Excusing Selfishness in Charitable Giving: The Role of Risk

Decisions involving charitable giving often occur under the shadow of risk. A common ﬁnding is that potential donors give less when there is greater risk that their donation will have less impact. While this behavior could be fully rationalized by standard economic models, this paper shows that an additional mechanism is relevant: the use of risk as an excuse not to give. In a laboratory study, participants evaluate risky payoﬀs for themselves and risky payoﬀs for a charity. When their decisions do not involve tradeoﬀs between money for themselves and the charity, they respond very similarly to self risk and charity risk. By contrast, when their decisions force tradeoﬀs between money for themselves and the charity, participants act more averse to charity risk and less averse to self risk. These altered responses to risk bias participants towards choosing payoﬀs for themselves more often, consistent with excuse-driven responses to risk. Additional results support the existence of excuse-driven types


Introduction
In the United States, 1 in 4 adults volunteer and 1 in 2 adults give to charities for an estimated combined value of $500 billion dollars per year.1An established literature documents potential motives for such giving; for instance, people feel good about themselves when they help others (Andreoni, 1989, 1990), value appearing nice to others (Harbaugh, 1998a; Bénabou and Tirole,  2006; Ariely et al., 2009), and desire to conform with social norms (Andreoni and Bernheim,  2009).2These motives, as well as standard economic models, may easily explain a common finding in charitable giving: individuals give less when when there is a greater risk that their donation will have less impact (Brock et al., 2013; Krawczyk and Lec, 2010). 3In this paper, however, I investigate whether an additional mechanism is relevant: do people use the risk that their donation may have less than the desired impact as an excuse not to give?
Given how often people are asked to give -over 50% of adults report being asked more than three times within the past year -reluctant individuals may desire an excuse not to give. 4 Previous literature in fact demonstrates a large scope for motivations broadly related to excuses.For instance, people often behave more selfishly when they can avoid learning how their decisions affect others (Dana et al., 2007; Bartling et al., 2014; Grossman, 2014), develop self-serving biases (Konow, 2000; Haisley and Weber, 2010), or rely on the possibility that their decisions did not influence the outcome (Dana et al., 2007; Andreoni and Bernheim, 2009; Linardi and McConnell,  2011; Falk and Szech, 2013). 5People also achieve more selfish outcomes by delegating decisions to others (Hamman et al., 2010; Coffman, 2011; Bartling and Fischbacher, 2012), or by avoiding situations that involve giving decisions (Dana et al., 2006; Broberg et al., 2007; Andreoni et al.,  2011; Lazear et al., 2012; DellaVigna et al., 2012). 6his paper differentiates itself from existing literature by documenting self-serving responses to objective risk in a social setting absent other factors, such as image concerns (Andreoni and  Bernheim, 2009), information acquisition (Dana et al., 2006), ambiguity (Haisley and Weber,  2010), or actions of others (Falk and Szech, 2013).In exploiting a within-subject experimental design, this paper also provides evidence for an individual level of consistency in self-serving tendencies.Motivated by related policy questions, this paper somewhat less commonly focuses on charitable giving decisions, but as verified in an additional study involving payoffs for other participants instead of a charity, it seeks to contribute to the broader other-regarding literature.
To begin, this paper conducts a laboratory study that allows for the needed control to isolate excuse-driven responses to risk from other responses to risk.Participants make a series of binary decisions between risky and riskless payoffs that may benefit themselves or the American Red Cross.A risky payoff is a lottery that yields a non-zero amount with probability P and $0 with probability 1 − P .A risky payoff is a "charity lottery" or a "self lottery" if the corresponding outcome is given to the American Red Cross or the participant, respectively.7A riskless payoff yields a non-zero amount with certainty.A riskless payoff is a "charity-certain amount" or "selfcertain amount" if it is given to the American Red Cross or to the participant, respectively.In other words, participants face four types of binary decisions that vary according to the involved payoffs -{self lottery, charity lottery} X {self-certain amount, charity-certain amount}.
Notice that participants do not face tradeoffs between payoffs for themselves and the charity when deciding between: (i) self lotteries and self-certain amounts, or (ii) charity lotteries and charity-certain amounts.In this no self-charity tradeoff context, excuses not to give are irrelevant as participants never decide whether or not to give -i.e., they cannot give in (i) or are forced to give in (ii).By contrast, participants always face tradeoffs between payoffs for themselves and the charity when deciding between: (iii) self lotteries and charity-certain amounts, or (iv) charity lotteries and self-certain amounts.In this self-charity tradeoff context, excuses not to give may be relevant.Changes in responses to risk across these contexts can thus exhibit the extent to which excuse-driven risk preferences influence charitable giving decisions.
Figure 1 shows the main results of my study by plotting how lottery valuations change as the probability P of the non-zero payment increases, i.e., as risk decreases.For ease of comparison, note that the lottery valuations are scaled as percentages of the corresponding riskless lottery valuations.In the no self-charity tradeoff context, participants' responses to risk in self lotteries and charity lotteries are nearly indistinguishable.From P = 1 to P = 0.5, or in response to 50% risk of a zero-dollar outcome, participants reduce their valuations by about 50% for both self lotteries and charity lotteries.These equivalent responses likely result in part from a normalization, detailed later in the design, that ensures participants are indifferent between the nonzero payoffs in the self lotteries and charity lotteries.Absent this normalization, different responses to risk in self lotteries and charity lotteries may have resulted from participants valuing money for themselves and the charity differently.While an emerging literature considers how individuals' responses to risk may differ over their own money and others' money, this is the first study, to my knowledge, to show equivalent responses to risk in self lotteries and charity lotteries when corresponding payoffs are normalized. 8n the self-charity tradeoff context, by contrast, participants' responses to self risk and charity risk diverge.Consistent with excuse-driven risk preferences, participants act both more averse to charity risk and less averse to self risk.In response to 50% risk, participants reduce their valuations by only 40% for self lotteries but by 60% for charity lotteries.The most stark findings, however, occur with the introduction of even small risk.From P = 1 to P = 0.95, or in response to only 5% risk of a zero-dollar outcome, participants' valuations for charity lotteries decrease by 32% in the self-charity tradeoff context.The reduction is four times larger than the corresponding 8% decrease in the no self-charity tradeoff context.That is, participants appear to overweight the possibility that charity lotteries yield zero-dollar payoffs, using it as an excuse to choose self certain-amounts over charity lotteries.I infer from the observed treatment effects that individuals exhibit excuse-driven risk preferences.By exploiting the within-subject design of this study, additional results provide evidence for excuse-driven types of participants and hence contribute to limiting the scope for non-excusedriven explanations.First, participants who appear more selfish in riskless decisions are more likely to also exhibit excuse-driven risk preferences in risky decisions.Second, participants with excuse-driven risk preferences are more likely to engage in other excuse behavior in a separate incentivized "moral wiggle room" task, as developed in Dana et al. (2007).While excuse-driven risk preferences involve unambiguously selfish decisions -by choosing self payoffs over charity payoffs more often -excuse-driven behavior in the moral wiggle room task involves avoiding information on whether or not decisions are selfish.
In an additional study, I test whether my results are more broadly relevant to prosocial behavior, as opposed to just charitable giving.I find strong evidence for excuse-driven risk preferences when participants decide between payoffs for themselves and payoffs for another study participant, as opposed to payoffs for a charity.
This paper proceeds as follows.Section 2 overviews the predictions according to the channels through which risk influences giving, Section 3 details the experimental design, Section 4 describes the results, and Section 5 concludes by highlighting further avenues for research.

