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Saving for a rainy day – and managing other unexpected shocks

by Dilek Önkal, Wasim Ahmed & Shari de Baets
Posted on May 14, 2019

Many households lack the necessary savings to deal with unexpected shocks like a car breaking down or losing a job.1 As a consequence, many people suffer from economic insecurity, risking future economic problems. So why do we find it so difficult – nearly impossible – to save for a rainy day? As previous research has shown, human beings have a number of biases or reasoning errors that influence our financial decision making, and not in a good way.

First of all, we are more oriented towards the present rather than the future2: when given a choice between receiving £50 now, or £100 in a year’s time, most of us will pick the immediate reward of £50. Secondly, people suffer from an optimism bias: we believe the future will be better than the past. We tend to ignore negative signals3, focusing instead on the positive signals. Lastly, we underestimate both a future rise in expenses (compared to rise in income) and the risk of unexpected costs in the near future (compared to expenses we had to bear in the near past).4

Whilst people can recall expenses made in the past, when asked to predict how much they’ll be spending in the future, such expenses are heavily underestimated. Despite the experienced frequency of similar expenses in the past, they are incorrectly classified as ‘unusual events’ (hence unlikely to occur in the future).

“First, we need to understand the processes behind expenses, savings plans and projections”

When a water pipe cracks…

Our research team would love to discover how people get better at predicting their future expenses, so we know how to actually help them to save more. In order to increase people’s financial well-being, the first step is to understand the processes behind expenses, savings plans and projections. We understand the reasoning errors that people tend to make, but it isn’t yet clear how increased awareness of unexpected shocks plays into this process. Can people be stimulated towards making more prudent estimates by providing information on likely-to-occur financial risk scenarios?

In our study, we ask our participants – an adult sample collected online via Prolific Academic, a crowd sourcing website for academic research – how much they think they’ll be spending during the next three months. Expenses and savings are broken down into various categories. We then focus on a common financial shock: a cracked water pipe. We inform them that…

  • … the costs for fixing the pipe will amount to 80% of their monthly income; OR
  • … the costs for fixing the pipe will amount to only 20% of their monthly income; OR
  • … the costs for fixing the pipe are completely covered by their insurance.

Participants randomly receive one of the three scenarios. After reading it, they have the opportunity to adjust their initial forecasts.

Many interesting questions arise. How will people react to the scenarios above? Will the second scenario affect any estimates? In the luckiest group (insurance to the rescue), will people see their luck as something positive, and perhaps adjust their predictions accordingly? How strongly will people react, compared across all three groups? Will there be large differences between individuals, and are these perhaps related to financial knowledge, or their current state of financial well-being?


Coming up next: an app

The knowledge that we gain from analysing our experiment will be crucial to design our financial awareness and planning app. We hope to empower a wide audience to better forecast expenses and plan for future savings. Our app would help alleviate the mental strain associated with these decisions.5

Are you interested in learning more about this project and regularly reading tips and tricks on expenses and savings? Follow these researchers on Twitter and Facebook


1 Grinstein-Weiss, M., Russell, B. D., Gale, W. G., Key, C. & Ariely, D. (2017) Behavioral Interventions to Increase Tax-Time Saving: Evidence from a National Randomized Trial. The Journal of Consumer Affairs, Spring, 3-26.

2 Ainslie, G. (1992) Picoeconomics. Cambridge: Cambridge University Press, Angeletos, G.-M., Laibson, D., Repetto, A., Tobacman, J. & Weinberg, S. (2001) The Hyperbolic Consumption Model: Calibration, Simulation, and Empirical Evaluation. Journal of Economic Perspectives, 15(47-68), O'Donoghue, T. & Rabin, M. M. (1999) Doing it now or later. American Economic Review, 89(1), 103-124. & Frederick, S., Loewenstein, G. & O'Donoghue, T. (2002) Time Discounting and Time Preference: A Critical Review. Journal of Economic Literature, 40(2), 351-401, Tam, L. & Dholakia, U. M. (2011) Delay and duration effects of time frames on personal savings estimates and behavior. Organizational Behavior & Human Decision Processes, 114, 142-152.

3 Weinstein, N. D. & Klein, W. M. (1996) Unrealistic Optimism: Present and Future. Journal of Social and Clinical Psychology, 15(1), 1-8. & Newby-Clark, I. R., Ross, M., Buehler, R., Koehler, D. J. & Griffin, D. (2000) People focus on optimistic scenarios and disregard pessimistic scenarios while predicting task completion times. Journal of Experimental Psychology: Applied, 6(3), 171-182.

4 Howard, C., Hardisty, D., Sussman, A. & Knoll, M. (2016) Understanding the Expense Prediction Bias", in Moreau, P. & Puntoni, S. (eds), Advances in Consumer Research. Duluth, MN: Association for Consumer Research, 190-194.

5 Ratner, R. K., Soman, D., Zauberman, G., Ariely, D., Carmon, Z., Keller, P. A., ... & Wertenbroch, K. (2008). How behavioral decision research can enhance consumer welfare: From freedom of choice to paternalistic intervention. Marketing Letters, 19(3-4), 383.