IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/14396.html
   My bibliography  Save this paper

Partial Prescriptions For Decisions With Partial Knowledge

Author

Listed:
  • Charles F. Manski

Abstract

This paper concerns the prescriptive function of decision analysis. I suppose that an agent must choose an action yielding welfare that varies with the state of nature. The agent has a welfare function and beliefs, but he does not know the actual state of nature. It is often argued that such an agent should adhere to consistency axioms which imply that behavior can be represented as maximization of expected utility. However, our agent is not concerned the consistency of his behavior across hypothetical choice sets. He only wants to make a reasonable choice from the choice set that he actually faces. Hence, I reason that prescriptions for decision making should respect actuality. That is, they should promote welfare maximization in the choice problem the agent actually faces. I conclude that any decision rule respecting weak and stochastic dominance should be considered rational. Expected utility maximization respects dominance, but it has no special status from the actualist perspective. Moreover, the basic consistency axiom of transitivity has a clear normative foundation only when actions are ordered by dominance.

Suggested Citation

  • Charles F. Manski, 2008. "Partial Prescriptions For Decisions With Partial Knowledge," NBER Working Papers 14396, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:14396
    Note: PE TWP
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w14396.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manski, Charles F., 1986. "Ordinal Utility Models Of Decision Making Under Uncertainty," SSRI Workshop Series 292682, University of Wisconsin-Madison, Social Systems Research Institute.
    2. Lawrence Blume & Adam Brandenburger & Eddie Dekel, 2014. "Lexicographic Probabilities and Choice Under Uncertainty," World Scientific Book Chapters, in: The Language of Game Theory Putting Epistemics into the Mathematics of Games, chapter 6, pages 137-160, World Scientific Publishing Co. Pte. Ltd..
    3. Sen, Amartya K, 1973. "Behaviour and the Concept of Preference," Economica, London School of Economics and Political Science, vol. 40(159), pages 241-259, August.
    4. Charles F. Manski, 2006. "Search Profiling With Partial Knowledge of Deterrence," Economic Journal, Royal Economic Society, vol. 116(515), pages 385-401, November.
    5. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    6. G. Hanoch & H. Levy, 1969. "The Efficiency Analysis of Choices Involving Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 36(3), pages 335-346.
    7. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    8. Levy, Haim & Kroll, Yoram, 1978. "Ordering Uncertain Options with Borrowing and Lending," Journal of Finance, American Finance Association, vol. 33(2), pages 553-574, May.
    9. Charles F. Manski, 2008. "Adaptive partial policy innovation: coping with ambiguity through diversification," CeMMAP working papers CWP10/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Besanko, David & Tong, Jian & Wu, Jianjun, 2016. "Dynamic game under ambiguity: the sequential bargaining example, and a new "coase conjecture"," Discussion Paper Series In Economics And Econometrics 1606, Economics Division, School of Social Sciences, University of Southampton.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charles Manski, 2011. "Actualist rationality," Theory and Decision, Springer, vol. 71(2), pages 195-210, August.
    2. Charles F. Manski & Aleksey Tetenov, 2023. "Statistical decision theory respecting stochastic dominance," The Japanese Economic Review, Springer, vol. 74(4), pages 447-469, October.
    3. Manski, Charles F., 2013. "Public Policy in an Uncertain World: Analysis and Decisions," Economics Books, Harvard University Press, number 9780674066892, Spring.
    4. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    5. Joseph Aharony & Sasson Bar†Yosef, 1987. "Tests of the impact of LIFO adoption on stockholders: A stochastic dominance approach," Contemporary Accounting Research, John Wiley & Sons, vol. 3(2), pages 430-444, March.
    6. Pamela Giustinelli & Charles F. Manski, 2018. "Survey Measures Of Family Decision Processes For Econometric Analysis Of Schooling Decisions," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 81-99, January.
    7. Klaus Nehring, 2006. "Decision-Making in the Context of Imprecise Probabilistic Beliefs," Economics Working Papers 0034, Institute for Advanced Study, School of Social Science.
    8. Dai, Zhixin & Hogarth, Robin M. & Villeval, Marie Claire, 2015. "Ambiguity on audits and cooperation in a public goods game," European Economic Review, Elsevier, vol. 74(C), pages 146-162.
    9. Robison, Lindon J. & Shupp, Robert S. & Myers, Robert J., 2010. "Expected utility paradoxes," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(2), pages 187-193, April.
    10. Grant, Simon & Quiggin, John, 2005. "Increasing uncertainty: a definition," Mathematical Social Sciences, Elsevier, vol. 49(2), pages 117-141, March.
    11. A. Ludwig & A. Zimper, 2013. "A parsimonious model of subjective life expectancy," Theory and Decision, Springer, vol. 75(4), pages 519-541, October.
    12. Lo, Kin Chung, 2009. "Correlated Nash equilibrium," Journal of Economic Theory, Elsevier, vol. 144(2), pages 722-743, March.
    13. Kin Chung Lo, 1998. "Epistemic Conditions for Agreement and Stochastic Independence of epsilon-Contaminated Beliefs," Working Papers 1998_02, York University, Department of Economics.
    14. Wang, Ming-Hui & Ke, Mei-Chu & Liang Liao, Tung & Chiang, Yi-Chein & Hsu, Chuan-Hao, 2020. "Alternative estimation method of earnings growth rate for PEGR strategy," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    15. Eichberger, Jurgen & Kelsey, David, 2000. "Non-Additive Beliefs and Strategic Equilibria," Games and Economic Behavior, Elsevier, vol. 30(2), pages 183-215, February.
    16. Fisher, Gordon & Willson, Douglas & Xu, Kuan, 1998. "An empirical analysis of term premiums using significance tests for stochastic dominance," Economics Letters, Elsevier, vol. 60(2), pages 195-203, August.
    17. Eddie Dekel & Barton L. Lipman, 2010. "How (Not) to Do Decision Theory," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 257-282, September.
    18. Lo, Kin Chung, 2000. "Epistemic conditions for agreement and stochastic independence of [epsi]-contaminated beliefs," Mathematical Social Sciences, Elsevier, vol. 39(2), pages 207-234, March.
    19. Yi-Chein Chiang & Mei-Chu Ke & Tung Liang Liao & Cin-Dian Wang, 2012. "Are technical trading strategies still profitable? Evidence from the Taiwan Stock Index Futures Market," Applied Financial Economics, Taylor & Francis Journals, vol. 22(12), pages 955-965, June.
    20. Guiso, Luigi & Sodini, Paolo, 2013. "Household Finance: An Emerging Field," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1397-1532, Elsevier.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:14396. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.