Predictions
To determine through which channels risk influences charitable giving decisions, I elicit participants' valuations of various self lotteries and charity lotteries.Participants receive the outcomes of self lotteries; the American Red Cross (ARC) receives the outcomes of charity lotteries.A "self lottery," denoted by P s , yields $10 for a participant with probability P and $0 for a participant with probability 1 − P .A "charity lottery," denoted by P c , yields $X for the charity with probability P and $0 for the charity with probability 1 − P .To ensure that charity lotteries are comparable to self lotteries, I determine participant-specific X values such that participants are indifferent between themselves receiving $10 with certainty and the charity receiving $X with certainty.In other words, if (U, V ) represents a bundle where a participant receives $U and the charity receives $V, then this study will yield valuations for: P (10, 0) + (1 − P )(0, 0) P s : self lottery with probability P and P (0, X) + (1 − P )(0, 0) P c : charity lottery for probability P where (10, 0) ∼ (0, X), and P ∈ {0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95}.
Valuations of self lotteries are denoted as Y j (P s ), and valuations of charity lotteries are denoted as Y j (P c ).The superscript j indicates whether lottery valuations are self-dollar valuations (j = s) or charity-dollar valuations (j = c).Self-dollar valuations are in dollars given to participants, and charity-dollar valuations are in dollars given to the charity.The resulting four types of lottery valuations, summarized in Table 1 and explained below, allow me to distinguish between three channels through which risk may influence giving.
In the no self-charity tradeoff context, valuations result from decisions involving no tradeoffs between payoffs for the participants and the charity.Y s (P s ) is the valuation such that participants are indifferent between themselves receiving $Y s (P s ) with certainty and themselves receiving the outcome of P s .Y c (P c ) is the valuation such that participants are indifferent between the charity receiving $Y c (P c ) with certainty and the charity receiving the outcome of P c .In the self-charity tradeoff context, valuations result from decisions involving tradeoffs between payoffs for the participants and the charity.Y c (P s ) is the valuation such that participants are indifferent between the charity receiving $Y c (P s ) with certainty and themselves receiving the outcome of P s .Y s (P c ) is the valuation such that participants are indifferent between themselves receiving $Y s (P c ) with certainty and the charity receiving the outcome of P c .
Since self-dollar valuations and charity-dollar valuations are elicited in different units, I consider valuations scaled as a percentage of the riskless lottery valuation.Self-dollar valuations (Y s (P s ) or Y s (P c )) are scaled as percentages of $10 being given to the participants.Charitydollar valuations (Y c (P c ) or Y c (P s )) are scaled as percentages of $X being given to the charity.In the following predictions and discussion of my results, I assume linear utility in payoffs as doing so allows for such rescaling.However, my results are robust to interpretations that do not rely on this rescaling.9 Since participant-specific X values imply (10, 0) ∼ (0, X), several models imply that participants should be indifferent between charity lotteries and self lotteries as they merely introduce the same 1 − P probability of a $0 outcome.That is: P (10, 0) + (1 − P )(0, 0) P s : self lottery with probability P ∼ P (0, X) + (1 − P )(0, 0) P c : charity lottery for probability P , ∀P. (1) For instance, this indifference is directly implied by the independence axiom, as in von Neumann-Morgenstern expected utility, and corresponds with what I define as standard risk preferences.
Prediction 1 (Standard Risk Preferences) All else equal, if participants have standard risk preferences for some probability P , then By contrast, if participants have what I define as charity-specific risk preferences, the indifference shown in relation 1 may not hold.For instance, in his theory of good intentions, Niehaus  (2014) proposes that individuals may receive a "warm glow" or good feeling from thinking they did good.In some cases, such warm glow giving could cause participants to hold optimistic beliefs about the impact of their donations and respond less to different charity risk levels.More generally, charity-specific risk preferences may result if participants' risk preferences or behavioral responses to risk differ for self payoffs and charity payoffs.
Prediction 2 (Charity-Specific Risk Preferences) All else equal, if participants have charityspecific risk preferences for some probability P , then By contrast, excuse-driven risk preferences allow for the possibility that the same charity lottery or the same self lottery may be valued differently depending on whether the context permits excuses not to give.In the no self-charity tradeoff context, participants never trade off payoffs for themselves with payoffs for the charity, so excuse-driven risk preferences are not relevant.However, in the self-charity tradeoff context, participants must trade off payoffs for themselves with payoffs for the charity, so excuse-driven risk preferences would bias them towards choosing payoffs for themselves.When participants decide between charity lotteries and self-certain amounts, they may overweight the possibility that charity lotteries yield zero-dollar charity payoffs as an excuse to choose the self-certain amounts over charity lotteries.A resulting increased aversion to charity risk would yield lower charity lottery valuations relative to those in the no self-charity tradeoff context.Alternatively, when participants decide between self lotteries and charity-certain amounts, they may favor the possibility that self lotteries yield non-zero self payoffs as an excuse to choose self lotteries over charity-certain amounts.A resulting decreased aversion to self risk would yield higher self lottery valuations relative to those in the no self-charity tradeoff context.
Prediction 3 (Excuse-Driven Risk Preferences) All else equal, if participants have excusedriven risk preferences for some probability P , then

Data and Design
There are two versions of my study.While Section 3.1 highlights my main study that involves charitable giving decisions, Section 3.2 details a modified version of the study that involves giving to another participant in the study, as opposed to a charity.

