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Partisan Consumerism: Experimental Tests of Consumer Reactions to Corporate Political Activity

To what extent do consumers’ preferences change when they learn about firms’ partisan allegiances? We address this question by conducting a series of experiments in which Democrats and Republicans were presented with factual information about corporate political donations. Outcomes were measured through expressed shopping intentions as well as a revealed consumer preference. Respondents became significantly more (less) likely to patronize chains that support (oppose) their party. The effects are found for both convenience samples and representative national samples and when information is conveyed in the context of a survey or unobtrusively via direct mail. Effects are especially large among those with strong partisan attachments. We conclude by arguing that the potential for partisan consumerism has risen with the advent of social media but may be undermined by a campaign finance system that increasingly allows for undisclosed corporate donations.

corporate partisan allegiance has not been studied systematically, leaving open the question of whether partisan polarization affects brand image and consumer choice. The current study seeks to fill that void.
Recent studies affirm the power of partisanship as a social identity that is expressed through in-group affinity and outgroup hostility (Iyengar at al. 2019). This tendency for individuals to view copartisans positively and opposing partisans negatively (Iyengar and Westwood 2015, 691), or "affective polarization," has been on the rise in the United States, and a growing number of studies demonstrate that partisan affect influences attitudes and behaviors that extend well beyond the political realm (e.g., Iyengar et al. 2019). We argue that partisanship is expressed in consumer preferences when corporate political activity provides cues about firms' partisan allegiances. In the studies reported below, we leverage information about corporations' political contributions in recent election cycles to convey partisan signals.
We investigate the phenomenon we label "partisan consumerism" through a series of novel experiments in which subjects are randomly exposed to factual information indicating which large, national chains donated money to majorparty candidates through their political action committees (PACs). Our experimental tests, described below, are conducted in survey and field settings and measure attitudinal (future patronage intentions) and behavioral (raffle entry with gift card selection) outcomes. Taken together, the four experiments we present suggest that party attachments express themselves in consumer choice when voters are informed about retailers' partisan allegiances. Ordinarily, this form of political expression is undercut by partisans' lack of information about which corporations support each party. 2 When such information is made salient, however, its effects appear to be substantial. Pooling our experiments, we further investigate treatment effect heterogeneity and find statistically significant differences between strong and weak partisans. 3 Both are responsive to information about corporate donations, but the apparent effects among strong partisans are especially large. We conclude by discussing the implications of these findings, arguing that the potential for partisan consumerism has risen with the advent of social media but may be undermined by a campaign finance system that increasingly allows for undisclosed corporate donations.

PRIOR RESEARCH ON POLITICAL CONSUMERISM
The widening lens of political behavior research has come to include the marketplace as a locus of political expression. The political consumerism hypothesis (Anderson and Cunningham 1972;Keum et al. 2004;Stolle and Micheletti 2015) contends that individuals select among products and producers based on social, political, and moral considerations, such as "fair trade" practices (Hainmueller, Hiscox, and Sequeira 2015), ethical labor standards (Hainmueller and Hiscox 2015b), and corporate political activity (Shah et al. 2007, 219).
