Advertisement

Experimental Economics

, Volume 14, Issue 3, pp 349–374 | Cite as

Saving behavior and cognitive abilities

  • T. Parker Ballinger
  • Eric Hudson
  • Leonie Karkoviata
  • Nathaniel T. WilcoxEmail author
Article

Abstract

Experiments on saving behavior reveal substantial heterogeneity of behavior and performance. We show that this heterogeneity is reliable and examine several potential sources of it, including cognitive ability and personality scales. The strongest predictors of both behavior and performance are two cognitive ability measures. We conclude that complete explanations of heterogeneity in dynamic decision making require attention to complexity and individual differences in cognitive constraints.

Keywords

Bounded rationality Heterogeneity Cognitive abilities Consumption and saving 

JEL Classification

C91 D91 E21 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

10683_2010_9271_MOESM1_ESM.pdf (215 kb)
(PDF 216 KB)

References

  1. Ballinger, T. P., Palumbo, M. G., & Wilcox, N. T. (2003). Precautionary saving and social learning across generations: An experiment. Economic Journal, 113, 920–947. CrossRefGoogle Scholar
  2. Beach, L. R., & Mitchell, T. R. (1978). A contingency model for the selection of decision strategies. Academy of Management Review, 3, 439–449. Google Scholar
  3. Benjamin, D. J., Brown, S. A., & Shapiro, J. M. (2006). Who is “behavioral”? Cognitive ability and anomalous preferences. Harvard University working paper. Google Scholar
  4. Brown, A. L., Chua, Z. E., & Camerer, C. F. (2009). Learning and visceral temptation in dynamic saving experiments. Quarterly Journal of Economics, 124, 197–231. CrossRefGoogle Scholar
  5. Browning, M., & Lusardi, A. (1996). Household saving: Micro theories and micro facts. Journal of Economic Literature, 34, 1797–1855. Google Scholar
  6. Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive motivation: the life and times of individuals varying in need for cognition. Psychological Bulletin, 119(2), 197–253. CrossRefGoogle Scholar
  7. Camerer, C. F., & Hogarth, R. M. (1999). The effects of financial incentives in experiments: a review and capital-labor-production framework. Journal of Risk and Uncertainty, 19(1–3), 7–42. CrossRefGoogle Scholar
  8. Camerer, C. F., Ho, T.-H., & Chong, K. (2004). A cognitive hierarchy model of behavior in games. Quarterly Journal of Economics, 119(3), 861–898. CrossRefGoogle Scholar
  9. Campbell, J. Y., & Mankiw, N. G. (1990). Permanent income, current income and consumption. Journal of Business and Economic Statistics, 8, 265–279. CrossRefGoogle Scholar
  10. Carbone, E. (2006). Understanding intertemporal choices. Applied Economics, 38, 889–898. CrossRefGoogle Scholar
  11. Carbone, E., & Hey, J. D. (2004). The effect of unemployment on consumption: an experimental analysis. Economic Journal, 114, 660–683. CrossRefGoogle Scholar
  12. Carroll, J. B. (1993). Human cognitive abilities: a survey of factor-analytic studies. Cambridge: Cambridge University Press. CrossRefGoogle Scholar
  13. Conlisk, J. (1980). Costly optimization versus cheap imitators. Journal of Economic Behavior and Organization, 1, 275–293. CrossRefGoogle Scholar
  14. Conlisk, J. (1996). Why bounded rationality? Journal of Economic Literature, 34, 669–700. Google Scholar
  15. Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: a methodological review and user’s guide. Psychonomic Bulletin and Review, 12, 769–786. CrossRefGoogle Scholar
  16. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. CrossRefGoogle Scholar
  17. Deaton, A. S. (1992). Understanding consumption. London: Oxford University Press. CrossRefGoogle Scholar
  18. Dyer, D., & Kagel, J. H. (1996). Bidding in common value auctions: how the commercial construction industry corrects for the winner’s curse. Management Science, 42, 1463–1475. CrossRefGoogle Scholar
  19. Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11, 19–23. CrossRefGoogle Scholar
  20. Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. In B. Ross (Ed.), The psychology of learning and motivation (Vol. 44, pp. 145–199). Amsterdam: Elsevier. Google Scholar
  21. Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999). Working memory, short-term memory, and general fluid intelligence: a latent variable approach. Journal of Experimental Psychology: General, 128, 309–331. CrossRefGoogle Scholar
  22. Feldman-Barrett, L., Tugade, M. M., & Engle, R. W. (2004). Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin, 130, 553–573. CrossRefGoogle Scholar
  23. Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19, 25–42. CrossRefGoogle Scholar
  24. Gabaix, X., & Laibson, D. (2000). A boundedly rational decision algorithm. American Economic Review, 90, 433–438. CrossRefGoogle Scholar
  25. Hall, R. E., & Mishkin, F. S. (1982). The sensitivity of consumption to transitory income: estimates from panel data on households. Econometrica, 50, 461–481. CrossRefGoogle Scholar
  26. Harrison, G. (1989). Theory and misbehavior of first-price auctions. American Economic Review, 79, 749–762. Google Scholar
  27. Harrison, G., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. CrossRefGoogle Scholar
  28. Hey, J., & Dardanoni, V. (1988). Optimal consumption under uncertainty: an experimental investigation. Economic Journal, 98(390), 105–116 (supplement). CrossRefGoogle Scholar
  29. Hogarth, R. (1975). Decision time as a function of task complexity. In D. Wendt & C. Vlek (Eds.), Utility, probability and human decision making (pp. 321–338). Dordrecht: Reidel. Google Scholar