Charitable Giving Study
From November 2013 -January 2014, I recruited one-hundred undergraduate students to participate in one of five study sessions via the Stanford Economics Research Laboratory.Each study session adhered to the following design.
After participants listen to instructions and correctly answer several understanding questions, they complete thirty price lists.10Each price list involves a series of binary decisions, from which one randomly selected decision is implemented for payments and added to their minimum participation fee of $20.11After participants complete these price lists, they answer several followup questions, which include demographic questions and moral wiggle room questions described later (see Section 4.3).Participants are then paid in cash and exit the study.All decisions in this study remain anonymous.Participants complete this study on laptops, via an online survey platform called Qualtrics, in the Stanford Economics Research Laboratory.
Participants first complete a "normalization" price list that determines participant-specific X values such that they are indifferent between $10 for themselves and $X for the charity.Participants are unaware that their choices in the normalization price list determine the non-zero payoff they will later face in decisions involving charity lotteries.Instead, in the normalization price list, they are just asked to make sixteen binary decisions between two Options (A and B).12 Option A always involves the participants receiving $10 with certainty.However, as they proceed down the sixteen rows of the price list, Option B increases from the charity receiving $0, $2, ..., to $30 with certainty.See Appendix A.1 for a screenshot of the normalization price list.
From participants' decisions in the normalization price list, I estimate participant-specific X values as follows.Assume a participant switches from choosing Option A to Option B on the i th row, and that this corresponds to the charity receiving $B i .It then follows that B i−1 ≤ X ≤ B i , and I estimate X as its upper bound of B i .I choose the upper bound as overestimations of X bias my results against finding evidence for excuse-driven risk preferences. 13here are two cases where X cannot be accurately estimated in my data.The first case involves "multiple switch points."Although Option A is fixed and Option B increases as a participant proceeds down the rows of the price list, a participant may choose Option B on row i but may not choose a higher valued Option B on some later row i + j, implying a violation of monotonicity in preferences.Only one participant has multiple switch points in the normalization price list, and this participant will be excluded from the remaining analysis.The second case involves "censored X values," which occur if a participant never chooses Option B, or always chooses $10 for themselves over the charity receiving any amount up to $30.Forty-two participants (out of the one-hundred participants) have censored X values.This occurrence is comparable to Engel (2011)'s meta study finding that 36% of dictators never give any positive amount -which normally could be as little as $1 -to their recipients in dictator games.My main results exclude participants with censored X values, although my results are robust to including this group by assuming their X values are equal to their lower bound of $30.
Therefore, my main results are likely most relevant among a population interested in donating to the charity in this study, i.e., the American Red Cross.This explanation is bolstered by participants' decisions in a second price list that serves as a buffer between the normalization task and valuation tasks.Participants complete the second price list immediately after the normalization price list, and it only differs by replacing the $10 payoff for participants in Option A with a $5 payoff for participants.In return, I find that 69% of participants with censored X values are also unwilling to give up $5 for themselves in order for the charity to receive $30.Even among participants without censored X, Figure 2 shows that 87% of these participants have X values that exceed $10 -i.e., they are only willing to give up $10 for themselves in exchange for the charity receiving more than $10.The average X value is correspondingly $17.30. 14fter completing the first and second price lists, participants complete twenty-eight price lists that provide data on their lottery valuations.In each of the "valuation" price lists, participants make twenty-one binary decisions between two Options (A and B).In a given price list, Option A is constant across all rows, and always involves a self lottery or a charity lottery.Recall that self lotteries yield $10 for the participants with probability P and $0 otherwise, while charity lotteries yield $X for the charity with probability P and $0 otherwise.On the other hand, Option 13 In particular, excuse-driven risk preferences imply that participants act more averse to risk in charity lotteries, or that valuations of charity lotteries significantly decrease as the probability P decreases.My estimation of X assumes that participants value the charity lottery with P = 1 at $10 for themselves.If they instead valued the charity lottery with P = 1 higher than $10 for themselves, then the drop in their valuations of charity lotteries as P decreases would be underestimated.
14 3% of the participants seem oddly "too prosocial," as their X values are $6.In this case, a seemingly dominant option would be for them to choose $10 for themselves, as they could then donate $6 to the charity (after the study) and still have $4 remaining for themselves.Such decisions could be explained, however, from them desiring to appear prosocial to the experimenter or having high transaction costs of donating to the charity.Each bar shows the percent of the participants with a given X value, where X is estimated for each participants such that they are indifferent between themselves receiving $10 and the charity receiving $X, or (10, 0) ∼ (0, X).The results include data for the 57 participants in my main subsample (i.e., excludes participants with X values that were censored or resulted from decisions with multiple switch points).
B always involves either a self-certain amount or a charity-certain amount that increases as they proceed down the rows of the price list.Self-certain amounts yield $0, $0.50, ..., or $10 to the participants with certainty, while charity-certain amounts yield $0, $ X 20 , ..., or $X to the charity with certainty.
Notice that the payoff recipients for the lotteries and certain amounts correspond with the desired two-by-two design previously displayed in Table 1: {self lottery, charity lottery} X {selfcertain amount, charity-certain amount}.There are correspondingly four "blocks," each with 7 price lists.Price lists within a block only differ according to the probability P involved in the lottery, where P ∈ {0.95, 0.90, 0.75, 0.50, 0.25, 0.10, 0.05}.Participants complete all price lists in one block, then all price lists in another block, and so on.Blocks are presented in a randomly determined order for each participant.Appendices A.3 -A.6 show example price lists from each block.
From participants' decisions in a valuation price list, I estimate their corresponding lottery valuations as follows.Imagine that participants switch from choosing a lottery in Option A to some certain amount in Option B on the i th row.Since the certain amount in Option B always increases as participants proceed down the rows, their valuations fall between B i−1 and B i .I then follow previous literature by estimating their valuations as the midpoint -i.e., B i−1 +B i

2
. 15 As with the normalization price lists, decisions from the valuation price lists may involve censoring problems and/or multiple switch points.While censoring remains a concern for participants with censored X values, it turns out not to be a concern for participants without censored X values. 16Multiple switch points occur for less than 1% of the valuation price lists, which is significantly less than the typical 15% observed in the literature. 17My main analysis will follow Meier and Sprenger (2010), among many others, by including these observations under the assumption that their first switch point is their true switch point.However, my results are also robust to excluding any participant or observation that involves multiple switch points in the valuation price lists.