Political consumerism may take many forms. Boycotts punish businesses for unfavorable behavior by withholding demand, while "buycotts" reward companies for favorable behavior via increased demand (Bennett and Entman 2001;Nielson 2010;Shah et al. 2007). Large segments of the American public report that they engage in boycotts and buycotts (Endres and Panagopoulos 2017;Newman and Bartels 2011), and this phenomenon is common in Western Europe (Ferrer-Fons and Fraile 2014), the Middle East (Benstead and Reif 2015), and Latin America (Echegaray 2015). Although by no means new (Micheletti, Follesda, and Stolle 2004), this form of consumerism is a manifestation of what Bennett (1998) terms "lifestyle politics" and arguably reflects the growing tendency to find political meaning in recreational experiences, fashion decisions, and other personal choices (Shah et al. 2007, 219). 4 Is political consumerism a force that corporations must heed? The answer seems to hinge on the political values at stake. Consumer demand has been shown to increase when products are advertised with reference to widely shared values, such as support for human rights (Hainmueller et al. 2015;Hainmueller and Hiscox 2015b) or environmental protection (Hainmueller and Hiscox 2015a), and many corporations tout their commitments to uncontroversial causes. As we move from consensus values to more contentious issues, the political stances of corporations are rarely stated overtly, and anecdotal evidence suggests that corporations are wise to avoid entangling themselves in divisive political issues. A telling case arose in June 2012, when the American fast-food chain Chick-fil-A became the center of controversy. Reports surfaced that the company's charitable arm, the WinShape Foundation, had donated millions to organizations hostile to same-sex marriage rights. Opponents called for protests and boycotts nationwide, while supporters rallied to eat at the restaurants (Severson 2012). A few weeks later, the chain sought to withdraw from the fray, issuing a statement that, "going forward, our intent is to leave the policy debate over same-sex marriage to the government and political arena." One implication of the Chick-fil-A fracas is that corporations wade into partisan politics at their peril. Party affiliation has long been recognized as a highly influential political orientation (Campbell et al. 1960), and recent work has underscored the range of ways in which partisan attachments express themselves. Building on social identity theory (Tajfel and Turner 1979), experiments by Huddy, Mason, and Aaroe (2015) show that partisans' political actions, such as campaign involvement, express a deep-seated group identity, which in turn leads partisans to rise to the defense of the party in-group. Although Huddy et al. (2015) do not analyze consumer preferences, their core argument implies that consumers will react to information about corporate campaign activity in ways that reflect their partisan predispositions, especially in environments in which people are routinely exposed to hostile rhetoric between warring partisan camps (Suhay, Bello-Pardo, and Maurer 2018). Corporations that support the opposing party will be perceived as a threat to the partisan in-group, while those that support one's own party will be seen as meriting in-group loyalty.
Recent research lends credence to the notion that partisan sentiment in the United States has economic repercussions. McConnell et al. (2018) present a series of experiments demonstrating that partisans are willing to forgo wages for the prospect of working for a copartisan or to avoid entering into a labor agreement that would financially benefit the opposing political party. Gift and Gift (2015) show that job applicants whose resumes signal their party affiliations receive fewer callbacks when applying for jobs in areas where their party is in the minority. 5 Such findings are consistent with theoretical perspectives that emphasize the role of partisanship as a social identity or that call attention to the many ways in which partisan affect is engaged and expressed (Chen and Rohla 2018;Iyengar and Westwood 2015;Iyengar et al. 2019;Lelkes and Westwood 2017;Nicholson et al. 2016). One unanswered question is whether partisanship affects consumer intentions and choices.
The many boycotts and buycotts that broke out during and after the 2016 Trump presidential campaign suggest the potential importance of partisan consumerism. Commercial entities were singled out in presidential "tweets" for their support of, or opposition to, Trump, attracting waves of media attention. 6 Survey evidence from tracking polls, such as YouGov's weekly BrandIndex ratings (a weighted score based on six distinct evaluations for each brand; higher scores reflect more favorable assessments), suggests that these tweets have had a polarizing effect on partisans' evaluations. During the month before President Trump denounced Nordstrom on Twitter for canceling his daughter Ivanka's product line (January 8-29, 2017), the average BrandIndex rating of Nordstrom was 15.7 for Republicans and 15.6 for Democrats. During the month following this tweet (February 12 through March 5), BrandIndex averages plummeted to 1.0 among Republicans and rose to 22.6 among Democrats-a sizable change given that the weekly series had a placid standard deviation of less than 4 prior to the controversy. 7 Yet it remains unclear whether these controversies changed partisans' behavior, as sales data are seldom made public, and even reliable sales data would not necessarily allow researchers to rule out the confounding effects of omitted variables. We therefore devise experimental tests of the partisan consumerism hypothesis by assessing the extent to which partisans change their consumer choices based on information about which political parties corporations support.

STUDIES 1 AND 2
During the summer of 2015, we conducted two survey experiments with Amazon Mechanical Turk respondents. In the first study, we randomly assigned information about two types of franchises, hamburger restaurants and large retail chains. In the second study, we expanded the list of categories from two to four by including pizza restaurants and drug stores. In all cases, we take advantage of the fact that there is often considerable variation in the donation patterns of chains within the same sector.

