Expense Neglect in Forecasting Personal Finances

EXPENSE NEGLECT 1 Expense Neglect in Forecasting Personal Finances Jonathan Z. Berman An T. K. Tran John G. Lynch, Jr. Gal Zauberman AUTHORS NOTE Jonathan Z. Berman (jberman@london.edu) is an Assistant Professor of Marketing at the London Business School; An T. K. Tran (att57@drexel.edu) is an Assistant Clinical Professor of Marketing at the LeBow College of Business, Drexel University; John G. Lynch, Jr. (john.g.lynch@colorado.edu) is the Ted Andersen Professor of Free Enterprise at the Leeds School of Business, University of Colorado Boulder; and Gal Zauberman (gal@wharton.upenn.edu) is the Laura and John J. Pomerantz Professor of Marketing and Professor of Psychology at The Wharton School, University of Pennsylvania. The authors would like to thank members of the Consumer Financial Decision Making Lab group at the University of Colorado and seminar participants at Erasmus University, INSEAD, UC-Berkeley, Yale University, the Utah Winter JDM Symposium, and the University of Pennsylvania. Correspondence concerning this article should be addressed to the first author.

EXPENSE NEGLECT 2 ABSTRACT This paper shows evidence for expense neglect in how consumers forecast their future spare money or financial slack. Even though people generally think that both their income and expenses will rise in the future, we find that they systematically under-weigh the extent to which their expected growing expenses will cut into their spare money (Studies 1-9). We rule out the possibility that these findings are due to: measurement error (Studies 2-5); a lack of confidence in estimating future expenses (Study 6); belief in greater flexibility of future expenses (Study 7); or a general optimism bias (Study 8). Study 9 shows that consumers who are chronically attuned to expenses (tightwads) are less likely to show expense neglect than those who are not (spendthrifts). Finally, we conduct a meta-analysis of our entire file-drawer (25 studies, 7,214 participants) and find that across all studies participants place about 2.7 times the weight on income change as they do on expense change when forecasting their financial slack, and that expense neglect is stronger for the distant than near future. Keywords: Forecasting, Financial Slack, Personal Finance, Expense Neglect

EXPENSE NEGLECT 3 Successfully managing one s personal finances is rarely straightforward. It is a complex problem to balance how much to spend and save each month in order to put one s hard earned money to its best use. When making monetary decisions, consumers often have to assess the overall state of their finances in order to maximize long-term wellbeing. These subjective assessments depend not just on consumers perceptions of their current bank account balances, but also on how their finances will change over time. Someone who is starting a new job may wonder whether to put away money for retirement immediately, or if he can afford to put it off until he gets his next raise. A couple looking to purchase a new home may ask if they will be able to afford to keep up with mortgage payments in the nicest part of town if and when they have children. A student with credit card debt must determine whether she will be able to afford to repay her next purchase plus interest once she graduates and hopefully gets a job. Mispredicting the state of one s future personal finances can be highly consequential. Those who mistakenly believe that they will have significantly more spare money in the future may choose to take out loans they will not be able to repay or may put off saving for retirement until it is too late (Thaler and Benarzi 2004; Lynch and Zauberman 2006). Those who mistakenly believe they will have more constrained resources in the future than reality may fail to spend enough money in the present and will miss out on essential life experiences (cf. Kivetz and Keinan 2006). Further, recent research shows that perceived resource availability significantly affects consumers thoughts, preferences, and actions. The more available resources consumers expect to have in the future, the more likely they discount delayed expenditures of the resource (Zauberman and Lynch 2005). Those who feel financially constrained are more likely to focus attention on solving financial problems in the present at the cost of the future (Shah,

EXPENSE NEGLECT 4 Mullainathan, and Shafir 2012) and are more likely to prefer scarce rather than abundant products (Sharma and Alter 2012). More broadly, indices such as the GfK NOP Consumer Confidence Barometer, the Bloomberg-Nanos Canadian Confidence Index, the Conference Board s Consumer Confidence Survey, and the University of Michigan Consumer Sentiment Index (MCSI) attempt to measure consumer s feelings about the state of their finances in order to provide meaningful inputs for manufacturers, retailers, and governments to manage their output. Greater consumer confidence signals that households feel positive about their future finances, and businesses should adjust their production in order to respond to the likelihood of stronger demand. These considerations motivated us to study how consumers form subjective assessments of their finances in the future. Although consumers often feel financially constrained in the present moment, they often view the future more favorably. We examined the entire MCSI data set, from 1978 to 2013, and found that Americans consistently anticipated that their finances would improve in the future. When asked to estimate their family s finances in a year s time, more respondents indicate that they expect their future finances to be better off than worse off in 407 out of 425 months. More recently, in the period from 2010 to 2013 the time period covering 24 of our 25 studies more consumers expected that their financial situation to be better off than worse off in 47 out of 48 months. In contrast, the most recent Federal Reserve Survey of Consumer Finances shows that during the same period, median net worth of all families fell by two percent (Bricker et al. 2014). In other words, despite households being on average worse off in 2013 than they were in 2010, they still consistently forecasted their future finances favorably over this period.