Partner Study
To test the robustness of my results to prosocial behavior more generally, I replicate my study in an environment where participants make decisions between payoffs for themselves and payoffs for another participant in the study.In March of 2014, I recruited forty-four undergraduate students to participate in one of two study sessions via the Stanford Economics Research Laboratory.The design features of this study only differ from Section 3.1 in two ways.First, I assign half of the participants to the Left Group and the remaining half of the participants to the Right Group, according to the side of the lab in which they are seated.Instead of one randomly selected decision being implemented for each participant, only one randomly selected decision is implemented for each participant in the randomly selected group (i.e., the Left Group or the Right Group).
Second, instead of choosing between self payoffs and charity payoffs, participants choose between self payoffs and partner payoffs.Partner payoffs involve payoffs given to participants' partners, who are randomly and anonymously selected to be another participant not in their group (i.e., participants in the Left Group have partners in the Right Group, and vice versa).When participants make decisions involving their partner, note that these decisions should not be influenced by realized reciprocity since only a decision made by a participant or a decision made by a participant's partner will be implemented.
face the estimated X in the study, I cannot consider other estimations of X.However, I can consider other estimations of the lottery valuations, and my results are robust to instead considering the upper bound. 16In over 96% of the valuation price lists, participants without censored X values switch from choosing Option A to Option B. In the remaining less than 4% of cases, participants always choose Option A and I assume the valuation is then the maximum certain amount offered.This approach can be explained by the following example.Consider a participant who always chooses a self lottery (say, $10 for themselves with 95% chance and $0 otherwise) over any charity certain amount (up to $X for the charity).Then, the self lottery valuation is weakly greater than $X for the charity.Monotonic preferences, however, imply the participant values the self lottery weakly less than $10 for themselves, and hence weakly less than $X for the charity (from the normalization task).It thus follows that the self lottery valuation is $X for the charity.
17 This lower occurrence of multiple switch points likely results from my design following Andreoni and Sprenger  (2011) by providing clarifying instructions before price lists and preselecting Option A in the first row of each price lists over the $0 certain amount in Option B (see Appendix A for corresponding screenshots of instructions).
As before, there are two cases where X cannot be accurately estimated in my data.The first case involves two participants with multiple switch points in the normalization price list.These two participants will be excluded from the remaining analysis.The second case involves thirteen participants with censored X values, which occur if a participant never chooses Option B, or always chooses $10 for themselves over their partner receiving any amount up to $30.As in the charity treatment, the main partner results exclude participants with censored X values, although they are robust to including this group by assuming their X values are equal to their lower bound of $30. Figure 3 shows that all of the participants without censored X values prefer $10 for themselves over $10 for their partner.While the average X value is slightly higher than in the charity treatment, both treatments have a median X value of $16.Each bar shows the percent of the participants with a given X value, where X is estimated for each participants such that they are indifferent between themselves receiving $10 and their partner receiving $X, or (10, 0) ∼ (0, X).The results include data for the 29 participants in my main subsample (i.e., excludes participants with X values that were censored or resulted from decisions with multiple switch points).

Results
Section 4.1 provides evidence against charity-specific risk preferences by documenting similar responses to self risk and charity risk in the no self-charity tradeoff context.Section 4.2 supports excuse-driven risk preferences by detailing the pattern of divergence between participants' responses to self risk and charity risk in the self-charity tradeoff context.Section 4.3 considers heterogeneous effects and provides support for the existence of excuse-driven "types" of participants.Section 4.4 confirms the robustness of the results in the partner study.

Evidence against Charity-Specific Risk Preferences
The left panel of Figure 1 plots the self lottery and charity lottery valuations in the no self-charity tradeoff context.With respect to participants' valuations of self lotteries, they appear more risk seeking with low probabilities (high risk) and risk averse with high probabilities (low risk).The corresponding inverse-S pattern of valuations as a function of risk is a standard empirical finding and replicates results from previous studies on risk.For instance, as shown in Appendix Figure B.1, estimates of cumulative prospect theory parameters for the self lottery data are very similar to previous studies. 18ith respect to the comparison of responses to risk in self and charity payoffs, Appendix Tables B.1 and B.2 confirm that the differences between valuations for charity lotteries and self lotteries are not statistically different on average nor do they exceed more than a few percentage points at any given probability level.These results also hold on a decision level; when considering an individuals' self and charity lottery valuations for a given probability, 42% are exactly the same, and 83% differ by no more than ten percentage points.

