Time Preference, Executive Functions and Ego ...

Time Preference, Executive Functions and Ego-Depletion: An Exploratory Study Ya'akov M. Bayer Beer-Sheva Mental Health Center, Department of Health Systems Management , Faculty of Heath Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel Yamima Osher Beer-Sheva Mental Health Center, Division of Psychiatry, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel Abstract The present research investigates the ways in which the time preferences of young adults are influenced by the level of their executive cognitive abilities and by situational changes in these abilities. Within the framework of this study, young adults were asked to respond to a questionnaire dealing with their time preferences in light of changing amounts and delay durations. Some were asked to do a Stroop task beforehand, while others performed a similar, but simpler task. This research assumes that, since the Stroop task requires that the individual reach a decision while overcoming an automatic tendency and an ingrained habit, this depletes his/her self-control resources. As such, when an individual is filling-out the questionnaire dealing with time preferences after a Stroop task, his/her ability to avoid automatic tendencies is depleted, making it difficult for him/her to reject the receipt of money in the present. The study found that, in general, those individuals having good executive cognitive abilities, namely those who got the highest scores on the Stroop task, were characterized by a lower rate of subjective discounting. In addition, the research showed a marked difference between those individuals who had experienced depletion and who had not, in that the depleted individuals tended to demand higher discount rates for having postponed the payment. This means that the depletion of executive-ability resources caused a behavior similar to that of those having the lowest executive abilities. This outcome may attest to the fact that a depletion in the available level of executive abilities in an individual reduces the ability of that individual to overcome his/her natural tendency to prefer the present, thus influencing his/her intertemporal choices.

Keywords: Time preferences, Ego-depletion, Executive functions, Inhibitions. 1. Introduction Executive functions are cognitive abilities which are significant factors in the ability to plan and to solve problems. Executive functions which are particularly important in decision making include the ability to inhibit impulsive responses and the ability to delay gratification (Aron et al., 2003). Studies have shown that a reduction in executive functioning has a negative impact on decision making (West, 1996; Raz et al., 1998). In addition, it has been shown that cognitive resources are limited (Baumeister et al., 1998), and that these resources may be depleted in certain circumstances, including by conditions which require their utilization – a phenomenon known as ‘ego-depletion’. Assignment of a depleting task requiring self-regulation may degrade performance on a subsequent task requiring self-regulation, even if the two tasks are entirely unrelated to one another (Vohs et al., 2008). In the field of economics, “time preference” is an expression relating to the evaluation of the utility/worth of a possession, action or sensation at a given time as compared to its perceived worth at a later time. Individuals have no absolute time preference; time preferences can only be determined in a relative manner. A person who tends to relate more to the present will focus on the preservation of utility in the present, or over a shorter time span than would the average person; someone with a high preference for the future will more strongly emphasize future utility than might an average person. Economic theory posits that individuals will naturally prefer consumption in the present as opposed to in the future, and will therefore demand compensation for the deferment of consumption (in the case of money, the payment of interest). Overcoming that tendency requires a certain degree of self-restraint and self-control – cognitive resources which, as discussed above, are vulnerable to ‘ego-depletion’. Analysis of this aspect is usually done by using a mathematical function to describe the reduction in the value of funds in the future compared to their present value (abatement rate). This study was conducted to test the hypotheses that 1) there would be a discernable relationship between level of executive functioning (inhibition/self-control) and complex economic decision making, as exemplified by decisions regarding time preferences, and

2) that an intervention designed to deplete the executive function of inhibition/selfcontrol would have measurable effects on those same decisions. Specifically, it was predicted that subjects with lower overall (1) and with ‘depleted’ (2) levels of inhibition/self-control would demand greater compensation for the deferment of consumption (demonstrate higher subjective discount rates). 2. Methods and Materials Subjects. Healthy young adults (ages 20 – 40) were recruited in Israel via internet advertisement offering a monetary prize (100 NIS, approximately $25.00) which would be raffled off among completers of an on-line questionnaire “in the framework of socialeconomic research". The advertisement was posted electronically at various universities, colleges, and work places. Appropriate responders to the advertisement were sent a link to the test materials.

