Procrastination and Impatience

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Presentation transcript:

Procrastination and Impatience Ernesto Reuben (Northwestern) Paola Sapienza (Northwestern) Luigi Zingales (Chicago)

Motivation Extensive literature on Impatience: Excessive credit card borrowing (Shui and Ausubel, 2004) Restrictions on savings withdrawals (Ashraf, Karlan, and Yin, 2006) Other: cutting credit cards, Christmas clubs, etc. Procrastination (Akerlof, 1991, O’Donoghue and Rabin, 1999, 2000) Canceling gym monthly subscriptions (Della Vigna and Malmendier, 2005) Procrastination in changing retirement savings plans (Choi, Laibson, Madrian, Metrick, 2002) Theoretically, the two are linked together (O’Donoghue and Rabin, 1999): People procrastinate activities where costs are up front because they are highly impatient Is that empirically true?

Our Contribution Study whether individuals who exhibit biases toward the present also tend to procrastinate Measures of impatience Elicit short-term discount rates from an economic relevant population (Chicago MBA students) Monetary payments are done with a check (equalizes transaction costs at all delivery dates) Measures of procrastination Time taken to cash the check Time they answer an on-line survey Time they filed their MBA application Model the effect of quasi-hyperbolic preferences on their discount rate choice and their cashing behavior

The Experiment Design 544 MBA students from University of Chicago GSB Play 5 games, 2 lotteries One game was paid at random Average payment $75.33 (from –$23 to $260) + $20 show-up fee. Payment = Check in mailbox Same transaction cost Same uncertainty Inform subject of his earnings (e.g. $75). If payment >$0, we ask them whether they prefer the won amount today or an increased amount in two weeks, with the following schedule

Measuring Impatience - Money Subjects makes 13 choices: $75.00 today or $75.00 in two weeks (0% more) $75.00 today or $75.75 in two weeks (1% more) $75.00 today or $76.50 in two weeks (2% more) … $75.00 today or $83.25 in two weeks (11% more) $75.00 today or $84.00 in two weeks (12% more) One choice is randomly implemented Note: 1% for two weeks = 29.5% per year, 2% = 67% per year, 5% = 256% per year, 12% = 1804% per year

Impatience - Money Mean Median Min Max Switching % 5.07% 4.00% 0.00% >12.00%

Why Money? If students had access to a credit card (85% did), always better off to make loan to us and use their credit card but ... they do not. McClure et al (2004): hyperbolic discounting with gift certificates => subjects are sensitive to the carrier of reward: check We tried to measure also with a good: chocolate We run an auction for chocolate at different days, but Many students bid zero (they do not like chocolate) We had hour-of-the-day effects (people got hungrier) In separate (smaller) sample we rerun same experiment with chocolate at different delivery dates For people who like chocolate strong correlation (0.4) between two measures of impatience

Impatience with different goods

Measuring Procrastination -1 Keep track of when the subjects cash the check Mean Median Min Max Weeks 3.70 2.14 0.00 29.29 6.74% never cashed the check

Measuring Procrastination -2 Launch an on line survey lasting a month Every week one i-phone was randomly drawn among all students who responded by that day (cumulative).

Other Data Registrar office Demographic characteristics Application submission date Survey questionnaire Various psychological tests Self-reported procrastination Do you tend to procrastinate? Trust – WVS question Cognitive Reasoning Test

Why a Model? Is the delay in cashing the check in the presence of very high discount rates necessarily irrational? No. Subjects might have a random cost of cashing the check. When they cash it depends upon each period realization of this cost. But if subject are sophisticated, the equilibrium check cashing policy should be anticipated in the decision to accept the check today versus in a week. What is different about today? That subject knows the realization of his cost of cashing the check What are the predictions?

D(t) = 1 if t = 0 D(t) = βδt if t ≥ 1 The Model Extension of Choi et al. (2005) Individuals have quasi-hyperbolic preferences: D(t) = 1 if t = 0 D(t) = βδt if t ≥ 1 We further assume δ = 1 Consistent with McClure et al (2004 and 2005), we assume that check is the carrier of reward Cashing the check in t results in a one-time transaction cost ct ct is drawn from a uniform distribution with support [0, ĉ] => Receiving the check today gives you pleasure, cashing it makes you incur a cost Not cashing the check in t entails a risk of losing the check p (6.7% never cashed).

Cashing behavior ct ß[pS + (1 – p)L] Individuals minimize losses due to cashing/losing the check When making the decision in period t an individual can: Cash the check and pay ct Delay the cashing and lose ß[pS + (1 – p)L] L is the expected future costs if check is not cashed in t β ≤ 1 models the level of impatience S is the size of the check

Cashing behavior c* = ß[pS + (1 – p)L(c*)] Equilibrium is a cutoff rule c* that makes individual indifferent between cashing the check and delaying: c* = ß[pS + (1 – p)L(c*)] where Solving for c* gives

The payment decision Choice between S at time t = 0 or S(1 + r) at time t = 1 Take the check in t = 0 if: Where σ(.) is the value of the check given the cashing behavior and is given by

Results 1) Even an exponential discounter will not necessarily delay receiving the check (if current realization of cost very low) => More general result: “impatient” behavior is not necessarily a proof of hyperbolic discounting 2) Sophisticated impatients will switch to later delivery at a higher rate than exponential discounters. 3) Naïve impatients are in between the two Intuition: by ignoring their procrastination in cashing the check, naïve subjects find it more appealing to postpone receiving the check even in presence of a very low realization of the cost.

Other implications: More likely to take the check in 2 weeks if The interest rate is high (large r) The amount of the check is high (large S, but only at high r) The level of impatience is low (large β) Percentage choosing to be paid in two weeks Correlation between money at stake and choosing to be paid in two weeks

Impatience and Procrastination Regress procrastination measure on two-week discount rate A: Tobit regression Positive relation between impatience and weeks to cash check Statistically and economically insignificant Two-week discount rate as dependent variable A B C Weeks to cash check 0.050 Weeks to answer survey – Money at stake -2.604*** CRT Score -0.658** Trust -1.813** Female -0.664 Log likelihood -645.62 Obs. 298

Impatience and Procrastination Regress procrastination measure on two-week discount rate B: Tobit regression Positive relation between impatience and weeks to answer survey Statistically and economically significant Two-week discount rate as dependent variable A B C Weeks to cash check 0.050 – Weeks to answer survey 1.252** Money at stake -2.604*** -2.813*** CRT Score -0.658** -0.547* Trust -1.813** -1.612* Female -0.664 -0.419 Log likelihood -645.62 -643.07 Obs. 298

Impatience and Procrastination Regress procrastination measure on two-week discount rate C: IV Tobit regression Positive relation between impatience and weeks to cash check (instrumented by other measures of procrastination) Statistically and economically significant Two-week discount rate as dependent variable A B C Weeks to cash check 0.050 – 1.145* Weeks to answer survey 1.252** Money at stake -2.604*** -2.813*** 0.461 CRT Score -0.658** -0.547* -0.841* Trust -1.813** -1.612* -3.349** Female -0.664 -0.419 -1.105 Log likelihood -645.62 -643.07 -1570.43 Obs. 298

Conclusions Even Chicago MBAs exhibit a very high level of impatience. Thanks to two field experiments, we are able to link a subject’s degree of impatience with his/her degree of procrastination. Once corrected for noise, this effect is economically relevant: one standard deviation increase in cashing the check is related to two standard deviation increase in the discount rate. Three further directions of research: Try to determine what % of the students are naïve in their procrastination Structural estimation of cost parameters to see how realistic they are Try to find out where procrastination comes from Biology Education