# Public Acceptance of International Redistribution in High-Income Countries

Adrien Fabre

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PUBLIC ACCEPTANCE OF
INTERNATIONAL REDISTRIBUTION
IN HIGH-INCOME COUNTRIES

ADRIEN FABRE

WORKING PAPER N°2025/26

DECEMBER 2025

<figure><img src="image_2.png" /></figure>
Public Acceptance of International Redistribution
in High-Income Countries

Adrien Fabre*

December 18, 2025

**Link to most recent version**

**Abstract**

Using an original survey of 12,000 respondents representative of eleven high-income countries (the United States, Japan, Russia, Saudi Arabia, and seven European countries), I examine public support for international redistribution and climate policies, as well as its sensitivity to key policy features such as the size of transfers and country coverage. Although global inequality is not a salient concern, it is perceived as a significant injustice. There is majority acceptance in every country for nearly all global policies tested, including those that would redistribute 5 percent of global income or entail personal costs for respondents. An information treatment shows that support for global policies causally increases among respondents who perceive them as likely; an effect opposite to warm glow. Support for international policies decreases only slightly as country coverage shrinks. Overall, the results reinforce previous findings and suggest that a broad coalition of countries could feasibly advance sustainable development.

WIL working papers are circulated for discussion and comment purposes. Short sections of text may be quoted without explicit permission provided that full credit is given to the author(s). CC BY-NC-SA 4.0

How to cite this working paper: Fabre, A., Public Acceptance of International Redistribution in High-Income Countries, World Inequality Lab Working Paper 2025/26

<footnote>*CNRS; CIRED. E-mail: adrien.fabre@cnrs.fr.</footnote>
# Contents

<table><tr><td>Contents</td><td>2</td></tr></table>

<table><tr><td>1 Introduction</td><td>3</td></tr></table>

<table><tr><td>2 Data and Design</td><td>10</td></tr></table>

<table><tr><td>3 Salience and Prioritization of Global Solidarity</td><td>14</td></tr></table>

<table><tr><td>3.1 Top-of-mind Considerations</td><td>14</td></tr></table>

<table><tr><td>3.2 Prioritization of Public Spending Items</td><td>18</td></tr></table>

<table><tr><td>4 Acceptance of Policies as a Function of Country Coverage</td><td>20</td></tr></table>

<table><tr><td>4.1 International Climate Scheme</td><td>20</td></tr></table>

<table><tr><td>4.2 Wealth Tax Funding LICs</td><td>24</td></tr></table>

<table><tr><td>5 Sincerity of Support for Global Redistribution</td><td>25</td></tr></table>

<table><tr><td>5.1 Conjoint Analysis</td><td>25</td></tr></table>

<table><tr><td>5.2 Testing Warm Glow</td><td>28</td></tr></table>

<table><tr><td>6 Breadth of Accepted International Policies</td><td>30</td></tr></table>

<table><tr><td>6.1 Acceptance of Currently Debated Global Policies</td><td>31</td></tr></table>

<table><tr><td>6.2 Support for Radical Proposals, Political Action, and Broad Values</td><td>33</td></tr></table>

<table><tr><td>6.3 Preferred Channels for Transferring Resources to LICs</td><td>37</td></tr></table>

<table><tr><td>6.4 Custom Global Income Redistribution</td><td>37</td></tr></table>

<table><tr><td>7 Conclusion</td><td>41</td></tr></table>

<table><tr><td>Bibliography</td><td>43</td></tr></table>

<table><tr><td>A Raw Results</td><td>50</td></tr></table>

<table><tr><td>A.1 Figures</td><td>50</td></tr></table>

<table><tr><td>A.2 Countries' slant in the open-ended fields</td><td>98</td></tr></table>

<table><tr><td>B Questionnaire</td><td>99</td></tr></table>

<table><tr><td>C Survey Sources and Features</td><td>121</td></tr></table>

<table><tr><td>C.1 Sources Regarding Plausible Global Policies</td><td>121</td></tr></table>

<table><tr><td>C.2 Country-specific Features and Policies' Costs</td><td>123</td></tr></table>

<table><tr><td>C.3 Definition of Keywords</td><td>127</td></tr></table>

<table><tr><td>C.4 Exploratory Factor Analysis</td><td>130</td></tr></table>

<table><tr><td>D Representativeness of the Surveys</td><td>132</td></tr></table>
<table><tr><td>E</td><td>Determinants of Support</td><td>136</td></tr><tr><td>F</td><td>The Determination of a Custom Redistribution</td><td>139</td></tr><tr><td>G</td><td>Attrition Analysis</td><td>143</td></tr><tr><td>H</td><td>Balance Analysis</td><td>145</td></tr><tr><td>I</td><td>Placebo Tests</td><td>146</td></tr><tr><td>J</td><td>Main Results on Selected Demographics, Including Vote</td><td>147</td></tr><tr><td>K</td><td>Main Results Weighted by Vote</td><td>149</td></tr><tr><td>L</td><td>Main Results on the Extended Sample</td><td>152</td></tr><tr><td>M</td><td>Influence of the Item Order on Answers</td><td>155</td></tr><tr><td>N</td><td>Supplementary Tables</td><td>156</td></tr><tr><td colspan="2">Bibliography</td><td>159</td></tr><tr><td colspan="2">List of Tables</td><td>161</td></tr><tr><td colspan="2">List of Figures</td><td>161</td></tr></table>

# 1 Introduction

The issue of North-to-South transfers of resources and power permeates negotiations in many areas, including debt restructuring, development assistance, tax cooperation, UN reform, and climate finance.<fnref n="1" /> In all international fora, Global South countries seek a more equal world order. Indeed, redirecting just 1% of high-income countries' output to low-income countries (LICs) would mechanically double their national income<fnref n="2" />, more

<footnote n="1">¹The (re)distribution of resources between countries is debated in different official fora, such as the G20, the OECD's Base Erosion and Profit Shifting project, the Conference on Financing for Development, the International Maritime Organization, the Global Solidarity Levies Taskforce, the UN Framework Convention on International Tax Cooperation, and the UN Framework Convention on Climate Change. Appendix C.1 provides references on official initiatives for global redistribution.</footnote>

<footnote n="2">²The GDP per capita of high-income countries (HICs) is 28 times greater than that of low-income countries (LICs) at Purchasing Power Parity (PPP) and 68 times greater in nominal terms, from World Bank 2024 data. Given that 625 million people live in one of the 25 low-income countries and 1.42 billion people in high-income countries, 1% of HICs' GDP corresponds to 60% of LICs' GDP using PPP values and 153% using nominal data.</footnote>
than enough to finance the eradication of extreme poverty (Sahoo et al. 2025).

Public attitudes in high-income countries (HICs) are key to understanding whether globally redistributive policies would be politically feasible. Recent large-scale surveys reveal worldwide support for a globally coordinated tax on billionaires (Cappelen et al. 2025b), a democratic world government for global issues (Ghassim & Pauli 2024), climate action at the global (rather than national) level (Dechezleprêtre et al. 2025), as well as globally redistributive climate or tax policies (Fabre et al. 2025).

Despite strong stated support even in HICs, international redistribution is rarely discussed in public debates, let alone advocated by policymakers. Fabre et al. (2025) conduct survey experiments in the U.S. and four Western European countries to understand this mismatch, focusing on a “Global Climate Scheme” (GCS) costly to these countries. The authors reject hypotheses that support for the GCS might be overstated: they find no social desirability bias in a list experiment, 6 out of 10 respondents prefer a political program that includes the GCS over one that does not, and most respondents are willing to sign a petition in favor of the GCS. While the authors find support reduced by 11 percentage points (p.p.) following a (fictitious) negative media campaign —an effect size similar to the actual decrease in support for the “Green New Deal” after it was publicly debated (Gustafson et al. 2019)— a campaign effect of this magnitude would not generate majority opposition to policies favored by three-quarters of the population, such as a globally redistributive wealth tax. Therefore, Fabre et al. (2025) conclude that support for global redistribution is genuine, and another hypothesis is needed to explain the lack of prominence of this issue. A promising candidate is “pluralistic ignorance”: the underestimation of public support. Indeed, pluralistic ignorance has been documented regarding climate action (Andre et al. 2024a,b; Mildenberger & Tingley 2019), the billionaire tax (Cappelen et al. 2025b), and the GCS (Fabre et al. 2025). Nevertheless, pluralistic ignorance has not prevented climate policies or a national wealth tax from entering public debates, suggesting that other mechanisms may be at play concerning global redistribution.

In this paper, I conduct a pre-registered large-scale survey to examine whether global redistribution policies are robustly accepted and to investigate the reasons for their lack of prominence. I test several hypotheses. Surveying eleven HICs, I test whether international policies are accepted by majorities in countries considered conservative and not yet surveyed on this topic, such as Japan, Poland, Russia, Saudi Arabia, and Switzerland. Recognizing that some key countries would likely not participate if these policies were implemented, I test how acceptance is affected when a climate scheme or a wealth tax is
international but not truly global. I explore three potential mechanisms that could explain the preference-prominence gap. First, I test for pluralistic ignorance. Second, I analyze the salience of global redistribution, and whether it is a vote-determining issue. Third, I test for "warm glow", whereby people delude themselves into supporting hypothetical policies in order to ease their conscience, notably by testing whether the support is only claimed for as long as the policies are deemed unlikely. Finally, I explore a variety of international policies, ranging from the plausible to the radical.

Throughout the paper, I make a distinction between *support* and *acceptance*. I use the term *support* to refer to the absolute share of *Somewhat* or *Strong support* on Likert scales, and *acceptance* to refer to relative support —specifically, the support share among non-*Indifferent* responses. Although binary (*Yes*/*No*) questions are typically worded in terms of "support", I generally report their results using the term *acceptance*. This approach avoids mistaking passive consent for active support among respondents who could not choose a neutral option.

The results confirm earlier studies: I find majority acceptance in every country surveyed for almost all globally redistributive policies tested. Policies currently discussed in international negotiations are accepted by large majorities. The most supported policy is the 2% tax on billionaire wealth proposed by Zucman (2024), with 81% acceptance in the pooled sample. Proposals such as debt relief for vulnerable countries, developed countries contributing 0.7% of their GDP in foreign aid, an expansion of the UN Security Council, or the Bridgetown initiative (expanding sustainable investments at low interests rates in LICs) all garner at least 70% acceptance overall.

Radical proposals are also widely accepted. Majorities in every country agree that "governments should actively cooperate to have all countries converge in terms of GDP per capita by the end of the century", and that globally coordinated climate policies are preferable to the status quo, even if they entail completely electrifying cars by 2045 and doubling the prices of heating fuel, flights, and beef. Overall, I find 64% acceptance for a progressive income tax that would finance poverty reduction in the Global South, which would collect 5% of world income from the global top 3%, with marginal tax rates ranging from 15% above $80,000 per year to 45% above $1 million. Relatedly, in an interactive task where respondents design their preferred global income redistribution, nearly half choose a redistribution that would make them poorer (versus less than 10% choosing one that would make them richer). The average custom redistribution entails over 5% of world income in transfers from the rich to the poor.
Before respondents could infer the survey's topic, they had to complete an open-ended field, a conjoint experiment, and a budget allocation task. When asked to allocate the revenue from a global wealth tax among five spending items, 87% of respondents allocate a positive amount to the global item (public services in LICs). This item receives an average preferred share of 17.5% of the revenue, slightly below an equal split of 20%. This indicates that most people prioritize sustainable development abroad less than the average issue, but still consider it worthwhile.

While policies to address global inequality are widely accepted, they have low salience. Indeed, this topic is rarely mentioned in open-ended fields at the beginning of the survey, where respondents were asked to write about various considerations. Respondents' top concern is the cost of living, and their most frequent wish is for greater purchasing power. While inequality is most often regarded as the greatest injustice—with some inconclusive indications that these responses relate to inequality at the global level—global inequality almost never appears among issues respondents consider important but neglected in public debate. The low priority placed on global redistribution may explain why it is seldom discussed in public debates, despite widespread acceptance of related policies.

Despite its low salience, global redistribution may be a vote-determining issue for some people, as the conjoint experiment suggests. In this task, respondents express their preference between two political programs, each composed of policies randomly selected from those prominently debated in their country. When a program includes a *global tax on millionaires with 30% of the revenue funding LICs*, the likelihood of that program being preferred increases by 5 p.p., while *cutting development aid* reduces it by 3 p.p. A direct question confirms that some voters might change their vote intention if a candidate campaigned on sustainable development: 36% of respondents report they would be more likely (versus 17% less likely) to vote for a party if it participated in a global movement for climate action, taxes on millionaires, and poverty reduction in LICs. In a related question, 68% of respondents (and 52% of the 561 millionaires<fnref n="3" /> who responded) state they could actively participate in such a movement (either by signing a petition, attending a demonstration, going on strike, or donating to a strike fund).

What if a sustainable development policy is international but not global? Acceptance decreases only slightly. In the case of a wealth tax with 30% of revenue financing LICs, acceptance is reduced from 74% to 68% when the policy is implemented only by some

<footnote n="3">³Millionaire is understood as having a net wealth of at least one million dollar or the equivalent in other currencies, cf. Question 15.</footnote>
countries (e.g. the EU, the UK, and Brazil) rather than all countries. Likewise, acceptance
of an International Climate Scheme (ICS), defined as a cap-and-trade with equal per capita
allocation of emissions rights, decreases from 68% to 65% when participating countries
shrink from a group covering 72% of world emissions to one covering 33% of emissions.

I identify pluralistic ignorance through an incentivized question that asks respondents for their belief regarding support for the Global (version of the) Climate Scheme, either among their compatriots or in the U.S. In Japan and in European countries, there is majority support for the GCS, yet most people believe there is not. Overall, the median respondent underestimates support in their own country by 16 p.p. and non-American respondents underestimate support in the U.S. by 22 p.p. Pluralistic ignorance may be an important reason why global solidarity solutions are neglected.

