Research Master in Economics and Business
Looking into the Future: Episodic Future Thinking
Reduces Delay Discounting among the Poor
Research Master in Economics and Business
Master Thesis
Looking into the Future: Episodic Future Thinking
Reduces Delay Discounting of the Poor
Jana Holthöwer
Student Number S2736934
University of Groningen
Faculty of Economics and Business
M.Sc. Research Master in Economics and Business
Supervisors: Prof. Dr. B.M. Fennis & Dr. M. Moeini Jazani
Admiraal de Ruyterlaan 38A
9726GV Groningen
The Netherlands
ABSTRACT
The financially deprived engage in increased delay discounting, thus preferring smaller-sooner rewards over larger-later ones. Increased delay discounting hinders the ability to act in line with long-term benefits and goals across various decision contexts. Hence, exploring interventions to decrease one’s myopic tendency to delay discounting has important implications for decisions concerning future-oriented outcomes. One intervention may be episodic future thinking (EFT), which is the ability to project the self in time to pre-experience an event. Our study 1 replicates previous findings in showing that EFT effectively reduces delay discounting and shows that the intervention is particularly effective among those with relatively lower income. However, these EFT effects have not been examined among the poor. In a second study, a 2 (EFT vs. episodic recent thinking) x 2 (financially deprived vs. financially non-deprived) between-subjects design, we manipulate the feeling of financial deprivation and show that EFT significantly reduces delay discounting among the financially deprived. We also examine the underlying process of EFT and find that future-self connection amplifies the effect of EFT on delay discounting among those who feel financially deprived. By identifying EFT as one psychological intervention that reduces delay discounting, this thesis contributes to research intending at improving the decision-making of the poor. In addition, we contribute to the literature of EFT by extending its reparative effects into economic decisions of the poor as well as by proposing one underlying process of this effect.
TABLE OF CONTENT
ABSTRACT ... 3
1. INTRODUCTION ... 5
2. THEORETICAL BACKGROUND ... 7
2.1 Financial Deprivation and Delay Discounting ... 7
2.2 Episodic Future Thinking ... 9
2.2.1 Definition ... 9
2.2.2 Mechanisms ... 10
2.2.3 Functions ... 12
2.3 Hypotheses Development ... 13
2.4 Potential Underlying Mechanisms ... 13
3. OVERVIEW OF THE CURRENT RESEARCH ... 16
3.1 Study 1 ... 16 3.1.1 Method ... 16 3.1.2 Results ... 18 3.1.3 Discussion ... 21 3.2 Study 2 ... 21 3.2.1 Method ... 21 3.2.2 Results ... 24 3.2.3 Discussion ... 29 4. GENERAL DISCUSSION ... 31 5. CONCLUSION ... 34 6. REFERENCES ... 35 7. APPENDIX ... 40
Appendix 1. Episodic cue generation – Task instructions ... 40
Appendix 2. Financial Deprivation Manipulation used in Study 2 ... 40
Appendix 3. Future-Self Connection Scale ... 41
1. INTRODUCTION
People often make decisions that have implications for the future. A decision to cash out retirement savings today will influence the available income after retirement. A decision to consume fatty food now will impact health conditions years later. A decision to stay up longer to watch the favorite TV series will influence your productivity and focus at work tomorrow. Considered in isolation, consumers satisfying their immediate impulses may be trivial. However, when combined into a temporally extended pattern of behavior, they can influence savings for retirement, healthcare, as well as psychological well-being (Schroeder, 2007). Opting for the smaller-sooner reward over the larger-later one is a tendency known as delay discounting (Haushofer & Fehr, 2014).
This myopic tendency is particularly evident in those suffering from disadvantaged economic conditions: Financial deprivation is associated with excessive discounting of delayed rewards (Mani et al., 2013; Shah, Mullainathan, & Shafir, 2012). The financially deprived engage in a number of counterproductive behaviors, such as questionable management of own finances, inadequate investments in health, or a preference for unskilled work over higher education. In short, they show an inclination towards those attitudes and practices that prioritize smaller immediate gratifications and sacrifice potential earnings and future financial security (Farah & Hook, 2017). Steep future discounting in economic decisions traps the financially deprived into a vicious cycle, inhibiting these people from escaping their poverty state. But why do consumers exhibit myopic tendencies and how can we prevent it?
2. THEORETICAL BACKGROUND
2.1 Financial Deprivation and Delay Discounting
Delay discounting has been witnessed in several experimental studies across a range of decision contexts, in which participants were randomized to treatment conditions in which the feeling of financial deprivation is manipulated (Liu et al., 2012). Research shows that just a feeling of poverty is sufficient to cause a shift in consumers’ intertemporal preferences towards immediate gratification (Callan, Shead & Olson, 2011). These participants tended to have fewer savings and more debts (Shah et al., 2012), engage more in gambling (Callan et al., 2011), and consume more calorie-rich food (Sim et al., 2018) and alcoholic drinks (Droomers et al., 1999).
Due to this tendency, the psychology literature tries to explain why poverty leads to delay discounting. While sociological and economic perspectives relate high discounting of the poor to factors such as individuals’ socioeconomic or dispositional characteristics and liquidity constraints (Lea et al., 1993; Rowe & Rodgers, 1997), the psychological perspective stresses the role of subjective, self-threatening aspects of experiencing financial deprivation in demonstrating delay discounting (Haushofer & Fehr, 2014; Liu et al., 2012; Mullainathan & Shafir, 2013). Participants who merely felt being financially deprived were more likely to prefer the immediately available, smaller monetary rewards over the larger rewards, that were available in a specific point in the future (Callan et al., 2011).
2.2 Episodic Future Thinking 2.2.1 Definition
Episodic future thinking, also referred to as prospective thinking, is a mental simulation to place ourselves in the future and pre-experience an event (Atance & O’Neill, 2001). This episodic simulation involves pre-experiencing an event in its entirety, including associated feelings, emotions, and sensations. Future-oriented thinking is a pervasive mental activity and able to take more or less abstract representational formats and to embrace different thematic contents (D’Argembeau et al., 2011). By increasing personal connection towards the future, EFT helps with goal-attainment, maintaining a personal sense of identity, and future planning (Atance & O’Neill, 2001; D’Argembeau et al., 2012).
