Tuesday, 9 November 2021

Information Economics

 From Wikipedia, the free encyclopedia

Jump to navigationJump to search
Not to be confused with Information economy.
Part of a series on
Economics
Branches and classifications
Concepts, theory and techniques
By application
Notable economists
Lists

Information economics or the economics of information is a branch of microeconomic theory that studies how information and information systems affect an economy and economic decisions. Information has special characteristics: It is easy to create but hard to trust. It is easy to spread but hard to control. It influences many decisions. These special characteristics (as compared with other types of goods) complicate many standard economic theories.[1]

The subject of "information economics" is treated under Journal of Economic Literature classification code JEL D8 – Information, Knowledge, and Uncertainty. The present article reflects topics included in that code. There are several subfields of information economics. Information as signal has been described as a kind of negative measure of uncertainty.[2] It includes complete and scientific knowledge as special cases. The first insights in information economics related to the economics of information goods.

In recent decades, there have been influential advances in the study of information asymmetries[3] and their implications for contract theory, including market failure as a possibility.[4]

Information economics is formally related to game theory as two different types of games that may apply, including games with perfect information,[5] complete information,[6] and incomplete information.[7] Experimental and game-theory methods have been developed to model and test theories of information economics,[8] including potential public-policy applications such as mechanism design to elicit information-sharing and otherwise welfare-enhancing behavior.[9]

Value of information[edit]

The starting point for economic analysis is the observation that information has economic value because it allows individuals to make choices that yield higher expected payoffs or expected utility than they would obtain from choices made in the absence of information. Data valuation is an emerging discipline that seeks to understand and measure the economic characteristics of information and data.[10]

Information, the price mechanism and organizations[edit]

Much of the literature in information economics was originally inspired by Friedrich Hayek's "The Use of Knowledge in Society" on the uses of the price mechanism in allowing information decentralization to order the effective use of resources. [11] Although Hayek's work was intended to discredit the effectiveness of central planning agencies over a free market system, his proposal that price mechanisms communicate information about scarcity of goods inspired Abba Lerner, Tjalling Koopmans, Leonid Hurwicz, George Stigler and others to further develop the field of information economics.[citation needed] Next to market coordination through the price mechanism, transactions can also be executed within organizations. The information requirements of the transaction are the prime determinant for the actual (mix of) coordination mechanism(s) that we will observe.[12]

Information asymmetry[edit]

Information asymmetry means that the parties in the interaction have different information, e.g. one party has more or better information than the other. Expecting the other side to have better information can lead to a change in behavior. The less informed party may try to prevent the other from taking advantage of him. This change in behavior may cause inefficiency. Examples of this problem are selection (adverse or advantageous) and moral hazard.[13]

A classic paper on adverse selection is George Akerlof's The Market for Lemons.[14] There are two primary solutions to this problem, signaling and screening.

For moral hazard, contracting between principal and agent may be describable as a second best solution where payoffs alone are observable with information asymmetry.[15]

Signaling[edit]

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 credibly transferring information to the other party and resolving the asymmetry.

This idea was originally studied in the context of looking for a job. 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.

Spence proposed 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 attending college the skilled people signal their skill to prospective employers. This is true even if they didn't learn anything in school, and school was there solely as a signal. This works because the action they took (going to school) was easier for people who possessed the skill that they were trying to signal (a capacity for learning).[16]

Screening[edit]

Joseph E. Stiglitz pioneered the theory of screening.[17] 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 optimal choice of the other party depends on their private information. By making a particular choice, the other party reveals that he has information that makes that choice optimal. For example, an amusement park wants to sell more expensive tickets to customers who value their time more and money less than other customers. Asking customers their willingness to pay will not work - everyone will claim to have low willingness to pay. But the park can offer a menu of priority and regular tickets, where priority allows skipping the line at rides and is more expensive. This will induce the customers with a higher value of time to buy the priority ticket and thereby reveal their type.