To test whether support might drop if the prospect of global policies materializes (a
form of *warm glow*), I manipulate the belief that large international transfers are likely in
the next fifteen years. More specifically, I inform a random half of the respondents that
“countries have agreed to demonstrate some degree of solidarity in addressing global
challenges”, providing diverse examples including the adoption of a shipping levy at the
International Maritime Organization that should partly finance LICs, developed coun-
tries’ commitments to finance climate action in developing countries, and the study by
the G20 of a coordinated tax on billionaires. The information treatment increases the be-
lief that transfers are likely by 7 p.p. from a baseline of 33%, and it also *increases* the share
of global policies supported by 1 p.p. An IV estimation shows that the share of policies
supported causally increases by 18 p.p. when people believe that international transfers
are likely, consistent with the non-causal effect estimated by OLS. In other words, I find
no evidence of *warm glow*. On the contrary, the effect goes in the opposite direction com-
pared to the *warm glow* hypothesis: if people believed that a global policy were likely,
they would be more likely to support it (which can be interpreted as a *status quo* bias).

Finally, I test respondents' broad values to verify their consistency with global redis-
tribution. The majority of respondents agree that "helping countries in need is the right
thing to do". However, only a minority is convinced that it is in HICs' long-term interest
to do so, or that it is their historical responsibility. Similarly, there is no majority support
for reparations for colonization and slavery in the pooled sample. These results suggest
that support for global solidarity is driven by a sense of empathy and duty rather than
guilt or interest.

Universalism has been identified as one of the best predictors of voting behavior (Enke
2020) and ideology (Cappelen et al. 2025a; Enke et al. 2023), particularly in Western countries (Cappelen et al. 2025a). I use a new question to measure universalism, asking respondents which group they advocate for when they vote. 45% choose a universalist response (either “Humans” or “Sentient beings (humans and animals)”), while 32% opt for their fellow citizens. Using a variance decomposition, I find that universalism is a stronger predictor of policy attitudes than sociodemographic variables such as income, country, or even vote choice, echoing the results of Enke et al. (2023). Besides, there is a majority of universalists in Europe, Saudi Arabia, and among left-wing voters.

This observation aligns with the cross-national differences observed in synthetic indicators: Saudi Arabia, Italy, and Spain exhibit the highest levels of support for global redistribution, while Japan, Switzerland, the U.S., and Poland show the lowest.

By studying in depth the support for global policies, this paper departs from the usual methodological approach of attitudinal surveys. In general, academic surveys focus on estimating effect sizes of some treatment on political attitudes, or identifying the socio-demographic factors and the beliefs that correlate with attitudes (e.g. Alesina et al. 2018; Douenne & Fabre 2022; Kuziemko et al. 2015). The magnitude of support for a given proposal is often deemed unsuitable for satisfactory estimation, because such attitudes are viewed as weakly held, inconsistent, or unstable. The measure of support is usually left to non-academic pollsters, who rarely apply all academic best practices: transparency, representative sampling, neutral and precise question wording, comparison with existing literature, and the use of multiple questions and complementary methods to correctly interpret the results. However, although estimating the extent of support is challenging, this question seems too important not to be addressed using scientific methods. Furthermore, Ansolabehere et al. (2008) refute common perceptions regarding policy attitudes, showing that they are as stable and nearly as predictive of vote choice as party identification. In this paper, I examine support for various policies, approach the question from diverse angles, and run a battery of pre-registered tests to check the reliability of stated support estimates.

**Related literature.** Previous cross-country surveys consistently find strong public support for globally redistributive policies (Cappelen et al. 2025b; Fabre et al. 2025) or global democratic governance (Ghassim & Pauli 2024).

The first questions on respondents' considerations contribute to an extensive literature in political science on “issue salience” —the priority attributed to a given issue. Is-
sue salience is now widely acknowledged as a key factor in determining voting behavior (Dennison 2019; Edwards et al. 1995; Egan 2013; Krosnick 1988; RePass 1971). Furthermore, according to open-ended responses, the “most important issues” relate to the economy and healthcare (Wlezien 2005). Although climate change and hunger appear in the top five problems when the question is framed at the global rather than national level (Yeager et al. 2011), public acceptance of sustainable development policies may be overshadowed by more pressing concerns in voters’ choices.

Although this paper focuses on multilateral policies, it relates to the literature on attitudes toward foreign aid. Kaufmann et al. (2019) and Fabre et al. (2025) find that, despite substantial overestimation of aid amounts, desired aid exceeds perceived aid in most countries. Hudson & van Heerde (2012) provide a critical review of the literature and show that the strong support for poverty alleviation largely stems from intrinsic altruism, in line with Eurobarometer data (Cho 2024).

Nair (2018) finds that US-Americans underestimate their rank in the global income distribution by 27 percentiles on average and overestimate the global median income by a factor of 10, which lowers their support for foreign aid. Similarly, Fehr et al. (2022) find that 9 out of 10 Germans express support for global redistribution, even though respondents underestimate their position in the global income distribution by an average of 15 percentiles.

Finally, the paper contributes to the literature analyzing dispositions towards free-riding on climate action and the ways in which support for climate agreements depends on their country coverage. Using conjoint analyses in Western countries, Bechtel & Scheve (2013) and Beiser-McGrath & Bernauer (2019b) demonstrate that climate agreements with broader country coverage are more likely to be preferred. In Germany and the U.S., Gampfer et al. (2014) also find stronger support for funding climate action in low-income countries when the cost is shared with other countries. Nevertheless, surveys consistently show that people support their country taking unilateral climate action, even in the absence of such action in other countries (Beiser-McGrath & Bernauer 2019a; Bernauer & Gampfer 2015; McGrath & Bernauer 2017). Aklin & Mildenberger (2020) show that the empirical evidence for free-riding is not compelling, and that climate inaction can be equally well explained by distributive conflicts. Still, survey evidence indicates some degree of conditional cooperation: support for domestic climate action increases if other countries join forces (Carlsson et al. 2025; Tam et al. 2025).
## 2 Data and Design

**Samples.** I conducted an original survey of 12,001 respondents representative of the adult population in eleven high-income countries (see Figure 1). The countries were chosen to span the diversity of high-income countries and the sample sizes to be commensurate with each country's population size.<fnref n="4" /> The survey was fielded online in 2025 using the companies Yandex (for Russia), Kantar (for Saudi Arabia), and Bilendi (for the other countries).<fnref n="5" />

In Russia, I could not administer the same questionnaire as in the other countries.<fnref n="6" /> I had to curtail it for two reasons. First, I could not use the platform Qualtrics, which prevented me from using certain question formats (such as constant sum scales) or embedding Javascript (used to design the interactive question). Second, I had to cut or reword some questions due to preventive censorship by the survey company. In the other countries, the questionnaires are almost identical, though the figures in the questions are adapted to the country-specific context (e.g. respondents are informed about the cost of the Global Climate Scheme to the average person in their country).<fnref n="7" />

<figure><img src="image_3.png" /><figcaption>Figure 1: Country coverage of the survey.</figcaption></figure>

<footnote n="4">⁴The sample sizes are as follows: U.S.: 3,000; Japan: 2,000; Russia: 1,001; Saudi Arabia: 1,000; Europe: 5,000, split in proportion to the countries' adult population sizes (except for Switzerland), i.e. France: 798; Germany: 1,048; Italy: 756; Spain: 603; Poland: 500; Switzerland: 469. The maximum margins of error (at the 5% threshold) for country samples range from ±1.8 p.p. in the U.S. to ±4.5 p.p. in Switzerland, with an intermediate value of ±3.1 p.p. in Saudi Arabia.</footnote>

<footnote n="5">⁵For all countries except Russia, responses were collected between April 15 and July 3, 2025. For Russia, responses were collected between September 19 and October 9, 2025. Each complete response was rewarded with approximately €3 in gift points.</footnote>

<footnote n="6">⁶To the best of my knowledge, Toews & Suvorov (2025) were the first to manage surveying the Russian public on climate attitudes.</footnote>

<footnote n="7">⁷Appendix C.2 lists the unique features of the questionnaire in each country.</footnote>
**Representativeness.** The samples are stratified to be representative of the country's adult population based on the following quota variables (with some exceptions<fnref n="8" />): gender, age (5 brackets), income (4), diploma (3), region (2 to 5), and urbanicity (2 to 3). The samples closely match the actual population frequencies along these dimensions, except for Russia and Saudi Arabia, where individuals without a high school diploma are somewhat underrepresented, as well as low-income individuals in Russia and non-Saudis in Saudi Arabia (see Tables S4-S7 in Appendix D). All results are reweighted to be fully representative of the population along the quotas, with weights trimmed between 0.25 and 4. Results aggregated at the global or European levels weigh each country in proportion to its adult population size. Descriptive results on a random branch use weights that are recomputed within that subsample.

Sociodemographic variables explain 10% to 15% of the variance in the main attitudinal outcomes, and this figure drops to 5% after accounting for country and vote (Figure S68). In other words, although variables such as age and diploma are significantly correlated with attitudes (see Tables S8-S9), differences in average acceptance of a policy between (say) age groups rarely exceed a dozen percentage points. In contrast, our measure of universalism is a stronger predictor than any sociodemographic variable.

While support for the main attitudinal outcomes is highest among left-wing voters and lowest among far-right voters, non-voters exhibit attitudes close to the center of the political spectrum (Appendix J). Besides, attitudes are much less polarized in Japan compared to Europe and the U.S. Figures S66-S67 show how the weighted samples compare to actual voting results in the most recent election. Although the proportion of self-reported non-voters is lower than in reality, voting patterns across the three main political leanings are similar to the actual distribution. Additionally, the main results are robust to reweighting by vote (Appendix K).

**Data Quality.** The median survey duration is 17 minutes (13 min in Russia). Best practices have been implemented to ensure top-notch data quality (Stantcheva 2023). The questionnaire was carefully worded in a neutral and informative way;<fnref n="9" /> tested on random people in public spaces to ensure correct comprehension; translated by professional

<footnote n="8">⁸In the U.S., I also use race (4 categories) as a quota variable. In Saudi Arabia, I do not use urbanicity, but I use citizenship (Saudi vs. non-Saudi). In Russia, I do not use region nor urbanicity.</footnote>

<footnote n="9">⁹At the end of the survey, 70% of the respondents find the survey politically unbiased (Figure S62). The most common comment left by respondents in the feedback field is that the survey was “interesting”; very few criticize it (Figure S63).</footnote>
translators, with figures converted into national currencies; and double-checked by native speakers.

Of all respondents who started the questionnaire, 23% respondents were allowed to continue (as their quotas were not full). Among them, 17% dropped out (including 10% who dropped out after the socio-demographic questions). The final sample is obtained after excluding 16% of respondents from the extended sample for suspicion of low quality: 9% for failing an attention test and 13% for completing the questionnaire in less than 6 minutes<fnref n="10" /> (including 5% for both reasons). I check for differential attrition and finds no correlation of treatment arms with attrition (Appendix G). I also show that the main results replicate in the extended sample (Appendix L).

The order of question items is randomized whenever possible. Item order generally has a significant but small effect on answers (2 to 14 p.p.), as shown in Appendix M. The size of this effect helps identify questions for which opinions are strongly held (e.g. a preference for a sustainable scenario over the status quo) versus weakly held (e.g. the preferred amount of climate finance).

**Incentives.** The questionnaire includes three incentivized questions, each awarding a $100 prize to one randomly selected winner. First, a comprehension question about the Global Climate Scheme (GCS) checks whether respondents understand the policy's cost. Second, a donation lottery allows respondents to choose what portion of the prize they would donate to a reforestation NGO, should they win. Third, a question assesses respondents' perception of the actual support for the GCS, rewarding a correct guess.

**Survey Structure.** While Appendix B provides the full questionnaire, Figure 2 depicts the survey flow with all random branches. The various treatments are independent and uniformly distributed. Whenever there is a treatment, the acceptance rates reported are computed using the control group. Appendix I runs placebo tests to check if earlier treatments affect unrelated outcomes.

After collecting sociodemographic characteristics, the questionnaire begins with broad questions to assess the prioritization and salience of global solidarity before respondents become aware of the survey topic. First, respondents answer open-ended fields on either their main concerns, wants, issues of interest, or perceived injustices. Second, they complete a conjoint experiment where they have to select their preferred political program,

<footnote n="10">¹⁰6 minutes corresponds to 30% of the expected median duration of 20 min. In Russia, the cutoff is 200 seconds, or 30% of the expected median duration of 11 minutes.</footnote>
<figure><img src="image_4.png" /><figcaption>Figure 2: Survey flow.</figcaption></figure>

or abstain. Both programs are randomly generated: each policy (or lack thereof) in five policy domains is selected at random from a pool of policies that are prominent in the country's public debate. Third, respondents allocate the revenue of a global wealth tax among five (national or global) spending items.

Then follow attitudinal questions about the main policies studied: a *Climate Scheme* at the national, global, or international level; an international wealth tax funding low-income countries; and ten plausible global solidarity policies. These questions include treatments that vary the international coverage of policies or test for warm glow.

The final part of the questionnaire explores attitudes towards more radical global redistribution scenarios and includes more sophisticated questions, such as an interactive task in which respondents can choose their preferred custom redistribution of global incomes by manipulating sliders.

The survey concludes with a comprehension question, synthetic questions (e.g. regarding one's moral circle), and a feedback field.
**Pre-registered Hypotheses and Data Availability.** The project has been approved by the CIRED institutional review board (IRB-CIRED-2025-2) and preregistered in the Open Science Foundation registry (osf.io/7mzn4). The study did not deviate from the registration; the questionnaires and hypotheses tests used are the ones specified *ex ante*. All data, code, and figures from the paper are available at github.com/bixiou/robustness_global_redistr.

# 3 Salience and Prioritization of Global Solidarity

In this section, I analyze the salience of global solidarity in undirected open-ended fields, and the prioritization of global programs in a budget allocation task.

## 3.1 Top-of-mind Considerations

At the beginning of the survey, respondents are randomly assigned one of four open-ended questions: their main concerns, their needs or wishes, an issue important to them but neglected in public debate, or the greatest injustice of all. The questions are deliberately broad and vague to let respondents express their top-of-mind considerations without any priming.

To analyze the answers, I automatically translated each field into English.<fnref n="11" /> Then, I used AI and my own reading of a few hundred answers to identify the most common concepts, from which I selected 27 categories. Next, I classified each answer into one or more of these categories, both manually (Figures S4-S7) and automatically using AI (Figure S3). Finally, I manually defined a list of 47 (disjunctions of) keywords and used it to automatically classify all responses.<fnref n="12" /> Figure S2 reports the 24 most common keyword matches.

