse selection is George Akerlof's "The Market for Lemons" from 1970, which brought informational issues at the forefront of economic theory. It discusses two primary solutions to this problem, signaling and screening.[6]

Signaling

Michael Spence originally proposed the idea of signaling. He proposed that in a situation with information asymmetry, it is possible for people to signal their type, thus believably transferring information to the other party and resolving the asymmetry.

This idea was originally studied in the context of matching in the job market. An employer is interested in hiring a new employee who is "skilled in learning." Of course, all prospective employees will claim to be "skilled at learning", but only they know if they really are. This is an information asymmetry. Skill in learning is malleable, and depends upon many factors, including diet, exercise and money.

Spence proposes, for example, that going to college can function as a credible signal of an ability to learn. Assuming that people who are skilled in learning can finish college more easily than people who are unskilled, then by finishing college the skilled people signal their skill to prospective employers. No matter how much or how little they may have learned in college or what they studied, finishing functions as a signal of their capacity for learning. However, finishing college may merely function as a signal of their ability to pay for college, it may signal the willingness of individuals to adhere to orthodox views, or it may signal a willingness to comply with authority.

Screening

Joseph E. Stiglitz pioneered the theory of screening. In this way the underinformed party can induce the other party to reveal their information. They can provide a menu of choices in such a way that the choice depends on the private information of the other party.

Examples of situations where the seller usually has better information than the buyer are numerous but include used-car salespeople, mortgage brokers and loan originators, stockbrokers and real estate agents.

Examples of situations where the buyer usually has better information than the seller include estate sales as specified in a last will and testament, life insurance, or sales of old art pieces without prior professional assessment of their value. This situation was first described by Kenneth J. Arrow in an article on health care in 1963.[7]

George Akerlof in The Market for Lemons notices that, in such a market, the average value of the commodity tends to go down, even for those of perfectly good quality. Because of information asymmetry, unscrupulous sellers can "spoof" items (like replica goods such as watches) and defraud the buyer. As a result, many people not willing to risk getting ripped off will avoid certain types of purchases, or will not spend as much for a given item. It is even possible for the market to decay to the point of nonexistence.[citation needed]

Application of information asymmetry in research

Since the seminal contributions of Akerlof, Spence, and Stiglitz, the pervasive effects of information asymmetry in markets have been documented and studied in numerous contexts. In particular, a substantial portion of research in the field of accounting can be framed in terms of information asymmetry, since accounting involves the transmission of an enterprise's information from those who have it to those who need it for decision-making. Likewise, financial economists apply information asymmetry in studies of differentially informed financial market participants (insiders, stock analysts, investors, etc.). Information asymmetry has also seen some use in behavioral economics as well.

Sources of information asymmetry

Information asymmetry within societies can be created and maintained in several ways. Firstly, media outlets, due to their ownership structure or political influences, may fail to disseminate certain viewpoints or engage in propaganda campaigns. Furthermore, an educational system relying on substantial tuition fees can generate information imbalances between the poor and the affluent. Imbalances can also be fortified by certain organizational and legal measures, such as document classification procedures or non-disclosure clauses. Exclusive information networks that are operational around the world further contribute to the asymmetry. Lastly, mass surveillance helps the political and industrial leaders to amass large volumes of information, which is typically not shared with the rest of the society.[8]

Effect of blogging on information asymmetry

Blogging is playing a more central role in reducing the effects of insider trading. According to Saxton and Anker, financial blogs provide figures reducing information asymmetry between corporate insiders and insider trading.[9] Blogging on financial websites provides bottom up communication from investors, analysts, journalists, and academics. Financial blogs prevent people in power from withholding financial information from the general public. The results of Saxton and Anker’s study finds that more participation on blogging sites from credible individuals reduces information asymmetry between corporate insiders as well as insider trading.[9] Compared to traditional forms of media such as newspapers and magazines, blogging provides an easy venue to provide information to the public.