Experimental design
In order to ensure that our experimental intervention was relevant to the participants, each survey experiment was 5. For work on consumer behavior that focuses not on party support but instead on partisan perceptual bias in assessments of the economy, see the conflicting results presented by Gerber and Huber (2009) and Mc-Grath (2017).
6. For example, on January 12, 2017, President Trump tweeted, "Thank you to Linda Bean of L.L.Bean for your great support and courage. People will support you even more now. Buy L.L.Bean." 7. A more systematic analysis of these aggregate tracking poll data across a range of firms that became embroiled in partisan rancor falls outside the scope of the current paper but reveals a similar pattern of partisan polarization. conducted over two waves of interviews. In the first wave, Mechanical Turk workers were paid $1 to complete a brief five-minute survey that assessed (1) the frequency with which they patronized each of the stores that would later appear in our second wave quiz, (2) their ratings of these stores, (3) their party identification, and (4) demographic characteristics. Respondents were also asked whether they would be willing to participate in a follow-up survey. A total of 4,030 respondents completed the baseline survey in study 1; another 5,335 completed the baseline survey in study 2. Approximately a week after each initial survey, we invited a subset of baseline respondents to complete a follow-up survey. Invitations were extended only to those who indicated a willingness to complete a follow-up survey, maintained an active Mechanical Turk account, provided an answer to the baseline survey's party identification question, and indicated that they patronized at least one of the chains in each of the shopping categories. Invitations totaled 3,457 in study 1 and 3,413 in study 2.
In order to motivate subjects to attend closely to the content of the quiz, the second wave survey was prefaced with the following instructions: "We will be asking you factual questions about some of the places where you may eat and shop. At the end of each section, you will be given the opportunity to enter a random drawing to win one of one hundred $10 gift cards. For each question you answer correctly, we will add an additional entry for you in order to increase your chances of winning." The overwhelming majority of respondents (96%) indicated their willingness to participate in each lottery, which is not surprising given that the prize was large in relation to the flat wage paid to those who participated in the survey.
In each study, we randomly assigned subjects to one of five experimental groups. 8 The first quiz focused on three hamburger chains (Burger King, McDonald's, and Wendy's). The quiz began with three questions on nonpolitical content (e.g., "Which of the three chains was the first to introduce a 'dollar menu'?"). All respondents saw the same three initial questions and answers. The final question was manipulated randomly in one of four ways. In the Republican Percentage condition, subjects were asked, "Which of these companies gave the largest percentage of their political contributions to Republican candidates in 2014?" and, after answering, were told that the correct answer is Wendy's: "Through their political action committee, Wendy's gave 93% of their total political contributions to Republican candidates in 2014." In the Democratic Percentage condition, subjects were asked, "Which of these companies gave the largest percentage of their political contributions to Democratic candidates in 2014?" and, after answering, told that the correct answer is Burger King. In the Republican Amount condition, subjects were asked, "Which of these companies gave the most dollars to Republican candidates in 2014?" and, after answering, told that the correct answer is McDonald's. The Democratic Amount question was worded similarly, and again the answer is McDonald's. Finally, a control condition asked subjects a nonpolitical question: "In 2010, which restaurant added sea salt to their fries?" Respondents were given the correct answer to every question; in this way we were able to deliver information about the partisan sympathies of chains in an unobtrusive way.
After each quiz, subjects were asked whether they would like to participate in a lottery for one of the one hundred $10 gift card prizes. There were no apparent effects of the treatment on willingness to participate in the lottery for any of the quizzes in either study 1 or study 2. 9 Those who agreed were then asked, "Which of the following companies would you like to receive a gift card to if you win the raffle?" and presented with the list of stores that appeared in the quiz. After selecting a gift card, respondents were asked their future shopping intentions. This sequence of randomly assigned quiz content, gift card preference, and anticipated patronage of each store was repeated for retail stores, pizza restaurants, and drug stores. 10 Assignment to treatment condition should be statistically unrelated to respondents' background covariates as measured in the baseline survey wave: age, gender, presidential approval, and the frequency with which they patronize the largest chain in each of the store categories. Multinomial regression of the assigned experimental condition on these covariates, as expected, produces insignificant likelihood ratio statistics. The p-values for the six random assignments range from .23 to .88.
