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Principle of uncertain future and utility

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Author Info
Harin, Alexander

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Abstract

The principle of uncertain future: the probability of a future event contains a degree of (hidden) uncertainty. As a result, this uncertainty (in a sense, similar to vibrations, fluctuations) pushes the probability value back from the bounds to the middle of its range (from ~100% and ~0% to the middle probability values). In other words, the real values of high probabilities are lower than the preliminarily determined ones. Conversely, the real values of low probabilities are higher than the preliminarily determined ones. This result provides the uniform solution of a number of fundamental problems: the underweighting of high and the overweighting of low probabilities, the Allais paradox, risk aversion, loss aversion, the Ellsberg paradox, the equity premium puzzle, etc. The principle and its consequences can be applied in the fields of banking, investment, insurance, trade, industry, planning and forecasting. Explanations of the principle and examples of solution of three types of basic utility problems are provided.

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File URL: http://mpra.ub.uni-muenchen.de/1959/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1959.

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Date of creation: 28 Feb 2007
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Handle: RePEc:pra:mprapa:1959

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Related research
Keywords: risk market banking industry development investments insurance hidden causes

Other versions of this item:

Find related papers by JEL classification:
D8 - Microeconomics - - Information, Knowledge, and Uncertainty
A1 - General Economics and Teaching - - General Economics
E22 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Capital; Investment; Capacity
G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies
C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

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  1. Hey, John D & Orme, Chris, 1994. "Investigating Generalizations of Expected Utility Theory Using Experimental Data," Econometrica, Econometric Society, vol. 62(6), pages 1291-1326, November. [Downloadable!] (restricted)
  2. Kenneth Y. Chay & Patrick J. McEwan & Miguel Urquiola, 2003. "The Central Role of Noise in Evaluating Interventions that Use Test Scores to Rank Schools," NBER Working Papers 10118, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Schoemaker, Paul J H, 1982. "The Expected Utility Model: Its Variants, Purposes, Evidence and Limitations," Journal of Economic Literature, American Economic Association, vol. 20(2), pages 529-63, June. [Downloadable!] (restricted)
  4. Tversky, Amos & Wakker, Peter, 1995. "Risk Attitudes and Decision Weights," Econometrica, Econometric Society, vol. 63(6), pages 1255-80, November. [Downloadable!] (restricted)
  5. John Quiggin, 2005. "The precautionary principle in environmental policy and the theory of choice under uncertainty," Murray-Darling Program Working Papers WPM05_3, Risk and Sustainable Management Group, University of Queensland. [Downloadable!]
  6. Carmela Di Mauro & Anna Maffioletti, 2004. "Attitudes to risk and attitudes to uncertainty: experimental evidence," Applied Economics, Taylor and Francis Journals, vol. 36(4), pages 357-372, March. [Downloadable!] (restricted)
  7. Capuano, Christian, 2006. "Strategic noise traders and liquidity pressure with a physically deliverable futures contract," International Review of Economics & Finance, Elsevier, vol. 15(1), pages 1-14. [Downloadable!] (restricted)
  8. Helga Fehr-Duda & Marc Schürer & Renate Schubert, 2006. "What Determines the Shape of the Probability Weighting Function?," Economics working paper series 06/54, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich. [Downloadable!]
  9. John Quiggin & Robert G. Chambers, 2005. "Economists and uncertainty," Risk & Uncertainty Working Papers WP2R05, Risk and Sustainable Management Group, University of Queensland. [Downloadable!]
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