The three different classification methods yield consistent results but differ in accuracy. While the keyword classification allows for an exact and reproducible search, the AI search is not limited to specific words and captures more matching responses. Overall, manual classification seems to provide the most accurate results, with a number of matches generally falling between those of the other two methods. For example, to the *injustice* question, 1.2% of answers match the keywords for *global inequality* and ChatGPT

<footnote n="11">¹¹I used onlinedoctranslator.com, which is powered by Google Translate.</footnote>

<footnote n="12">¹²The list of keywords is provided in Appendix C.3.</footnote>
identifies this category in 7.5% of answers, versus 3.2% according to my manual coding.<fnref n="13" />
Indeed, the AI incorrectly classifies unspecific answers like “poverty” in this category,<fnref n="14" />
while the keyword search misses answers like “inequality among humans”. Given this
observation, I use the manual classification as the benchmark and the two other methods
as robustness checks.

While less accurate than the classifications, word clouds (Figure 3) provide a simple visualization of the most common concepts in each question. By far, the most frequent *concerns* or *wishes* of respondents relate to their purchasing power, with concepts such as “money”, “inflation”, the “cost of living”, or “financial stability” appearing in 31% of these fields. Within countries, the share of people concerned with money decreases with income: it ranges from 22% in the top income decile to 35% in the bottom one.<fnref n="15" /> The next most frequent *concerns* are health (or the healthcare system, 13%), far-right governments (or related concepts such as “Trump” or “trade tariffs, 10%) and war (either in general or specific conflicts, such as the Gaza War, 9%). Most *wishes* are personal, with the next most frequent (after money) relating to one’s own or one’s relatives’ health (21%) or peace of mind (10%). Interestingly, almost none of the responses mention relational considerations, such as love, friendships, loneliness, intimate life, or the desire to have children (except in Saudi Arabia, where the latter was mentioned). Though the predominance of materialistic considerations is consistent with previous studies (Singer 2011; Wlezien 2005), further research is needed to determine whether this arises from the context (an impersonal survey) or truly reflects people’s primary thoughts.

Asked about the greatest injustice, the most frequent answers relate to “inequality” or “poverty”, with 19% of occurrences (28% in Europe but only 9% in the U.S.). It is unclear whether these respondents are thinking about inequality in their own country or at the global level, since only 11% of them specify a geographical scope. One clue is that 2% mention their own country versus 10% the global level (or Global South issues such as “clean water” or “starvation”). Italians, Poles, and Spaniards are the most likely to mention “global inequality” or “global poverty”, while Japanese and Russian respondents

<footnote n="13">¹³The keyword matching searches the regular expression global poverty|global inequal |hunger|drinking water|starv, ignoring case. The automatic and manual classifications are based on the category definition “Inequality at the international level / Hunger or poverty in poor countries”.</footnote>

<footnote n="14">¹⁴Interestingly, out of the 47 (one-word) answers “poverty”, (the zero-shot prompt passed to) ChatGPT-4.1 coded only 42 of them as *global inequality*, illustrating the lack of consistency of this classifier.</footnote>

<footnote n="15">¹⁵At the country level, the concern for money is significantly correlated with inequality (an additional point in the Gini index is associated with 0.8 p.p. more respondents concerned with money). Interestingly, the concern for money is higher in richer countries, though the correlation vanishes once one controls for the Gini.</footnote>
<figure><img src="image_5.png" /><figcaption>Figure 3: Most common concepts in open-ended fields. (Questions 19-22)</figcaption></figure>

(c) "What according to you is the greatest injustice of all?"

(d) "Can you name an issue that is important to you but is neglected in the public debate?"

<figure><img src="image_6.png" /></figure>

are the least likely to do so. The next most common answers relate to "discrimination" (based on gender, race, or sexual orientation, 9%), "violence" or "wrongful convictions" (many respondents denounce the unjust sentencing of innocents, 9%), or their country's "welfare state" (with people criticizing either the lack of public services or the excessive welfare given to undeserving people, 8%).
Asking people about "an issue important to them but neglected in the public debate" fails to uncover unusual topics. 21% of respondents are unable to identify such an issue. The most frequently mentioned concepts are "public services" (12%), the "cost of living" (10%), "health" (9%), "ageing" (6%), and the "environment" (6%).<fnref n="16" /> The fact that the most frequently mentioned topics are already well-publicized suggests that public debate reflects or shapes what people have in mind.

Reading and coding each field not only results in an arguably more accurate classification, but also offers insight into how people think. For example, most people reason from their own perspective (e.g. "my pension is too low", "I want to buy a house") and do not refer to the broader picture or to political reforms. To get a sense of respondents' own words, random selections of responses are displayed at bit.ly/fields2025. In addition to the manual classification presented in this section, I compiled a list of topics that are uniquely prevalent in each country, which I report in Appendix A.2.

The topics mentioned vary according to sociodemographic characteristics. For example, a respondent who mentions *immigration* is 3.5 times more likely to vote for the far right (correlation of .17); one who mentions *old age* is twice as likely to be 65 or older (correlation of .13). Beyond these examples, the strongest effects I find are that *criticizing the far right* correlates with voting for the left (.16), mentioning *health* with age (.11), *employment* with being unemployed (.09), *animals* with extendeding one's moral circle to sentient beings (.09), *education* with being a student (.09), *the environment* with voting for the left (.08), and *money* with one's income (—.08).

Our topic of interest, *global inequality*, does not emerge as an issue salient to most people. Indeed, most considerations relate to issues that directly affect oneself or one's family, and political considerations (regarding e.g. public services, pensions, or taxes) are often framed at the national level. *Global redistribution* almost never appears as a *wish*. Furthermore, *global inequality* is rarely mentioned as a neglected *issue* or as a *concern*, in contrast to international issues such as war, climate change, or the rise of the far right. However, it is mentioned as frequently as these other international issues in terms of *injustice*.

In summary, the low salience of global solidarity may explain why this topic fails to mobilize political forces, despite being referred to as a just cause and it being accepted by majorities (as shown below).

<footnote n="16">¹⁶Although “immigration” is one of the most frequent words according to the word cloud, the issue is only mentioned in 5% of cases.</footnote>
## 3.2 Prioritization of Public Spending Items

Fabre et al. (2025) find that 58% of US-Americans and 71% of Western Europeans would support a global tax on millionaires funding low-income countries (LICs), with only 26% and 14% opposing it, respectively. Meanwhile, around half of them would prefer to allocate half (rather than none) of the revenue from a global wealth tax to LICs. It seems that the more leeway respondents are granted to allocate the revenue from such a tax, the less they would allocate to LICs. The greatest leeway tested by Fabre et al. (2025) let the respondents select their preferred share for LICs versus domestic healthcare and education, and the average preference was 33.4% —that is, 66.8% of an equal split. Naturally, one expects respondents to split the revenue among all desirable spending items, so if LICs compete with not one but several national items, the share allocated to LICs is expected to diminish. If this share is less than 67% of an equal split, it would mean that (Fabre et al. 2025) overestimated the prioritization of LICs, perhaps due to an excessive salience of LICs when only one alternative is proposed, or because the domestic alternative —healthcare and education— was not the most desired. Conversely, if several items pertain to a global issue and each global item is considered individually desirable, the total “global spending” should rise proportionately.

To test whether the results in (Fabre et al. 2025) provide an accurate picture of the prioritization of global spending as well as to uncover the prioritization of different global causes, I conduct a revenue allocation task with five spending items. In each of the two variants of this task, respondents use sliders to allocate the revenue of a hypothetical global wealth tax (at a rate of 2% on wealth in excess of $5 million), after being informed of the revenue the tax would collect in their country (from $1 billion in Poland to $514 billion in the U.S.) versus in all LICs combined ($1 billion).

In the *Few* variant, one global item (“Education, Healthcare and Renewable energy in LICs”) competes with four domestic ones. In every country, the most prioritized item is “Domestic: Education and healthcare”, with an average preferred share of 26% (Figures S25, S26). The global item is the least prioritized overall, at 17.5% (from 14% in Japan to 21% in Saudi Arabia and Spain). However, global spending is the second most prioritized item in Europe (19%) and Saudi Arabia. Furthermore, global spending is 31% higher than the expected 13.4% (that is, 66.8% of 20%)<fnref n="17" /> and only 13% of respondents do not allocate

<footnote n="17">¹⁷The one-sided test that global spending is lower than 33.4% is rejected at the 1% threshold in all countries except Japan, where it is rejected at the 10% threshold. If one restricts the comparison to the countries surveyed by (Fabre et al. 2025), the global item is allocated 17.8%, which is 34% more than expected. The most credible explanation for outperforming expectations is that the domestic item chosen by Fabre et al.</footnote>
any revenue to it (Figure 4).

<figure><img src="image_7.png" /><figcaption>Figure 4: Preferred split of revenue from a global wealth tax. The first two items are from the *Few* variant with 5 fixed items (the *Global* one and the most preferred one are displayed); the last four items are from the *Many* variant with 5 items taken at random out of 13 (the 4 *Global* ones are displayed). (Questions 24-25)</figcaption></figure>

In the *Many* variant, five items are selected at random from a pool of four global and nine domestic items. While domestic healthcare (27%) and education (22%) are the most prioritized items, the average allocation for global items ranges from 16% for “Forestation and biodiversity projects” to 19% for “Education and Healthcare in LICs” (Figures 4, S27-S28). On average, tasks include 1.5 global items, which together receive 26.9% of the revenue —again, equivalent to 17.5% per global item. Interestingly, there is no significant correlation between the number of global items and the average allocation per global item.<fnref n="18" />

Overall, the revenue allocation tasks validate and confirm the findings from Fabre

<footnote>(2025) was the preferred one. Indeed, the global item is allocated 68% of the “Domestic: Healthcare and Education” share, almost exactly as expected.</footnote>

<footnote n="18">¹⁸In Russia, the question could not be asked in the same way due to different software. Instead, respondents had to choose what share of the global tax revenue to allocate to sustainable development in low-income countries. On average, Russians allocate 12.2% to LICs, with a median allocation of just 5%, but only 12% allocate nothing to LICs.</footnote>
et al. (2025). Most people would favor using a substantial share of the revenue from a global wealth tax to finance sustainable development in LICs, even though global spending is somewhat less prioritized than domestic spending.

# 4 Acceptance of Policies as a Function of Country Coverage

While acceptance of global climate or redistributive policies is widespread (Cappelen et al. 2025b; Fabre et al. 2025), acceptance may drop if policies are not truly *global* but only *international*, i.e. if key countries such as China, Russia, or the U.S. do not participate. Indeed, people may be concerned about a domestic loss of competitiveness resulting from the expatriation of taxpayers to low-tax jurisdictions; or about unfair burden-sharing if non-cooperating countries free-ride on decarbonization or sustainable development funding. In this section, I examine the acceptance of globally redistributive policies depending on the coalition of countries that would implement them. I study, in turn, a carbon price and a wealth tax.

## 4.1 International Climate Scheme

**Presentation of the Schemes.** “Cap and dividend” is a reference climate policy (Baer et al. 2000; Barnes et al. 2008; Bertram 1992; Blanchard & Tirole 2021; Grubb 1990), whereby fossil fuel companies at the source of emissions must buy emission permits on a carbon market, with the revenue from carbon pricing rebated equally to individuals. The limited and declining number of emission permits guarantees that emissions are capped according to the climate objective. As polluting companies pass the cost of emission permits down the value chain, the carbon price is ultimately paid by consumers, in proportion to their carbon footprint. Meanwhile, the equal cash transfer (or “dividend”) offsets price increases for the average consumer. Those with a higher-than-average carbon footprint financially lose, while those with a lower carbon footprint (who are on average poorer) financially gain.

Using simple *Yes/No* questions, I test the acceptance of three types of “cap and dividend” (or “Climate Scheme”) policies that differ by geographical scope: the National, Global, and International Climate Schemes (Figures 6, S30). While average consumers in a high-income country are financially unaffected by the National Climate Scheme (NCS), they lose out in the Global and International versions, since their carbon footprint is larger
than the world (or climate coalition) average.

The National Climate Scheme (NCS) is accepted by 68% of respondents (ranging from 56% in Poland to 88% in Saudi Arabia).<fnref n="19" />

**The Global Climate Scheme.** Before presenting the Global Climate Scheme (GCS), respondents are instructed to pay careful attention, with the incentive that they may win a $100 lottery prize if they correctly answer a comprehension question at the end of the survey. When presented with the Global Climate Scheme (GCS), respondents are informed that the cash transfer would lift 600 million people out of extreme poverty, and the cost to them is made salient. Respondents are informed of the amount of the cash transfer, as well as the price increases and the net cost to the average person in their country (e.g. 2% price increases and a net cost of $90 per month in the U.S., or 2% and €45 per month in Germany).<fnref n="20" /> The GCS is accepted by 55% of respondents (from 49% in the U.S. and Russia to 85% in Saudi Arabia). The salience of costs in the GCS question may explain the somewhat lower acceptance of the GCS compared to the NCS.<fnref n="21" />

**Pluralistic Ignorance.** After assessing support for the GCS, respondents are asked in an incentivized way about their belief concerning the actual support, either in their country or in the U.S. (Figure S30).<fnref n="22" /> In every country and for any variant of the question, actual support is underestimated. The median respondent underestimates the support in their own country by 16 p.p. and the support in the U.S. by 22 p.p. In Japan and in European countries, the underestimation is more severe, with most people wrongly believing that the GCS does not garner majority support in their country. Such pluralistic ignorance might explain why politicians do not dare to propose global climate justice policies.

<footnote n="19">¹⁹The acceptance of the NCS is higher than the support for a *tax*-and-dividend policy found in other surveys (Douenne & Fabre 2022; Mildenberger et al. 2022), 12 p.p. higher than in Dechezleprêtre et al. (2025). Indeed, most people prefer emissions trading schemes to carbon taxes (Funke et al. 2025), and support drops (before recovering) in specific contexts, such as the Yellow Vests movement.</footnote>

<footnote n="20">²⁰The computations use a carbon price of $95/tCO₂. For Russia, Saudi Arabia, and the U.S., computations assume universal country coverage and the cash transfer is $35 per month. For Europe and Japan, the net loss is computed in a non-universal but *High* participation scenario, which implies a lower cash transfer (€20 per month) and a higher net cost (by about $10 per month) since the coalition's average carbon footprint is lower than the world average. Appendix C.2 reports the country-specific figures.</footnote>

<footnote n="21">²¹Acceptance of the GCS is also around 10 p.p. lower than in Fabre et al. (2025). There may be different reasons for this: attitudes may have changed in the two-year interval; and I added information on the price increases, which allows respondents to estimate the cost to themselves (rather than to their average fellow citizen).</footnote>

<footnote n="22">²²US-Americans are asked about either their country or the EU. In Russia, I was not permitted to enquire about beliefs regarding a foreign country.</footnote>
Interestingly, support is strongly correlated with the perception of support: 51% of respondents who support the GCS perceive it as supported by at least 50% in their own country, compared to only 24% of those who do not support it.<fnref n="23" /> In other words, in addition to pluralistic ignorance, there is a false consensus effect.