EXPENSE NEGLECT 5 In the present research, we consider one reason why consumers view their future finances favorably by examining subjective feelings of financial slack. We define financial slack as the perceived surplus (or lack) of spare money an individual has at a given point in time (Zauberman and Lynch 2005). At a fundamental level, the amount of financial slack consumers have at a given point in time is a function of their income (inflow) and expenses (outflow). Whereas increasing income contributes to having more financial slack, increasing expenses decreases financial slack. The above analysis of the MCSI may suggest that consumers are optimistic about their future finances, and thereby consistently believe that their finances will improve with time. However, we explore a different explanation, namely that consumers improperly account for their expenses (and consequently under-weigh growth in expenses) when forecasting their finances. Specifically, we examine how consumers utilize their own stated assessments of their income and expenses to determine how much financial slack they will have in the future. Our main interest is in evaluating the weight that consumers place on their anticipated income and expenses in predicting their future financial slack. By weight, we mean the extent to which consumers consider their own income and expenses expectations to determine how much financial slack they will have in the future. This question is different from research that examines how accurate consumers are in their predictions about their income or expense estimates (Peetz and Buehler 2009, 2012; Sussman and Alter 2012; Ülkümen, Thomas, and Morwitz 2008). Rather, we re interested in how consumers form subjective estimates of their future finances, given their own stated assessment of changes in their future income and expenses. Objective and Subjective Determinants of Available Financial Resources

EXPENSE NEGLECT 6 Subjective feelings of financial slack represent the extent to which consumers believe that they are in a surplus or deficit state with respect to their available spare money. When assessing the future financial slack, income and expenses are equally relevant. It s simple arithmetic. In any given period, consumers generate financial resources and spend them. The amount of available slack that a consumer expects to have in a given period should be related to the stock of that slack account in the prior period plus inflows of income minus the outflows of expenditures in the most recent period. Inflows include salary, bonuses, investment returns, social security checks, interest, etc., whereas outflows include money spent on rent, bills, travel expenses, entertainment as well as savings commitments, debt payments, donations to charity, etc. If the mental models of financial slack matched the accounting rules of bank balances, as it should, then a dollar of inflow would have exactly the same weight in predicting future slack as a dollar of outflow. For example, a waitress who needs an extra $80 a month in spare money can achieve her goal either by raising her income (e.g., working an extra shift that will garner her $80 in after-tax cash) or by cutting her expenses (e.g., suspending her $80/month cable package). That is, the weights of inflows (income) and expenses (outflows) in affecting slack should be equal and opposite in sign. However, we find that people systematically under-weigh their own stated expenses relative to income, and therefore rely too heavily on forecasts of income when predicting their future finances. Because income and expenses are weighed equally in actual bank balances, it may not seem difficult to forecast changes in spare money over time. However, existing research demonstrates that it is surprisingly difficult to estimate dynamic systems with inflows and outflows, suggesting that forecasting future spare money may not be so simple. Most people are flummoxed by even basic stock-flow problems, such as predicting the number of people in a

EXPENSE NEGLECT 7 department store with people entering and exiting at different rates (Booth Sweeney and Sterman 2000; Cronin and Gonzalez 2007; Cronin, Gonzalez and Sterman 2009; Sterman and Booth Sweeney 2002). Forecasting finances into the future is even a more difficult stock-flow problem than those studied previously. With financial decisions, expected changes over time in income and expenses are not independent. Those who get a raise often expect to increase their spending; those who lose a source of income often expect to cut their spending. Thus, when forecasting spare money into the future, consumers need to also account for how consumption and expenses rise with increases in income. Expense Neglect in Forecasting Financial Slack In the studies we present, we show that consumers neglect to properly account for their own stated expenses relative to income when forecasting their financial slack. In each study, we ask participants to estimate how their income, expenses, and subjective financial slack (i.e., spare money ) will change over time. We then use each individual i's own predictions of how their stated income and expenses will change over time to predict that person s own estimates of how slack will change over time, as represented in equation 1. (1) Slack Change i = β 0 + β 1 (Income Change i ) + β 2 (Expense Change i ) + ε i Under the model in equation 1, three conditions should hold. First, controlling for expense changes, income changes should be positively associated with slack changes; as income increases, so does spare money. Second, controlling for income changes, expense changes should

EXPENSE NEGLECT 8 be negatively associated with slack changes; as spending increases, spare money decreases. Third, and most critically, the weight of a unit change in income change should be equal to the weight of a unit change in expenses (β 1 = -β 2 ), since a dollar increase in income should have the same impact on financial slack as a dollar decrease in expenses. However, we find robust evidence that people do not properly weigh their own reported expense change when estimating their future money slack change. We report in detail 9 of the studies we have conducted, as well as a meta-analysis of our entire file drawer of 25 studies (N = 7,214). We have four main findings. First, consumers expect their incomes to increase in the future, and more so in the distant than near future. Second, consumers expect their expenses to increase in the near future, and expect larger increases in the distant future. Third, consumers expect to have more financial slack in the near future than today, and expect larger increases in the distant future. Our primary finding, though, is that predictions of changes in financial slack are much more driven by expected changes in income than by expected changes in expense a pattern we call expense neglect. When participants are asked to forecast how much financial slack they will have in the future, participants rely heavily on their own income forecasts and neglect or underweigh their own expense forecasts (i.e., in equation 1, β 1 > -β 2 ). In other words, while people do expect that their expenses will rise slightly in the future, they do not properly adjust their estimates of their future financial slack to capture these expectations. Expense Neglect is Neither a Form of the Planning Fallacy nor an Optimism Bias Before reporting our studies in detail, we next articulate what we are not studying as we have found in presenting this work that audiences tend to expect our findings to connect to

