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The Effect of Credit on Spending Decisions: The Role of the Credit Limit and Credibility


  • Dilip Soman

    () (Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong)

  • Amar Cheema

    () (University of Colorado at Boulder, Boulder, CO 80309)


The objective of the present research is to study consumer decisions to utilize a line of credit. The life-cycle hypothesis from economics argues that consumers should intertemporally reallocate their incomes over their life stream to maximize lifetime utility. One form of intertemporal allocation is to use past income (in the form of savings) in the future. A second form is the use of future income in the present. This can only be done if consumers have access to a temporary pool of money that they can draw from and replenish in the future—a function performed by consumer credit. However, our research reinforces prior findings that consumers are unable to correctly value their future incomes, and that they lack the cognitive capability to solve the intertemporal optimization problem required by the life-cycle hypothesis. Instead, we argue that consumers use information such as the credit limit as a signal of their future earnings potential. Specifically, if consumers have access to large amounts of credit, they are likely to infer that their lifetime income will be high and hence their willingness to use credit (and their spending) will also be high. Conversely, consumers who are granted lower amounts of credit are likely to infer that their lifetime income will be low and hence their spending will be lower. However, based on research in the area of consumer skepticism and inference making, we also argue for a moderating role of the credibility associated with the credit limit. Specifically, we argue that the above effect of credit availability would be particularly strong for consumers who believe that the credit limit credibly signals their future earnings potential (i.e., a naïve consumer who has limited experience with consumer credit). However, as consumers gain experience with credit, they start discounting credit availability as a predictor of their future and start questioning the validity of the process used to set the credit limit. Hence, with experience the effect of credit limit on the willingness to use credit should be attenuated. We test these predictions in five separate studies. In the first experimental study, we manipulate credit limit and credibility and pose subjects with a hypothetical purchase opportunity. Consistent with our prediction, credit limit impacted the propensity to spend, but only when the credibility was high. In the second experimental study, we replicate these findings even when subjects were given information about their expected future salaries, and also show that the credit limit influences their expectation of future earnings potential. In the third study, we show that the mere availability (and increase) of current liquidity cannot explain our findings. In the fourth study, we conduct a survey of consumers in which we measure a number of demographic characteristics and also ask them for their propensity to spend in a given purchase situation. In the fifth study we use the Survey of Consumer Finances (SCF) dataset, a triennial survey of U.S. families that is designed to provide detailed information on the use of financial services, spending behaviors, and selected demographic characteristics. Results from both studies 4 and 5 provide further support for our proposed framework—credit limits influence spending to a greater extent for consumers with lower credibility: younger consumers and less-educated consumers. Across all studies we achieved triangulation by using a variety of approaches (surveys and experiments), subjects types (young students and older consumers), nature of predictor variables (manipulated and measured), dependent measures (purchase likelihood, credit card balance, new charges), and methods of analysis (ANOVA and regression), and consistently found that increasing credit limits on a credit card increases spending, especially when the credibility of the limit is high. This paper joins a growing body of literature in marketing and behavioral decision theory that goes beyond the traditional domains of inquiry (e.g., product choice, effects of marketing mix variables) and focuses on consumer decisions relating to the appropriate use of income to finance consumption. Our framework differs from prior research on the effect of payment mechanisms on spending in two significant ways. First, we are interested in the effects of the availability of credit on spending, and not necessarily in the effect of the transaction format that is associated with each payment mechanism. Second, while prior research has studied the point-of-purchase and historic (i.e., prepurchase) effects of credit, the present research is concerned with the availability of credit in the future. Specifically, our framework is invariant to the current and prior usage of credit by the consumer.