**International Climate Scheme.** To test how country coverage influences the acceptance of the International Climate Scheme (ICS), respondents are randomly assigned to one of four variants. They can visualize the country coverage on a map (see examples in Figure 5), where their own country is striped to denote its potential participation. Respondents are also informed of the number of countries that would participate in the assigned scenario, the list of these countries or world regions, and their share of world emissions.

<figure><img src="image_8.png" /><figcaption>Figure 5: Example maps of the International Climate Scheme question. (Question 35).</figcaption></figure>

The *Mid* scenario covers 56% of world emissions and includes China and Global South countries. The *Low* scenario replaces China with the EU and covers 33% of emissions. The *High scenario* adds various high-income countries to the *Mid* scenario, including the EU, the UK, Japan, Canada, and South Korea, and covers 72% of emissions. The last variant, *High color*, combines the *High* participation scenario with a colored map that displays not only the country coverage, but also the net gain or cost for each country, with China appearing as neither gaining nor losing from the policy.<fnref n="24" />

<footnote n="23">²³The median perception of support in one's own country is 20 p.p. higher among those who support the GCS (50% versus 30%). Reciprocally, support for the GCS reaches 72% among the 39% of respondents who believe that a majority in their country supports it, compared to 44% among those who do not.</footnote>

<footnote n="24">²⁴In a standard cap and dividend, China should lose, as its carbon footprint exceeds the world average. However, the Global Climate Scheme departs slightly from the standard policy so that middle-income countries do not lose out (Fabre 2025).</footnote>
<figure><img src="image_9.png" /><figcaption>Figure 6: Percentage of support for the National, Global, and International Climate Schemes (*Yes/No* questions). (Questions 26-35.)</figcaption></figure>

As expected, the wider the coverage, the higher the acceptance. However, this effect is relatively small, as acceptance is only 3.8 p.p. higher in the *High* variant (at 68%) compared to the *Low* variant (65%). Interestingly, acceptance among Europeans significantly increases when China is added to the coalition, but does not rise further when other HICs are also added. Conversely, for US-Americans and Japanese, the participation of the EU or China yields similar levels of acceptance, and only the combined participation of China, the EU, and other HICs significantly increases acceptance.

The effect of country coverage is entirely driven by the 74% of respondents who understand that the GCS would result in increased gasoline prices. It is worth noting that acceptance is higher among the minority of respondents who misunderstand the policy: by 5 p.p. for the GCS and 4 p.p. for the ICS.

Acceptance is 6.6 p.p. lower in the *High color* variant compared to the *High* variant. Three reasons may explain this effect. First, the cost may be more salient with the colored map. Second, some respondents may be concerned by the information (made explicit in the question) that China would neither gain nor lose from the policy. Third, with the colored map, respondents learn how their own country fares compared to others. In fact, the effect is no longer significant (and of opposite sign) for countries that appear to lose less than 0.5% of their GDP (Spain and Switzerland).

Notice that acceptance of the ICS in the *Low* coverage variant is similar to that of the
NCS. This suggests that the average respondent is willing to pay the ICS's higher cost for the guarantee of poverty alleviation and decarbonization in the Global South.

Finally, the greater acceptance of the ICS compared to the GCS is somewhat puzzling. Perhaps people view the proposal as more credible when a list of participating countries is provided, compared to the GCS, which is framed as if all countries might join (or, on the contrary, as one in which the participation of any country is uncertain). Relatedly, acceptance may be stronger for more precise or more visual proposals, either because they are viewed as more advanced or because they induce an experimenter demand bias. The greater acceptance could also be due to costs being less salient in the ICS question (but acceptance is still greater than in the GCS in the *High color* variant, where costs are visible). Unfortunately, the data does not allow testing these different hypotheses.

## 4.2 Wealth Tax Funding LICs

I test the effect of country coverage on the acceptance of an internationally redistributive wealth tax using a simple *Yes/No* question with three random variants. The policy is described as a 2% tax on wealth above $1 million, with 30% of its revenue financing public services in LICs. In the *Global* variant, all countries except the respondent's own are assumed to participate. The *HIC* variant covers all HICs (except the respondent's country). The *International* variant covers some countries and not others, with the precise coverage varying by respondent's country but always including Brazil and European countries (or the whole EU) and excluding China and the U.S.<fnref n="25" />

Here again, acceptance increases with the country coverage, but the effect is small. The middle-ground *HIC* variant garners 70% acceptance (from 58% in Switzerland to 81% in Saudi Arabia). Compared to *HIC*, acceptance is 4.8 p.p. higher with *Global* coverage, while it is only 1.4 p.p. and non-significantly lower with *International* coverage (Figure 7).

Overall, the results indicate that the acceptance of internationally redistributive policies is quite robust to country coverage. This confirms that the issues of competitiveness or free riding are not decisive factors in public support (Aklin & Mildenberger 2020).

<footnote n="25">²⁵More precisely, in the U.S., excluded countries differ and are *China, Japan, and Canada*. As for included countries, in addition to *Brazil*, they are: *the EU and the UK* for Switzerland, Saudi Arabia, and the U.S.; *the EU* for Russia and the UK; and *France, Germany, Spain, and the UK* (except one's own country) for EU countries.</footnote>
<figure><img src="image_10.png" /><figcaption>Figure 7: Percentage of support for an international wealth tax with 30% of revenue funding LICs, depending on the country coverage (Yes/No question). (Questions 41-43).</figcaption></figure>

# 5 Sincerity of Support for Global Redistribution

Skeptics about the public's support for global redistribution would argue that this support is not reflected in real-stake decisions or that it mostly results from *warm glow*. According to the *warm glow* hypothesis, many people would express their support to enjoy moral comfort as long as the policy appears out of reach and supporting it seems harmless. In case of *warm glow*, support would vanish if (i) the prospect of implementation materialized or if (ii) moral comfort could be obtained from a substitute. In this section, I test whether global redistribution is a vote-determining issue using a conjoint analysis, and I test both forms of *warm glow* (i and ii) using two other survey experiments.

## 5.1 Conjoint Analysis

I conduct a conjoint experiment in all countries except Russia and Saudi Arabia. This question is positioned at the beginning of the survey, before respondents know the survey's topic. Respondents are presented with two random political programs, framed as the fictitious programs of the leading candidates in the next election, and are asked which candidate they would vote for (27% of the respondents choose the outside option *Neither of them*). Each program contains a policy or an absence of policy, chosen at random, for each of five policy domains (the order of which is also randomized). Our domain of interest is *Foreign policy*, whose pool contains three policies: *Cut development aid*, *International*
tax on millionaires with 30% financing healthcare and education in low-income countries, and a country-specific policy. The policies, except for these two of interest, have been selected from the programs of the main candidates in the country's most recent election, ensuring coverage of the entire political spectrum and the most prominent proposals in the national public debate.

Figure 8 shows the effect of including our policies of interest in a program on the likelihood that it is preferred (see Figures S10-S23 for full country-by-country results<sup>26</sup>). More specifically, following Hainmueller et al. (2014), Figure 8 and Table S18 present the results of the following regression, estimated by simple OLS with standard errors clustered by respondent:<sup>27</sup>

$$ (1) \qquad \text{Preferred}_{pi} = \beta_0 + \beta_1 \text{Cut\_aid}_{pi} + \beta_2 \text{Intl\_tax}_{pi} + \beta_3 \text{Foreign3}_{pi} + \varepsilon_{pi} $$

where $pi$ denotes the program $p$ faced by respondent $i$, and each variable is a dummy.

Both policies significantly affect program choice: the internationally redistributive millionaire tax increases the likelihood that a program is preferred by 5 p.p., while cutting development aid decreases it by 3 p.p. At the country level, the effects are generally non-significant due to lack of power, but when significant, they are of the same sign as the global effect. On average, the effects of the tax are of similar size to the effects of other policies,<sup>28</sup> suggesting that certain global redistribution proposals may be as vote-determining as policies prominent in the national debate.

One concern with this type of conjoint analysis is that it involves unrealistic political programs, namely programs that contain both left and far-right policies, which distorts the actual choices that voters may face. De la Cuesta et al. (2022) showed that to fully address this issue, one should weigh each pair of programs by the probability that it would arise in a real election. Since this probability cannot be computed, the best practice is to bound the effects by estimating them with extreme probabilities. The results just pre-

<footnote n="26"><sup>26</sup>With a few exceptions, raising the minimum wage is among the most popular policies, alongside re-distributive taxes or transfers, anti-immigration regulations, and abortion rights. Conversely, a ban on new combustion-engine cars is among the least popular ones.</footnote>

<footnote n="27"><sup>27</sup>More specifically, I estimate the average marginal component effect (AMCE), which is the change in the probability that a program is chosen if a policy is present rather than not, averaged across all possible values in the other policy domains. Hainmueller et al. (2014) show that the linear model is an unbiased estimator of the AMCE under uniform and independent randomization of attributes. I verify that the results are similar when using a conditional logit: the average marginal effects of *Int'l tax* and *Cut aid* are 6 p.p. and -3 p.p., respectively.</footnote>

<footnote n="28"><sup>28</sup>A simple permutation test shows that the effects of *int'l tax* is not significantly lower than the average absolute effect size (it is just 4% lower, *p*=.48) but the effects of *cut aid* is significantly lower (*p*.=.01).</footnote>
<figure><img src="image_11.png" /><figcaption>Figure 8: Effect on the likelihood that a political program is preferred of containing the following policies (compared to no foreign policy in the program). No control is included, 95% confidence intervals are shown. (See Figure S9 for effects by vote.) (Question 23)</figcaption></figure>

sented are based on one extreme, the uniform distribution. To construct the other extreme, I classify each policy proposal according to its originating political party<sup>29</sup> and consider a program consistent if it does not contain policies from both the *left* and the *far right*. Then, I re-estimate the regression after dropping the 29% of pairs with an inconsistent program, effectively assigning them a probability of zero. Effects are preserved: +5 p.p. for the tax and -3 p.p. for cutting aid.<sup>30</sup> This indicates that the results are robust to the critique of De la Cuesta et al. (2022).

<footnote n="29"><sup>29</sup>Interestingly, the most popular policies originate from left-wing parties, except in Germany and Switzerland. Indeed, the average deviation from the mean effect is highest for policies originating from the *Left*, and lowest for those from the *Center-right or Right*.</footnote>

<footnote n="30"><sup>30</sup>In the main specification, I consider our policies of interest as consistent with any program. As an alternative, I classify them as either *left* (for the tax) or *far right* (for cutting aid). In that case, only 43% of observations are retained, yet effects are still preserved (+5 p.p. for the tax and -4 p.p. for cutting aid).</footnote>
## 5.2 Testing Warm Glow

Some people might claim to support a policy of global redistribution merely to ease their conscience. If support were mainly due to this psychological mechanism, called *warm glow*, it might dissipate when the prospect of the policy materializes or if the policy support could be replaced by a substitute with the same moral appeal.

**Moral Substitute.** Following Nunes & Schokkaert (2003), warm glow would be revealed if support for the GCS decreased after respondents are offered the opportunity to express generosity towards the cause of climate change. To test this hypothesis, right before the GCS page, I assign a random subset of the respondents to a donation lottery, while the control group faces no question.<fnref n="31" /> In the *Donation* branch, respondents must decide how much they would donate to the reforestation NGO *Just One Tree*, should they win the question's $100 lottery. Lower support for the GCS in the treated group would be evidence of warm glow, or moral licensing, as it would indicate that the support derives (at least partially) from moral satisfaction at having recently supported a just cause.

On the contrary, support for the GCS is 3 p.p. higher in the *Donation* branch compared to the control group, and the coefficient is positive in every country, though often not significant (Figure 9a, Table S19). While the reason for this positive effect remains unclear,<fnref n="32" /> the results show no evidence of warm glow.

**Realism Treatment.** To test the hypothesis that some people express support for global redistribution only as long as its implementation seems unlikely, I randomly assign half of the respondents to receive information about ongoing negotiations on globally redistributive policies. Among other things, treated respondents are informed that the International Maritime Organization recently adopted a levy on maritime carbon emissions that should partly finance LICs; that the G20 considered introducing a global tax on billionaires; that the UN General Assembly recently agreed on the principle of expanding the UN Security Council to new members; and that the UN Secretary-General supports financial system reforms that would drive resources towards sustainable development (see Question 36).

<footnote n="31">³¹More precisely, right before the GCS question, the sample is split into three branches: the *Donation* lottery, the NCS question, and the control group. The NCS treatment is excluded from this analysis as it is unrelated to this experiment (restricting the NCS question to a subsample was done to prevent it from influencing responses to the GCS).</footnote>

<footnote n="32">³²Perhaps the *Donation* question triggers thoughts favorable to the GCS, such as the realization that individual actions like donations are ill-suited to address climate change, so that we need a global policy, even if it is imperfect.</footnote>
<figure><img src="image_12.png" /><figcaption>Figure 9: Testing warm glow (negative effects would indicate the presence of warm glow). Regressions include controls, 95% confidence intervals are shown.</figcaption></figure>

Then, respondents are asked “how likely [it is] that international policies involving significant transfers from HICs to LICs will be introduced in the next 15 years”, right before their support for ten plausible global policies is tested.<fnref n="33" /> Here, warm glow would be revealed if the information treatment increased the belief that global redistribution is likely but decreased support for global policies.

The treatment was designed to satisfy the exclusion restriction required for the instrumental variables (IV) strategy. The exclusion restriction states that the treatment affects support for global policies only through its impact on beliefs that global redistribution is likely. Table 1 reports the corresponding regression results. Although the treatment is randomly assigned, the preferred specification includes the sociodemographic variables as controls to improve accuracy.<fnref n="34" /> Informed respondents are 7 p.p. more likely to believe that global redistribution is likely, from a baseline of 33% in the control group. With an effective F-statistic of 67, this highly significant effect provides a strong first stage for the

<footnote n="33">³³Section 6.1 reports acceptance of these policies and Appendix C.1 describes the corresponding international negotiations.</footnote>

<footnote n="34">³⁴See Table S21 for results without controls. In fact, some effects are no longer significant in the specification without controls, with *p*-values for the IV and the direct effect at .11 and .12, respectively (Table S21).</footnote>
IV estimation. Assuming that the exclusion restriction holds, the IV is well identified. The local average treatment effect estimated by 2SLS is 18 p.p., indicating that believing global redistribution is likely causally *increases* the share of global policies supported. This estimate is consistent with both the non-causal OLS coefficient of 15 p.p. and the direct effect of the treatment on policy support, estimated at 1 p.p. (see Figure 9b and Table S20).