EFT is just one of various forms of prospection. Szpunar et al. (2014) proposed a taxonomy that distinguishes among four forms of prospection: planning, intention, prediction, and simulation. Each form varies according to its representational contents from semantic (i.e., intentions, predictions, simulations, or plans that relate to more general or abstract states of the world that might occur in the future) to episodic (i.e., intentions, predictions, simulations, or plans that relate to specific autobiographical events that might occur in the future). The term EFT encompasses all four prospection forms, yet in practice, EFT studies almost always refer to episodic simulation. Episodic simulation is the construction of a mental representation of a specific autobiographical future event. Also, the form of simulation fits best our research aim. As the terms episodic future thinking and episodic simulation are frequently used interchangeably (Schacter, Addis, & Buckner, 2008), we will continue to refer to episodic future thinking.
2.2.2 Mechanisms
2.2.2.1 Cognitive Mechanisms
The capacity of simulating future events is supported by cognitive mechanisms that involve the extraction of elements of past experiences and the use of this information in order to form new mental representations. These representations are then projected into the future. It has been argued that EFT critically depends on the episodic memory system (Schacter et al., 2012; Tulving, 2002). In particular, episodic memory allows individuals to flexibly retrieve and recombine elements of their past experiences into new representations of events that might happen in the future. However, EFT is not only the direct expression of episodic memory or recombination of episodic details; sometimes, general or abstract knowledge of the situation, context, or environment is sufficient to construct future episodes and thoughts (Szpunar, 2010). This shows that imagining how things could evolve in the future may be constructed without necessarily relying on the contents of specific episodic memory as such.
through EFT (Schacter et al., 2012). Besides this, Liu et al. (2013) explored how episodic prospection modulates delay discounting by emotion and suggested that the valence of emotion of imagined future events may play a critical role in intertemporal choices. They found that positive emotion made people choose the larger-later reward, whereas negative emotion made people choose the smaller-sooner reward.
2.2.2.2 Neural Mechanisms
2.2.3 Functions
2.3 Hypotheses Development
As discussed, delay discounting has been proven to be a peculiar behavior of the financially deprived that leads to myopic behavior which in turn perpetuates their disadvantaged state. Given the results of previous studies on episodic future thinking and delay discounting across problematic populations that typically have high discounting rates, we expect similar reparative results of EFT among the poor. Episodic future thinking could represent a viable intervention tool to aid financially deprived individuals in controlling their impatience. EFT may be employed in specific training procedures to control impatient behaviors accountable for a range of suboptimal decisions in one’s life. This work investigates whether EFT has a moderating effect on the main relationship between perceived financial constraints and delay discounting, such that the poor become more patient after engaging in episodic future thinking. We expect the reparative effect of EFT on discounting to be larger among the financially deprived consumers, relative to the financially non-deprived consumers. Formally stated:
H1: Episodic future thinking moderates the link between financial deprivation and delay discounting, such that the mitigating effect of EFT on delay discounting is stronger among the financially deprived than it would be among the non-deprived.
Two specific contrast hypotheses follow from this primary, moderation hypothesis:
H1a: Among the financially deprived, episodic future thinking will reduce delay discounting, compared to the episodic recent thinking.
H1b: Replicating past findings, in the episodic recent thinking condition, the financially deprived show increased preferences for smaller-sooner rewards compared to their non- deprived counterparts.
2.4 Potential Underlying Mechanisms
and future selves as highly connected are less prone to immediate gratification in intertemporal choice tasks. Hershfield (2011) investigated how the perception of one’s self may substantially influence decision making over time. Assuming that every individual is a collection of overlapping identities and the degree of connection among these is negatively correlated to their temporal distance, Hershfield (2011) discussed how conflicts between temporally distinct selves cause myopic behavior in intertemporal decision making. Specifically, individuals who perceive their future-self as more similar to their current state and are able to vividly imagine this, may feel more connected to it and are more prone to make choices that are beneficial in the future. In contrast, estrangement from their future selves would describe saving as a choice between spending money today or giving it a ‘stranger’ years from today (Hershfield et al., 2011). Reasonably, the extent to which a person feels connected to his/her future selves should make him/her appreciate being the future recipient and, therefore, affect the willingness to save. Because EFT activates thinking about one’s self in different delays in the future, we propose that future-self connection is a potential underlying process of EFT in reducing delay discounting. In line, Lin & Epstein (2014) have mentioned that episodic future thinking may foster the connection to one’s future self. A recent study has found that EFT and future-self connection are significantly correlated so that “adolescents who felt connected to their future selves imagined the future with greater episodic richness” (McCue et al., 2019: p.151). Therefore, future-self connection which is boosted by EFT may enable the financially deprived to reduce their tendency to discount larger-later rewards. Formally stated:
H2: A person’s future-self connection mediates the interaction between the feeling of financial deprivation and episodic future thinking on delay discounting.
about a future event may boost how positive the poor feel. In turn, this may lead to a reduction of their discounting tendencies. From this, we derive the following hypothesis:
H3: A person’s positive affect mediates the interaction between the feeling of financial deprivation and episodic future thinking on delay discounting.
Third, episodic future thinking may be linked to one’s subjective time perception. Traditional research in consumer behavior and economics has assumed that people process time between payoffs objectively and consider time as objective information (i.e. calendar time). An important and robust finding is that the rate at which an outcome is discounted over time (delay discounting) decreases as the time horizon gets longer (Thaler, 1981). This is known as hyperbolic discounting. However, recent findings suggest that consumers’ time perception (i.e., the time between two payoffs) may be one factor influencing their impatience (i.e., opting for smaller-sooner payoffs) in intertemporal choices (Zauberman et al, 2009; Kim & Zauberman, 2009). Specifically, the findings show that consumers perceive future times and durations subjectively. For instance, while six months from now may seem close to some people, it may seem long to others. As outcomes in intertemporal decisions are separated by time, the subjective perception of time influences which payoff is eventually preferred. Applied to our paper, the intertemporal behavior of financially deprived might be driven, at least partly, by how the length of each future delay is perceived. It can be argued that engaging in EFT could change the time perception by making the future seem subjectively closer. Formally stated: H4: A person’s subjective perception of time mediates the interaction between the feeling of financial deprivation and episodic future thinking on delay discounting.