The distribution of quiz answers strongly suggests that the political information was novel to respondents. Table A1 (tables A1-A8 are available online) indicates the correct answer to each experimentally manipulated question, and table A2 summarizes respondents' answers to each of the quiz questions. Whereas a large proportion of subjects knew, 8. In study 1, we included a sixth condition that asked subjects about which chain contributed the most to both parties. 9. In study 1, an average of 96.2% of respondents assigned to a treatment and 96.0% of those assigned to control agreed to participate in a lottery; corresponding numbers for study 2 are 95.9% and 95.0%.
10. The chain stores were presented in random order, and a fresh random assignment of experimental condition was performed for each store category. for example, that bacon is not a standard ingredient in Burger King's "Whopper" hamburger, answers to the factual questions about political donations were scarcely more accurate than would be expected by random guessing. The fact that the political information is new to respondents has important implications for the interpretation of our results because it suggests that a large majority of each treatment group had an opportunity to update their evaluations of the chain stores based on the information provided.
How subjects respond to information about political contributions presumably depends on their own party attachments. Republicans should evaluate Wendy's more favorably upon learning that Wendy's is the hamburger chain that gives the largest proportion of its donations to Republicans; the same news should produce a less favorable assessment among Democrats. For this reason, we assess treatment effects separately according to whether subjects identified as Republicans or Democrats in the baseline survey of each study via the party identification item used by the American National Election Studies (ANES) since the 1950s: "Generally speaking, do you usually think of yourself as a Republican, a Democrat, an Independent, or something else?" Although the distribution of partisans in our two studies is more Democratic than would be typical of a representative national survey, we nevertheless have ample numbers of Democrats and Republicans for purposes of assessing treatment effects for each partisan group. In the first study, we obtained responses from 949 Democrats and 349 Republicans; in the second study, 1,029 Democrats and 466 Republicans. Taken together, we have a total of 48 experimental comparisons: six sets of experimental tests (hamburger and retail chains in study 1; hamburger, retail, pizza, and pharmacy chains in study 2), each featuring four treatment group comparisons to a control condition, which are in turn analyzed separately for self-described Democrats and Republicans. This wealth of comparisons provides a precise assessment of whether, and to what extent, political information affects subjects' gift card preferences. Table A3 presents detailed results for each study, treatment condition, and partisan group so that readers can inspect each experimental comparison. Entries in boldface indicate an instance in which a theoretical prediction is confirmed empirically. For example, the second column of table A3 indicates that in study 1, 28% of Democrats who were randomly informed that Wendy's gave disproportionately to Republicans selected a Wendy's gift card, as opposed to 49% of Democrats assigned to the control group. The obverse results for Republicans are presented three rows below: Wendy's is the preferred gift card among 56% of Republicans who were informed of Wendy's GOP support, as compared to 41% among Republicans in the control group.

Results
The overall pattern follows the pattern predicted by the partisan consumerism hypothesis. For each of the 48 comparisons of a treatment group with a control group, we assess whether the apparent treatment effect is in the predicted direction. For Democratic respondents, the prediction is that demand for gift cards from firm j diminishes (increases) when that firm is shown to support Republicans (Democrats). For Republicans, these predictions are reversed. We find that 36 of the 48 comparisons point in the predicted direction. Randomization inference shows that a set of estimates this lopsided would occur by chance with p ! :001. 11 In order to assess the average magnitude of the treatment effect, we pool the data and use logistic regression as well as ordinary least squares regression to predict gift card preference. The linear model may be expressed as where the independent variable of interest (T i ) is a treatment indicator scored 1 if the firm is shown to support one's party, 21 if the firm is shown to oppose one's party, and 0 otherwise. For example, when Wendy's is presented as a pro-Republican firm, the outcome is scored 1 if the respondent prefers a Wendy's gift card and zero otherwise; the treatment indicator is scored 1 for treated Republicans, 21 for treated Democrats, and 0 for everyone in the control condition. The covariates include 47 indicator variables (S ki ) for each experimental stratum (e.g., Republicans in study 1 who receive a hamburger chain treatment) less one. In other words, every respondent is assigned to one condition in each experiment; the observations are "stacked" so that all 48 experiments are analyzed at once; and the inclusion of the S ki indicators provides a different intercept to each distinct experiment. To assess robustness, we examine how the results are affected by the inclusion of a covariate (P i ) measured in the screening wave of the survey, which gauges past patronage for the relevant firm on a scale ranging from 1 to 5. Standard errors are assessed using bootstrapping, which takes account of the fact that, within a given experiment, subjects in the control group appear repeatedly in the pooled regression.