<table><caption>Table 1: Effect on support for global redistribution of believing that it is likely.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Believes global<br>redistribution likely</th><th colspan="3">Share of plausible global policies supported</th></tr><tr><th>IV 1st Stage<br>(1)</th><th>IV 1st Stage<br>(2)</th><th>IV 2nd Stage<br>(3)</th><th>OLS<br>(4)</th><th>Direct Effect<br>(5)</th></tr></thead><tbody><tr><td>Information treatment</td><td>0.077***<br>(0.010)</td><td>0.074***<br>(0.009)</td><td></td><td></td><td>0.013**<br>(0.007)</td></tr><tr><td>Believes global redistribution likely</td><td></td><td></td><td>0.181**<br>(0.086)</td><td>0.145***<br>(0.007)</td><td></td></tr><tr><td>(Intercept)</td><td>0.332***<br>(0.007)</td><td>0.078<br>(0.067)</td><td>0.216***<br>(0.065)</td><td>0.220***<br>(0.064)</td><td>0.230***<br>(0.066)</td></tr><tr><td>Controls: sociodemos and vote</td><td></td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Effective F-statistic</td><td>65.04</td><td>67.09</td><td></td><td></td><td></td></tr><tr><td>Observations</td><td>12,001</td><td>12,001</td><td>12,001</td><td>12,001</td><td>12,001</td></tr><tr><td>R<sup>2</sup></td><td>0.006</td><td>0.134</td><td>0.174</td><td>0.176</td><td>0.141</td></tr></tbody></table>

Note: Robust standard errors (HC1) are reported in parentheses. *p<0.1; **p<0.05; ***p<0.01. As in Appendix E, control variables are: vote, gender, age, income, education, urbanity, likelihood of becoming millionaire, living with partner, employment status, foreign born, country region.

Again, the effects go in the opposite direction to warm glow. In this case, increased support may stem from enhanced credibility of policies that are known to be discussed in international organizations. Overall, the results of these two experiments provide no evidence that support for global redistribution is affected by warm glow. On the contrary, they suggest that support is sincere and robust to the prospect of implementation or to the possibility of a moral substitute.

# 6 Breadth of Accepted International Policies

Knowing that some internationally redistributive policies are sincerely supported and may influence voting behavior, I now examine the range of international policies that
could be accepted. In this section, I analyze, in turn, the support for global policies cur-
rently debated in the international community, as well as more radical proposals; I also
assess broader willingness to defend global solidarity, analyze the preferred channels to
transfer resources to LICs, and I use a custom redistribution task to reveal the preferred
extent of international transfers.

**6.1 Acceptance of Currently Debated Global Policies**

**Plausible Global Policies.** Figure 10 reveals the acceptance of plausible global policies (see Figure S32 for absolute support). These policies are deemed “plausible” because they are debated in international organizations, as detailed in Appendix C.1. Almost every policy garners majority acceptance in each country. The only exception is the acceptance among Japanese respondents of a globally redistributive tax on carbon emissions from aviation, at 46%. This proposal has the most salient cost: a 30% increase in flight prices. It is the least supported in every country. The most supported policies, with over two-thirds acceptance in every country and a majority of absolute support in the pooled sample, are the 2% minimum tax on billionaires' wealth proposed by Zucman (2024), the expansion of low-interest-rate sustainable investments in LICs (Bridgetown Initiative 2025), and developed countries contributing to the climate loss and damage fund. Figure S72 shows that most policies garner majority support across the political spectrum in Europe and Japan, whereas Trump voters oppose more policies than they support.

**Ranking of Countries in Terms of Support for Global Redistribution.** On average, respondents support 51% of the plausible policies and oppose 21% of them. This means they support +30 p.p. more policies than they oppose (Figure S1). The countries with the highest mean difference between support and opposition are Saudi Arabia (+50 p.p.), Italy (+49) and Spain (+39). In contrast, net support is lowest in Japan (+20), Switzerland (+24), Poland, and the U.S. (+25).

Other synthetic indicators of support for global redistribution show consistent country rankings. In particular, the countries previously identified as having the highest and lowest net support retain their rankings when ordered by average latent support for global redistribution (Figure S1). To construct this latent variable, I standardize all variables of support and average them, weighted by loadings obtained from an exploratory factor analysis (see details and loading weights in Appendix C.4).

One might wonder why the countries leading in support are the Saudi kingdom and
<figure><img src="image_13.png" /><figcaption>Figure 10: Acceptance of plausible global redistribution policies (Percentage of *Somewhat* or *Strongly support* among non-*Indifferent* responses). See Figure S32 for the absolute support. (Question 38).</figcaption></figure>

right-wing-dominated Italy. Breaking down the support by political leaning and other selected sociodemographics, Figures S71-S73 shed some light on this question. In Saudi Arabia, half of the adult population is immigrant. However, foreign workers do not drive the results, as Saudi citizens exhibit slightly higher support than non-Saudis.<fnref n="35" /> As for Italy, it is both the country with the lowest gap in support between left-wing and far-right voters (along with Japan, at 33 p.p.) and the country with the highest support among left-wing voters.<fnref n="36" />

**Climate Finance Goal.** Climate finance refers to the financing of climate action in developing countries by developed countries. In 2024, countries agreed on a "New Collective Quantified Goal" (NCQG) of climate finance set at $300 billion per year by 2035, which is triple the previous goal. However, while developing countries such as India called for $600 billion in grants (or grant-equivalent funding), the NCQG does not specify the share

<footnote n="35">³⁵Therefore, tentative explanations may rather come from Saudi society. While Saudis benefit from a generous welfare state, the Islamic pillar of Zakat (almsgiving) might further foster a culture of generosity.</footnote>

<footnote n="36">³⁶While the former point may be linked to the vision of Italy's far-right leader of an Africa-Italy partnership (trading off foreign aid with cooperation in fighting immigration), the Italian population might also be influenced by the Vatican's messages in favor of global solidarity.</footnote>
of finance that should be provided as grants. Currently, the goal is being met with only $26 billion in grants and the remainder in loans (OECD 2024).

I test the preferred amount for the NCQG in grant-equivalent terms, using two random variants. Both variants inform respondents of the current situation and the agreed goal, expressing amounts in both absolute terms and as a proportion of developed countries' GDP. The *Short* variant uses qualitative, textual responses, and features a middle category of $100 billion (namely, "Meet the newly agreed goal by tripling grants and loans ($100 billion in grants, or 0.15% of GDP). "). The *Full* variant provides more detailed explanations in the question text and then uses numerical answers, with a midpoint of $300 billion.

In both variants, the median preferred NCQG is $100 billion in grants, with 19% of respondents choosing an amount of $600 billion or larger (Figures S35-S36).

That differently framed variants yield consistent results suggests that, despite its length, the question was well understood. The median choice of a climate finance quantum in line with the internationally agreed NCQG can be interpreted in two distinct ways. Either diplomats of HICs are defending the level of generosity that reflects the median preferences of their compatriots, or respondents' attitudes are anchored in existing agreements (or in their governments' stance). The results presented below are more consistent with the latter interpretation, as they reveal majority acceptance of much larger international transfers.

## 6.2 Support for Radical Proposals, Political Action, and Broad Values

In the final part of the questionnaire, I pose a variety of questions to assess the range of global solidarity policies, actions or values that people may accept (Figure 11).

**Sustainable Future versus Status Quo.** Respondents were asked which scenario they would prefer for the next twenty years: a sustainable future or the status quo (note that scenarios were not labeled that way in the questionnaire, but were instead randomly named *A* or *B*). In the sustainable scenario, most countries cooperate to tax millionaires and meet the +2°C target, through the electrification of cars and the doubling of prices for heating fuel or gas, air travel, and beef. Although overall purchasing power is preserved (through a reduction in sales tax), people change their habits (e.g. flying and eating meat are cut by half). In the status quo, no policy is implemented, people maintain their lifestyles, and global warming reaches +3°C by 2100, causing more severe disasters.
Overall, 68% of respondents prefer the sustainable future over the status quo.

**Global Income Redistribution.** I test the support for a global tax on top incomes to finance poverty reduction in LICs, with the tax targeting either the global top 1% or top 3%, depending on random assignment. The top 1% variant describes an additional 15% tax on after-tax individual income in excess of $120,000 per year (at Purchasing Power Parity), while the top 3% variant features additional rates of 15%, 30%, and 45% above $80,000, $120,000, and $1 million, respectively. Each tax is calibrated to finance the poverty gap, with poverty defined using thresholds of $250 and $400 per month for the top 1% and top 3% variants, respectively. These taxes entail international transfers of 2% and 5% of world nominal income, respectively (see Appendix C.2 for details). Two numerical examples explain to respondents how the tax would affect taxpayers' income. The question also states the share of affected taxpayers worldwide and in their country, as well as the share of their country's GDP that would be transferred. For example, in the U.S., the top 1% tax would affect the top 8% and transfer 3% of GDP, while the top 3% tax would affect the top 18% and transfer 8% of GDP (see Figure S39). These figures are about half as high in Japan and Germany, and around four times lower in France and Spain.

Overall, 56% (resp. 50%) of the respondents support the top 1% (resp. top 3%) tax, and 25% (resp. 28%) oppose it (Figure S40). The top 1% tax obtains majority of absolute support in every country except Japan. Both variants are accepted by a majority in every case except Switzerland for the top 3% variant (in which case 18% of Swiss people would be affected). Overall, the tax garners majority acceptance even among the 6% of respondents who would be affected, though this is not the case in every country for the top 3% variant (Figure S41).

**Global Convergence.** A simple question captures the acceptance of global solidarity: "Should governments actively cooperate to have all countries converge in terms of GDP per capita by the end of the century?" Overall, 61% answer *Yes* and 26% *No*, with the lowest relative agreement (i.e. excluding people not responding) in the U.S., at 56%.

**Willingness to Act.** Two questions asked the respondents how they would react to a "worldwide movement in favor of a global program to tackle climate change, implement taxes on millionaires and fund poverty reduction in [LICs]".

In a multiple-choice question (censored in Russia), 29% report they could participate
in the movement by either attending a demonstration (19%), going on strike (7%), or do-
nating $100 to a strike fund (10%). This share rises to 68% in favor of the movement when
including the 52% of respondents who “could sign a petition and spread ideas” (Figure
S45). Taken at face value, these results would mean that a successful global solidarity
movement could collect up to $10 billion and organize some of the largest demonstra-
tions in history, matching Earth Day mobilizations.<fnref n="37" /> Interestingly, 52% of the 584 mil-
lionaires<fnref n="38" /> who answered the survey would be in favor of such a movement.

When asked whether they would be more or less likely to vote for the political party
they feel closest to if it were part of such a movement, 36% of the respondents state they
would be more likely versus 17% less likely (Figure S46). Among the 5% of respondents
who did not vote in the last election and feel closest to a left-wing party, the share more
likely to vote in that case increases to 46% (versus 10% who are less likely).

**Reasons for Helping LICs.** In a multiple-choice question, I asked respondents which reasons for HICs supporting LICs they agree with, among arguments involving *duty*, *long-term interest*, or *historical responsibility*. At 54%, the reason most frequently chosen in every country (except France) is *duty*, specifically "Helping countries in need is the right thing to do" (Figure S47). Additionally, 38% select *interest*, and 25% *responsibility*, with only 16% disagreeing with every reason.

**Reparations.** In former colonial or slave States,<fnref n="39" /> I asked respondents whether they would support "reparations for colonization and slavery to former colonies and descendants of slaves", specifying that the reparations "could take the form of funding education and facilitating technology transfers". Consistent with the general disagreement that HICs have a *historical* responsibility to support LICs, only a minority of 35% of respondents support reparations (except in Italy where 56% do), while 42% oppose them (Figure S48). This suggests that framing global solidarity as a decolonial struggle might be counterproductive.

**Agreement That Own Taxes Should Solve Global Problems.** Overall, 41% agree and 28% disagree that “[their] taxes should go towards solving global problems”. With 60%

<footnote n="37">³⁷On April 22, 1970, 20 million US-Americans (10% of the population) demonstrated for the environment. Since then, Earth Day events regularly mobilize hundreds of millions of people worldwide.</footnote>

<footnote n="38">³⁸In the weighted subsample of millionaires, 60% are US-Americans and 26% Europeans.</footnote>

<footnote n="39">³⁹I did not ask this question in Japan or Russia, because these countries' historiographies do not present their past as colonial but rather as an empire.</footnote>
relative agreement, there is a relative majority in favor of one's own taxes financing global solidarity, though a lower one than for specific proposals that would make the richest contribute.<fnref n="40" /> As explained in Section 2, the present results replicate well the “Global Solidarity Report” that first asked this question (Global Nation 2023)

<figure><img src="image_14.png" /><figcaption>Figure 11: Acceptance of broad action or radical proposals of global redistribution. (Questions 44-46, 49-51, 53, 61).</figcaption></figure>

**Moral Circle.** Asked “Which group of people do you advocate for when you vote?”,<fnref n="41" /> 45% select a universalist answer (“Humans” or “Sentient beings (humans and animals)”), which is more than the most common answer, referring to one’s fellow citizens (32%). Universalists are fewer in Japan (30%) but constitute a majority in Europe (50%) and Saudi Arabia (57%), as shown in Figures 12 and S61. Among those who lean to the left, 59% are universalists, compared to 32% on the center-right or far-right.