EXPENSE NEGLECT 9 literatures that are different from our focus. We are not studying some form of a planning or budget fallacy (Buehler, Griffin and Ross 1994; Kahneman and Tversky 1979; Peetz and Buehler 2009). Overestimating changes in income or underestimating changes in expenses could lead consumers to falsely expect that spare money will increase in the future. However, our focus in this research is not on whether consumers are accurate in their predictions of future income, expenses, or financial slack (cf. Peetz and Buehler 2009; 2012; Sussman and Alter 2012; Ülkümen, Thomas, and Morwitz 2008). Rather, we are interested in the weighting of income and expenses to predict financial slack. Similarly, the effects we show are unrelated to any form of generalized optimism bias (cf. Puri and Robinson 2007). If consumers are generally optimistic, they may anticipate having greater income and few expenses than in reality. However, regardless of how accurate consumers are in their predictions, we can still evaluate how their income and expense estimates feed into their slack estimates. Expense neglect predicts that consumers will primarily base their estimates about their future financial slack on their own income estimates, and will not sufficiently account for their own expense estimates. One might nonetheless argue that expense neglect is a special case of optimism bias. Perhaps the relative weights of income and expenses in predicting future spare money are a function of optimism. We examine this directly by measuring individual differences in optimism in Study 8, and find that while optimistic people expect to have greater future income and fewer future expenses than pessimists, optimism does not affect the relative weighting of income or expenses. OVERVIEW OF STUDIES

EXPENSE NEGLECT 10 Nine studies show that consumers exhibit expense neglect when forecasting their future financial slack. Study 1 shows evidence for expense neglect in forecasting future slack across a range of samples taken from participants with varying financial conditions. Studies 2 5 show that these results hold through multiple ways in which slack, income, and expenses are measured. Studies 6 9 examine possible causes of expense neglect. We first show that this effect cannot be explained by greater confidence in predictions of future income than in predictions of future expenses (Study 6), beliefs about increasing flexibility regarding future expenses (Study 7), or by a general optimism bias (Study 8). We test an attention account, and show that those who are chronically attuned to expenses are more likely to account for expenses in their forecasts of spare money (Study 9). Finally, we present a meta-analysis of our entire file-drawer, which covers 25 separate studies and 7,214 participants. Across studies we find that consumers place about 2.7 times the weight on standardized income change as they do on standardized expense change, and that expense neglect is more prominent for forecasting the more distant versus the near future. STUDY 1: EXPENSE NEGLECT ACROSS VARYING POPULATIONS Study 1 examines how consumers attend to their expected income change and expense change when estimating how their financial slack will change with time. We followed Cook and Campbell s (1979) research strategy of deliberate sampling for heterogeneity by examining four different groups with varying financial circumstances and different realistic prospects for improvement in the near future (employed, unemployed, executives, and students). Method

EXPENSE NEGLECT 11 We conducted three initial surveys in October and November of 2011 across different populations. Survey 1 was administered to 300 participants (51.7% female; mean age = 47.5) via a national online panel. This survey sampled equal groups of those who were employed full time, employed part time, unemployed, and out of the labor force. The first two groups were combined to create a sample of 150 employed participants (53.3% female; mean age = 46.4) and the latter two were combined to create a sample of 150 unemployed participants (50.0% female; mean age = 48.6). Survey 2 was administered to 216 students (52.2% female; mean age = 20.4) at a private northeastern university. Survey 3 was administered to 64 business executives from an online panel (15.6% female; mean age = 48.7). Participants first estimated their spare money over this week, a week in three months, and a week in twelve months on an 11-point scale ranging from 1 = Very little spare money to 11 = A lot of spare money. Next, participants estimated their expected change in income and expenses in three and twelve months on an 11-point scale anchored by -5 = I expect my income [expenses] to greatly decrease ; 0 = I expect my income [expenses] will remain the same ; and +5 I expect my income [expenses] to greatly increase. In the present study, participants indicated their expected income change before indicating their expected expense change. In all subsequent studies, we counterbalance the presentation order of these questions. Results Slack, Income and Expense Change: Slack change scores were calculated by subtracting individual ratings of future slack from ratings of current slack for each time period. Figure 1a displays expected slack change for each sample, while Figure 1b displays expected changes in income and expenses for each sample.