The results presented in table 1 demonstrate that the treatment significantly affects preferences. The estimated effect is a 0.199 change in log-odds of gift card preference, with a standard error of 0.039 (p ! :001). This estimate is scarcely affected by the inclusion of a covariate measuring past consumption. 12 To convey the size of this effect in percentage point terms, we estimate the same model using ordinary least squares (OLS) regression. Without controlling for covariates, the average treatment effect is a 4.0 percentage point change in gift card preference.
This treatment effect is also apparent when consumer preference is measured by an outcome other than choice of gift card. Respondents were subsequently asked about their future shopping and dining intentions. For example, respondents were asked, "Thinking ahead, and using the following scale, how often do you plan to eat at the following hamburger restaurants?" An ordered series of five response options ranged from "never" to "several times a week." In order to compare treatment and control response distributions along the same underlying logistic metric as the analysis above, we used ordered logit to regress frequency of anticipated dining or shopping on a dummy variable for treatment. Consistent with the findings regarding the gift card, 40 of 48 estimated treatment effects are in the predicted direction, significantly greater than the 24 estimates we would expect under the null hypothesis of no treatment effect (p ! :001). Pooling the ordered logistic regression analysis in the same way that we did for the logistic analysis of gift card preference, we obtain very similar results. Table 2 reports that the model without pretreatment covariates produces a change in log-odds of 0.161 with a standard error of 0.028; with covariates, the estimate climbs to 0.199 with a standard error of 0.031. In both cases, p ! :001. In keeping with the literature on consumer choice, it seems to make little difference whether we work with a stated shopping preference or a revealed preference for the purpose of assessing treatment effects in these two studies. 13 If anything, treatment effects for stated preferences appear to be a shade weaker. Applying a linear probability model to a binary version of this dependent variable scored 0 if the respondent "never" intends to shop or dine and 1 otherwise, we find a shift in probability of 2.2 or 2.7 percentage points, depending on whether covariates are included. In both cases, p ! :001. These effects are large enough to be economically consequential, and the mere threat of such consumer reactions (perhaps amplified in scope by social media) is believed to be sufficient to provoke abrupt changes in corporate policy (Manjoo 2017).