Test materials and procedure All data were collected on line via a dedicated computer program. Data were collected anonymously, and the study was approved by the relevant ethics committee at the Ben Gurion University of the Negev. In addition to collection of demographic data, the executive function of inhibition was measured by one of two variations of a 35-item version of a Stroop-like task, in which respondents are asked to identify the block of color which is the same color as are the letters of the printed color name. In the simple, “non depleting” version, all 35 items were simple matching of word to color (the name of the color appeared printed in black or color-congruent ink, with one of two color blocks presented consisting of the named color) whereas in the “depleting” version, 15 of the 35 items were non-congruent (for example the word “red” appeared printed in blue ink, and the subject was required to choose the blue block rather than the red): this more challenging task was intended to ‘deplete’ inhibitory abilities. Participants were randomly assigned to receive either version one or version two. Time preference was measured using a forced choice questionnaire which offered subjects a theoretical choice between various combinations of immediate vs deferred payments. For example, subjects were asked if they would prefer a given sum now, or given sum + X% after a given interval of time. Ten choices were made. Items varied by

base amount (200 vs 2000 NIS, roughly 50 vs 500 USD), by time interval (week, month, 2, 6, and 12 months), and by the % of increase for the deferred sum. Risk preference was examined by presenting three questions that included a choice between lotteries at different risk levels, through which the individual's tendency to take financial risks is estimated. The higher this index (between 0 and 3), the higher the tendency for higher risk choices. The structure of the questionnaire is based on similar questionnaires from the literature used to assess individual time and risk preferences (Lahav et al., 2011; Eckel & Grossman, 2008). The Cognitive Reflection Test (Frederick, 2005) was also administered as an additional measure of inhibitory executive function. This three item test presents subjects with “tricky” mathematical word problems, and tests the tendency to choose the (incorrect) ‘intuitive’ answer, vs the logically thought out and correct answer.

Statistical analysis The abatement rate, D(r,t), was calculated using hyperbolic formula, according to theory and literature on the subject (Ainslie,1991). The regression equation is described as follows: 1

1

P=FT∗ 𝐷(𝑟, 𝑡) = FT ∗ (1+t∗SDR) = 𝐹𝑇 ∗ (1+𝑡(𝑘+𝑎∗𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒1+𝑏∗𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒2+𝑐∗𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒3…..)) FT – the future sum requested by the individual in order to delay consumption until after time-period T (in the future); P is the value of sum requested in the present; and r is the SDR needed for a T time-period delay.

Personal or subjective discount rate (SDR) is represented as follows: 𝑆𝐷𝑅 = (𝑘 + 𝑎 ∗ 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒1 + 𝑏 ∗ 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒2 + 𝑐 ∗ 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒3 … . . ) It is important to note that the abatement rate is affected by the SDR, The lower the SDR, the higher the future value (lower abatement rate). Demographic variables shown by previous studies to have an effect upon time preferences include gender (Dittrich & Leipold, 2014), age (Sozou & Seymour, 2003), and income level (Andersen et al., 2008; Anderhub et al., 2001); these factors were

therefore entered into various regression models in order to test the hypothesis that being subjected to “cognitive depletion” would result in significant changes to economic decision making.

Executive functioning was measured by scores on the Stroop test; scores ranged from zero (low inhibitory function) to 20 (high inhibitory functioning) based on a combination of correct choices made and rapidity of response. The second measure of inhibitory functioning, the CRT, was found to correlate highly to the Stroop, and was therefore excluded from further regression analyses as it added no additional information.

3. Results Two hundred eighty eligible respondents completed the computerized testing session. As described in the procedure section, respondents were randomly administered either the “depleting” or the “non-depleting” version of the Stroop-like task. Demographic data for the resulting two groups are presented in Table 1. There were no significant differences between groups for age [t(278)=1.51, NS], gender [t(278)=0.11, NS], or years of education [t(278)=-0.47,NS].

[Table 1 here]

Hypothesis 1. Relationship between executive functioning and abatement rate This analysis was conducted within the group of 139 subjects who completed the full Stroop task. As may be seen in Fig. 1, showing the relation between abatement function (describing the change in value between present and future amounts of money1, in days, up to one year) and executive function, higher Stroop scores are characterized by lower abatement rates (lower SDRs) at all time points assessed. [Figure 1 here]

F – the future sum requested by the individual in order to delay consumption until after time-period T (in the future); P is the value of sum requested in the present; and r is the SDR needed for a T time-period delay 1

Full results of the hyperbolic regressions based on this formula2, 1

P=F∗ 𝐷(𝑟, 𝑡) = 𝐹 ∗ (1+𝑡(𝑘+𝑎∗𝑠𝑡𝑟𝑜𝑜𝑝𝑠𝑐𝑜𝑟𝑒+𝑏∗𝑎𝑚𝑜𝑢𝑛𝑡+𝑐∗𝑖𝑛𝑐𝑜𝑚𝑒…..)) are presented in Table 2. [Table 2 here] As can be seen in Table 2, level of executive functioning was the strongest subjectrelated predictor of the abatement rate. As predicted in hypothesis one, higher levels of executive (inhibitory) functioning predicted lower abatement rate (lower SDRs). The other strong predictor of SDR was the variable of monetary amount in question (200 vs 2000 NIS). The negative correlation indicates that subjects demand a relatively lower discount rate in return for delaying repayment of a larger sum, as opposed to a smaller sum. This is consistent with earlier studies (for example Thaler, 1981; Lahav et al., 2015). Hypothesis 2. Relationship between depleted cognitive resources and abatement rate This analysis incorporated the data from all subjects, and compared the abatement rates of the depleted vs the non-depleted groups – those who completed the Stroop task and those who were presented with only the simple, non-challenging Stroop-like task. Results are presented in Figure 2. [Figure 2 here] As can be seen in Figure 2, the “cognitively depleted” group consistently demanded higher SDRs, regardless of whether the amount in question was large or small, and at all time points. Figure 3 shows that this relationship also exists in the hyperbolic model. The figure shows the relation between abatement function (describing the change in value between