Evidence for Excuse-Driven Risk Preferences
The right panel of Figure 1 plots the self lottery and charity lottery valuations in the self-charity tradeoff context.Participants' responses to charity risk and self risk now diverge by fifteen percentage points on average.Appendix Tables B.3 and B.4 confirm this difference overall and at the various probability levels.These results also hold on a decision level; when considering an individuals' self and charity lottery valuations for a given risk level, 78% are not the same, and 54% differ by more than ten percentage points.
To show that the observed divergence is consistent with excuse-driven risk preferences, consider the difference-in-differences estimates from Equation 2. The dependent variable Y li is an individual i's valuation of a particular lottery l.While the coefficient on charity li captures whether or not there are significant differences between charity and self lottery valuations in the no self-charity tradeoff context, the coefficients on tradeoff li and charity*tradeoff li indicate the extent to which there are excuse-driven risk preferences.
where Y li ≡ valuation of a lottery l (as a % of corresponding riskless lottery valuation) charity li ≡ indicator for charity lottery tradeoff li ≡ indicator for lottery being elicited in self-charity tradeoff context charity*tradeoff li ≡ interaction variable of charity li and tradeoff li λ P ≡ probability fixed effect, P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1 } (P=0.05excluded) Column 1 of Table 2 displays the corresponding regression results with no controls.To begin, note that the coefficient on charity li is not statistically different than zero, consistent with the lack of evidence for charity-specific risk preferences.However, the coefficient on tradeoff li shows that participants' self lottery valuations are about five percentage points higher on average in the self-charity tradeoff context.Participants appear to overweight the possibility that self lotteries yield non-zero-dollar payoffs, using it as an excuse to choose self lotteries over charity certainamounts more often than their non-excuse-driven risk preferences would imply.Additionally, the sum of the coefficients on tradeoff li and charity*tradeoff li shows that participants' charity lottery valuations are about ten percentage points lower in the self-charity tradeoff context.Participants appear to overweight the possibility that charity lotteries yield zero-dollar payoffs, using it as an excuse to choose self certain-amounts over charity lotteries more often than their non-excusedriven risk preferences would imply.
Columns 2 -4 confirm the robustness of the results to the inclusion of individual fixed effects regardless of whether or not observations or participants with multiple switch points are excluded, and Column 5 finds similar results with probability fixed effects.Column 6 shows that the results hold with interval regressions, where the dependent variables are the upper and lower bounds of the lottery valuations, as opposed to the midpoint of the range implied by participants' price lists decisions.While Columns 1 -6 exclude participants with censored values of X, Column 7 shows that the results are even larger when considering Tobit regressions that include participants with censored values of X -i.e., individuals who are never willing to give up $10 for themselves in exchange for the charity receiving any certain amount up to $30.As these individuals could be considered the most selfish in this study, this larger finding could in part result from more selfish individuals being more excuse-driven.The possibility for such heterogeneous effects, or excuse-driven types of individuals, is further explored in the next section.
These results show that participants appear to use risk, regardless of whether it is charity risk or self risk, as an excuse not to give.While the charity risk results may be more similar to typical charitable giving decisions, the self risk results highlight a key advantage of the laboratory environment as they serve as an useful robustness check of excuse-driven risk preferences.For instance, contrary to the study instructions and the adhered policy of no deception in the Stanford  c )), and charity-dollar valuations of self lotteries (Y c (P s )) or charity lotteries (Y c (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charitydollars are scaled as percentages of $X i .The results are from regressions of Equation 2. Probability fixed effects are shown when included, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.
Economics Research Laboratory, participants could believe that the experimenter will resolve charity lotteries or distribute outcomes of charity lotteries in a manner biased against the charity receiving its payoffs.Alternatively, participants may believe there is some additional risk in how charities will use any donations they receive.Neither of these possibilities, however, can explain why participants use self risk, not just charity risk, as an excuse not to give.
These results are robust to several other considerations as well.First, Appendix Tables B.5 and B.6 confirm these results when separately looking at charity lottery valuations or self lottery valuations.Second, Appendix Tables B.7 and B.8 provide evidence for excuse-driven risk preferences when separately considering valuations elicited in self-dollars or charity-dollars as to avoid the need to rescale valuations. 19Third, Appendix Table B.9 shows that the results are robust to the order in which participants value charity lotteries or self lotteries, and the differencein-differences estimations ease other framing effects that may arise from the multiple price list elicitations procedure.20Fourth, similar findings are observed when considering decision level results, as shown by the fraction of lottery valuations that fall below or exceed their expected value in Appendix Figure B.2.

Evidence for Excuse-Driven Types of Participants
This section investigates the possibility of excuse-driven "types" of participants.21Documenting the existence of such types may help to unify the literature on excuse-driven behavior and to limit the scope for non-excuse-driven explanations.
To begin, it is useful to note that there is an individual-level of consistency in excuse-driven behavior across lottery valuations: participants who appear to use self risk as an excuse not to give, by acting less averse to self risk in the self-charity tradeoff context, also appear to use charity risk as an excuse not to give, by acting more averse to charity risk in the self-charity tradeoff context. 22On one extreme, Figure 4 displays the valuations for a participant without excusedriven risk preferences: this participant always responds to self risk and charity risk in the same manner across both contexts.By contrast, Figure 5 displays valuations for a participant with clear excuse-driven risk preferences: this participant almost always acts less averse to self risk and more averse to charity risk in the self-charity tradeoff context.The majority of participants, without censored X values, appear to similarly exhibit excuse-driven risk preferences to varying degrees: for 65% of the participants, the average difference in their lottery valuations across contexts is in a self-serving direction that ranges from just under 1 to 42 percentage points.In addition to an individual-level consistency across lottery valuations, selfish participants may be more likely to exhibit excuse-driven risk preferences.In this study, participants' level of selfishness is indicated by their X values -i.e., how much does the charity have to receive such that they are willing to give up $10 for themselves.To consider whether participants' X values correspond with the extent of their excuse-driven behavior, I interact the main treatment effects with (X − X), where X is the average X value among the participants.As shown in Column 2 of Table 4, participants with higher X values have a significantly larger tendency to exhibit excuse-driven risk preferences.A one dollar increase in a participant's X value corresponds with, in self-charity tradeoff context, a $1.11 increase in self lottery valuations and a $0.45 decrease in their charity lottery valuations, on average.
To consider an arguably more demanding test for excuse-driven types of participants, I examine whether excuse-driven risk preferences in lottery valuations correlate with excuse-driven behavior in a separate task that replicates a "moral wiggle room" task developed in Dana et al.  (2007). 23The moral wiggle room task involves two important features.First, behavior in this task involves a well-studied phenomenon that is believed to be excuse-driven: participants often behave more selfishly by avoiding information on whether or not their action is selfish. 24econd, excuse-driven behavior in the moral wiggle room task differs from excuse-driven risk preferences in lottery valuations, making it a useful out-of-context consideration.For instance, while excuse-driven behavior in the moral wiggle room task involves participants avoiding information on whether or not their actions are selfish, excuse-driven risk preferences occur even though participants know their actions are selfish as they choose self payoffs over charity payoffs.
Participants complete the moral wiggle room task as part of a follow-up survey at the end of the study.In order to classify excuse-driven types of participants, each participant answers three questions in this task, and one question is randomly selected to count for payments.In each question, participants choose between two options -A and B -that yield payoffs for themselves and payoffs for the charity (i.e., the American Red Cross).These payoffs, as shown in Table 3, involve a bundle (U, V ) that corresponds with the participant receiving $U and the charity receiving $V.In the aligned state, the options are A : ($6, $5) and B : ($5, $1), so A yields maximum payoffs for both the participants and the charity.In the unaligned state, the options are A : ($6, $1) and B : ($5, $5), so A yields maximum payoffs for the participant, but B yields maximum payoffs for the charity.
In the first question, or choice-to-reveal question, there is an equal probability that partici-pants face payoffs in the unaligned state or in the aligned state.While participants are not told which state they are in, they may reveal their state, for free, before choosing between A and B.
Choosing to reveal their state allows participants to ensure their preferred payoffs for themselves and the charity.However, excuse-driven participants in the moral wiggle room task may choose not to reveal their state; in doing so, they can then choose A without knowing whether or not A is selfish.Studies documenting excuse-driven behavior in the moral wiggle room task typically document such avoidance leading to an increase in overall selfish behavior. 25n the second question, or revealed-unaligned-state question, participants know they are in the unaligned state and must choose between A and B. In this case, choosing A is selfish since it results in lower charity payoffs in exchange for higher self payoffs.
In the third question, or revealed-aligned-state question, participants know they are in the aligned state, and then must choose between A and B. In this case, choosing A is not selfish as it yields the highest payoffs for both the participants and the charity.
While the aggregate results detailed in Appendix C provide evidence for excuse-driven behavior in the moral wiggle room task, I turn to individual level results to classify participants according to their behavior in the moral wiggle room task.Aside from one participant (out of the one-hundred), all participants are classified into one of the following three categories. 26irst, 44% of the participants are selfish-types as they choose the selfish option A in the revealedunaligned-state question.These participants also choose the (potentially) selfish option A in the choice-to-reveal question.Second, 35% of the participants are generous-types as they choose the fair option B in the revealed-unaligned-state, and indicate that they place some value on the charity payoffs in the choice-to-reveal question by choosing to reveal their state.Note that conditional on participants revealing their state in the choice-to-reveal question, I do not classify them according to their decision after the revelation; while I could classify whether participants who learn they are in the unaligned-state as choosing the selfish option or not, I could not make the same classification for participants who learn they are in the aligned-state.Third, 20% of the participants are wiggler-types as they choose the fair option B in the revealed-unaligned-state, but instead choose the potentially selfish option A in the choice-to-reveal question after choosing not to reveal their state.That is, wiggler-types, or those susceptible to excuse-driven behavior in the moral wiggle room task, only choose the potentially selfish option when they can and do avoid free information on whether or not their choice is selfish.Among participants in my main subsample (as relevant later in Table 4), the relative representation of types changes to selfish-types (23%), generous-types (51%), and wiggler-types (25%). 27oth generous-types and wiggler-types choose the fair option B in the revealed-unalignedstate question.Wiggler-types, however, avoid learning their state in the choice-to-reveal question and choose the potentially selfish option A. If there is an individual-level of consistency in excusedriven behavior out-of-sample, then wiggler-types should be more likely to exhibit excuse-driven risk preferences than generous-types.
As shown in the third column of Table 4, wiggler-types are more likely to exhibit excusedriven risk preferences, particularly with respect to using charity risk as an excuse not to give. 28n self-charity tradeoff context, they have significantly lower charity lottery valuations and qualitatively, although not significantly, higher self lottery valuations.Similar results may be expected for selfish-types, particularly in light of the earlier finding shown in Column 2: individuals with higher X values show a greater tendency to exhibit excuse-driven behavior.While qualitatively consistent with this possibility, the binary classification of selfish-types does not significantly correspond with more excuse-driven behavior.This may in part be explained by the somewhat surprising finding of an insignificant correlation between participants' values of X and classifications as selfish-types.There is also an insignificant correlation between participants' values of X and classifications as wiggler-types, which suggests that these two characteristics may independently be important predictors of excuse-driven behavior.The fourth column of Table 4 in fact confirms that the same results hold even when there are interactions of the treatment effects with (X − X), wiggler-types, and selfish-types.As a matter of interest, no significant interaction effects are observed when the treatment effects are instead interacted with an indicator for a participant's sex or stated degree of how favorably they view the American Red Cross.c )), and charity-dollar valuations of self lotteries (Y c (P s )) or charity lotteries (Y c (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X i .The results are from regressions of Equation 2 modified to include the shown interactions.(X − X) is a participant's X minus the average X. selfish is an indicator for choosing A in the revealed-unaligned state.wiggler is an indicator for choosing B in the revealed-unaligned-state but A in the choice-to-reveal question after choosing not to reveal their state.For observations involving multiple switch points, the first switch point is assumed.Participants with censored X values or X values that resulted from decisions with multiple switch points are excluded.