EXPENSE NEGLECT 12 ---Insert Figures 1a and 1b about here--- On average participants in each sample estimated that their income and expenses will increase from the present to three months in the future. We reject the null hypothesis that changes = 0 (all Ms > 0.45; one-sample ts > 3.15, ps <.002). This pattern is even more pronounced when comparing the present to twelve months in the future. Participants in all groups expected that their income and expenses to increase more in twelve months as compared to three months (paired ts > 2.30, ps <.025). Predictions of Slack Growth: We examined the extent to which participants weighed income changes versus expense changes when estimating their future financial slack growth. Across all participants we ran separate regressions for the three months and twelve months time periods. Each regression included income change, expense change for the ith respondent in group j, a dummy code for the separate groups as our independent variables, and slack change as our dependent variable. We refer to this as the full model : (2) SlackChange ij = β 0 + β 1 (Income Change ij ) + β 2 (Expense Change ij ) + β 3-5 (Group j ) + ε ij Results show significant expense neglect. When estimating slack change in the short term (this week vs. three months), greater income change led to greater slack change (β =.27, SE =.05; t(574) = 5.41, p <.001), but expected expense change did not significantly influence slack change (β =.04, SE =.06; t(574) =.69, p =.49). Similarly, when estimating slack change in the long term (this week vs. twelve months), greater income change lead to greater slack change (β

EXPENSE NEGLECT 13 =.46, SE =.06; t(574) = 8.13, p <.001), but expected expense change did not significantly influence slack change (β = -.04, SE =.06; t(574) = -.70, p =.49). We employed the following model comparison test to evaluate whether the coefficient on income is significantly larger in magnitude than the coefficient on expenses to show that people under-weigh expenses relative to income. This test compared the fit of the regression above (the full model) to a constrained model that sets income and expenses to have equal and opposite signs. The constrained model for Study 1 is listed below: (3) SlackChange ij = β 0 + β 1 (Income Change ij Expense Change ij ) + β 2-4 (Group j ) + ε ij If participants weigh expense change and income change equally, then a constrained model that requires income and expenses to have equal and opposite signs (equation 3) should not fit worse than the full model where the parameters on income and expenses are not constrained (equation 2). However, if participants are weighing income and expenses unequally, then the full model should fit significantly better than the constrained model. Results show that the full model that allows the weights of income and expenses to vary 2 independently fits significantly better than the constrained model for both the three month (R Full 2 2 =.06 vs. R Constrained =.02; F(1, 574) = 20.74, p <.001) and twelve month (R Full =.12 vs. 2 R Constrained =.07; F(1, 574) = 33.48, p <.001) time periods. Clearly, participants are not attending to income and expenses equally. We further examine the robustness of these results by evaluating each of the four groups separately. Table 1 displays these results along with the results from a model comparison that compares the full versus the constrained model for each group.

EXPENSE NEGLECT 14 ---Insert Table 1 about here--- Note that the lower weight of income compared to expenses is not an artifact of correlation between income and expense predictors. The within-sample correlations between income growth and expense growth are relatively low (rs <.35), and we see low variance inflation factors across all regressions (VIFs < 1.14; Cohen, Cohen, West and Aiken 2003). In all subsequent studies, we find no evidence for multicollinearity affecting our results. Further, multicollinearlity cannot explain the significantly better fit of equation 2 compared to equation 3. Discussion Study 1 demonstrates expense neglect across four samples of markedly different respondents. Even though participants anticipated their expenses going up in both the near and distant future, they do not take this into account when forecasting their future spare money. For the twelve months time period, only the executives did not show a significant degree of expenses neglect, although their pattern of coefficients on income and expenses was similar to those in the other groups. STUDIES 2 5: MEASURMENT ERROR DOES NOT EXPLAIN EXPENSE NEGLECT In Studies 2-5, we rule out a number of alternative explanations that would suggest these results are due to ways in which we measure income, expenses, and financial slack. Specifically, we show that this effect holds when we: (1) explicitly define income and expenses to each participant; (2) adjust the current time period for estimates of income, expense, and

EXPENSE NEGLECT 15 slack from a week to a month which reflects a more natural time frame for evaluating finances; (3) take estimates of income and expenses at two points in time rather than asking about changes over time; (4) account for any scale compatibility effects by having participants evaluate financial slack in terms of constraint as opposed to spare money ; (5) use a multi-scaled measure of slack that reflects more specified of assessments of financial slack; and (6) estimate income and expenses using both a modulus and dollar estimates to control for different uses in the response scale. Each study was run on Mechanical Turk. Additional details pertaining to each study can be found in Web Appendix A. Across all subsequent studies in the manuscript, we make the following changes. First, we counterbalance the order of the slack questions with the income and expense questions. Second, we explicitly define income and expenses to participants. For the income question, participants read, We would like for you to think about your monthly income. This includes all the money that you will earn from salary, bonuses, social security checks, interest, alimony receipts, etc. For the expenses question, participants read, We would like for you to think about your monthly expenses. This includes all the money that you spend in a given month such as your rent, bills, travel expenses, entertainment etc. as well as any savings commitments, debt payments and donations to charity. Third, we adjust the time period for estimates of income, expense, and slack from a week to a month, which reflects a more natural time frame for participants to evaluate their finances. Study 2: Estimating Future Financial Constraint Does Not Increase the Weight Placed on Expenses