2

Cluster-corrected standard errors were used throughout as appropriate.

present and future amounts of money, in days, up to one year3) and group type (depleted and non-depleted). The non-depleted group is characterized by lower abatement rates (lower SDRs) at all time points assessed. [Figure 3 here] Full results of the hyperbolic regressions based on this formula4, 𝐷(𝑟, 𝑡) =

1 (1 + 𝑡(𝑘 + 𝑎 ∗ 𝐷𝑒𝑝𝑙𝑒𝑡𝑖𝑜𝑛 𝑙𝑒𝑣𝑒𝑙 + 𝑏 ∗ 𝑎𝑚𝑜𝑢𝑛𝑡 + 𝑐 ∗ 𝑖𝑛𝑐𝑜𝑚𝑒 … . . ))

are presented in Table 3. [Table 3 here] As can be seen in Table 3, group (easy vs difficult, “depleting” Stroop) significantly predicted abatement rate at all levels of time delay. As predicted by hypothesis 2, the “depleted” group consistently demanded higher SDR for delayed payment. 4. Discussion This study demonstrates both that executive functioning (specifically, inhibitory function) is inversely correlated with subjective discount rates (SDR), and that said functioning can be experimentally manipulated in ways which will impact significantly upon SDRs. Classic economic theory is based on the assumption of “homo economicus”, and the rational basis of behavior is a central tenant of this theory. This approach assumes that the economic decisions of an individual are based on rational thought processes, and therefore should be consistent and predictable. This study suggests that at least some economic decisions are also influenced by cognitive states, in this case – depletion of cognitive resources which affect impulsivity. We have shown that an individual’s executive abilities impact on their time preferences in two ways: both as given individual differences (‘trait’ factor) and also as a function of

F – the future sum requested by the individual in order to delay consumption until after time-period T (in the future); P is the value of sum requested in the present; and r is the SDR needed for a T time-period delay. 3

4

Cluster-corrected standard errors were used throughout as appropriate.

immediate previous demands on said abilities (“state” factor). We show that for each delay period, the most important influence on time preference is the level of executive functioning. Our results support our hypotheses: level of executive functioning influences an individual’s time preference as reflected in the subjective discount rate for young adults, and that an individual’s SDR can be affected by situational depletion of executive function-related cognitive resources. Poorer and depleted executive function are associated with higher required SDRs and with increased preference for short term (present) vs longer term (future) gain. While the impact of executive functioning on decision making is not new to the literature (see for example Achtziger et al., 2015 and Achtziger et al., 2016), we believe this is one of the few studies to show that such a brief intervention can deplete executive functioning sufficiently as to have a measurable and predictable impact on economic decision making (SDR). Our findings are consistent with other studies showing that the reduction in available cognitive resources in the realm of impulse control is expressed as a weakening of the ability to delay gratification (Muraven et al., 2002; Vohs & Heatherton, 2000; study #3 in Joireman et al., 2008). This sort of impulsiveness has both a developmental and a situational aspect; in addition to young children, adults who are under the influence of alcohol, for example, or extremely tired, may exhibit similar behavior. These findings have real-world implications in the realms of marketing and consumer education. For example, greater awareness of the effects of ego depletion might lead to increased ability to withstand high pressure sales tactics. One limitation of this study is that all of the subjects were relatively young; it would be important to see if the same results are achieved in other age ranges. A second limitation is that 84% of respondents were female. Although we did not find gender to be a significant factor, replication in more representative samples would be in order. There might also be questions of generalizability since the sample was recruited primarily online. Finally, it should be noted that our procedure involved decisions which had no realworld consequences; further research could investigate situations wherein decisions are related to actual (as opposed to theoretical) outcomes.

Taken together, this body of research could offer useful insights into the effects of cognitive depletion on financial decision making, and suggest ways in which these distortions might be minimized or prevented.