Following Enke et al. (2024), I construct an alternative measure of universalism based on the vocabulary used in open-ended fields.<fnref n="42" /> Although latent support for global re-

<footnote n="40">⁴⁰This confirms that the willingness to pay for global solidarity, even through taxes, does not equate to acceptance of global redistribution proposals.</footnote>

<footnote n="41">⁴¹In Russia and Saudi Arabia, the question was asked differently. It read: “Which group do you advocate for? For example, if you were the richest person on Earth, which group would you predominantly help with your money?”</footnote>

<footnote n="42">⁴²More specifically, I use the Moral Foundation Dictionary (MFD) 2.0 (Frimer et al. 2019) and define *universalism* as the number of occurrences of *care* or *fairness* words minus the number of *loyalty* or *authority* words. I also test an alternative definition, based on the extended MFD (Hopp et al. 2021), that uses weights rather than dummy variables to indicate a word's belonging to a moral dimension. The latter definition is</footnote>
distribution is significantly correlated with this measure, the correlation is only .05, less
than the correlation with manual, keyword, or AI classifications of a field as relating to
inequality or poverty (at .09, .08, and .06, respectively), and much less than the correlation
with our universalism variable based on moral circle (at .37). Furthermore, the correlation
between the two measures of universalism is only .03. This observation demonstrates that
the various indicators labeled as "universalism" by different authors may not all capture
the same dimension.

<figure><img src="image_15.png" /><figcaption>Figure 12: "Which group of people do you advocate for when you vote?"<sup>41</sup> (Question 62).</figcaption></figure>

6.3 Preferred Channels for Transferring Resources to LICs

Asked to evaluate ways of transferring resources to reduce poverty in LICs on a 4-point Likert scale, the most preferred option in every country is “Cash transfers to parents (child allowances), to the disabled and to the elderly”, with 16% selecting it as the *Best way* overall, and 49% as a *Right way* or *Best way* (Figures 13, S42-S43). “Unconditional transfers to the national government” is the only option seen as a *Wrong way* by the majority, but this share falls from 51% down to 21% (becoming the third most supported option out of seven) when “transfers to the national government [are] conditioned on the use of funds for poverty reduction programs”. Interestingly, “unconditional cash transfers to each household” are controversial: they are the second most chosen *Best way*, yet 33% view them as a *Wrong way*. Conversely, “transfers to public development aid agencies which then finance suitable projects” is uncontroversial, with only 16% considering it a *Wrong way*, while 37% rate it as a *Right* or *Best way*.

6.4 Custom Global Income Redistribution

The last task of the questionnaire allowed respondents to manipulate the shape of the
global income distribution.<fnref n="43" /> The question text included the following instructions:

even less (though still significantly) correlated with the latent support for global redistribution, at .03.

<footnote n="43">⁴³Appendix C.2 details how I obtained the world distribution of PPP incomes.</footnote>
<figure><img src="image_16.png" /><figcaption>Figure 13: "How do you evaluate each of these channels to transfer resources to reduce poverty in LICs?"
Percentage of *Right* or *Best way* (other options: *Wrong* or *Acceptable way*). (Question 48).</figcaption></figure>

"Below you will find a graph of the world distribution of after-tax income and three sliders that vary it. The current distribution is in red, and your custom one is in green. The first two sliders control the proportion of winners and the proportion of losers, among all humans. The third slider controls the degree of redistribution from the richest to the poorest. If you do not want new policies to reduce global inequality, you can set the third slider to zero."

The interactive question is available at bit.ly/custom_global_redistr, an explainer video atyoutu.be/gSfsQwczT7w, and the algorithm translating slider positions into a redistribution is described in Appendix F. Figure 14 displays what respondents see below the instructions, including the interactive graph and a table summarizing how their custom redistribution would affect five example income levels (including their own, asked right before). To mitigate potential anchoring at the sliders' initial positions,<fnref n="44" /> sliders are initialized in one of two random positions: either 60% of winners, 20% of losers, and a degree of redistribution of 2 out of 10 (as in Figure 14); or 40%, 10%, and 7/10, respectively. Given the complexity of the task and its inconvenience on mobile devices, respondents are given the explicit option to skip it.

<footnote n="44">⁴⁴To test for anchoring, I regress responses on the sliders' initial positions. I define the anchoring effect as the effect size relative to the difference between the initial positions of the two variants. It is always significant, at 36% for the share of winners, 57% for the share of losers, and 42% for the degree of redistribution. While anchoring plays a role, the responses converge to a middle point between the two anchors, indicating that the anchors themselves may have been defined by the surveyor (myself) drifting away from a shared</footnote>
<figure><img src="image_17.png" /><figcaption>Figure 14: Custom global redistribution: screenshot of the bottom of the page. (Question 55).</figcaption></figure>

preference in opposite directions.
Overall, 56% are satisfied with their custom redistribution and 43% skip it. Although the non-response rate may seem high, it is relatively evenly spread across the population. Indeed, the share of satisfied respondents is 52% for non-voters, 54% for center-right or right-wing voters, 57% for far-right voters, and 61% for left-wing voters; while it ranges from 49% for people without a high-school diploma to 57% for those with a post-secondary diploma. The limited heterogeneity in response rates across crucial sociodemographic groups suggests that the task enabled motivated respondents to make an informed choice regarding their preferred redistribution with little sacrifice in terms of sample representativeness.

Figure S49 shows the median preferred redistribution among satisfied respondents, i.e. the curve obtained by setting the sliders at their median preferred values: 49% of winners, 18% of losers, and a degree of redistribution of 5/10, resulting in a transfer of 5.4% of world income from rich to poor and in a minimum income of $287 per month. Interestingly, 48% choose to lose from their custom redistribution while only 9% choose to win; the median satisfied respondent selects parameters such that they neither win nor lose. Besides, 10% of satisfied respondents opt for the status quo, preserving the current income distribution. Finally, Figure S50 presents the average preferred redistribution among satisfied respondents, obtained by pointwise averaging custom curves. The average preferred redistribution transfers 5.4% of world income from the top 27% to the bottom 73% and entails a minimum income of $247 per month. As shown in Figure S70, at the top of the distribution, the average preferred redistribution can be achieved with a 7% marginal income tax rate above $25,000 and a 16% rate above $40,000 per year (at Purchasing Power Parity).

Figures S52-S53 reveal limited heterogeneity in custom redistributions across countries. However, Figures S54-S57 show greater variation at the individual level, though the bulk of respondents favor a custom redistribution implying transfers of 4% to 5% of world income and a minimum income of $150 to $350 per month.

Fabre (2022) applied the same method to uncover French preferences regarding national income redistribution and tested support for the median and average preferred redistributions on a separate sample. Excluding the 22% to 24% of people not responding, 51% of respondents accepted the average redistribution and 67% the median one.<fnref n="45" /> While one cannot be sure that these results would replicate in the context of a global redis-

<footnote n="45">⁴⁵Fabre (2022) also tested a redistribution obtained from median parameters and a 5% lower aggregate income to account for adverse behavioral responses. This was accepted by 62% of French respondents.</footnote>
tribution, they suggest that a majority might accept the average or median redistribution described above.

# 7 Conclusion

Applying the theory of optimal taxation, Kopczuk et al. (2005) show that the level of U.S. foreign aid could only be rationalized if the U.S. government placed a value 2,000 times higher on the welfare of a US-American than on that of a foreigner (although this ratio should be reduced by the proportion of foreign aid transfers diverted or wasted). Our results contradict the notion that government action accurately reflects attitudes towards global redistribution, and are consistent with a conservative bias among legislators (Broockman & Skovron 2018; Gilens & Page 2014; Pilet et al. 2024). Indeed, a majority of respondents in high-income countries support a global tax on top incomes to finance poverty reduction in low-income countries. Additionally, over two-thirds of respondents accept a tax on the wealth of millionaires with 30% of the revenue financing LICs, even in the case of only a few countries implementing it. In every country, majorities accept an International Climate Scheme that is costly to them but beneficial to the poorest globally, showing that most people value climate action and poverty reduction.

The revenue allocation task sheds light on how much people value global versus domestic public goods. On average, respondents allocate 17.5% of the revenue from a hypothetical global wealth tax to sustainable development out of the five specified categories. This indicates that people are neither selfless universalists, who would allocate all the revenue from this tax to the poorest countries, nor devoid of altruism towards foreigners, as this would imply allocating nothing to global spending. The custom redistribution task confirms that most people would actually prefer much greater global redistribution than currently exists, as the average respondent opts for a global minimum income of $247 per month, financed by transfers amounting to over 5% of world income.

An exploration of respondents' underlying values reveals that support for global redistribution primarily stems from a sense of duty and empathy towards the destitute. For some, this issue appears important enough to factor into their voting decision. Indeed, the likelihood that a political program is preferred increases if it includes a globally redistributive tax on millionaires and decreases if it includes cuts to foreign aid. Additionally, one-third of respondents report that they would be more likely to vote for a political party if it were part of a global movement for sustainable development, and a similar propor-
tion state that they could themselves participate in such a movement.

These results raise the question of why so few policymakers campaign on sustain-
able development proposals. The lack of supply of such campaigns might stem from
pluralistic ignorance among policymakers and activists, consistent with the public's un-
derestimation of support for a Global Climate Scheme. Alternatively, it could be due to a
lack of demand from constituents. Indeed, global inequality is rarely a top-of-mind con-
sideration. People's most frequent concerns relate to self-interested issues such as their
purchasing power or health; articulated political demands generally refer to national is-
sues such as public services; and the most salient international issues are climate change,
Wars, and the rise of the far right.

The low salience of global inequality may manifest as a lack of popular mobilization, resulting in it being a low priority for policymakers. Combined with the necessary trade-off between global redistribution and fellow citizens' purchasing power, policymakers may prioritize the latter —which is the primary concern of voters—to the point of ignoring universalist attitudes. Status quo bias is a compounding factor: the weakness of global institutions and the primacy of national polities make international cooperation unlikely, which may discourage universalist thought and make it seem utopian. Indeed, support for global policies is partly caused by the belief that they are possible, as our information experiment demonstrated. Therefore, the organization of the world order based on nation-states might silence demands for universalist reforms and perpetuate a cycle where the low salience of universalist concerns and status quo institutions reinforce each other.

Nevertheless, the survey results suggest some untapped potential for global solidarity. In light of these findings, it is unlikely that the public would resist global redistribution policies. This is especially true for balance sheet operations with expansionary impacts and indirect costs, such as debt restructuring, liquidity provision, the expansion of lending by Multilateral Development Banks, and their recapitalization through the rechanneling of Special Drawing Rights. These reforms are widely accepted and are the natural focus of multilateral initiatives (Bridgetown Initiative 2025; FfD4 2025). Since public attitudes do not appear to be a limiting factor, further research is needed to understand policymakers' motivations and the obstacles they face in cooperating on sustainable development reforms.
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## Acknowledgements

I received funding from the Agence Nationale de la Recherche for this research (ANR-24-CE03-7110). The randomized controlled trials were registered in the American Economic Association's registry for randomized controlled trials under ID AEARCTR-0017248. I am grateful to Alina Timoshkina and Gerhard Toews for helping me launch the survey in Russia. I thank researchers who kindly gave me access to their data: Félix Bajard for wealth distribution and Amory Gethin for income distribution. I am grateful to Armon Rezai and Wien Universität for helping me use Qualtrics. I thank Romain Espinosa for his attentive reading and useful feedback. I am grateful to the translators and the numerous people who graciously tested the survey, proofread the translations, and gave feedback, including Gianluca Drappo, Valeria Glebova, Anne Guillemot, Marya Kayyal, Lu Li, Lilian Leupold, Guadalupe Manzo, Rintaro Matsuda. I am grateful to Erwan Akrour, Marius Le Hénaff, and Raquel Oliveira for research assistance on the quotas and the pools of policies. I thank seminar, workshop or conference participants for useful feedback, at: the University of Brasília, Unicamp, the University of São Paulo, WZB Berlin, Paris-Saclay, the World Inequality Lab, MSE-Sorbonne, the Bundesbank, FSR Climate Conference, the New Economic School, CIRED, Fürth.
# A Raw Results

## A.1 Figures

<table><caption>Figure S1: Average synthetic indicators of support for global redistribution. (Question 38). (Back to Section 6.1.)</caption><thead><tr><th></th><th>All</th><th>Europe</th><th>Saudi Arabia</th><th>Italy</th><th>Spain</th><th>Germany</th><th>United Kingdom</th><th>Russia</th><th>France</th><th>Poland</th><th>USA</th><th>Switzerland</th><th>Japan</th></tr></thead><tbody><tr><td>Latent support for global redistribution (standardized)</td><td>0.00</td><td>0.11</td><td>0.49</td><td>0.39</td><td>0.23</td><td>0.08</td><td>0.05</td><td>0.04</td><td>0.02</td><td>-0.09</td><td>-0.10</td><td>-0.11</td><td>-0.21</td></tr><tr><td>Share of plausible global policies supported</td><td>0.51</td><td>0.56</td><td>0.64</td><td>0.65</td><td>0.58</td><td>0.55</td><td>0.55</td><td>0.50</td><td>0.55</td><td>0.49</td><td>0.48</td><td>0.53</td><td>0.38</td></tr><tr><td>Share of plausible global policies opposed</td><td>0.21</td><td>0.21</td><td>0.14</td><td>0.16</td><td>0.19</td><td>0.21</td><td>0.21</td><td>0.18</td><td>0.22</td><td>0.23</td><td>0.23</td><td>0.28</td><td>0.18</td></tr><tr><td>Difference between share of plausible policies supported and opposed</td><td>0.30</td><td>0.36</td><td>0.50</td><td>0.49</td><td>0.39</td><td>0.34</td><td>0.34</td><td>0.31</td><td>0.33</td><td>0.25</td><td>0.25</td><td>0.24</td><td>0.20</td></tr><tr><td>Ratio of share of plausible policies supported over supported or opposed</td><td>0.70</td><td>0.72</td><td>0.80</td><td>0.79</td><td>0.74</td><td>0.71</td><td>0.71</td><td>0.71</td><td>0.71</td><td>0.67</td><td>0.68</td><td>0.65</td><td>0.67</td></tr></tbody></table>
<figure><img src="image_18.png" /><figcaption>Figure S2: Keyword classification of open-ended fields (matches with at least one keyword in a list). (Questions 19-21). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_19.png" /><figcaption>Figure S3: AI classification of open-ended fields (using ChatGPT-4.1). (Questions 19-21). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_20.png" /><figcaption>Figure S4: Manual classification of open-ended fields. (Questions 19-21). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_21.png" /><figcaption>Figure S5: Manual classification of concerns fields: “What are your main concerns these days?” (Question 19). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_22.png" /><figcaption>Figure S6: Manual classification of *wish* fields: “What are your needs or wishes?” (Question 20). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_23.png" /><figcaption>Figure S7: Manual classification of injustice fields: “What according to you is the greatest injustice of all?” (Question 21). (Back to Section 3.1.)</figcaption></figure>
<figure><img src="image_24.png" /><figcaption>Figure S8: Manual classification of issue fields: “Can you name an issue that is important to you but is neglected in the public debate?” (Question 22). (Back to Section 3.1.)</figcaption></figure>
Figure S9: Effect by vote at the last election on the likelihood that a political program is preferred of containing the following policy (compared to no foreign policy in the program). (See Figure 8 for the simple figure). (Question 23). (Back to Section 3.1.)