EXPENSE NEGLECT 16 Study 2 (N = 302) makes two changes to the design in Study 1, in addition to those mentioned in the preceding paragraph. We ask participants to make static estimates of income and expenses at two points in time rather than asking participants to report estimate changes over time. Specifically, participants estimated the amount of income and expenses they expect to have next month and over a month in two years from now (on 11-point scales anchored by 1 = Very little to 11 = A lot ). We also test whether a scale compatibility effect is driving our results (Slovic, Griffin, and Tversky 1990; Tversky, Sattah, and Slovic 1988). Both income and spare money may be associated with inflows that create wealth, whereas expenses are associated with outflows that inhibit wealth accumulation. It may be that when participants think about spare money, they are more likely to attend to income, an input that contributes to spare money, rather than expenses, an output that reduces spare money. To test this, half the participants estimated their financial constraint, a measure that is presumably more associated with outputs that limit wealth, whereas the other half of participants estimated their spare money, as in the previous study. We first examined whether asking participants about their spare money versus financial constraint affected the weight of income change and expenses change on slack change. The financial constraint measure was reverse-coded such that higher numbers indicated more financial slack. Change scores were computed to determine how much participants expected their income, expense, and slack to increase or decrease in the future. Next, we ran the following regression: (4) Slack Change = β 0 + β 1 (Response Scale) + β 2 (Income Change i ) + β 3 (Expense Change i ) + β 4 (Response Scale*Income Change i ) +

EXPENSE NEGLECT 17 β 5 (Response Scale*Expense Change i ) + i Response scale was contrast coded (-1 = Financial Constraint, +1 = Spare Money). Results show that neither the response scale by expenses change interaction (t(296) = -.19, p =.85) nor the response scale by income change interaction (t(296) =.09, p =.93) were significant, suggesting that the response scale did not affect the weight placed on either income or expense change when estimating slack. There was also no simple main effect of response scale on slack change when income change and expense change were coded as zero (t(296) = -.80, p =.42). We collapsed across response scale and regressed slack change on income change and expense change to test for expense neglect. We replicate expense neglect, finding that the coefficient on income change (β =.47, SE =.06, t(299) = 7.98, p <.001) is 2.5 times the size of the coefficient on expense change (β = -.19, SE = 0.06, t(299) = -3.44, p <.001). Further, the full model (R 2 =.19) that allowed the income change and expense change parameters to vary explains significantly more variance than the constrained model where income and expenses are fixed to have equal and opposite signs (R 2 =.15; F(1, 299) = 13.60, p <.001). Study 3: Multi-Item Measures of Financial Slack Does Not Eliminate Expense Neglect In Study 3 (N = 74), we test for the possibility that participants are interpreting spare money and financial constraint more broadly than intended. We account for this possibility by introducing an additional financial slack measure that asks participants how likely they would be able to make an emergency repayment of a given amount out of their liquid discretionary funds. A measure that asks participants about their ability to make a fixed payment out of their liquid

EXPENSE NEGLECT 18 funds is robust to different ways in which people may be thinking about financial slack, and also excludes any wealth effects that may arise from the purchase of illiquid assets. 1 Participants were asked about their personal finances next month and in two years time. We created a three-item measure of financial slack that included the spare money and the reverse-coded financial constraint measures used in the previous study, and the following likelihood of repayment question: Imagine that next month [in 24 months] you had an unexpected expense of $1,500 such as a medical bill or a necessary car repair. How likely is it that you would be able to pay this bill in full and on time without having to dip into your retirement fund, borrow money, or charge it to a credit card? on a scale ranging from 1 = Very unlikely to 11 = Very likely. We replicate expense neglect using a three-item measure of slack change (α =.69). We first ran a regression with income change and expense change to predict slack change. The coefficient on income change (β =.81, SE =.13, t(71) = 6.24, p <.001) is 2.0 times the size of the coefficient on expense change (β = -.41, SE =.13, t(71) = -3.10, p =.003). Further, the full model (R 2 =.36) that allows the income and expense parameters to vary explains significantly more variance than the constrained model where income and expenses have equal and opposite signs (R 2 =.30; F(1, 71) = 6.88, p =.011). Importantly, our results replicate if we only evaluate the likelihood of repayment item as the measure of financial slack. In this case, the coefficient on income change (β =.93, SE =.22, t(71) = 4.23, p <.001) is 3.4 times the size of the coefficient on expense change (β = -.27, SE =.23, t(71) = -1.19, p =.003), and the full model (R 2 =.20) explains a significantly greater 1 For instance, consider an individual who expects to receive a raise in the future, and expects to spend the money on an illiquid asset, such as a mortgage. It is possible that this person would indicate an increase in income (the raise), expenses (the mortgage payment) and financial slack (a wealth increase due to the mortgage), a pattern of results that would appear as if this person was neglecting expenses.