STUDY 3
We sought to verify that the effects we observed in the convenience samples hold when we replicate the study using a nationally representative subject pool. Study 3 was conducted as part of the Cooperative Congressional Election Study (CCES) and featured similar quizzes on 12. The estimated change in log-odds after controlling for past purchase behavior is 0.204, with a standard error of 0.042 (p ! :001). Note that the average shift in preference across all of the assigned information conditions arguably understates the true magnitude of the information effect. In some instances, the information revealed to respondents conveys at most a weak signal of party support. See table A4. Among pizza chains, for example, the largest percentage donor to Democrats is Domino's, but that firm gives Democrats a meager 22%. It should not be surprising to find in table A3 that this information fails to make Domino's appreciably more attractive in the eyes of Democrats or less attractive in the eyes of Republicans. Because we provided only truthful information to respondents (and therefore did not randomly vary the reported donations made by each corporate chain), our experiment does not allow for a direct test of the hypothesis that partisan consumerism matters most when corporations display substantial support, but the data certainly hint that this is the case. (2011) for a meta-analysis of preferences for specific products and short time horizons; see also Loomis (2011) for metaanalyses of the scale differences between stated and revealed willingness to pay. hamburger chains and retail stores. 14 Outcomes were measured via future shopping and dining intentions, using question wording from studies 1 and 2. The results from eight tests (two partisan groups by two experimental conditions by two types of chain stores) confirm the results presented above: all eight ordered logistic regression estimates are in the predicted direction. Pooling the results from the eight strata from this study and applying the same model specifications as above, table 3 reports a change of log-odds of 0.304 with a standard error of 0.078. Applying OLS regression to a binary variable of never versus non-never shopping intentions, we find an average treatment effect of 6.8 percentage points (p ! :001). 15

STUDY 4
Studies 1, 2, and 3 demonstrate that partisans respond to information about restaurant and retail chains' record of partisan support. The results are robust across parties and outcome measures, yet two questions remain about the generalizability of the results. The first is whether the effect can be induced in some way other than via a survey quiz that incentivizes respondents to pay close attention. The second is whether the treatment effect persists over time. Studies 1, 2, and 3 asked respondents about their preferences and intended behavior shortly after they encountered the experimental information. In order to address these questions, study 4 tests the effect of a postcard mailed to the home address of panel survey respondents, who answered an endline survey a week later.

Experimental design
Study 4 was conducted in partnership with YouGov, which recruited a sample of respondents from its national online panel. Subjects were restricted to self-identified Democrats or Republicans based on the stem question of the ANES party identification measure. 16 Respondents completed a preliminary survey that probed them about basic political attitudes and consumer preferences. These responses furnish pretreatment, baseline measures of social, political, and consumer attitudes and behaviors. A total of 1,658 respondents completed the initial wave, fielded June 15-24, 2016. Our experimental treatment consisted of a postcard mailing designed to provide information about the political contributions of firms in the 2014 federal elections. A professional graphics designer produced visually engaging color postcards. The content of the postcards was designed to parallel as closely as possible the key treatment elements in studies 1-3. (See appendix, available online, for reproductions of the postcards.) To enhance power, the treatment focused on just two 14. The preelection wave measured party identification as part of the common content, but included no questions on shopping habits. The fast food and retail quizzes were conducted during the postelection survey. Of the 907 respondents who completed the postelection survey, 331 of them identified as Democrats, and 250 as Republicans. The wording of the quiz items may be found in the appendix.
15. As strong as these results are, they would be even stronger if we were to prime partisan considerations directly rather than in an oblique way via a quiz. The 2016 CCES preelection survey asked, "Large corporations often donate money or free equipment to the Republican and Democratic national conventions. In 2016, [Apple Inc. / Ford Motor Company] announced that it would not be a sponsor of the 2016 Republican National Convention, which it had supported in 2008 and 2012. Does this decision make you more likely to purchase products made by [Apple Inc. / Ford Motor Company], less likely, or will it make no difference?" As expected, Republicans and Democrats offered sharply different responses.
16. Thus, independents, including those who lean toward one party, are excluded. chain stores with sharply contrasting patterns of party support. One postcard highlighted PAC contributions by Bed Bath & Beyond, a chain that directed 71% of its donations to Democratic candidates in the 2014 cycle; the other provided parallel information about Wendy's, a chain that directed 93% of its contributions to GOP candidates in 2014. 17 The postcards also noted that these percentages were higher than two competing firms in each commercial category (McDonald's and Burger King for hamburger chains; Target and Walmart for big-box store chains).
YouGov randomly assigned half of the respondents to receive the Bed Bath & Beyond postcard and the other half to receive the Wendy's postcard. Postcards were mailed using first-class postage on June 30, 2016. Approximately one week following expected delivery of the postcards, YouGov fielded a follow-up online survey among subjects who had completed the baseline survey and were mailed a postcard. The second wave of the survey featured questions about respondents' social and political views, and, crucially, about future consumer intentions. A total of 1,446 subjects completed the follow-up wave of the survey, a reinterview rate of 87%. Reinterview rates differed insignificantly across experimental conditions: 86.6% among those receiving the Wendy's postcard and 87.9% among those receiving the Bed Bath & Beyond postcard. Of those who completed the end-line survey, 71% were white, 58% were female, and 58% described themselves as Democrats. Fully 68% reported that they eat at Wendy's and 58% that they shop at Bed Bath & Beyond at least "a few times a year" in the baseline survey.