3. OVERVIEW OF THE CURRENT RESEARCH
Our key prediction is that episodic future thinking has a stronger reparative effect in a discounting task among the financially deprived than among the financially non-deprived. To test this hypothesis, we conduct two experimental studies. The online survey is designed using the research software Qualtrics. All participants are recruited via Amazon Mechanical Turk (MTurk) and take part on a voluntary basis, in exchange for a financial compensation conditional upon successful completion of the survey. Using MTurk as a crowdsourcing platform allows us to gather a larger sample whose demographics are diverse and crucially not limited to the university population.
Study 1 measures the effect of EFT on the link between income and delay discounting. Income is commonly used to measure financial status and as low-income individuals feel more financially deprived and display impulsive behavior (i.e., delay discounting), income is used to operationalize financial deprivation. In Study 2, we experimentally manipulate the feeling of poverty and measure the moderating effect of EFT on the relationship between the income manipulation and delay discounting. We also measure several potential underlying mechanisms, i.e. future-self connection, subjective perception of time, and affect. The sample size of both studies is determined using the G*Power analysis (v3.1; Erdfelder, Faul, Buchner, & Lang, 2009) to have a power of 0.80 and an α-error probability of 0.05 to detect the hypothesized effects. In study 1, power analysis for a linear regression yields a sample size of 787 to detect a small-sized effect (f= 0.01) if it is present. In study 2, the analysis for an ANOVA yields a sample size of 795. Due to potential exclusions while screening the data, sample sizes for both studies collected via MTurk exceeded the minimum number of participants.
3.1 Study 1 3.1.1 Method
3.1.1.1 Procedure
generation and of the delay discounting tasks do not coincide. Rung & Madden (2019) have shown that EFT effectively reduces delay discounting when participants were cued to engage in future thinking without a time-delay matching with the delay of the discounting task. The last part of the survey consists of several questions about our independent variable income, demographics, English proficiency and attentiveness while completing the study.
3.1.1.2 Measures
Income – IV. Participant’s personal gross annual income is measured using 20 income brackets
with $10,000 increments, ranging from 1 (under $10,000) to 20 (190,000 or more). For the data analysis, we assigned the midpoint of the respective income bracket as the corresponding participant’s income amount (e.g. $35,000 when bracket 4 ($30,000-$39,999) is chosen). Using linear extrapolation, $195,000 is considered as the income value for those who selected the highest income category ($190,000 or more). Furthermore, income values are divided by 10,000 to interpret the results more easily.1
Episodic Cue Generation – Moderator. Using methods adapted from previous researchers
(e.g. Lin & Epstein, 2014; Snider et al., 2017) participants are randomly assigned to either the episodic future thinking group or the control group. Participants in the EFT condition are asked to think about and describe the most positive event that could realistically happen at each of three delays in the future (3 months, 6 months, 15 months). Participants in the ERT condition are asked to think about a positive event that will recently occur at each of three time points from the next 24 hours (3 hours, 6 hours, 15 hours) (see Appendix 1 for detailed instructions of the EFT conditions).
For all conditions, the episodic component of the task occurs when the participants are asked to describe in detail what they are imagining vividly about each event. Participants are prompted with questions to encourage elaboration on the future event. Example questions include what they will be doing, with whom, where they will be, and how they feel. For each point of time, participants integrated the future event and sensory information into a concise event cue that later used in the delay discounting task. The cues for the EFT group is a continuation of the sentence ‘In __ months from now, I will be …’. For the ERT group the sentence to be continued was ‘In __ hours, I will be …’.
Delay Discounting – DV. During the delay discounting task, participants specify the amount
of money (in US$) they would require in four different time delays in the future (2 months, 5 months, 9 months, and 18 months) to make them indifferent to receiving $65 immediately (Van den Bergh, Dewitte, & Warlop, 2008). Indifference points signify the subjective value of a reward when it is delayed by a particular time period. The indifference points are used to compute participant’s area under the discounting curve (AUC) value, with AUC ranging from 0 (steepest discounting) to 1 (no discounting) (Myerson et al., 2001).
Additional Measures. Several characteristics that could covary with income are measured,
such as age, gender, level of education (1=less than high school/still attending high school, 2=high school diploma or GED, 3=associate or vocational degree , 4=college or university degree, 5=master’s degree, 6=Doctoral student or holder of a doctoral degree, 7=other), and ethnicity (1=European-American, 2=African-American, 3=Hispanic, 4=Asian-American, 5=Native-American, 6=Pacific Islander, 7=other). These demographic variables are measured to test the robustness of our findings. In addition, participants rate the vividness of the episodic associations (1=not vivid at all, 7=very vividly) as well as the difficulty in imagining the events on a 7-point Likert scale (1=extremely difficult, 7=extremely easy) (Peters & Büchel, 2010).
3.1.2 Results
3.1.2.1 Data Inspection and Sample Characteristics
For the first study, we recruited 828 participants. In total, 73 participants are excluded from the analysis, as they did not complete the survey, failed the attention check, or wrote texts that clearly indicated that they did not do the task properly. This yielded a final sample of 755 participants (406 females, Mage = 37, SDage = 12.89). Personal annual income, based on the
bracket chosen (M = 4.77, SD = 3.49), ranged from 1 to 20 and was non-normally distributed with skewness of 1.56 (SE = 0.089). Household annual income, based on the bracket chosen (M = 6.70, SD = 4.08), ranged from 1 to 20 and was non-normally distributed with skewness of 1.05 (SE = 0.089). The frequencies in terms of absolute values and percentage are displayed in Table 1 for the variables ethnic background and education.