EXPENSE NEGLECT 19 amount of variance than the constrained model (R 2 =.13; F(1, 71) = 6.66, p =.012). This increases our confidence that our core effect is not due to the way that participants were thinking about the subjective financial slack questions used in the previous studies. Study 4: Ruling out Response Language Using Magnitude Estimation In the previous studies, we utilize an 11-point ratings scale to evaluate participants estimations regarding their income and expenses. It is possible that consumers are using the scale to rate their income differently from the way in which they use the scale to rate their expenses (Lynch, Chakravarti, and Mitra 1991). If so, then we may not be accurately measuring differential weighting of participants true feelings about how their income and expenses will change in the future. In Study 4 (N = 244), we examine whether the use of a modulus to measure income and expense change can account for expense neglect. The use of a modulus is a standard technique in magnitude estimation in psychophysics to keep estimations on a common scale (Stevens 1957). In all conditions, participants estimated their available financial slack in the current month, 3 months later, 12 months later, and 36 months later using a single item that asked participants to rate their available spare money on the same 11-point scale used Studies 1-3. There were two different measurement conditions for income and expense. In the Ratings Scale condition, participants rated their monthly income and expense change in 3, 12, and 36 months on an 11-point scale. In the Modulus condition, participants were asked to imagine a pile of 100 poker chips that represent the size of their current income. Participants were then instructed to write down how many poker chips would represent their income in 3, 12, and 36 months. Participants used the same procedure to estimate their change in expenses over this time. Finally,

EXPENSE NEGLECT 20 participants were asked to set their current income at 100 poker chips and were asked to tell us how many poker chips represented their current expenses. This was used to scale current income to current expenses. For brevity, we present the results for the 12 months time frame below. The results for 3 and 36 months are presented in Web Appendix A. Participants in the Modulus condition showed significant expense neglect. We log transformed the income and expenses change measures (ln +1), which greatly increases the fit of our full model (R 2 =.20) compared to using raw values (R 2 =.11). We regressed slack change on ln(income change +1) and ln(expense change +1). The coefficient on income change (β = 1.02, SE =.19, t(116) = 5.32, p <.001) is 3.9 times the size of the coefficient on expense change (β = -.26, SE =.21, t(116) = -1.23, p =.22). Further, the full model (R 2 =.20) that allows the income and expense parameters to vary explains a significantly greater amount of variance than the constrained model where income and expenses have equal and opposite signs (R 2 =.12; F(1, 116) = 11.47, p =.001). The reader may notice a change in the predictions of the normative model with equal weights on income and expense when calculating coefficients based on log transformations. With log transformations, the coefficient on the income and expense change now represents a percentage change rather than an additive change. As a result, the coefficient compares increases in percentage changes of income and expenses. However, if average current income is greater than average current expenses as is the case in the present study then the log model suggests that the coefficient on expenses normatively should be greater than the coefficient on income. To illustrate, consider someone who currently makes $2,000 in income and spends $1,000 in expenses per month. Now, imagine that this person s income increases by 10% to $2,200, which corresponds to a $200 increase in slack. In order to match this increase in income with a decrease

EXPENSE NEGLECT 21 in expenses, this person s expenses would need to decrease by 20% so they are spending $200 less per month. In this case, a 10% increase in income is equal in weight to a 20% decrease in expenses. As a result, the equal weights model presents a conservative test of expense neglect. Expense neglect was again found in the Ratings Scale condition. We ran a regression with income change and expense change to predict slack change. The coefficient on income change (β =.92, SE =.12, t(122) = 7.82, p <.001) is 1.5 times the size of the coefficient on expense change (β = -.60, SE =.12, t(122) = -5.10, p <. 001). Further, the full model (R 2 =.37) that allows the income and expense parameters to vary explains a significantly greater amount of variance than the constrained model (R 2 =.34; F(1, 122) = 5.31, p =.022). In sum, study 4 shows that our results hold when using a common scale to measure income and expense change. Note that even though the modulus uses a common scale, the Ratings Scale condition still does a better job of explaining the observed data (R 2 Modulus =.20 vs R 2 RatingsScale =.34), a result that holds across all time periods. This supports the notion that participants are not using the response scales differently when evaluating income and expenses, and ratings scales are sufficient for estimating perceptions about income and expenses. 2 Nonetheless, in the next study, we ask participants to estimate their income and expenses using dollars, another common scale that may be more natural for participants to evaluate. Study 5: Measuring Income and Expenses in Dollars Does Not Eliminate Expense Neglect 2 One might conjecture that ratings scale produces a better model fit because slack is also measured using the same scale. We conducted a replicate of the present study with university students (N = 208), but used a modulus to measure financial slack instead of a ratings scale. We find that using a ratings scale to measure income and expenses fits the data better across 3 months (R 2 Modulus =.19 vs R 2 RatingsScale =.27) and 12 months (R 2 Modulus =.07 vs R 2 RatingsScale =.10), though not for 36 months (R 2 Modulus =.14 vs R 2 RatingsScale =.12). Thus the appropriateness of using ratings scales to measure income and expenses appears robust to different measures of slack. Furthermore, there is no evidence that this measurement scale drives the observed results.