Suggested Citation

  • Dilip Soman & Amar Cheema, 2002. "The Effect of Credit on Spending Decisions: The Role of the Credit Limit and Credibility," Marketing Science, INFORMS, vol. 21(1), pages 32-53, September.
  • Handle: RePEc:inm:ormksc:v:21:y:2002:i:1:p:32-53

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    References listed on IDEAS

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    Cited by:

    1. Ranyard, Rob & Hinkley, Lisa & Williamson, Janis & McHugh, Sandie, 2006. "The role of mental accounting in consumer credit decision processes," Journal of Economic Psychology, Elsevier, vol. 27(4), pages 571-588, August.
    2. Carol C. Bertaut & Michael Haliassos, 2001. "Debt Revolvers for Self Control," University of Cyprus Working Papers in Economics 0208, University of Cyprus Department of Economics.
    3. Jonathan K. Budd & Peter G. Taylor, 2015. "Calculating optimal limits for transacting credit card customers," Papers 1506.05376,, revised Aug 2015.
    4. Cliff Robb, 2011. "Financial Knowledge and Credit Card Behavior of College Students," Journal of Family and Economic Issues, Springer, vol. 32(4), pages 690-698, December.
    5. repec:taf:applec:v:49:y:2017:i:24:p:2365-2378 is not listed on IDEAS
    6. Lonnie Turpin & Matiur Rahman & Alberto Marquez, 2016. "Optimization over a collection of decision trees with three-valued outcomes," Economics Bulletin, AccessEcon, vol. 36(4), pages 1959-1965.
    7. Till Treeck, 2014. "Did Inequality Cause The U.S. Financial Crisis?," Journal of Economic Surveys, Wiley Blackwell, vol. 28(3), pages 421-448, July.
    8. Markus Christen & Ruskin Morgan, 2005. "Keeping Up With the Joneses: Analyzing the Effect of Income Inequality on Consumer Borrowing," Quantitative Marketing and Economics (QME), Springer, vol. 3(2), pages 145-173, June.
    9. So, Meko M.C. & Thomas, Lyn C., 2011. "Modelling the profitability of credit cards by Markov decision processes," European Journal of Operational Research, Elsevier, vol. 212(1), pages 123-130, July.
    10. Nofsinger, John R., 2012. "Household behavior and boom/bust cycles," Journal of Financial Stability, Elsevier, vol. 8(3), pages 161-173.
    11. Till van Treeck, 2012. "Did inequality cause the U.S. financial crisis?," IMK Working Paper 91-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    12. Miotto, Ana Paula S. C. & Parente, Juracy, 2015. "Antecedentes e consequências do gerenciamento das finanças domésticas na classe média baixa brasileira," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 55(1), January.
    13. Margaret S. Trench & Shane P. Pederson & Edward T. Lau & Lizhi Ma & Hui Wang & Suresh K. Nair, 2003. "Managing Credit Lines and Prices for Bank One Credit Cards," Interfaces, INFORMS, vol. 33(5), pages 4-21, October.
    14. Hoelzl, Erik & Kamleitner, Bernadette & Kirchler, Erich, 2011. "Loan repayment plans as sequences of instalments," Journal of Economic Psychology, Elsevier, vol. 32(4), pages 621-631, August.
    15. Xinhua Gu & Bihong Huang & Pui Sun Tam & Yang Zhang, 2015. "Inequality and Saving: Further Evidence from Integrated Economies," Review of Development Economics, Wiley Blackwell, vol. 19(1), pages 15-30, February.
    16. Guglielmo Forges Davanzati & Andrea Pacella, 2010. "Emulation, indebtedness and income distribution: A monetary theory of production approach," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 7(1), pages 147-165.
    17. van Treeck, Till. & Sturn, Simon., 2012. "Income inequality as a cause of the Great Recession? : A survey of current debates," ILO Working Papers 994709343402676, International Labour Organization.
    18. Bertaut, Carol C. & Haliassos, Michael, 2005. "Credit cards: Facts and theories," CFS Working Paper Series 2006/19, Center for Financial Studies (CFS).
    19. Samuel Sekyi, 2017. "Rural Households’ Credit Access and Loan Amount in Wa Municipality, Ghana," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 506-514.
    20. repec:bla:apacel:v:32:y:2018:i:1:p:131-138 is not listed on IDEAS
    21. Bouyon, Sylvain, 2015. "Towards a Balanced Contribution of Household Credit to the Economy," ECRI Papers 10554, Centre for European Policy Studies.
    22. repec:jso:coejbm:v:6:y:2018:i:1:p:66-83 is not listed on IDEAS
    23. repec:eee:ijrema:v:33:y:2016:i:1:p:123-139 is not listed on IDEAS


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