Ethnic Composition Education
n % n %
European-American 568 75.2 Still attending high school 3 0.4 African-American 64 8.5 High school diploma or GED 180 23.8 Hispanic 39 5.2 Associate or vocational degree 121 16.0 Asian-American 49 6.5 College / University degree 327 43.3 Native-American 7 0.9 Master’s degree 93 12.3 Pacific Islander 0 0.0 Doctoral student / Holder of a doctoral degree 21 2.8
3.1.2.2 Income, Episodic Future Thinking, and Delay Discounting
We regressed participants’ area under the curve (AUC) on EFT (0 = ERT, 1 = EFT), income2
(mean-centered), and their interaction term (Figure 1). Results of Study 1 reveal a significant main effect of income, b = 0.026, SEb = 0.003, t(751) = 8.438, p < 0.000, 95% CI [0.02, 0.032],
a significant main effect of episodic future thinking, b = 0.046, SEb = 0.016, t(751) = 2.803, p
= 0.005, 95% CI [0.014, 0.078], and the significant critical interaction between income and episodic future thinking, b = −0.02, SEb = 0.005, t(751) = −4.149, p = 0.000, 95% CI [−0.029,
−0.01]. There is a significant difference in delay discounting between those who thought about the future (EFT) (M = 0.44 SD = 0.23) and those who did not (ERT), M = 0.40, SD = 0.24; F(1,753) = 5.540, p = 0.019. Together, these results indicate that episodic future thinking moderates the effect of income on delay discounting, such that participants who thought about their future showed reduced delay discounting compared to those who thought about recent events. We further investigated this interaction by analyzing the effects of EFT on AUC at one standard deviation below and above the income mean (Aiken & West, 1991). As predicted, among those with relatively lower income in our sample (MIncome – 1 SD), thinking about future
events, relative to thinking about recent events, significantly increased AUC and thus reduced delay discounting, b = 0.114, SEb = 0.023, t(751) = 4.942, p = 0.000, 95% CI [0.069, 0.159]. In
contrast, among those with relatively higher income (MIncome + 1 SD), thinking about the future,
relative to the ERT condition, did not further increase AUC, b = −0.023, SEb = 0.023, t(751) =
−0.971, p = 0.332, 95% CI [−0.068, 0.023].
The findings of study 1 show that EFT is a particularly effective intervention in reducing delay discounting among relatively low-income people. To pinpoint the range of income values for which the mitigating effect of EFT (vs. ERT) on delay discounting was significant (α = 0.05 criterion) in our sample, we further probed the interaction between income and EFT on AUC using the Johnson–Neyman technique (Johnson & Neyman, 1936). The analysis revealed as transition point an income value of $49,325. This means that, relative to ERT, episodic future thinking significantly reduced delay discounting of people (67.42%) whose income was below $49,325. In sum, these results show support for H1, in that episodic future thinking moderates the link between financial deprivation and delay discounting. In particular, the moderating effect of EFT on delay discounting is found to be stronger among the individual with low income.
Figure 1. The area under the discounting curve (AUC) as a function of income and episodic thinking conditions
in Study 1. A greater AUC indicates a higher preference for larger-later payoffs (i.e., reduced delay discounting). Error bands denote 95% confidence intervals of the regression estimates.
3.1.2.3 Robustness Checks
In several regression analyses, we test whether the interaction between income and episodic future thinking (Model 1) remains significant after controlling for participants’ demographic characteristics that may covary with income. Specifically, we control for participants’ age and gender in Model 2, and for ethnicity, household size, and level of education in Model 3. In Model 4, we control for the variables that measure the vividness of the episodic associations and the difficulty in imagining the events. As shown in Table 2, the critical interaction between income and EFT on AUC remains significant even after controlling for the participants’ characteristics. Hence, the results corroborate the robustness of our main findings.
Model 1 Model 2 Model 3 Model 4
Variable B SE t B SE t B SE t B SE t Intercept 0.390 0.011 34.39*** 0.430 0.027 15.78*** 0.380 0.041 9.36*** 0.480 0.059 8.123*** Income 0.026 0.03 8.44** 0.026 0.003 8.25*** 0.025 0.003 7.99*** 0.024 0.003 7.818*** EFT 0.046 0.016 2.80*** 0.046 0.016 2.84** 0.047 0.016 2.92** 0.044 0.016 2.662** Income × EFT -0.02 0.005 -4.15*** -0.02 0.005 -4.26*** -0.022 0.005 -4.61*** -0.021 0.005 -4.372*** Age 0.000 0.001 0.62 0.000 0.001 0.13 0.000 0.001 0.571 Gender -0.026 0.0162 -1.59 -0.019 0.016 -1.18 -0.017 0.016 -1.056 Ethnicity 0.004 0.006 0.64 0.003 0.006 0.586 Education Level 0.022 0.007 2.96** 0.021 0.007 2.862** Household Size -0.017 0.006 -2.90** -0.016 0.006 -2.682** Vividness -0.024 0.01 -2.518* Difficulty to imagine 0.008 0.008 0.995 Adjusted R2 0.097 0.100 0.123 0.132 R2 change 0.022*** 0.025*** 0.022***
3.1.3 Discussion
Consistent with prior research, this study shows that the discounting rate (AUC) is sensitive to the income level, which means that individuals with lower income were more likely to discount future payoffs than higher income subjects (Haushofer & Fehr, 2014). The results of this study support our Hypothesis 1. As expected, relative to episodic recent thinking, thinking about the future had a stronger effect on reducing delay discounting for low-income people (compared to high-income people). The mitigating effect of EFT on the discounting behavior of the financially deprived is robust and remains significant even after controlling for several socioeconomic and demographic variables that can covary with income. While we used income as a measure of financial deprivation in Study 1, Study 2 will conceptually replicate this study by manipulating feeling of financial deprivation directly.
3.2 Study 2 3.2.1 Method
3.2.1.1 Procedure
3.2.1.2 Measures
Financial Deprivation – IV. The manipulation is adapted from Callan, Shead & Olsen (2011).