Our outcome measure is drawn from a series of survey items probing subjects about their consumer intentions. Using the same wording and format as in studies 1-3, one set of questions asked respondents about their consumer intentions with respect to three fast-food hamburger chains (in random order: Wendy's, McDonald's, and Burger King), while another set inquired about big-box shopping intentions at Target, Walmart, and Bed Bath & Beyond. For each chain, subjects indicated whether they expected to eat or shop either "several times a week," "about once a week," "once or twice a month," "a few times a year," or "never." We again use ordered logistic regression to estimate the latent treatment effect.
As a manipulation check, the second wave interview concluded with two knowledge questions that tested participants' ability to recall the content of the postcards. One question asked, "Which of the following hamburger restaurants gave the highest percentage of its political contributions to Republicans in 2014?" The other asked, "Which of the following big-box stores gave the highest percentage of its political contributions to Democrats in 2014?" The mailings caused the treatment group to become significantly more knowledgeable. Just 6.4% of the untreated group correctly answered the first question, as compared to 27.2% of the treated group. The second question was correctly answered by 3.8% of the untreated group and 14.4% of the treated group. The p-values of these contrasts are well below .001 in both cases. Table 4 reports ordered logistic regression estimates pooled for study 4. Without controlling for past consumer behavior, 17. The postcards informed respondents that the percentages reported were based on numbers compiled by opensecrets.org. The text of the postcards characterizes these contributions as PAC contributions, but the opensecrets.org statistics we cited combine PAC contributions with contributions from corporate executives. Statistics reported in the two MTurk studies were characterized in a similar way, due to our misreading of the opensecrets.org report. In the 2016 CCES, we experimentally varied question wording to refer to contributions by PACs or by corporate executives and found no difference. the estimated treatment effect is only a 0.044 increase in log-odds (SE p 0:074). After controlling for past consumer behavior, this estimate rises to 0.200 with a standard error of 0.082 (p ! :05). As explained in the note to table 4, the unexpected jump in coefficients reflects random imbalance in the treatment assignment-in the pretreatment survey, the treatment group reported lower rates of patronage of the targeted chain stores. Expressed in terms of a linear probability model, favorable information reduces the probability that respondents say they will "never" shop at a given chain by 4.3 percentage points.

Results
Looking back over the assortment of experiments, how large is the effect of information about corporations' political donations in substantive terms? Pooling the observations for all studies in which shopping intentions were modeled using ordered logistic regression (N p 4;239), we obtain an estimate suggesting that the interventions changed the latent logistic response proclivity by 0.206. This movement on the logistic scale is equivalent to shifting the proportion saying that they plan to "never" patronize a chain store from 26.9% (in the control condition) up to 31.1% (in the negative information condition) or down to 23.0% (in the positive information condition). This shift in demand is similar in magnitude to the results of other field experiments that test the effects of information about fair trade (Hainmueller et al. 2015), sweatshop labor (Hainmueller and Hiscox 2015b), or environmental pollution (Hainmueller and Hiscox 2015a). Whereas previous experiments have demonstrated the effect of information on demand for specific products within a store, ours show that information also affects demand for one chain store over another. The latter effect on consumer preference is potentially more consequential because, once in a store, a customer may buy many items.

EVIDENCE OF HETEROGENEOUS EFFECTS
One corollary to the hypothesis that partisan attachments can shape consumer preferences is that, all things being equal, treatment effects should increase with the strength of respondents' party attachments. We use the standard ANES follow-up question on partisan strength to divide subjects in the four studies into "weak" and "strong" partisans. Table 5 simply reestimates the ordered logistic models for these two partisan subgroups. The results indicate that treatment effects increase with the intensity of partisan attachments. Pooling all of the studies, ordered logistic regression produces estimates of 0.251 for strong partisans and 0.168 for weak partisans, with standard errors of 0.036 and 0.032, respectively. The difference in coefficients is significant in the expected direction, with a one-tailed p-value of less than .05. This pattern suggests that the effects we observe would be even more pronounced if corporate political allegiances were disclosed to party activists and leaders, who are especially ardent partisans.