  30. Hunt, E. (1999). Intelligence and human resources: past, present and future. In P. L. Ackerman, P. Kyllunon, & R. Roberts (Eds.), Learning and individual differences: process, trait and content determinants (pp. 3–30). Washington: American Psychological Association. CrossRefGoogle Scholar
  31. Kahneman, D., Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica, 47, 263–291. CrossRefGoogle Scholar
  32. Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: an individual-differences perspective. Psychonomic Bulletin and Review, 9, 637–671. CrossRefGoogle Scholar
  33. Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The generality of working-memory capacity: a latent-variable approach to verbal and visuo-spatial memory span and reasoning. Journal of Experimental Psychology: General, 133(2), 189–217. CrossRefGoogle Scholar
  34. Kellogg, C. E., & Morton, N. W. (1999). Beta III manual. San Antonio: The Psychological Corporation. Google Scholar
  35. McDaniel, T. M., & Rutström, E. E. (2001). Decision making costs and problem solving performance. Experimental Economics, 4, 145–161. Google Scholar
  36. Millner, E., & Pratt, M. (1992). A test of risk inducement: is inducement of risk-neutrality neutral? Virginia Commonwealth University Department of Economics working paper. Google Scholar
  37. Nagel, R. (1995). Unraveling in guessing games: an experimental study. American Economic Review, 85(5), 1313–1326. Google Scholar
  38. Nisbett, R. E., & Ross, L. D. (1980). Human inference: strategies and shortcomings of social judgment. Prentice-Hall: Englewood Cliffs. Google Scholar
  39. Payne, J., Bettman, J., & Johnson, E. (1988). Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory and Cognition, 14, 534–552. CrossRefGoogle Scholar
  40. Porteus, S. D. (1965). Porteus maze tests: fifty years’ application. Palo Alto: Pacific Book Publishers. Google Scholar
  41. Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Raven’s progressive matrices and vocabulary scales. San Antonio: The Psychological Corporation. Google Scholar
  42. Read, D., Loewenstein, G., & Rabin, M. (1999). Choice bracketing. Journal of Risk and Uncertainty, 19, 171–197. CrossRefGoogle Scholar
  43. Russo, J. E. (1978). Comments on behavioral and economic approaches to studying market behavior. In A. A. Mitchell (Ed.), The effect of information on consumer and market behavior (pp. 65–74). Chicago: American Marketing Association. Google Scholar
  44. Rydval, O., & Ortmann, A. (2004). How financial incentives and cognitive abilities affect task performance in laboratory settings: an illustration. Economics Letters, 85(3), 315–320. CrossRefGoogle Scholar
  45. Spearman, C. (1904). “General intelligence” objectively determined and measured. American Journal of Psychology, 15, 201–293. CrossRefGoogle Scholar
  46. Selten, R., Sadrieh, A., & Abbink, K. (1999). Money does not induce risk neutral behavior, but binary lotteries do even worse. Theory and Decision, 46, 211–249. CrossRefGoogle Scholar
  47. Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: an individual differences approach. Journal of Experimental Psychology: General, 125, 4–27. CrossRefGoogle Scholar
  48. Shah, P., & Miyake, A. (1999). Models of working memory: an introduction. In A. Miyake & P. Shah (Eds.), Models of working memory: mechanisms of active maintenance and executive control (pp. 1–26). Cambridge: Cambridge University Press. Google Scholar
  49. Smith, V. L. (1982). Microeconomic systems as an experimental science. American Economic Review, 72, 923–955. Google Scholar
  50. Stahl, D., & Wilson, P. (1995). On player’s models of other players: theory and experimental evidence. Games and Economic Behavior, 7, 218–254. CrossRefGoogle Scholar
  51. Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: implications for the rationality debate? Behavioral and Brain Sciences, 23, 645–665. CrossRefGoogle Scholar
  52. Thaler, R. H. (1994). Psychology and savings policies. American Economic Review, 84, 186–192. Google Scholar
  53. Tuckman, B. W. (1991). The development and concurrent validity of the procrastination scale. Educational and Psychological Measurement, 51, 473–480. CrossRefGoogle Scholar
  54. Turley-Ames, K. J., & Whitfield, M. M. (2003). Strategy training and working memory task performance. Journal of Memory and Language, 49, 446–468. CrossRefGoogle Scholar
  55. Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task-dependent? Journal of Memory and Language, 28, 127–154. CrossRefGoogle Scholar
  56. Wilcox, N. (1993a). Lottery choice: incentives, complexity and decision time. Economic Journal, 103, 1397–1417. CrossRefGoogle Scholar
  57. Wilcox, N. (1993b). On a lottery pricing anomaly: time tells the tale. Journal of Risk and Uncertainty, 7, 311–324. CrossRefGoogle Scholar
  58. Whiteside, S. P., & Lynam, D. R. (2001). The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30, 669–689. CrossRefGoogle Scholar
  59. Winkler, R. L., & Murphy, A. M. (1973). Experiments in the laboratory and the real world. Organizational Behavior and Human Performance, 20, 252–270. CrossRefGoogle Scholar

Copyright information

© Economic Science Association 2011

Authors and Affiliations

  • T. Parker Ballinger
    • 1
  • Eric Hudson
    • 2
  • Leonie Karkoviata
    • 3
  • Nathaniel T. Wilcox
    • 4
    Email author
  1. 1.Department of Economics and FinanceStephen F. Austin State UniversityNacogdochesUSA
  2. 2.New Mexico Public Defender DepartmentLas CrucesUSA
  3. 3.College of BusinessUniversity of Houston-DowntownHoustonUSA
  4. 4.Economic Science InstituteChapman UniversityOrangeUSA

Personalised recommendations