Information goods[edit]

Buying and selling information is not the same as buying and selling most other goods. There are three factors that make the economics of buying and selling information different from solid goods:

First of all, information is non-rivalrous, which means that consuming information does not exclude someone else from also consuming it. A related characteristic that alters information markets is that information has almost zero marginal cost. This means that once the first copy exists, it costs nothing or almost nothing to make a second copy. This makes it easy to sell over and over. However, it makes classic marginal cost pricing completely infeasible.

Second, exclusion is not a natural property of information goods, though it is possible to construct exclusion artificially. However, the nature of information is that if it is known, it is difficult to exclude others from its use. Since information is likely to be both non-rivalrous and non-excludable, it is frequently considered an example of a public good.

Third is that the information market does not exhibit high degrees of transparency. That is, to evaluate the information, the information must be known, so you have to invest in learning it to evaluate it. To evaluate a bit of software you have to learn to use it; to evaluate a movie you have to watch it.

The importance of these properties is explained by De Long and Froomkin in The Next Economy.

Network Effects[edit]

Carl Shapiro and Hal Varian described Network effect (also called network externalities) as products gaining additional value from each additional user of that good or service.[18] Network effects are externalities in which they provide an immediate benefit when an additional user joins the network, increasing the network size. The total value of the network depends upon the total adopters but carries only a marginal benefit for new users. This leads to a direct network effect for each user's adoption of the good, with an increased incentive for adoption as other user's adopt and join the network.[19] The indirect network effect occurs as a complementary goods benefit from the adoption of the initial product.[20]

The growth of data is constantly expanding and growing at an exponential rate, however, the application of this data is far lower than the creation of it.[21][22]

New data brings about a potential increase in bad information which can crowd out the good information. This increase in unverified information is due to the easy and free nature of creating online data, disrupting potential for users from finding sourced and verified data.[23]

Critical Mass[edit]

As new networks are developed, early adopters form the social dynamics of the greater population and develop product maturity known as Critical mass. Product maturity is when they become self-sustaining and is more likely to occur when there are positive cash flows, consistent revenue flows, customer retention and brand engagement.[24] To form a following, low initial prices need to be offered, along with wide-spread marketing to help create the snowball effect.

More information[edit]

In 2001, the Nobel prize in economics was awarded to George Akerlof, Michael Spence, and Joseph E. Stiglitz "for their analyses of markets with asymmetric information".[25]

See also[edit]

References[edit]