Replication of Results in Partner Study
In the partner study, payoffs benefit another participant in the lab as opposed to the charity.Results may therefore differ from the above discussed charity study due to several reasonsperhaps most notably if excuse-driven behavior is only relevant to charitable giving and not prosocial behavior more broadly.Additionally, while the partner version eliminates differences in how payments to oneself and others are being distributed, it also introduces role-uncertainty (Iriberri and Rey-Biel, 2011) as participants do not know if their decisions or their partners' decisions will be implemented for payment.
As shown in Figure 6 and Appendix Table B.10, evidence for excuse-driven risk preferences is similar, and if anything, larger in the partner study.In the no self-partner tradeoff context, participants respond very similarly to risk.By contrast, in the self-partner tradeoff context, participants act more averse to partner risk and less averse to self risk.Table 5 provides evidence for excuse-driven risk preferences when pooling data from the charity study and partner study, and as shown in Column 2, finds qualitatively but not significantly larger evidence for excusedriven risk preferences in the partner study.Moreover, as shown in Columns 3 and 4 of Table 5, it remains true that participants with higher values of X are more likely to exhibit a stronger tendency for excuse-driven behavior.c )), and charity-dollar valuations of self lotteries (Y c (P s )) or charity lotteries (Y c (P c )); and in the partner-study: self-dollar valuations of self lotteries (Y s (P s )) or partner lotteries (Y s (P p )), and partner-dollar valuations of self lotteries (Y p (P s )) or partner lotteries (Y p (P p )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars or partner-dollars are scaled as percentages of $X.The results are from regressions of Equation 2 modified to include the shown interactions and modified such that charity is replaced by other (an indicator for charity or partner).(X − X) is a participant's X minus the average X. partner-study is an indicator for the partner study.For observations involving multiple switch points, the first switch point is assumed.Participants with censored X values or X values that resulted from decisions with multiple switch points are excluded.

