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The More You Know? – Consumption Behavior and the Communication of Economic Information

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  • Jeannette Brosig-Koch
  • Klemens Keldenich

    ()

Abstract

This paper uses a laboratory experiment to analyze the impact of different types of information on consumption and savings behavior. Based on a buffer stock savings model, three treatment dimensions are used: The amount of information subjects receive about the likelihood of income shocks, whether subjects are informed about other people's beliefs about these shocks, and the framing of shocks. The results reveal that – even with little information about the random term determining the income shock – consumption decisions are surprisingly close to the optimal consumption path. If at all, more information rather worsens than improves consumption behavior. Nevertheless, in line with the theoretical prediction, observed behavior is robust to the framing and other people's beliefs about income shocks. Given that actual decisions are significantly correlated with the optimal consumption amount (and not with easier accessible variables like cash-on-hand) suggests that subjects do not simply use naive heuristics to determine their consumption.

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Bibliographic Info

Paper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen in its series Ruhr Economic Papers with number 0387.

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Length: 29 pages
Date of creation: Dec 2012
Date of revision:
Handle: RePEc:rwi:repape:0387

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Keywords: Consumption; framing; beliefs;

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  1. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer, vol. 10(2), pages 171-178, June.
  2. Christopher D. Carroll, 1996. "Buffer-Stock Saving and the Life Cycle/Permanent Income Hypothesis," NBER Working Papers 5788, National Bureau of Economic Research, Inc.
  3. Daniel Schunk, 2009. "What Determines Household Saving Behavior? An Examination of Saving Motives and Saving Decisions," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 229(4), pages 467-491, August.
  4. Alexander L. Brown & Zhikang Eric Chua & Colin F. Camerer, 2009. "Learning and Visceral Temptation in Dynamic Saving Experiments-super-," The Quarterly Journal of Economics, MIT Press, vol. 124(1), pages 197-231, February.
  5. Stephen Zeldes, . "Optimal Consumption with Stochastic Income: Deviations from Certainty Equivalence," Rodney L. White Center for Financial Research Working Papers 20-86, Wharton School Rodney L. White Center for Financial Research.
  6. Christopher D. Carroll, 2001. "A Theory of the Consumption Function, With and Without Liquidity Constraints (Expanded Version)," NBER Working Papers 8387, National Bureau of Economic Research, Inc.
  7. Martin Browning & Annamaria Lusardi, 1996. "Household Saving: Micro Theories and Micro Facts," Journal of Economic Literature, American Economic Association, vol. 34(4), pages 1797-1855, December.
  8. Maciejovsky, B. & Kirchler, E., 2001. "Simultaneous Over-and Underconfidence: Evidence from Experimental Aseet Markets," Papers 185, Flinders of South Australia - Discipline of Economics.
  9. Deaton, Angus, 1992. "Understanding Consumption," OUP Catalogue, Oxford University Press, number 9780198288244, October.
  10. Hey, John D & Dardanoni, Valentino, 1987. "Optimal Consumption under Uncertainty: An Experimental Investigation," Economic Journal, Royal Economic Society, vol. 98(390), pages 105-16, Supplemen.
  11. Enrica Carbone & John D. Hey, 2004. "The effect of unemployment on consumption: an experimental analysis," Economic Journal, Royal Economic Society, vol. 114(497), pages 660-683, 07.
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