  1. ^ • Beth Allen, 1990. "Information as an Economic Commodity," American Economic Review, 80(2), pp. 268–273.
      • Kenneth J. Arrow, 1999. "Information and the Organization of Industry," ch. 1, in Graciela Chichilnisky Markets, Information, and Uncertainty. Cambridge University Press, pp. 20–21.
       • _____, 1996. "The Economics of Information: An Exposition," Empirica, 23(2), pp. 119–128.
       • _____, 1984. Collected Papers of Kenneth J. Arrow, v. 4, The Economics of Information. Description and chapter-preview links.
       • Jean-Jacques Laffont, 1989. The Economics of Uncertainty and Information, MIT Press. Description Archived 2012-01-25 at the Wayback Machine and chapter-preview links.
  2. ^ Kenneth J. Arrow, 1996. "The Economics of Information: An Exposition," Empirica, 23(2), pp. 120–21.
  3. ^ Charles Wilson, 2008. "adverse selection," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
  4. ^ • John O. Ledyard, 2008. "market failure," The New Palgrave Dictionary of Economics, 2nd Ed. Abstract.
       • Armen A. Alchian and Harold Demsetz, 1972. "Production, Information Costs, and Economic Organization," American Economic Review, 62(5), pp. 777–795. 
       • Sanford J. Grossman and Joseph E. Stiglitz, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, 70(3), pp. 393–408 Archived 2012-04-04 at the Wayback Machine.
       • Stiglitz, Joseph E. (2008). "Information". In David R. Henderson (ed.). Concise Encyclopedia of Economics (2nd ed.). Indianapolis: Library of Economics and Liberty. ISBN 978-0865976658. OCLC 237794267.
       • _____, 1987. "The Causes and Consequences of the Dependence of Quality on Prices," Journal of Economic Literature, 25(1), pp.1–48.
       • _____, 2000. "The Contributions of the Economics of Information to Twentieth Century Economics," Quarterly Journal of Economics, 115(4) , pp. 1441–1478.
       • _____, 2002. "Information and the Change in the Paradigm in Economics," American Economic Review, 92(3), pp. 460–501[dead link]. from Nobel Prize Lecture Archived 2011-05-10 at the Wayback Machine, December 8, 2001.
  5. ^ Jan Mycielski, 1992. "Games with Perfect Information," Handbook of Game Theory with Economic Applications, v. 1, Elsevier, ch. 3, pp. 41–70.
  6. ^ • Adam Brandenburger, 2008. "epistemic game theory: complete information," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       • Sylvain Sorin, 1992. "Repeated Games with Complete Information," Handbook of Game Theory with Economic Applications, v. 1, Elsevier, ch. 4, pp. 71–107.
  7. ^ • Aviad Heifetz. 2008. "epistemic game theory: incomplete information,"The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       • Robert J. Aumann and Aviad Heifetz, 2002. "Incomplete Information," Handbook of Game Theory with Economic Applications, v. 3, Elsevier, ch. 43, pp. 1665–1686.
       • Shmuel Zamir, 1992. "Repeated Games of Incomplete Information: Zero-Sum," Handbook of Game Theory with Economic Applications, v. 1, Elsevier, ch. 5, pp. 109–154.
       • Françoise Forges, 1992. "Repeated Games of Incomplete Information: Non-Zero-Sum," Handbook of Game Theory with Economic Applications, v. 1, Elsevier, ch. 6, pp. 155–177.
  8. ^ • S. S. Lippman, and J. J. McCall, 2001. "Information, Economics of," International Encyclopedia of the Social & Behavioral Sciences, pp. 7480–7486.
       • Eric Rasmusen, 2007. Games and Information, 4th ed. Description and chapter-preview links.
       • Charles R. Plott and Vernon L. Smith, 2008. Handbook of Experimental Economics Results, v. 1, Elsevier, Part 2: Market Economics of Uncertainty and Information and Part 4: Games, respectively, chapters 34–40 & 45–66 preview links.
       • Karl-Gustaf Löfgren, Torsten Persson, and Jörgen W. Weibull, 2002. "Markets with Asymmetric Information: The Contributions of George Akerlof, Michael Spence and Joseph Stiglitz," Scandinavian Journal of Economics, 104(2), pp. 195–211Archived 2012-04-25 at the Wayback Machine.
  9. ^ • Roger B. Myerson, 2008. "mechanism design," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       • _____, 2008. "revelation," principle," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
       • _____, 2008. "Perspectives on Mechanism Design in Economic Theory," American Economic Review, 98(3), pp. 586–603 Archived 2012-05-25 at the Wayback Machine. Revised from Nobel-prize lecture.
       • Noam Nisan and Amir Ronen, 2001. "Algorithmic Mechanism Design," Games and Economic Behavior, 35(1–2), pp. 166–196.
  10. ^ "The Value of Data".
  11. ^ • F. A. Hayek, 1945. "The Use of Knowledge in Society," American Economic Review, 35(4), pp. 519–530.
       • _____, 1948. Individualism and Economic Order, Chicago. Description and chapter-preview links.
  12. ^ Sytse Douma & Hein Schreuder (2013) "Economic Approaches to Organizations", 5th edition, London: Pearson
  13. ^ "Sources of Inefficiency". LumenLearning.
  14. ^ George Akerlof, 1970. "The Market for 'Lemons': Quality Uncertainty and the Market Mechanism," Quarterly Journal of Economics, 84(3), pp. 488–500.
  15. ^ Bengt Holmstrom, 1979. "Moral Hazard and Observability,", Bell Journal of Economics, 10(1), pp. 74–91 Archived 2012-04-07 at the Wayback Machine.
  16. ^ Michael A. Spence, 1973. "Job Market Signaling," Quarterly Journal of Economics, 83(3), pp. 355–377.
  17. ^ Joseph E. Stiglitz, 1975. "The Theory of 'Screening', Education, and the Distribution of Income," American Economic Review,65(3), pp. 283–300.
  18. ^ Carl Shapiro; Hal R. Varian (1999). Information rules : a strategic guide to the network economy. Boston, Mass.: Harvard Business School Press. ISBN 0-87584-863-X. OCLC 39210116.
  19. ^ Klemperer P. (2018) Network Goods (Theory). In: Macmillan Publishers Ltd (eds) The New Palgrave Dictionary of Economics. Palgrave Macmillan, London
  20. ^ Klemperer P. (2018) Network Goods (Theory). In: Macmillan Publishers Ltd (eds) The New Palgrave Dictionary of Economics. Palgrave Macmillan, London
  21. ^ Greaton, Timothy (23 December 2019). "What's causing the exponential growth of data?". Nikko Asset Management.
  22. ^ Koutroumpis, Pantelis (8 August 2009). "The economic impact of broadband on growth: A simultaneous approach". Telecommunications Policy. 33 (9): 471–485. doi:10.1016/j.telpol.2009.07.004.
  23. ^ Kim, Henry (29 March 2017). "When Bad Information Crowds out the Good". Medium.
  24. ^ "How to Achieve Critical Mass for a Product Launch". Interaction Design Foundation. September 2020.
  25. ^ "The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2001". nobelprize.org. Retrieved 10 April 2018.