Conclusion
In examining how individuals respond to risk in charitable giving decisions, this study documents a novel pattern of behavior.When participants cannot use risk as an excuse not to give, in the no self-charity tradeoff context, they respond very similarly to risk in self lotteries and charity lotteries.However, when participants may use risk as an excuse not to give, in the self-charity tradeoff context, they act more averse to charity risk and less averse to self risk.
This excuse-driven interpretation is bolstered by documenting an individual level of consistency in excuse-driven behavior.Participants' extent of excuse-driven risk preferences is strongly correlated with their level of selfishness, and engagement in excuse-driven behavior in a moral wiggle room task, as developed in Dana et al. (2007).In an additional study, excuse-driven risk preferences are similarly strong when participants decide between payoffs for themselves and payoffs for another study participant.
As the observed excuse-driven risk preferences yield violations of transitivity29 , these results may be most easily rationalized with a menu-dependent model that allows for different responses to risk depending on whether or not the environment permits excuses. 30Another possibility may involve fleshing out models where individuals infer their type based off of their own past behavior, but their inference about their prosocial tendencies is less informative in the presence of risk. 31ther fruitful avenues for future work may involve testing related policy implications.The evidence for excuse-driven types of individuals, in particular, indicates that charities may be able to exploit the heterogeneity in the types of potential donors when determining how to target fundraising requests.Potential implications for nonprofit organizations may also relate to other avenues for excuse-driven behavior in charitable giving; for instance, Exley (2015) demonstrates how individuals may use lower charity performance metrics as excuses not to give.

Block 1, List 1
In this list: -Option A will always be you receive $10 dollars (and the ARC receives nothing).
-Option B will be the ARC receives some dollar amount (and you receive nothing).As you proceed down the rows of a list, the amount the ARC receives will increase from $0 to $30.In this list: -Option A will always be you receive $5 dollars (and the ARC receives nothing).
-Option B will be the ARC receives some dollar amount (and you receive nothing).As you proceed down the rows of a list, the amount the ARC receives will increase from $0 to $30. -Option A will always be you receive $10 dollars with probability 95%, and $0 otherwise (and the ARC receives nothing).
-Option B will be you receive some dollar amount (and the ARC receives nothing).As you proceed down the rows of a list, the amount you receive will increase from $0 to $10. -Option A will always be the ARC receives $20 dollars with probability 95%, and $0 otherwise (and you receive nothing).
-Option B will be the ARC receives some dollar amount (and you receive nothing).As you proceed down the rows of a list, the amount the ARC receives will increase from $0 to $20. -Option A will always be the ARC receives $20 dollars with probability 95%, and $0 otherwise (and you receive nothing).
-Option B will be you receive some dollar amount (and the ARC receives nothing).As you proceed down the rows of a list, the amount you receive will increase from $0 to $10. -Option A will always be you receive $10 dollars with probability 95%, and $0 otherwise (and the ARC receives nothing).
-Option B will be the ARC receives some dollar amount (and you receive nothing).As you proceed down the rows of a list, the amount the ARC receives will increase from $0 to $20.In following Tversky and Kahneman (1992), among many others, I assume a probability weighting function of π(p) = p γ /((p γ + (1 − p) γ ) 1 γ ) and a power bernoulli utility of u(x) = x α .Solving for the certainty equivalent or self-dollar valuation of the self lottery, Y s (P s ), as a function of p yields the following: Y s (P s ) = p γ 10 α /((p γ + (1 − p) γ ) 1 γ ) 1 α .Estimating this equation via non-linear least squares with standard errors clustered at the individual level yields α = 1.07(0.03)and γ = 0.77(0.02).These results include data for 99 participants (i.e., excludes the one participant whose X value resulted from decisions with multiple switch points).For the 1% of valuations involving multiple switch points, the first switch point is assumed.Andreoni & Sprenger estimates are of the same equation given the α = 1.07 and γ = 0.73 from Andreoni and Sprenger  (2011).Tversky & Kahnemann estimates are of the same equation given the α = 0.88 and γ = 0.61 from Tversky and Kahneman (1992).

Figure B.2: Decision Level Results
No Self-Charity Tradeoff The error bars show the confidence interval for two standard errors.The calculations for the no self-charity tradeoff context result from the charity-dollar valuations of charity lotteries, Y c (P c ), and the self-dollar valuations of self lotteries, Y s (P s ).The calculations for the self-charity tradeoff context result from the self-dollar valuations of charity lotteries, Y s (P c ), and the charity-dollar valuations of self lotteries, Y c (P s ).Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X i .The results include data for the 57 participants in my main subsample (i.e., excludes participants with X values that were censored or resulted from decisions with multiple switch points).For the 1% of valuations involving multiple switch points, the first switch point is assumed. in the no self-charity tradeoff context -i.e., self-dollar valuations of self lotteries (Y s (P s )), and charity-dollar valuations of charity lotteries (Y c (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X i .The results are from regressions of Y li = β 0 + β 1 charity li + ( P λ P + i µ i ) + li , where Y li is the valuation of a lottery l by individual i (in the case of the Tobit regression, this involves the upper and lower bounds of Y li ); charity li is an indicator for charity lotteries; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1} (P=0.05excluded); µ i are fixed effects for individual i (individual i = 1 excluded).Probability fixed effects are shown when included, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with multiple switch points, respectively, are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.The dependent variables are differences in lottery valuations D P in the no self-charity tradeoff context -i.e., self-dollar valuations of self lotteries minus charity-dollar valuations of charity lotteries (Y s (P s ) − Y c (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charitydollars are scaled as percentages of $X i .The results are from regressions of D P i = P λ P + i , where D P i is the difference in lottery valuations for probability P by individual i; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1, 0.05}.Probability fixed effects are shown, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.The dependent variables are differences in lottery valuations D p in the self-charity tradeoff context -i.e., charity-dollar valuations of self lotteries minus self-dollar valuations of charity lotteries (Y c (P s ) − Y s (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charitydollars are scaled as percentages of $X i .The results are from regressions of D P i = P λ P + i , where D P i is the difference in lottery valuations for probability P by individual i; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1, 0.05}.Probability fixed effects are shown, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.)), and charity-dollar valuations of self lotteries (Y c (P s )).Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X i .The results are from regressions of Y li = β 0 + β 1 tradeoff li + ( P λ P + i µ i ) + li , where Y li is the valuation of a lottery l by individual i (in the case of the Tobit regression, this involves the upper and lower bounds of Y li ); tradeoff li is an indicator for valuations occurring in the self-charity tradeoff context; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1} (P=0.05excluded); µ i are fixed effects for individual i (individual i = 1 excluded).Probability fixed effects are shown, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.Valuations in self-dollars are scaled as percentages of $10.The results are from regressions of Y li = β 0 + β 1 charity li + ( P λ P + i µ i ) + li , where Y li is the valuation of a lottery l by individual i (in the case of the Tobit regression, this involves the upper and lower bounds of Y li ); tradeoff li is an indicator for valuations occurring in the self-charity tradeoff context; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1} (P=0.05excluded); µ i are fixed effects for individual i (individual i = 1 excluded).Probability fixed effects are shown, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.c )), and charity-dollar valuations of self lotteries (Y c (P s )).Valuations in charity-dollars are scaled as percentages of $X i .The results are from regressions of Y li = β 0 + β 1 tradeoff li + ( P λ P + i µ i ) + li , where Y li is the valuation of a lottery l by individual i (in the case of the Tobit regression, this involves the upper and lower bounds of Y li ); tradeoff li is an indicator for valuations occurring in the self-charity tradeoff context; λ P are fixed effects for lotteries with probability P ∈ {0.95, 0.9, 0.75, 0.5, 0.25, 0.1} (P=0.05excluded); µ i are fixed effects for individual i (individual i = 1 excluded).Probability fixed effects are shown, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.-i.e., self-dollar valuations of self lotteries (Y s (P s )), charity-dollar valuations of charity lotteries (Y c (P c )), charity-dollar valuations of self lotteries (Y c (P s )), and self-dollar valuations of charity lotteries (Y s (P c )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X i .The results are from regressions of Equation 2. "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 1 participant is always excluded because their X value resulted from decisions with multiple switch points.The dependent variables are lottery valuations Y l -i.e., self-dollar valuations of self lotteries (Y s (P s )), partnerdollar valuations of partner lotteries (Y p (P p )), partner-dollar valuations of self lotteries (Y p (P s )), and self-dollar valuations of partner lotteries (Y s (P p )). Valuations in self-dollars are scaled as percentages of $10, and valuations in charity-dollars are scaled as percentages of $X.The results are from regressions of Equation 2 modified such that charity is replaced by partner.Probability fixed effects are shown when included, and "Ind FE" indicates whether or not individual fixed effects are included."Obs with MSP" and "Ind with MSP" indicate whether or not observations with, or individuals that have observations with, multiple switch points are included.When observations involving multiple switch points are included, the first switch point is assumed."Censored X" indicates whether or not participants with censored X values are included.Note that 2 participants are always excluded because their X values resulted from decisions with multiple switch points.