Bibliography Achtziger, A., Alos-Ferrer, C., & Wagner, A.K. (2015). Money, depletion, and prosociality in the dictator game. Journal of Neuroscience, Psychology, and Economics, 8(1), 1-14. Achtziger, A., Alos-Ferrer, C., & Wagner, A.K. (2016). Impact of self-control depletion on social preferences in the ultimatum game. Journal of Economic Psychology, 53, 1-16. Ainslie, G. (1991). Derivation of ‘rational’ economic behavior from hyperbolic discount curves. American Economic Review, 334-340. Anderhub, V., Güth, W., Gneezy, U., & Sonsino, D. (2001). On the interaction of risk and time preferences: An experimental study. German Economic Review, 2(3), 239-253. Andersen, S., Harrison, G. W., Lau, M. I., & Rutström, E. E. (2008). Eliciting risk and time preferences. Econometrica, 76(3), 583-618. Aron, A. R., Dowson, J. H., Sahakian, B. J., & Robbins, T. W. (2003). Methylphenidate improves response inhibition in adults with attention-deficit/hyperactivity disorder. Biological Psychiatry, 54(12), 1465-1468. Baumeister, R. F., Bratslavsky, E., Muraven, M., & Tice, D. M. (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology, 74(5), 1252. Dittrich, M. and Leipold, K. (2014). Gender differences in time preferences. Economics Letters, 122(3), 413-415. Eckel, C. C. Grossman, P.J (2008). Forecasting Risk Attitudes: An Experimental Study Using Actual and Forecast Gamble Choices. Journal of Economic Behavior and Organization, 68(1). Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19(4), 25-42. Joireman, J., Balliet, D., Sprott, D., Spangenberg E., Schultz J. (2008). Consideration of future consequences, ego-depletion, and self control: Support for distinguishing beween CFCImmediate and CFC-Future sub-scales. Personality and Individual Differences, 45, 15-21. Lahav, E., Benzion, U., & Shavit, T. (2011). The effect of military service on soldiers’ time preference-Evidence from Israel. Judgment and Decision Making, 6(2), 130-138. Lahav,E., Shavit, T., and Benzion, U. (2015). Sweet Sixteen: Changing time preferences in the transition from middle school to high school, for different scenerios. Journal of the Experimental Analysis of Behavior, 103(1), 22-32. Muraven, M., Collins, R.L. & Neinhaus, K. (2002). Self-control and alcohol restraint: An initial application of the self-control strength model. Psychology of Addictive Behaviors, 16, 113-120. Raz, N., Gunning-Dixon, F. M., Head, D., Dupuis, J. H., & Acker, J. D. (1998). Neuroanatomical correlates of cognitive aging: evidence from structural magnetic resonance imaging. Neuropsychology, 12(1), 95. Sozou, P. D., and Seymour, R. M. (2003). Augmented discounting: Interaction between ageing and time–preference behaviour. Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(1519), 1047-1053.

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Tables and figures:

Gender Age (% female) (mean + SD)

Education [years] (mean + SD)

Depletion group N=139 Non-depletion group N=141

84

29.76 + 5.2

15.21 + 1.64

84

30.68 + 5.0

15.31 + 1.77

Table 1. Demographic data

Figure 1. Abatement rates over time for groups of differing levels of executive (inhibitory) functioning – from high (Stroop score = 20) to low (Stroop score = 0), Forecast based on the estimation of the following hyperbolic model: . 𝑃 = 𝐹 ∗ 𝐷(𝑟, 𝑡) = 𝐹 ∗

1 (1 + 𝑡(𝑘 + 𝑎 ∗ 𝑠𝑡𝑟𝑜𝑜𝑝𝑠𝑐𝑜𝑟𝑒))

Hyperbolic Model Regression k Stroop test score Amount (0=200, 1=2000) Personal income+

Model (1)

Model (2)

Model (3)

Model (4)

0.0045696*** 0.0081717*** 0.0105455*** 0.0128054*** (0.0006725) (0.014948) (0.0015556) (0.0018308) -0.0004082*** -0.0004097*** -0.0003593*** (0.0001115) (0.0001112) (0.0001223) -0.002385*** -0.0024759*** (0.0003759) (0.0004281) -0.0008066* (0.0004791)

Risk

Model (5)

Model (6)

Model (7)

0.0124164*** (0.0018935) -0.0003853*** (0.0001226) -0.0022853*** (0.0003789) -0.0008942** (0.0004127) 0.0016499 (0.0010466)

0.0097507*** (0.0032374) -0.0003344*** (0.0001221) -0.0022984*** (0.0003696) -0.0009577** (0.0004033) 0.0016459 (0.0010352) 0.0000791 (0.0000847)

1174 0.8405 0.8391

1174 0.8411 0.8397

0.008749*** (0.0031297) -0.0003057*** (0.0001121) -0.0022958*** (0.0003773) -0.0010016** (0.0004231) 0.00164 (0.0012663) 0.0001025 (0.0000914) 0.0009075 (0.0015208) 1174 0.8416 0.8403

Age Gender 1=Men Number of obs R-squared adjusted R2

1384 0.8347 0.8335 *** p