Effect of artificial intelligence on information asymmetry

Tshilidzi Marwala and Evan Hurwitz studied the influence of artificial intelligence on the theory of asymmetric information and observed that artificial intelligent agents decrease the degree of information asymmetry and thus the market where these agents are used are more efficient than when they are not used. They also observed that the more artificial intelligent agents which are used in the market the less is the volume of trades in the market because information asymmetry facilitate trade of goods and services.[10][11]

See also

Notes

  1. ^ Charles Wilson (2008). "adverse selection," The New Palgrave Dictionary of Economics 2nd Edition. Abstract.
  2. ^ John O. Ledyard (2008). "market failure," The New Palgrave Dictionary of Economics, 2nd Ed. Abstract.
  3. ^ Christozov D., Chukova S., Mateev P., Chapter 11. Informing Processes, Risks, Evaluation of the Risk of Misinforming, in Foundations of Informing Science, ISI, 2009, pp. 323-356
  4. ^ http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2001/stiglitz-lecture.pdf
  5. ^ "The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2001: Information for the Public", press release from the Royal Swedish Academy of Sciences, Nobel Foundation, nobelprize.org, October 2001, accessed November 12, 2007.
  6. ^ Johannes Hörne (2008). "signalling and screening" The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  7. ^ Arrow, Kenneth J. (1963). "Uncertainty and the Welfare Economics of Medical Care". American Economic Review. 53 (5). American Economic Association: 941–973. JSTOR 1812044.
  8. ^ The tools used to create information asymmetries are described in the following article http://ssrn.com/abstract=2383166
  9. ^ a b Saxton, G. D. and A. E. Anker (2013). "The Aggregate Effects of Decentralized Knowledge Production: Financial Bloggers and Information Asymmetries in the Stock Market." Journal of Communication 63(6): 1054-1069.
  10. ^ Marwala, Tshilidzi; Hurwitz, Evan (2015). "Artificial Intelligence and Asymmetric Information Theory". arXiv:1510.02867. {{cite arXiv}}: Cite has empty unknown parameter: |url= (help)
  11. ^ https://blogs.cornell.edu/info2040/2015/11/26/artificial-intelligence-can-reduce-information-asymmetry/

References

  • Aboody, David; Lev, Baruch (2000). "Information Asymmetry, R&D, and Insider Gains". Journal of Finance. 55 (6): 2747–2766. doi:10.1111/0022-1082.00305.
  • Brown, Stephen; Hillegeist, Stephen; Lo, Kin (2004). "Conference calls and information asymmetry". Journal of Accounting and Economics. 37 (3): 343–366. doi:10.1016/j.jacceco.2004.02.001.
  • Akerlof, George A. (1970). "The Market for 'Lemons': Quality Uncertainty and the Market Mechanism". Quarterly Journal of Economics. 84 (3). The MIT Press: 488–500. doi:10.2307/1879431. JSTOR 1879431.
  • Hayes, Beth (1984). "Unions and Strikes with Asymmetric Information". Journal of Labor Economics. 2 (1): 57–83. doi:10.1086/298023. JSTOR 2535017.
  • Izquierdo, Segismundo S.; Izquierdo, Luis R. (2007). "The impact of quality uncertainty without asymmetric information on market efficiency". Journal of Business Research. 60 (8): 858–867. doi:10.1016/j.jbusres.2007.02.010. ISSN 0148-2963.
  • Mas-Colell, Andreu; Whinston, Michael D.; Green, Jerry R. (1995). Microeconomic Theory. New York: Oxford University Press. ISBN 0-19-507340-1. (Chaps. 13 and 14 discuss applications of adverse selection and moral hazard models to contract theory.)
  • Saxton, Gregory; Anker, Ashley. "The Aggregate Effects of Decentralized Knowledge Production: Financial Bloggers and Information Asymmetries in the Stock Market". Journal of Communication. 63 (6). Wiley Subscription Services, Inc: 1054–1069. doi:10.1111/jcom.12060.
  • Spence, Michael (1973). "Job Market Signaling". Quarterly Journal of Economics. 87 (3). The MIT Press: 355–374. doi:10.2307/1882010. JSTOR 1882010.
  • Stigler, George J. (1961). "The Economics of Information". Journal of Political Economy. 69 (3): 213–225. doi:10.1086/258464. JSTOR 1829263.
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