EXPENSE NEGLECT 22 In Study 5 (N = 121), participants estimated their income and expenses in dollars. Participants were asked to answer four separate focal questions asking participants to estimate their income and expenses next month and in 24 months in dollars. These questions were embedded in a larger set of estimates, so that participants would not reduce the task to a simple algebra problem. Participants then evaluated their financial slack using the three-item measure used in study 3 (α =.82). As in the previous study, we logged transformed the income change and expense change measures (ln + 1), which greatly improves the fit of the full model (R 2 =.10) compared to using raw values (R 2 =.02). We ran a regression with income change and expense change to predict slack change, and find that the coefficient on income change (β =.63, SE =.24, t(120) = 2.58, p =.009) is significant, whereas the coefficient on expense change (β =.22, SE =.35, t(120) = 0.64, p =.52) is positive and not significant. Further, the full model (R 2 =.10) that allows the income and expense parameters to vary explains a significantly greater amount of variance than the constrained model (R 2 =.04; F(1, 118) = 7.61, p =.007), again replicating expense neglect. As noted in Study 4, given that participants current income is greater than current expenses, the equal weighting model represents a conservative test of expense neglect when using log transformed predictors. Together, studies 2 5 replicates expense neglect, and shows that this bias is robust to a range of different operational definitions and measures of financial slack, income, and expenses. We are therefore confident that the effect is neither a measurement nor a statistical artifact. In the following studies, we investigate possible mechanism for the effect. STUDY 6: UNCERTAINTY DOES NOT EXPLAIN EXPENSE NEGLECT

EXPENSE NEGLECT 23 The present study examines whether expense neglect is due to differing levels of confidence about future income and expenses. If participants feel that their estimates about their income are more certain than their estimates about their expenses, then they may rely more heavily on income than expenses when estimating future financial slack. 3 To test this, we directly ask participants to report their level of confidence in their estimates. Method We recruited 301 participants (32.6% female; mean age = 31.8; median household income = $40 to $50k) via Mechanical Turk to participate in a study about personal finances. Participants evaluated their financial slack, income, and expenses in the next month and in 24 months from the present. After each estimate, participants were asked, How confident are you in your response? on a scale ranging from 1 = Not at all confident to 11 = Extremely confident. To measure financial slack, participants were asked the spare money and likelihood of repayment questions. The change scores for these items were combined to create a two-item slack change measure (r =.49). Financial constraint was not rated in this study. Results & Discussion Slack, Income and Expense Change: Relative to next month, participants expected their slack (M = 1.87, SD = 2.25), income (M = 1.55, SD = 1.99), and expenses (M = 0.76, SD = 1.75) to grow over the next two years (paired ts > 7.5, ps <.001). 3 If participants were highly uncertain in their expense estimates, then across our studies, the coefficients on expense change should also likely be noisier (i.e., have a larger standard error) than the coefficients on the income change. We do not find this, suggesting that uncertainty over expenses does not explain expense neglect. Nonetheless, we directly test this account in the present study.

EXPENSE NEGLECT 24 Predictions of Slack Change: We again replicate expense neglect. We ran a regression with income change and expense change to predict slack change, and find that the coefficient on income change (β =.62, SE =.06, t(299) = 10.62, p <.001) is 3.1 times the size of the coefficient on expense change (β = -.20, SE =.07, t(299) = -2.97, p =.003). Further, the full model (R 2 =.28) that allows the income and expense parameters to vary explains more variance than the constrained model (R 2 =.20; F(1, 299) = 32.88, p <.001). Confidence Ratings: A 2 x 2 repeated measures ANOVA showed a significant interaction such that relative confidence in income vs. expense ratings varied by time period (next month vs 24 months), F(1, 300) = 11.26, p <.001. Planned contrasts show that next month, participants were slightly more confident about their income (M = 9.34, SD = 1.93) than their expenses (M = 9.14, SD = 1.83), paired t(300) = 1.77, p =.077. However, predicting 24 months out, they were actually significantly less confident about their income (M = 7.83, SD = 2.42) than their expenses (M = 8.09, SD = 2.39), paired t(300) = -2.27, p =.024. In sum, study 6 shows that expense neglect is not due to differing levels of confidence between income and expenses. While the effect is small, participants were actually slightly more confident in their own expense estimates than their own income estimates in two years. As a result, it is unlikely that differences in confidence levels are causing people to neglect expenses when forecasting their future financial slack. STUDY 7: CATEGORY FLEXIBILITY DOES NOT EXPLAIN EXPENSE NEGLECT Study 7 examines whether expense neglect can be explained by differing beliefs in the flexibility of future income and expenses. Consumers may expect that their expenses will increase in the future, but also consider some of these expenses to be discretionary and capable