Participants are randomized to one condition in which they are asked about their monthly discretionary income. A simple definition of discretionary income is given to the participants. To tell a credible cover story, participants are asked to provide demographic information (age, gender, marital status, household size, residence) so that the computer can calculate the Comparative Discretionary Income (CDI) index score. Then, they indicate their monthly discretionary income (in US$) using a slider, which has different end-point values depending on the condition they are randomized to. While those in the financially deprived condition are given values ranging from $1,700 or less to $50,000 and above, those in the non-deprived condition see options ranging from $0 to $1,700 and above. The rationale behind this method lies in the documented evidence that responses at the top or bottom of a scale tend to result in individuals making corresponding inferences about their personal circumstances (Schwarz, 1999). In this case, those seeing the $1,700 and above scale should experience relative satisfaction, while respondents to the $50,000 and above scale should feel financially deprived. The end-point of $1,700 is adjusted to the average monthly discretionary income in the United States, which has been $1,729 in 2014 based on Bureau of Labor Services (BLS) data (Stoffel, 2015). Once the participants indicated the amount, they are informed that the system now calculates the CDI index score. More specifically, participants read this text:
‘As next step, our system will calculate your Comparative Discretionary Income (CDI) Index score. This index measures your financial standing in terms of your average monthly discretionary income relative to that of similar others. Based on your previous responses, the index produces a score using your profile and the information in our database from people who match your profile. The score will tell you how much monthly discretionary income you have relative to people who match your profile.
Please click onto the next side to calculate your CDI index score.’
‘The statistical analysis uses information from your profile and the information in our database from people who matched your profile. The CDI index score shows on average how much monthly discretionary income you have relative to the people matching your profile. In contrast to your positive result, a negative CDI index score means that you have on average less discretionary income than similar others.’
To further reinforce this manipulation, participants are given feedback about their financial situation. The financial non-deprivation condition is presented with a text telling them they have an adequate amount of financial resources, relative to others. They are then asked to think about how it feels to be financially adequate and to have sufficient money to use at their will or when required in daily life, relative to other people who do not, and to write their considerations about this in a short essay. Participants in the financial deprivation condition are told that they lack financial resources, relative to others, and are asked to consider the factors limiting such financial resources (e.g. mortgage or rent, expenses, lack of income, etc.). Similar to the first group, they are then asked to briefly report in writing their feelings on being financially deprived and not having sufficient money to use at their will or when required in daily life, relative to those who have more than sufficient disposable income and financial resources. (See Appendix 2).
Delay Discounting – DV. The measurement is the same as in Study 1 (see 3.1.1.2 Measures)
with the only difference that only two future points are used, i.e. 6 months and 9 months.
Episodic Cue Generation – Moderator. The manipulation of EFT is the same as for Study 1
(see 3.1.1.2 Measures), with the difference that participants in the EFT condition write about 6 months and 9 months, while those in the ERT condition write about 6 hours and 9 hours from now.
Future-Self Connection – Mediator. This measure is adopted from Ersner-Hershfield et al.
(2009). Participants are asked to indicate how similar/connected or dissimilar/disconnected they feel to their future-self at each of the two time delays (i.e. 6 months and 9 months) on a 7-point scale (1 = disconnected, 7 = connected). The scale consists of two circles arranged from no overlap (i.e., no similarity between the current self and future self) to almost complete overlap visually representing maximum similarity connection (see Appendix 3).
Subjective Time Perception – Mediator. Participants answer the question ‘How long do you
Affective States – Mediator. Using the 20 items PANAS (positive and negative affect
schedule) scale developed by (Watson, Clark, & Tellegen, 1988), participants’ Affective States are measured. Participants indicate to what extent they feel each of the states at that moment on a 5-point scale (1=not at all, 5=extremely). The 10 positive items are averaged into a positive
affect variable and the 10 negative items into a negative affect variable.
Additional Measures. The same variables as for Study 1 (see 3.1.1.2 Measures). In addition,
personal annual income is measured using 20 income brackets with $10,000 increments, ranging from 1 (under $10,000) to 20 ($190,000 or more).
3.2.2 Results
3.2.2.1 Data Inspection and Sample Characteristics
For Study 2, we recruited 803 participants. In total, 67 participants are excluded from the analysis, as they did not complete the survey, failed the attention check, or wrote texts that clearly indicated that they did not do the task properly. This yielded a final sample of 736 participants (448 females, Mage = 37.26, SDage = 10.76). Subjects’ annual income, based on the
bracket they chose (M = 4.99, SD = 3.72), ranged from 1 to 20 and was non-normally distributed with skewness of 1.66 (SE = 0.09). Table 3 below displays the frequencies for the demographic variables ethnic background, employment status, and education.3
Ethnic Composition Emploment Status Education
n % n % n %
European-American 550 73.6 Full-time 413 55.3 Still attending high school 1 0.1
African-American 64 8.6 Part-time 126 16.9 High school diploma or GED 190 25.4 Hispanic 34 4.6 Self-employed 81 10.8 Associate / vocational degree 407 54.5
Asian-American 44 5.9
Unemployed but
looking for a job 35 4.7 College / University degree 94 12.6
Native-American 6 0.8 Retired 16 2.1 Master’s degree 5 0.7 Pacific
Islander 2 0.3
Housewife or
househusband 52 7.0
Doctoral student / Holder of
a doctoral degree 24 3.2 Other 36 4.8 Unable to
work/Other 13 1.7 Other 15 2.0
Table 3. Frequency tables for the demographic variables Ethnic Composition, Employment Status, and Education
3.2.2.2 Financial Deprivation, EFT, and Delay Discounting
We subject participants’ AUC to a 2 (financial status: financially deprived vs. financially non-deprived) x 2 (episodic cues: EFT vs. ERT) between-subjects ANOVA. The results reveal a main effect of financial status, F(1,735) = 13.104, p < 0.001, η2p = 0.018, a main effect of
episodic future thinking, F(1,735) = 5.433, p = 0.02, η2p = 0.007, and the critical two-way
interaction between financial status and EFT, F(1,735) = 8.316, p = 0.004, η2p = 0.011 (see
Figure 2 and Figure 3).