Figure
Figure 1: Preview of Results

Figure
Figure 2: Distribution of X

Figure
Figure 3: Distribution of X in Partner Study

Figure
Figure 4: Example Participant without Excuse-Driven Risk Preferences

Figure
Figure 5: Example Participant with Excuse-Driven Risk Preferences Valuations of Charity Lotteries

Figure
Figure 6: Lottery Valuations in Partner Study

For
each row, all you have to do is decide whether you prefer Option A or Option B. Indicate your preference by selecting the corresponding button.Most people begin by preferring Option A and then switch to Option B, so one way to complete this list is to determine the best row to switch from Option A to Option B

For
each row, all you have to do is decide whether you prefer Option A or Option B. Indicate your preference by selecting the corresponding button.Most people begin by preferring Option A and then switch to Option B, so one way to complete this list is to determine the best row to switch Price List: Example from Self Dollar Valuation of Self Lottery, Y s (P s ), Block Block 2, List 1 In this list:

For
each row, all you have to do is decide whether you prefer Option A or Option B. Indicate your preference by selecting corresponding button.Most people begin by preferring Option A and then switch to Option B, so one way to complete this list is to determine the best row to switch from Option 10 with probability 95%, and $0 otherwise You: $0 You: $10 with probability 95%, and $0 otherwise You: $0.50 You: $10 with probability 95%, and $0 otherwise You: 10 with probability 95%, and $0 otherwise You: $10 A.4 Valuation Price List: Example from Charity Dollar Valuation of Charity Lottery, Y c (P c ), Block Block 3, List 1 In this list:

For
each row, all you have to do is decide whether you prefer Option A or Option B. Indicate your preference by selecting the corresponding button.Most people begin by preferring Option A and then switch to Option B, so one way to complete this list is to determine the best row to switch from Option receives) ARC: $20 with probability 95%, and $0 otherwise ARC: $0 ARC: $20 with probability 95%, and $0 otherwise ARC: $1 ARC: $20 with probability 95%, and $0 otherwise ARC: 20 with probability 95%, and $0 otherwise ARC: $20 A.5 Valuation Price List: Example from Self Dollar Valuation of Charity Lottery, Y s (P c ), Block Block 4, List 1 In this list:

For
each row, all you have to do is decide whether you prefer Option A or Option B. Indicate your preference by selecting the corresponding button.Most people begin by preferring Option A and then switch to Option B, so one way to complete this list is to determine the best row to switch from Option 20 with probability 95%, and $0 otherwise You: $0 ARC: $20 with probability 95%, and $0 otherwise You: $0.50 ARC: $20 with probability 95%, and $0 otherwise You: 20 with probability 95%, and $0 otherwise You: $9.50 ARC: $20 with probability 95%, and $0 otherwise You: $10 A.6 Valuation Price List: Example from Charity Dollar Valuation of Self Lottery, Y c (P s ),

For
Figure B.1: Estimates from Cumulative Prospect Theory

Table 1 :
Types of Lottery Valuations Resulting from Binary Decisions

Table 3 :
Moral Wiggle Room Payoffs

Table 4 :
Examining Heterogeneous Effects * * p < 0.05, * * * p < 0.01.Standard errors are clustered at the individual level and shown in parentheses.The dependent variables are lottery valuations Y l -i.e., self-dollar valuations of self lotteries (Y s (P s )) or charity lotteries (Y s (P

Table 5 :
Lottery Valuations in Charity Study and Partner Study * p < 0.05, * * * p < 0.01.Standard errors are clustered at the individual level and shown in parentheses.The dependent variables are lottery valuations Y l -i.e., in the charity-study: self-dollar valuations of self lotteries (Y s (P s )) or charity lotteries (Y s (P * p < 0.10, *

Table B
p < 0.10, * * p < 0.05, * * * p < 0.01.Standard errors are clustered at the individual level and shown in parentheses.The dependent variables are self lottery valuations Y l -i.e., self-dollar valuations of self lotteries (Y s (P s *

Table B .
7: Lottery Valuations in Self Dollar Valuations * p < 0.05, * * * p < 0.01.Standard errors are clustered at the individual level and shown in parentheses.The dependent variables are lottery valuations elicited in self-dollar valuations Y l -i.e., self-dollar valuations of self lotteries (Y s (P s )), and self-dollar valuations of charity lotteries (Y s (P c )).

Table B
p < 0.10, * * p < 0.05, * * * p < 0.01.Standard errors are clustered at the individual level and shown in parentheses.The dependent variables are lottery valuations Y l *