<figure><img src="image_25.png" /><figcaption>(b) Int'l tax on millionaires with 30% financing health and education in low-income countries.</figcaption></figure>

<figure><img src="image_26.png" /></figure>
<figure><img src="image_27.png" /><figcaption>Figure S10: Conjoint analysis in France (Average Marginal Component Effect). Cf. Figure S19 for French. (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_28.png" /><figcaption>Figure S11: Conjoint analysis in Germany (Average Marginal Component Effect). Cf. Figure S20 for German. (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_29.png" /><figcaption>Figure S12: Conjoint analysis in Italy (Average Marginal Component Effect). Cf. Figure S21 for Italian. (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_30.png" /><figcaption>Figure S13: Conjoint analysis in Poland (Average Marginal Component Effect). Cf. Figure S22 for Polish. (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_31.png" /><figcaption>Figure S14: Conjoint analysis in Spain (Average Marginal Component Effect). Cf. Figure S23 for Spanish. (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_32.png" /><figcaption>Figure S15: Conjoint analysis in the UK (Average Marginal Component Effect). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_33.png" /><figcaption>Figure S16: Conjoint analysis in Switzerland (Average Marginal Component Effect). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_34.png" /><figcaption>Figure S17: Conjoint analysis in Japan (Average Marginal Component Effect). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_35.png" /><figcaption>Figure S18: Conjoint analysis in the U.S. (Average Marginal Component Effect). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_36.png" /><figcaption>Figure S19: Conjoint analysis in France (in French, cf. Figure S10 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_37.png" /><figcaption>Figure S20: Conjoint analysis in Germany (in German, cf. Figure S11 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_38.png" /><figcaption>Figure S21: Conjoint analysis in Italy (in Italian, cf. Figure S12 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_39.png" /><figcaption>Figure S22: Conjoint analysis in Poland (in Polish, cf. Figure S13 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_40.png" /><figcaption>Figure S23: Conjoint analysis in Spain (in Spanish, cf. Figure S14 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_41.png" /><figcaption>Figure S24: Conjoint analysis in Japan (in Japanese, cf. Figure S17 for English). (Question 23). (Back to Section 5.1.)</figcaption></figure>
<figure><img src="image_42.png" /><figcaption>Figure S25: Average preferred revenue split for a global wealth tax (variant few). (Question 24). (Back to Section 3.2.)</figcaption></figure>
<figure><img src="image_43.png" /><figcaption>Figure S26: Decomposition of preferred shares for each spending item in the revenue split (All countries together; variant few). (Question 24). (Back to Section 3.2.)</figcaption></figure>
<figure><img src="image_44.png" /><figcaption>Figure S28: Average preferred revenue split for a global wealth tax (variant many). (Question 25). (Back to Section 3.2.)</figcaption></figure>

<figure><img src="image_45.png" /></figure>
Figure S29: "By taking this survey, you will be automatically entered into a lottery to win up to [amount lotteries: $100]."

Should you be selected in the lottery, you will have the option to channel a part of this additional compensation to the charity *Just One Tree* to plant trees.

In case you win the lottery, what share of the [amount lotteries: $100 prize] would you donate to plant trees?" (Question 27).

<figure><img src="image_46.png" /></figure>

Figure S30: Support for the National, Global, and International Climate Schemes, and median belief regarding the support for the GCS. (Questions 26-35). (Back to Section 4.1.)

<figure><img src="image_47.png" /></figure>
Figure S31: "According to you, how likely is it that international policies involving significant transfers from high-income countries to low-income countries will be introduced in the next 15 years?" (Question 37).

<figure><img src="image_48.png" /></figure>
<figure><img src="image_49.png" /><figcaption>Figure S35: Preferred North-to-South climate grant funding in 2035, specified in qualitative terms or in terms of who advocates for that amount (NCQG, variant Short). (Question 40). (Back to Section 6.1.)</figcaption></figure>

<figure><img src="image_50.png" /></figure>
<figure><img src="image_51.png" /><figcaption>Figure S37: Support for an international wealth tax with 30% of revenue funding LICs, depending on the country coverage (*Yes/No* question). (Questions 41-43).</figcaption></figure>

<figure><img src="image_52.png" /></figure>
<figure><img src="image_53.png" /><figcaption>Figure S39: Acceptance of a global progressive income tax on the richest households to finance global poverty reduction (Questions 45-46, Percentage of *Somewhat* or *Strongly support* among non-*Indifferent* responses), and features of the tax presented to the respondents (Section C.2). (Back to Section 6.2.)</figcaption></figure>

<figure><img src="image_54.png" /></figure>
<figure><img src="image_55.png" /><figcaption>Figure S41: Acceptance of a global progressive income tax on the richest households to finance global poverty reduction among respondents affected by the tax (Questions 45-46, Percentage of Somewhat or Strongly support among non-Indifferent responses), and share of respondents affected by the tax (Section C.2).

(Back to Section 6.2.)</figcaption></figure>

<figure><img src="image_56.png" /><figcaption>Figure S42: “How do you evaluate each of these channels to transfer resources to reduce poverty in LICs?”

Percentage of Best way (other options: Right, Wrong or Acceptable way). (Question 48).

(Back to Section 6.3.)</figcaption></figure>

<figure><img src="image_57.png" /></figure>
Figure S43: "How do you evaluate each of these channels to transfer resources to reduce poverty in LICs?"

Percentage of Wrong way (other options: Best, Right or Acceptable way). (Question 48).

(Back to Section 6.3.)

<figure><img src="image_58.png" /></figure>

Figure S44: "Should governments actively cooperate to have all countries converge in terms of GDP per capita by the end of the century?" (Question 49).

<figure><img src="image_59.png" /></figure>
<table><caption>Figure S45: "If there was a worldwide movement in favor of a global program to tackle climate change, implement taxes on millionaires and fund poverty reduction in low-income countries, to what extent would you be willing to be part of that movement? (Multiple answers possible)" (Question 50). (Back to Section 6.2.)</caption><thead><tr><th></th><th>All</th><th>Europe</th><th>France</th><th>Germany</th><th>Italy</th><th>Poland</th><th>Spain</th><th>United Kingdom</th><th>Switzerland</th><th>Japan</th><th>Saudi Arabia</th></tr></thead><tbody><tr><td>Would not support such a movement</td><td>32</td><td>28</td><td>29</td><td>31</td><td>18</td><td>29</td><td>25</td><td>31</td><td>36</td><td>44</td><td>26</td><td>33</td></tr><tr><td>Could sign a petition and spread ideas</td><td>52</td><td>55</td><td>53</td><td>53</td><td>58</td><td>54</td><td>57</td><td>55</td><td>48</td><td>51</td><td>40</td><td>50</td></tr><tr><td>Could attend a demonstration</td><td>19</td><td>21</td><td>22</td><td>18</td><td>26</td><td>15</td><td>27</td><td>19</td><td>14</td><td>4</td><td>24</td><td>23</td></tr><tr><td>Could go on strike</td><td>7</td><td>9</td><td>7</td><td>11</td><td>15</td><td>8</td><td>10</td><td>5</td><td>6</td><td>2</td><td>9</td><td>7</td></tr><tr><td>Could donate [$100] to a strike fund</td><td>10</td><td>10</td><td>8</td><td>12</td><td>12</td><td>7</td><td>10</td><td>12</td><td>13</td><td>2</td><td>18</td><td>12</td></tr></tbody></table>
Figure S46: "Let us call "your political party" the party you voted for in the last election, or the party that represents your views most closely.

**Imagine** there was a **worldwide coalition** of political parties in favor of a common program to tackle climate change, implement taxes on millionaires and fund poverty reduction in low-income countries.

**Would you be more likely to vote for your party if it were part of that coalition?"**
(Question 51).
(Back to Section 6.2.)

<figure><img src="image_60.png" /></figure>

Figure S47: "Some people think that high-income countries should support low-income countries.

Among the different reasons given, which ones do you agree with? (Multiple answers possible)" (Question 52).
(Back to Section 6.2.)

<figure><img src="image_61.png" /></figure>
Figure S48: "Some people argue that Western countries owe reparations for colonization and slavery to former colonies and descendants of slaves.

Reparations could take the form of funding education and facilitating technology transfers, to address unequal opportunities passed down from the past.

**Do you support or oppose reparations** of this kind for colonization and slavery? **"**
(Question 53).

(Back to Section 6.2.)

<figure><img src="image_62.png" /></figure>
<figure><img src="image_63.png" /><figcaption>Figure S49: Global redistribution obtained from median custom parameters: 49% of winners; 18% of losers; degree of redistribution of 5 (out of 10). (Question 55). (Section 6.4.)</figcaption></figure>
<figure><img src="image_64.png" /><figcaption>Figure S50: Average custom global redistribution. (Question 55). (Back to Section 6.4.)</figcaption></figure>
<table><caption>Figure S51: Mean answers to custom redistribution. (Question 55). (Back to Section 6.4.)</caption><thead><tr><th></th><th>All</th><th>Europe</th><th>France</th><th>Germany</th><th>Italy</th><th>Poland</th><th>Spain</th><th>United Kingdom</th><th>Switzerland</th><th>Japan</th><th>Saudi Arabia</th><th>USA</th></tr></thead><tbody><tr><th>Preferred share of winners</th><td>47.4</td><td>47.9</td><td>47.2</td><td>46.5</td><td>48.7</td><td>49.5</td><td>49.0</td><td>48.4</td><td>44.8</td><td>46.8</td><td>49.9</td><td>46.8</td></tr><tr><th>Preferred share of losers</th><td>17.7</td><td>17.7</td><td>18.4</td><td>17.5</td><td>17.2</td><td>16.8</td><td>18.5</td><td>17.4</td><td>18.4</td><td>17.7</td><td>17.5</td><td>17.8</td></tr><tr><th>Preferred degree of redistribution</th><td>4.7</td><td>4.8</td><td>4.6</td><td>4.6</td><td>5.2</td><td>4.9</td><td>5.0</td><td>4.8</td><td>4.4</td><td>4.5</td><td>5.0</td><td>4.5</td></tr><tr><th>Implied minimum income (in PPP $/month)</th><td>242.0</td><td>251.1</td><td>238.0</td><td>238.6</td><td>272.4</td><td>264.6</td><td>264.2</td><td>246.6</td><td>222.7</td><td>233.0</td><td>274.3</td><td>232.5</td></tr><tr><th>Implied transfer (in % of world income)</th><td>5.1</td><td>5.4</td><td>5.0</td><td>5.1</td><td>5.9</td><td>5.9</td><td>5.7</td><td>5.3</td><td>4.7</td><td>4.7</td><td>5.9</td><td>4.9</td></tr><tr><th>Loses in own custom redistribution</th><td>46.4</td><td>41.1</td><td>42.5</td><td>46.9</td><td>35.2</td><td>11.4</td><td>35.8</td><td>54.9</td><td>73.9</td><td>36.9</td><td>40.5</td><td>56.6</td></tr><tr><th>custom_redistr_satisfied</th><td>55.8</td><td>58.2</td><td>52.8</td><td>56.8</td><td>63.3</td><td>56.7</td><td>62.8</td><td>58.7</td><td>54.1</td><td>39.6</td><td>67.6</td><td>58.4</td></tr><tr><th>custom_redistr_skip</th><td>42.9</td><td>40.0</td><td>44.4</td><td>41.4</td><td>34.8</td><td>42.4</td><td>35.5</td><td>40.0</td><td>43.5</td><td>59.2</td><td>32.4</td><td>40.8</td></tr></tbody></table>

<table><caption>Figure S52: Mean answers to custom redistribution among respondents satisfied with their custom redistribution. (Question 55). (Back to Section 6.4.)</caption><thead><tr><th></th><th>All</th><th>Europe</th><th>France</th><th>Germany</th><th>Italy</th><th>Poland</th><th>Spain</th><th>United Kingdom</th><th>Switzerland</th><th>Japan</th><th>Saudi Arabia</th><th>USA</th></tr></thead><tbody><tr><th>Preferred share of winners</th><td>47.6</td><td>48.4</td><td>48.4</td><td>47.0</td><td>49.3</td><td>50.6</td><td>48.9</td><td>48.8</td><td>45.1</td><td>45.8</td><td>50.0</td><td>46.5</td></tr><tr><th>Preferred share of losers</th><td>18.3</td><td>18.2</td><td>19.8</td><td>17.5</td><td>17.0</td><td>16.7</td><td>19.7</td><td>18.4</td><td>19.6</td><td>18.9</td><td>17.6</td><td>18.2</td></tr><tr><th>Preferred degree of redistribution</th><td>4.7</td><td>4.9</td><td>4.4</td><td>4.7</td><td>5.3</td><td>5.2</td><td>5.1</td><td>4.6</td><td>4.4</td><td>4.4</td><td>4.9</td><td>4.5</td></tr><tr><th>Implied minimum income (in PPP $/month)</th><td>247.3</td><td>259.5</td><td>239.1</td><td>242.9</td><td>282.2</td><td>288.5</td><td>272.8</td><td>248.4</td><td>217.6</td><td>224.9</td><td>267.5</td><td>232.8</td></tr><tr><th>Implied transfer (in % of world income)</th><td>5.4</td><td>5.8</td><td>5.3</td><td>5.5</td><td>6.2</td><td>6.6</td><td>6.0</td><td>5.6</td><td>4.7</td><td>4.6</td><td>5.8</td><td>5.1</td></tr></tbody></table>
<figure><img src="image_65.png" /><figcaption>Figure S54: Preferred share of winners in the custom redistributions among satisfied respondents. (Question 55). (Back to Section 6.4.)</figcaption></figure>

<figure><img src="image_66.png" /><figcaption>Figure S55: Preferred share of losers in the custom redistributions among satisfied respondents. (Question 55). (Back to Section 6.4.)</figcaption></figure>

<figure><img src="image_67.png" /><figcaption>Figure S56: Minimum worldwide income implied by custom redistributions among satisfied respondents (in PPP $ per month). (Question 55). (Back to Section 6.4.)</figcaption></figure>

<figure><img src="image_68.png" /></figure>
<figure><img src="image_69.png" /><figcaption>Figure S58: "Comprehension question: one respondent with the expected answer will get [amount lotteries: $100]."</figcaption></figure>

How would gasoline prices change as a result of the Global Climate Scheme? Gasoline prices would..." (Correct answer: *increase*) (Question 60).