Figure 2 & Figure 3. The Area Under the Discounting Curve (AUC) for each experimental condition. A smaller
AUC indicates a higher preference for smaller-sooner payoffs (i.e., increased DD)
Analysis of simple effects reveal that, in the deprived condition, participants who episodically thought about their future (M = 0.62, SD = 0.18) showed less delay discounting (i.e., larger AUC) than did those in the episodic recent thinking condition (M = 0.56, SD = 0.17; F(1,735) = 13.698, p < 0.001, η2p = 0.018, 95% CIMean-Difference [0.033, 0.106]). This is consistent with
our Hypothesis 1a. In the ERT condition, participants who felt financially deprived (M = 0.56, SD = 0.17) showed increased preferences for smaller-sooner rewards (i.e., smaller AUC) compared to their non-deprived counterparts (M = 0.64, SD = 0.19; F(1,735) = 21.783, p < 0.001, η2
p = 0.029, 95% CIMean-Difference [-0.123, -0.050]). This replicates past findings that
financial deprivation increased delay discounting (supports H1b). Nevertheless, among participants in the EFT condition, there is no significant difference in delay discounting whether they felt financially deprived (M = 0.62, SD = 0.18) or non-deprived (M = 0.63, SD = 0.19; F < 0, p = 0.608, η2
p = 0.000, 95% CIMean-Difference [-0.047, 0.028]). This suggests that episodic
future thinking eliminated the gap in delay discounting between those who felt financially
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 Financially
Deprived Financially Non-Deprived
Ar ea u nd er th e Di sc ou nt in g Cu rv e ERT EFT 0,5 0,52 0,54 0,56 0,58 0,6 0,62 0,64 0,66 Financially
Deprived Financially Non-Deprived
deprived and those who did not. Overall, these results confirm the central hypothesis of this research. That is, EFT moderates the link between financial deprivation and delay discounting, such that EFT effectively mitigates negative consequences of feeling financially deprived on delay discounting.
3.2.2.3 Testing the Role of Future-Self Connection
Results of a 2 (financial status: deprived vs. non-deprived) × 2 (episodic cue: ERT vs. EFT) between-subjects ANOVA on participants’ future-self connection reveal a main effect of financial status, F(1,735) = 5.795, p = 0.016, η2p = 0.008, such that those who did not feel
financially deprived had a higher future-self connection (M = 5.06, SD = 1.64) than those who felt financially deprived (M = 4.76, SD = 1.75). In addition there is a critical two-way interaction between financial status and EFT, F(1,735) = 5.190, p = 0.023, η2p = 0.007.
However, there is no main effect of episodic future thinking, F < 0, p = 0.897 (see Figure 4).
Figure 4. Future-self connection as a function of financial deprivation and episodic future thinking
The analysis of simple effects reveals that, in the financially deprived condition, participants who thought about the future have a higher future-self connection (M = 4.90, SD = 1.68) than those who did not (M = 4.60, SD = 1.82; F(1,735) = 2.918, p = 0.088, η2
p = 0.004, 95% CI Mean-Difference [-0.065, 0.646]). This effect is close to being significant. Also, in the financial
non-deprivation condition, there is no significant difference in one’s future-self connection between those who engaged in future thinking (M = 4.92, SD = 1.62) and those who did not (M = 5.19, SD = 1.65; F(1,735) = 2.292, p = 0.13, η2p = 0.003, 95% CIMean-Difference [-0.616, 0.080]). In sum,
this suggests that episodic future thinking did not significantly boost future-self connection among both participants in the future or recent condition. However, among those in the ERT
1 2 3 4 5 6 7
Financially Deprived Financially Non-Deprived
condition, there is a significant difference between those who felt financially deprived (M = 4.60, SD = 1.82) and those who did not feel financially deprived, M = 5.19, SD = 1.65; F(1,735) = 11.305, p = 0.001, η2p = 0.015, 95% CIMean-Difference [-0.927, 0.243]. In sum, this is consistent
with our expectations that EFT fosters future-self connection among the financially deprived, although the effect is only marginally significant. Hence, we proceeded to test whether the effect of EFT on delay discounting of the financially deprived is statistically mediated through the connection to one’s future-self. We used Hayes’ (2013) PROCESS macro (model 8) to test our hypothesis 2. A 10,000- resampled percentile bootstrap revealed a significant indirect effect of financial status × EFT on delay discounting via future-self connection, (moderated mediation index = -0.017, SEbootstrap = 0.008, 95% CI [-0.032, -0.003]). As expected, among the financially
deprived, future-self connection mediated the effect of EFT (vs. ERT) on delay discounting, b = 0.069, SE = 0.019, 95% CI [0.035, 0.106]. However, this was not the case for participants in the financially non-deprived condition, b = -0.007, SE = 0.019, 95% CI [-0.044, 0.030]. These findings support the notion that EFT boosts the future-self connection among the financially deprived, which in turn reduces their tendency of delay discounting. In sum, these results show support for our hypothesis (H2): episodic future thinking boosts one’s future-self connection among those who feel financially deprived, which in turn reduces their delay discounting behavior.
3.2.2.4 Testing the Role of Affect
At first, responses of the positive (α = 0.90) and negative (α = 0.92) affective states are averaged separately to create positive and negative affect indexes. Next, we conducted a 2 (financial status: deprived vs. non-deprived) × 2 (episodic cue: ERT vs. EFT) between-subjects ANOVA on participants’ positive affect. The analysis only finds a critical interaction between financial status and EFT, F(1,733) = 5.260, p = 0.022, η2
p = 0.007. In particular, there is a significant
difference among those who felt financially deprived so that those in the future condition felt more positive (M = 3.33, SD = 1.28) than those in the recent condition, M = 2.962, SD = 1.14; F(1,733) = 8.482, p = 0.004, η2p = 0.011, 95% CIMean-Difference [0.120, 0.615]. In addition, among
those in the recent condition, there is a significant different so that participants who felt financially deprived were less positive (M = 2.96, SD = 1.14) than those who did not feel deprived, M = 3.29, SD = 1.19; F(1,733) = 6.768, p = 0.009, η2
p = 0.009, 95% CIMean-Difference
Next, we used Hayes’ (2013) PROCESS macro (Model 8). A 10,000-resampled percentile bootstrap revealed no significant indirect effect of financial status × EFT on delay discounting via positive affect, index of moderated mediation = 0.001, SEbootstrap = 0.003, 95% CI [−0.004,
0.007]). Consequently, positive affect does not mediate the relationship between financial status x EFT on delay discounting. To confirm this, a follow-up analysis showed that when controlling for participants’ positive affect, the interaction between financial status and EFT on delay discounting remained significant, F(1,732) = 8.278, p = 0.004, η2p = 0.011. However, positive
affect is not a significant predictor of delay discounting, F < 1, p = 0.635. Hence, Hypothesis 3 is not supported and thus, positive affect is not the process behind EFT.