DISCUSSION
Although the literature on party identification is vast, political scientists seldom study the effects of partisanship on consumer preference, presumably because behaviors such as shopping and dining are considered outside the scope of politics. Building on prior research on political consumerism and on party identification, our experiments demonstrate that consumer preferences are influenced by party attachments. Consumers who identify with a party respond to information about the partisan coloration of firms such as Wendy's or Walmart. It appears that few people have much background knowledge about the political sympathies of leading national chains, but, when told which corporations are the largest contributors to a political party, respondents express their partisanship through their consumption choices. Both Democrats and Republicans reward firms that provide financial backing to their party and punish firms that contribute money to the opposing party. This effect was demonstrated in studies 1, 2, and 3, which were carried out in the context of an online survey experiment. 18 Study 4 was less far-reaching in terms of chain stores and relied on smaller subject pools, yet the research design assesses the narrow but important question of whether this effect can be produced outside the survey context and sustained over several days. The overall pattern of results suggests that partisans, on average, reward or punish firms upon learning that their campaign contributions lopsidedly favor one party. Is this pattern a manifestation of partisanship in general, or is it specific to the polarized partisan environment of the contemporary United States? Absent experiments that allow for cross-country or over-time comparisons, we cannot presently answer this question directly. However, recent research, such as Michelitch's (2015) study of price discrimination against out-partisans at election time in Ghana, suggests that economic expressions of partisanship may be found outside the United States and become more prevalent during periods of heightened partisan competition.
Although partisan consumerism is of interest to those who study political expression, the market implications of this phenomenon are ambiguous. If equivalent numbers of Democrats and Republicans move in opposite directions in response to this information, the net effect on consumer preferences may be zero. However, in regions or market niches where the partisan balance strongly favors one party, this type of information could change a firm's market share. This suggests a testable hypothesis: open endorsements of political parties and causes will be rare except where local support approximates a supermajority. (See Gentzkow and Shapiro [2010] for an analogous argument concerning market forces that contribute to "media slant" in news coverage.) From a policy standpoint, one potentially disturbing ramification of these findings is the possibility that they might persuade some corporations to deemphasize their PACs or publicly documented contributions in favor of more discreet categories of political financing. These opaque methods of funding-known colloquially as "dark money"include giving to organizations, like the Chamber of Commerce, which have refused to disclose their donors on the grounds that their activities do not constitute electioneering.
Our findings suggest the far-reaching implications of information that facilitates political expression outside the Note. All studies control for past purchasing behavior except for CCES, which did not measure this covariate. The p-values are calculated using bootstrapping with 10,000 simulations, clustering by respondent. The p-values correspond closely to one-tailed tests based on t-ratios using conventional ordered logit standard errors.
18. In a companion paper (Farrer et al. 2018), we show that information conveyed by quizzes can also change shopping intentions based on companies' reputation for upholding environmental values or LGBT equality. immediate realm of politics. A growing number of organizations, such as grabyourwallet.org, make use of publicly disclosed information in order to orchestrate boycotts and buycotts. At the same time, information costs are declining for politically minded consumers, as products such as the "Buy Partisan" app make corporations' political giving available in real time as products are evaluated in stores or online. The speed and scope of social media-borne information campaigns have arguably raised the stakes of corporate involvement in partisan politics (Surowiecki 2017).
Finally, our findings give credence to legislative proposals designed to increase transparency so that the public is informed about the financial backers whenever communications mention candidates. Given the uncertain prospects of such legislation in the current political environment, the fact that many major donors of dark money are publicly traded corporations creates other options to shine light on their activities, such as shareholder suits or Securities and Exchange Commission-required disclosure. Our studies suggest that, if successful, these disclosure channels would provide information that many citizens would find useful as they make consumer choices.