Asymmetric Information and Ranked Information Are Equivalent in Making Information Utilization Heterogeneous

Article DOI: https://doi.org/10.57017/jaes.v17.3(77).07

Author(s):

Taiji HARASHIMA Department of Economics, Kanazawa Seiryo University, Japan

Abstract:

In information economics, any piece of information is assumed to have the same value across people, even if the information is distributed asymmetrically. However, in actuality, information has different values across people, even if it is distributed equally, because people utilize the same information differently and reach different conclusions with it. In this paper, I construct a model of heterogeneous information utilization by introducing the concept of ranked information. I conclude that the effects of asymmetric information and ranked information on economic activities are essentially equivalent. However, there are still some differences between them, and ranked information will be more economically important than asymmetric information. Furthermore, ranked information can cause an extreme economic inequality.

How to cite:

Harashima, T. (2022). Asymmetric Information and Ranked Information Are Equivalent in Making Information Utilization Heterogeneous. Journal of Applied Economic Sciences, Volume XVI, Fall, 3(77), 250 – 261. https://doi.org/10.57017/jaes.v17.3(77).07

References:

[1] Becker, R. A. (1980). On the Long-run Steady State in a Simple Dynamic Model of Equilibrium with Heterogeneous Households. The Quarterly Journal of Economics, 95, 2, 375–382. https://doi.org/10.2307/1885506

[2] Cattell, R. B. (1963). Theory of Fluid and Crystallized Intelligence: A Critical Experiment. Journal of Educational Psychology, 54, 1-22. https://doi.org/10.1037/h0046743

[3] Cattell, R. B. (1971). Abilities: Their Structure, Growth, and Action, Houghton Mifflin, Boston.

[4] Chiriță, P-Al., Diederich, J., & Nejdl, W. (2005). MailRank: Using Ranking for Spam Detection, Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 373–380. https://doi.org/10.1145/1099554.1099671

[5] Collins, M. (2002). Ranking Algorithms for Named-entity Extraction: Boosting and the Voted Perceptron, in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, pp. 7. https://doi.org/10.3115/1073083.1073165

[6] Edlin, A. & Stiglitz, J.E. (1995). Discouraging Rivals: Managerial Rent-Seeking and Economic Inefficiencies. American Economic Review, 85 (5). 1301-1312. https://doi.org/10.7916/D8JW8QVW

[7] Greenwald, B. C. & Stiglitz, J.E. (1986). Externalities in Economies with Imperfect Information and Incomplete Markets. The Quarterly Journal of Economics, 101(2), 229-264. https://doi.org/10.2307/1891114

[8] Grossman, Sanford J. & Joseph E. Stiglitz (1980). On the Impossibility of Informationally Efficient Markets. American Economic Review, 70(3), 393–408. https://doi.org/10.7916/D8765R99

[9] Harashima, T. (2009). A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element, MPRA (Munich Personal RePEc Archive) Paper No. 15508.

[10] Harashima, T. (2010). Sustainable Heterogeneity: Inequality, Growth, and Social Welfare in a Heterogeneous Population, MPRA (Munich Personal RePEc Archive) Paper No. 24233.

[11] Harashima, T. (2012a). Sustainable Heterogeneity as the Unique Socially Optimal Allocation for Almost All Social Welfare Functions. MPRA (Munich Personal RePEc Archive) Paper No. 40938.

[12] Harashima, T. (2012b). A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence. MPRA (Munich Personal RePEc Archive) Paper No. 43151.

[13] Harashima, T. (2016). A Theory of Total Factor Productivity and the Convergence Hypothesis: Workers’ Innovations as an Essential Element, in Japanese. Journal of Kanazawa Seiryo University, 50(1), 55–80.

[14] Harashima, T. (2017). Sustainable Heterogeneity: Inequality, Growth, and Social Welfare in a Heterogeneous Population, in Japanese. Journal of Kanazawa Seiryo University, 51(1), 31–80.

[15] Harashima, T. (2020a). Sustainable Heterogeneity as the Unique Socially Optimal Allocation for Almost All Social Welfare Functions, in Japanese. Journal of Kanazawa Seiryo University, 54(1), 71–95.

[16] Harashima, T. (2020b). A Theory of Intelligence and Total Factor Productivity: Value Added Reflects the Fruits of Fluid Intelligence, in Japanese, Journal of Kanazawa Seiryo University, 53(2), 65–82.

[17] Harashima, T. (2020c). Economic Inequality Exacerbated by Economic Rents from Exploitative Contracting. MPRA (Munich Personal RePEc Archive) Paper No. 104178.

[18] Harashima, T. (2020d) Preventing Widening Inequality: Economic Rents and Sustainable Heterogeneity. MPRA (Munich Personal RePEc Archive) Paper No. 103377.

[19] Harashima, T. (2021a). Preventing Widening Inequality: Economic Rents and Sustainable Heterogeneity, in Japanese. Journal of Kanazawa Seiryo University, 55(1): 17–37.

[20] Harashima, T. (2021b). Economic Inequality and Heterogeneous Success Rates of Investment. MPRA (Munich Personal RePEc Archive) Paper No. 110688.

[21] Harrington, E. F. (2003). Online Ranking/Collaborative Filtering Using the Perceptron Algorithm, Proceedings of the Twentieth International Conference on Machine Learning, Washington DC.

[22] Lord, Frederic M. & Melvin R. Novick. (1968). Statistical Theories of Mental Test Scores, Addison-Wesley, Reading, MA.

[23] Raven, J. C. (1962). Advanced Progressive Matrices: Sets I and II, H. K. Lewis, London.

[24] Raven, J. C., & Court, J. H. (1998). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Section 1: General Overview. Harcourt Assessment, San Antonio, TX.

[25] Stiglitz, J. E. (2002). Information and the Change in the Paradigm in Economics, abbreviated version of Nobel Lecture. American Economic Review, 92(3), 460-501. DOI: 10.1257/00028280260136363

[26] Stiglitz, Joseph E. (2017). The Revolution of Information Economics: The Past and the Future. NBER Working Papers, No. 23780.

[27] Snow, R.E., Kyllonen, P.C. & Marshalek. B. (1984). The Topography of Ability and Learning Correlations, in Sternberg, R. J. (Ed.) Advances in the Psychology of Human Intelligence Volume 2, Erlbaum, Hillsdale, NJ.

[28] van der Linden, Wim J. & Hambleton, R.K. (Eds.) (1997). Handbook of Modern Item Response Theory, Springer-Verlag, New York.