In a similar vein, we ran a 2 (financial status: deprived vs. non-deprived) × 2 (episodic cue: ERT vs. EFT) between-subjects ANOVA on participants’ negative affect. The findings show reveal only a main effect of financial status, F(1,733) = 21.215, p < 0.001, η2
p = 0.028, such
that on average participants in the deprived condition (M = 1.76, SD = 0.93) felt more negative than their non-deprived counterparts did (M = 1.47, SD = 0.79). However, neither the main effect of EFT, F =1.016, p = 0.314, nor its interaction with financial status were significant, F < 1, p = 0.326, suggesting that episodic future thinking did not influence participants’ negative affect in our sample. Consequently, it is unlikely that negative affect mediates the interaction between financial status and EFT on delay discounting. Confirming this, a follow-up analysis reveals that when we controlled for participants’ negative affect, the interaction between financial status and EFT on delay discounting remained significant, F(1,732) = 7.467, p = 0.006, η2
p = 0.01. Yet, negative affect is a significant predictor of delay discounting, F = 15.336, p <
0.001. To ultimately confirm that negative affect does not mediate the effect, we used Hayes’ (2013) PROCESS macro (Model 8). A 10,000-resampled percentile bootstrap found no significant indirect effect of financial status × EFT on delay discounting via negative affect, index of moderated mediation=-0.004, SEbootstrap=0.004, 95% CI [−0.013, 0.004]).
Consequently, negative affect does not mediate the effectiveness of episodic future thinking among the poor on delay discounting.
3.2.2.5 Testing the Role of Subjective Perception of Time
The results of a 2 (financial status: deprived vs. non-deprived) × 2 (episodic cue: ERT vs. EFT) between-subjects ANOVA on participants’ subjective perception of time reveal a main effect of financial status, F(1,735) = 4.428, p = 0.036, η2p = 0.006, such that on average those who felt
= 5.373, p = 0.021, η2
p = 0.007, such that on average participants in the EFT condition (M =
65.03, SD = 30.96) perceived the time subjectively closer compared to those in the ERT condition (M = 70.06, SD = 31.13). However, there is no critical interaction between financial status and EFT, F = 1.484, p = 0.223. The latter suggests that these two factors did not have a unique, joint effect on the subjective perception of time. Hence, it is unlikely that the subjective perception of time is a process mediating the interaction between financial status and episodic future thinking on delay discounting. A follow-up analysis reveals that when we controlled for participants’ subjective perception of time, the interaction between financial status and EFT on delay discounting remained significant, F(1,734) = 6.809, p = 0.009, η2p = 0.009. Yet, subjective
perception of time is a significant predictor of delay discounting, F =153.396, p < 0.001, η2p =
0.173.
To completely rule out a moderated mediation, we used Hayes’ (2013) PROCESS macro (Model 8). A 10,000-resampled percentile bootstrap revealed no significant indirect effect of financial status × EFT on delay discounting via subjective perception of time, index of moderated mediation = −0.014, SEbootstrap = 0.011, 95% CI [−0.035, 0.008]). Overall,
Hypothesis 4 is not supported, thus, the effectiveness of EFT among the poor on delay discounting is not driven by the subjective perception of time.
3.2.3 Discussion
Study 2 replicated our findings in Study 1 suggesting that EFT reliably reduces delay discounting. In this study, income is manipulated and thereby introduced a feeling of financial deprivation or financial adequacy. The main analysis finds support for hypotheses 1a and 1b. According to our predictions, results of a 2x2 between-subjects ANOVA and subsequent contrast analyses show that participants feeling financially deprived exhibited an increased preference for immediate rewards in intertemporal choice, compared to those feeling non-deprived. This is consistent with previous research (Mani et al., 2013; Shah et al., 2012). More importantly, among the financially deprived, those who episodically thought about their future showed a reduced delay discounting tendency, compared to those thinking about recent events. Henceforth, EFT moderates the main relationship between perceived financial constraints and delay discounting. Simply put, consistent with our expectation, EFT is more (less) effective in reducing impatience in intertemporal decisions among those who were in the financially deprived (non-deprived) condition.
suggested that future-self connection is one mechanism mediating the relationship between financial deprivation and EFT on delay discounting (supporting H2). Specifically, EFT enhances one’s future-self connection among those who feel financially deprived, which in turn lower their delay discounting tendency. Hence, EFT fosters one’s connection to the future self which resulted in an increased tendency to accept the larger-later monetary payoffs over the immediate ones. However, no statistical support is found for the other potential processes namely, affect (H3) and subjective perception of time (H4). Therefore, we can rule out an affect-based explanation for our results as well as a time perception-affect-based explanation. Overall, the statistics of the main variables, financial (non-) deprivation and episodic future thinking experimental conditions are summarized in Table 4.
Deprived Non-Deprived
EFT ERT EFT ERT
AUC 0.62 (0.18) 0.55 (0.17) 0.63 (0.19) 0.64 (0.19) Future-Self Connection 4.90 (1.68) 4.60 (1.82) 4.92 (1.62) 5.19 (1.65) Positive Affect 3.33 (1.28) 2.96 (1.14) 3.24 (1.24) 3.29 (1.19) Negative Affect 1.69 (0.87) 1.82 (0.98) 1.46 (0.89) 1.47 (0.68) Subjectjective Time Perception 65.98 (30.85) 74.05 (29.74) 63.96 (31.15) 66.47 (31.98)
Sample size per cell (n) 191 180 168 200
Table 4. Summary statistics of the main outcome variables in Study 2, as a function of financial status and EFT
4. GENERAL DISCUSSION
Impulse buying is ubiquitous, with 90% of people making such purchases at least occasionally (Hausmann, 2000), and 80% of people referring to some negative consequences from these purchases (Rook, 1987). This myopic behavior of discounting larger-later payoffs is particularly evident in those who lack financial resources. Specifically, poverty impedes cognitive function, likely because poverty-related concerns consume mental resources, thus leaving less for other tasks (Mani et al., 2013). In addition, impaired executive functions are associated with increased delay discounting (Hinson et al., 2003). Connecting findings in the literature of psychology of poverty and episodic future thinking, we hypothesized and statistically found across two studies that EFT reduces delay discounting of the financially deprived. Particularly, the effect of EFT (manipulated) on delay discounting of the financially deprived (manipulated) was robust and remained significant even after controlling for participants’ demographic and socioeconomic characteristics. Consistent with our proposition, we show that EFT is highly important for the poor as they live more in the present than in the future and thus make impulsive, short-term decisions (Haushofer & Fehr, 2014; Liu et al., 2012). These results show similar patterns and comparable reparative effects to studies that have showed the effectiveness of EFT among those populations that typically have high discounting tendencies and suffer from issues like obesity, gambling, smoking, and alcohol addiction.