Further reading[edit]

Papers[edit]

  • Bakos, Yannis and Brynjolfsson, Erik 2000. "Bundling and Competition on the Internet: Aggregation Strategies for Information Goods" Marketing Science Vol. 19, No. 1 pp. 63–82.
  • Bakos, Yannis and Brynjolfsson, Erik 1999. "Bundling Information Goods: Pricing, Profits and Efficiency" Management Science, Vol. 45, No. 12 pp. 1613–1630
  • Brynjolfsson, Erik, and Saunders, Adam, 2009. "Wired for Innovation: How information technology is reshaping the economy", [1], ISBN 0-262-01366-5 ISBN 978-0-262-01366-6
  • Mas-Colell, Andreu; Michael D. Whinston, and Jerry R. Green, 1995, Microeconomic Theory. Oxford University Press. Chapters 13 and 14 discuss applications of adverse selection and moral hazard models to contract theory.
  • Milgrom, Paul R., 1981. "Good News and Bad News: Representation Theorems and Applications," Bell Journal of Economics, 12(2), pp. 380–391.
  • Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, 78(2), p p. 311–329.
  • _____, 1974. "Advertising as Information," Journal of Political Economy, 82(4), pp. 729–754.

Technology], 978-0134645957

Monographs[edit]

Dictionaries[edit]

"bubbles" by Markus K. Brunnermeier
"information aggregation and prices" by James Jordan.
"information cascades," by Sushil Bikhchandani, David Hirshleifer and Ivo Welch.
"information sharing among firms" by Xavier Vives.
"information technology and the world economy" by Dale W. Jorgenson and Khuong Vu.
"insider trading" by Andrew Metrick.
"learning and information aggregation in networks" by Douglas Gale and Shachar Kariv.
"mechanism design" by Roger B. Myerson.
"revelation principle" by Roger B. Myerson.
"monetary business cycles (imperfect information)" by Christian Hellwig.
"prediction markets" by Justin Wolfers and Eric Zitzewitz.
"social networks in labour markets" by Antoni Calvó-Armengol and Yannis M. Ioannides.
"strategic and extensive form games" by Martin J. Osborne.
on
Labels: , ,

No comments:

Post a Comment

Subscribe to: Post Comments (Atom)