EXPENSE NEGLECT 25 of being cut if need be. If so, they may discount flexible expenses when considering future financial slack. For example, a consumer that expects to purchase a cable package once he receives a raise may also consider this to be a flexible expense: if he receives an unexpected bill in the future, he would be able to pay this bill by canceling his cable package and freeing up spare money. As a result, he may indicate that his income, expenses, and spare money will all increase in the future, leading to a pattern of results that will look like expense neglect. If category flexibility can explain expense neglect, then we should see that participants who expect their expenses to be more flexible in the future place less weight on expenses than those who expect to have less flexible expenses in the future. Method We recruited 500 participants (43.2% female; mean age = 33.2; median household income = $30 to $40k) via Mechanical Turk to participate in a study about personal finances. Participants were asked about financial slack, income, and expenses in the next month and in 24 months from the present. Financial slack was measured using only the likelihood of repayment item. After each estimate of their income and expenses, participants were asked the following: Some people's income is [expenses are] highly flexible, and they have the ability to quickly increase or decrease their income [expenses] if need be. Other people's income is [expenses are] not at all flexible, and they would find it impossible to quickly adjust their income [expenses]. Participants then evaluated their income/expense flexibility on an 11-point scale ranging from 1 = Not at all flexible to 11 = Extremely flexible. Results & Discussion

EXPENSE NEGLECT 26 Slack, Income and Expense Change: Relative to next month, participants expected their slack (M = 1.63, SD = 2.81), income (M = 1.09, SD = 1.76), and expenses (M = 0.22, SD = 2.09) to grow over the next two years (paired ts > 2.35, ps <.02). Predictions of Slack Change: We again replicate expense neglect. We ran a regression with income change and expense change to predict slack change, and find that the coefficient on income change (β =.43, SE =.07, t(497) = 6.09, p <.001) is positive and significant, while the coefficient on expense change (β =.04, SE =.06, t(497) = 0.63, p =.53) is not significantly different from zero. Further, the full model (R 2 =.08) that allows the income and expense parameters to vary explains significantly more variance than the constrained model where income and expenses have equal and opposite signs (R 2 =.02; F(1, 497) = 33.32, p <.001). Category Flexibility: Next, we tested to see if the extent to which income and expenses are considered to be flexible affects the weight placed on expenses. To do so, we first took change scores between extent to which participants expected their income flexibility and expenses flexibility to change over time, and ran the following regression: (5) Slack Change = β 0 + β 1 (Income Change i ) + β 2 (Expense Change i ) + β 3 (Income Flexibility Change i ) + β 4 (Expense Flexibility Change i ) + β 5 (Income Change i *Income Flexibility Change i ) + β 6 (Expense Change i *Expense Flexibility Change i ) + i Both income flexibility change (M = 0.74, SD = 2.00) and expense flexibility change (M = 0.52, SD = 2.09) were mean centered, whereas income change and expense change were coded such that 0 meant no change.

EXPENSE NEGLECT 27 Table 2 displays the regression results, and shows that category flexibility does not affect the weighting of either income or expenses. Both the income change by income flexibility change interaction and the expense change by expense flexibility change interaction are not significant. Thus, those expecting greater income or expense flexibility in the future did not weigh these inputs any differently than those reporting less income or expense flexibility. ---Insert Table 2 about here--- Interestingly, we do find a significant positive relationship between increased expense flexibility and increased slack, suggesting that the more participants believe that their expenses will be flexible in the future, the more they expect to have greater financial slack in the future. However, participants are still insensitive to their overall level of expenses: controlling for flexibility, the coefficient on expense change remains not significantly different from zero. In sum, study 7 shows that beliefs regarding the flexibility of expenses cannot explain expense neglect. Although participants who expected to have greater expense flexibility in the future reported having greater slack in the future, there was no relationship between expense flexibility change and expense change. STUDY 8: OPTIMISM DOES NOT EXPLAIN EXPENSE NEGLECT Study 8 examines whether expense neglect can be explained by generalized optimism. In particular, it may be that people who are optimistic and view the future favorably are also more likely to ignore expenses when forecasting their future slack.

EXPENSE NEGLECT 28 Method We recruited 1,004 participants 4 (39.0% female; mean age = 30.1; median household income $40k - $50k) via Mechanical Turk. Participants first rated their available financial slack next month and in two years from the present using the same three-item measure developed in Study 4 ( =.81). Participants then evaluated their expected monthly income and expenses next month and in two years from the present. The income, expense, and slack measures were all rated using 11-point scales. Finally, participants were given the Life Orientation Test Revised (LOT-R) as a measure of generalized optimism (Scheier, Carver, and Bridges 1994). The scores for the LOT-R range from 0 (extreme pessimist) to 24 (extreme optimist). Results & Discussion Slack, Income and Expense Change: Relative to next month, participants expected their slack (M = 2.55, SD = 2.54), income (M = 1.94, SD = 2.19), and expenses (M = 0.20, SD = 2.15) to grow over the next two years (paired ts > 2.87, ps <.005). Predictions of Slack Growth: We again find evidence for expense neglect. We ran a regression with income change and expense change to predict slack change, and find that the coefficient on income change (β =.62, SE =.03, t(1001) = 19.22, p <.001) is 3.0 times the size of the coefficient on expense change (β = -.21, SE =.03, t(1001) = -6.56, p <.001). Further, the full model (R 2 =.27) that allows the income and expense parameters to vary explains significantly more variance than the constrained model where income and expenses have equal and opposite signs (R 2 =.20; F(1, 1001) = 99.82, p <.001). 4 We recruited this number of participants to match the sample recruited in Study 9, which was run prior to the present study. These sample sizes were matched to ensure that we would not under-power the present study.