Furthermore, we explored the underlying process of EFT and revealed that the effect of future thinking in decreasing delay discounting tendencies is driven by an increase in the connection to one’s future-self. While conflicts between the present and future self lead to impulsive decision making in discounting tasks, a connectedness to one’s future self leads to making choices that are beneficial for the future (Hershfield, 2011). Our findings show that EFT activates thinking and vividly imagining future events, which leads to an enhanced future-self connection. Particularly, those who subsequently perceived their future-self as more similar to their current state feel more connected to it. In turn, this connectedness leads to a greater willingness to delay gratification. Nevertheless, the results also show that a participant’s subjective perception of time, and affective states (positive and negative) did not explain the effect of EFT on delay discounting of the financially deprived.
poverty trap they are caught in. Poverty alleviation is a complex and long process which cannot be overcome by simple psychological interventions. Thus, this research does not aim at arguing that psychological interventions like EFT can replace financial resources. Rather, we pose that EFT can shift the temporal perspective, thereby effectively reducing the present bias of the poor. In particular, EFT allows the financially deprived to make more far-sighted decisions that are better aligned with their long-term benefits and interests. Discounting tasks are relevant in many real-world behaviors such as peoples’ employment and savings decisions, educational investments and their health attitude (Jachimowicz et al., 2017). Advances in understanding delay discounting may provide policymakers with insights into the source of problems they are concerned with. To the degree that discounting adds to these problematic behaviors of the poor, understanding either how to reduce their discounting behavior or how to structure intertemporal choices so as to weaken the impact of time preferences is critical. Second, we contribute to the literature of EFT by extending its reparative effects into economic decisions of those living in poverty. The effectiveness of EFT in reducing delay discounting has been confirmed across a variety of populations who suffer from impulsive decision making, such as obese children (Daniel et al., 2015), obese adults (Daniel et al., 2013b), smokers (Stein et al., 2016) and alcohol-dependent individuals (Snider et al., 2017). With exception (O’Donnell et al., 2018), past research has not examined the effectiveness of episodic future thinking in reducing delay discounting among the low-income people4. Moreover, we explored the underlying process of
EFT. Prior studies have examined the cognitive and neural mechanisms of episodic future thinking, yet we took on a different approach in that we focused on the motivational basis of EFT (i.e. future-self connection). It can be assumed that an individual’s ability to greatly imagine a future event assists in feeling connected to the future (Hershfield & Bartels, 2018; Blouin-Hudon & Pychyl, 2017).
Our work also provides directions for future research. First, most EFT studies have examined the intervention in just one (lab) training session. Future research should consider long-term experiments as these allow to discover differences between intended and actual behavior. The effectiveness of EFT should be studied over time, with the possibility that more extensive training may increase a) the effectiveness of episodic future thinking on delay discounting and b) the types of contexts in which EFT works for the poor. Further investigation is needed to determine the time duration as well as the durability of the effect of EFT.
Second, future research could consider two other potential mechanisms, namely construal level (abstract thinking) and optimism. On the one hand, EFT might modulate intertemporal preference by making the future more concrete, thus changing the construal levels (Lempert & Phelps, 2016; Trope & Liberman, 2003). Relevant in the context of delay discounting, construal level theory (CLT) states that the level of construal covaries with psychological (e.g. temporal) distance. Notably, psychological distance and construal level have a bidirectional relationship, meaning that the level of construal impacts the perception of distance and vice versa (Trope & Liberman, 2010). Cheng, Shein, & Chiou (2012) argue that temporally distant future events might activate high-level construals, which should promote a future-oriented mindset. Yi et al. (2017) have tested the impact of construal level manipulations on delay discounting and found that a concrete construal of the future led to an increased preference for delayed payoffs, compared to concrete construal of the present. This finding is consistent with research on EFT (Daniel et al., 2013a; 2013b; Lin & Epstein, 2014). Taken together, EFT may be conceptualized as an all-concrete manipulation (Rung & Madden, 2018). That is, if the default construal of the smaller-sooner reward is concrete, then thinking vividly about the larger-later one may render its construal to more concrete.
Third, a follow-up study on the underlying mechanism could manipulate the process of the future-self connection in a 2 (financially deprived vs. financially non-deprived) x 2 (EFT vs. ERT) x 2 (future-self connection vs. control) between-subject design. When the process is satisfied or EFT is present, we will hopefully find the same reduced discounting effect. Hershfield et al. (2011) have manipulated future-self connection by exposing participants to visual representations of their age-processed future selves and have found less discounting of future payoffs and higher allocations to saving accounts. As many people fail at saving for retirement, it would be relevant to apply EFT and future-self connection in a savings task. In a similar savings study, O’Donnell et al. (2017) have found that future thinking regarding financial goals strengthens the effect of EFT on reducing delay discounting. Altogether, this might be particularly relevant for the poor as they are more inclined towards buying something now to satisfy the immediate gratification rather than saving that money to achieve a desired financial goal.
Lastly, one limitation of the research is that no support was found for the other two proposed underlying mechanisms. All mentioned process variables have been operationalized in previous papers and are existing, valid scales. Future research may further advance our proposed mechanisms using different measurement scales in order to find another underlying processes mediating the interaction effect between financial deprivation and delay discounting.
5. CONCLUSION
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