<figure><img src="image_70.png" /><figcaption>Figure S59: Relative agreement for: "To what extent do you agree or disagree with the following statement? "My taxes should go towards solving global problems."" (Percentage of Agree or Strongly agree among non-Neither agree nor disagree responses). (Question 61).</figcaption></figure>

<figure><img src="image_71.png" /></figure>
Figure S60: Absolute agreement for: "To what extent do you agree or disagree with the following statement? "My taxes should go towards solving global problems."" (Percentage of Agree or Strongly agree). (Question 61).

<figure><img src="image_72.png" /></figure>

Figure S61: "Which group of people do you advocate for when you vote?"⁴¹ (Question 62).
(Back to Section 6.2.)

<figure><img src="image_73.png" /></figure>
<figure><img src="image_74.png" /><figcaption>Figure S63: Manual classification of *feedback* fields: "The survey is nearing completion. You can now enter any comments, thoughts, or suggestions in the field below." (Question 64).
(Back to Section 2.)</figcaption></figure>

<figure><img src="image_75.png" /></figure>
<figure><img src="image_76.png" /><figcaption>Figure S65: "Were you or your parents born in a foreign country?" (Question 5).</figcaption></figure>

<figure><img src="image_77.png" /></figure>
<figure><img src="image_78.png" /><figcaption>Figure S66: Vote in the last election, compared to actual results among voters. (Questions 16, 18). (Back to Section 2.)</figcaption></figure>
<figure><img src="image_79.png" /><figcaption>Figure S67: Vote in the last election, compared to actual results on the entire population. (Questions 16, 18). (Back to Section 2.)</figcaption></figure>
## A.2 Countries' slant in the open-ended fields

Reading and coding each field one by one took about 30 hours. It gives first-hand insight on the topics vary significantly across countries. Here are what I noted as each country's unique topics. Compared to other countries, the concepts overrepresented in each country are as follows:

* France: insecurity, holidays or free time, the public deficit, equality, gender equality;

* Germany: old age poverty, immigration, the return of growth or the economic situation, free time, war (in Europe), bureaucracy;

* Italy: health, serenity or peace of mind, war, work stress and free time, world hunger, femicides;

* Poland: war, inequality, holidays, honesty, disabled people;

* Spain: "health, money and love", housing, corruption, water access, global poverty, squatters;

* the UK: the cost of living, immigration, having a comfortable life, mental health, the Holocaust, roads dangerous for driving, being unjustly imprisoned, cut to the winter fuel allowance;

* Switzerland: equality, immigration, gender equality;

* Japan: the level of pensions, a cut on the consumption tax, the price of rice, the declining birth rate, childcare support, reducing the number of parliament members, foreigners' preferential treatment, excessive social assistance or the lack of reward for hard work, stock prices;

* Russia: metaphysical questions or profound interrogations, "lies", buying a house or a car, traveling, the desire to live;

* Saudi Arabia: hobbies such as sports or soccer, the willingness to become millionaire (or billionaire), one's business project,<fnref n="46" /> buying a house, one's car, satisfaction with one's income, "self-injustice" or sin, raising children, Palestine, the oppression of orphans, travel;

* the U.S.: the economy, Trump, breaches of the Constitution, abortion, gun control.

<footnote n="46">⁴⁶This can be linked to the high risk-taking disposition of Saudis (Falk et al. 2018).</footnote>
# B Questionnaire

The U.S. version of the questionnaire is presented. Features that vary across countries are placed in square brackets within the question text, as follows: [feature_name: U.S. value]. The features values for each country are provided in this spreadsheet. Random branches or conditions for displaying the question are specified in square brackets before the question text (cf. Figure 2 for the survey flow). The question text is followed by square brackets that refer to Sections, Figures, and Tables presenting the question results, and the variable name(s) corresponding to the question. Finally, response options are displayed in italics. Unless otherwise specified, responses are compulsory and a single response much be chosen.

(Back to Section 2.)

## Welcome

1. Welcome to this survey!

This survey is **anonymous** and is conducted **for research** purposes on a representative sample of [sample_size: 3,000] [nationality: American people].

It takes around 20 min to complete.

The survey contains lotteries and awards for those who get the correct answer to some comprehension questions.

If you are attentive and lucky, **you can win up to [amount lotteries: $100]**.

Please answer every question carefully.

By clicking on the button below, you consent to the terms and conditions.

## Socio-demographics

2. What is your gender? [gender]
Woman; Man; Other

3. What is your country? [hidden_country]
4. What is your age? [age_exact, age]
   Below 18; 18 to 20; 21 to 24; 25 to 29; 30 to 34; 35 to 39; 40 to 44; 45 to 49; 50 to 54; 55 to 59; 60 to 64; 65 to 69; 70 to 74; 75 to 79; 80 to 84; 85 to 89; 90 to 99; 100 or above

5. Were you or your parents born in a foreign country? [Figure S65; foreign]
Yes, I was born in a foreign country; Not me but both my parents were born in a foreign country; Not me but one of my parents was born in a foreign country; No, I was born in this country and my parents too

6. Do you live with your partner (if you have one)? [couple]
Yes; No

7. How many people are there in your household?
The household includes: **you**, your spouse, **your family members** who live with you, and your dependents (not flatmates). [hh_size]
1; 2; 3; 4; 5 or more

8. How many children under the age of 14 live with you? [Nb_children_14]
0; 1; 2; 3; 4 or more

9. [new page] [Only in: US] What race or ethnicity do you identify with? (Multiple answers are possible) [race]
White; Black or African American; Hispanic; Asian; American Indian or Alaskan Native; Native Hawaiian or Pacific Islander; Other; Prefer not to say

10. What is the [periodicity_text: monthly] [income_type: gross] income of your house-hold, [income_type_long: after taxes and transfers]?
This includes all sources of income: wages, pensions, welfare payments, property income, dividends, self-employment earnings, Social Security benefits, and income from other sources. [income]
[All but RU, US: Custom thresholds, taking into account household composition. Questions 6-8, and corresponding to the country's deciles and quartiles of standard of living, cf. the sheet "Income" in this spreadsheet; RU, US: Items based on household total income deciles and quartiles, namely in US: Less than $17,000; between $17,001 and $30,000; between $30,001 and $36,000; between $36,001 and $43,000; between $43,001 and $56,000; between $56,001 and $72,000; between $72,001 and $91,000; between $91,001 and $115,000; between $115,001 and $130,000;
between $130,001 and $150,000; between $150,001 and $213,000; More than $213,000; I prefer not to answer]

11. What is your highest completed education level? [education]
[Country-specific, usually: 0-1 Primary or less; 2 Medium school; 2 Some high school; 3 High school diploma; 3-4 Vocational training; 5 Short-cycle tertiary; 6 Bachelor's; 7-8 Master's or higher]

12. What is your employment status? [employment_status]
Full-time employed; Part-time employed; Self-employed; Unemployed (searching for a job); Student; Retired; Inactive (not searching for a job)

13. [Only the first digits asked in RU, SA] What is your zipcode?
We ask for the zipcode to balance the sample in terms of degree of urbanization (rural, town or city). The survey will be terminated if your zipcode is not recognized.
[zipcode]

14. Are you a homeowner or a tenant? (Multiple answers are possible) [home_owned]
Tenant; Owner; Landlord renting out property; Hosted free of charge

15. [new page] How likely are you to become a millionaire at some point in your life?
[Figure S64; millionaire]
Very unlikely; Unlikely; Likely; Very likely; I am already a millionaire

16. [Except in: RU, SA] Did you vote in the [election: 2024 presidential election]? [Figures S67-S66; voted]
Yes; No; Prefer not to say; I didn't have the right to vote in [country_name: the United States].

## Vote

17. [Only in: SA] What is your nationality?
If you have both the Saudi and a foreign nationality, choose "Saudi". [nationality_SA]
Saudi; India; Bangladesh; Syria; Yemen; Egypt; Pakistan; Indonesia; Philippines; Sudan; Myanmar; Jordan; Sri Lanka; Nepal; Turkey; Somalia; Lebanon; Other

18. [Except in: RU, SA] [If voted: Which candidate did you vote for in the [election: 2024 presidential election]?; Otherwise: Even if you did not vote in the [election: 2024]
presidential election], please indicate the candidate that you were most likely to have voted for or who represents your views more closely.] [Figures S67-S66; vote] [Candidates/parties with at least 1% of votes, e.g. in US: Harris; Trump; Other; Prefer not to say. In FR, IT, PL, ES, election is the 2024 European election]

## Open-ended field

[Four random branches; Section 3.1; Figures 3, S2-S7; Random answers can be found on bit.ly/fields2025; field, variant_field]

19. [Branch: concerns] What are your main concerns these days? [Figure S5; concerns_field]

20. [Branch: wish] What are your needs or wishes? [Figure S6; wish_field]

21. [Branch: injustice] What according to you is the greatest injustice of all? [Figure S7; injustice_field]

22. [Branch: issue] Can you name an issue that is important to you but is neglected in the public debate? [Figure S8; issue_field]

## Conjoint analysis

23. [Except in: RU, SA] Imagine if the two top candidates in your constituency in the next general election campaigned with the following policies in their party's platforms.

Which of these candidates would you vote for?

<table><thead><tr><th>Candidate A</th><th>Candidate B</th><th></th></tr></thead><tbody><tr><td>[Random policy]</td><td>[Random policy]</td><td>[Policy field in random order]</td></tr><tr><td>[Random policy]</td><td>[Random policy]</td><td>[Policy field in random order]</td></tr><tr><td>[Random policy]</td><td>[Random policy]</td><td>[Policy field in random order]</td></tr><tr><td>[Random policy]</td><td>[Random policy]</td><td>[Policy field in random order]</td></tr><tr><td>[Random policy]</td><td>[Random policy]</td><td>[Policy field in random order]</td></tr></tbody></table>

[Section 5.1; Figures 8, S9-S23; conjoint]
Candidate A; Candidate B; Neither of them
Revenue split of global tax

[Two random branches; field, variant_split]

24. [Branch: Few] Imagine a wealth tax applied to households with a net worth above [tax_threshold: $5 million], implemented in every country around the world.

[tax_country_name: In the U.S.], the tax revenues collected would be [tax_revenue: $514 billion] per year (that is, [tax_revenue_gdp: 2]% of [tax_country_gdp: U.S. GDP]), while it would be [LIC_revenue: $1 billion] in all low-income countries combined (700 million people live in a low-income country, most of them in Africa). Each country would retain part of the revenues it collects and use it for different domestic purposes. The remaining part would be pooled globally to finance sustainable development in low-income countries.

What percentage of the global wealth tax revenue should be allocated to each
category?

The total allocation must sum to 100%.

[Section 3.2; Figures 4, S25-S26; revenue_splitFew]

Domestic: Education and Healthcare; Domestic: Social welfare programs; Domestic: Reduction in the federal income tax; Domestic: Reduction of the deficit; Global: Education, Healthcare and Renewable energy in low-income countries

25. [Branch: Many] Imagine a wealth tax applied to households with net worth above [tax_threshold: $5 million], implemented in all countries around the world.

[tax_country_name: In the U.S.], the tax revenues collected would be [tax_revenue: $514 billion] per year (that is, [tax_revenue_gdp: 2]% of [tax_country_gdp: U.S. GDP]), while it would be [LIC_revenue: $1 billion] in all low-income countries combined (700 million people live in a low-income country, most of them in Africa). Each country would retain part of the revenues it collects and use it for different domestic purposes. The remaining part would be pooled globally to finance sustainable development.

What percentage of the global wealth tax revenue should be allocated to each
**category?**

The total allocation must sum to 100%.

[Section 3.2; Figures 4, S27-S28; revenue_split:many]

[Five items are chosen at random among the 13 possible ones: *Domestic: Education and Research*; *Domestic: Healthcare*; *Domestic: Defense*; *Domestic: Deficit reduction*; *Domestic: Justice and Police*; *Domestic: Retirement pensions*; *Domestic: Social welfare programs*; *Domestic: Infrastructure* (public transport, water systems...); *Domestic: Income tax reduction*; *Global: Education and Healthcare in low-income countries*; *Global: Renewable energy and infrastructure to cope with climate change*; *Global: Loss and Damage Fund* (to rebuild after climate disasters); *Global: Forestation and biodiversity projects*)]

**Warm glow – moral substitute**

*[Three random branches: NCS; Donation; control group; variant_warm_glow]*

26. [Branch: NCS] Do you agree with the following policy?

Climate Scheme:

To meet the national climate target, a limited number of permits to emit greenhouse gases would be issued nationally. Polluting firms would be required to buy permits to cover their greenhouse gas emissions. Such a policy would make fossil fuel companies pay for their emissions and gradually raise the price of fossil fuels. Higher prices would encourage people and companies to use less fossil fuels, reducing greenhouse gas emissions.

The revenues generated by the sale of permits would finance an equal cash transfer. Each [country_adjective: American] would receive [amount_expenses: $115]per month, thereby offsetting price increases for the average [country_adjective: American].

**Do you support the Climate Scheme?** [Section 4.1; Figures 6, S30; ncs_support]

Yes; No

27. [Branch: Donation] By taking this survey, you will be automatically entered into a lottery to win up to [amount lotteries: $100].

Should you be selected in the lottery, you will have the option to channel a part of this additional compensation to the charity *Just One Tree* to plant trees.
In case you win the lottery, what share of the [amount lottery: $100 prize] would you donate to plant trees? [Section 5.2; Figures 9a, S29; donation]

*Share to plant trees*

## Cap & Share

28. Do you support the following policy?

To ensure that you have attentively read the description, we will ask some comprehension questions later in the survey: those who get correct answers can win [amount lotteries: $100].

**Global Climate Scheme:**

In 2015, all countries agreed to contain global warming "well below +2 °C". To achieve this, there is a maximum amount of greenhouse gases we can emit globally.

To meet the climate target, a limited number of permits to emit greenhouse gases would be issued globally. Polluting firms would be required to buy permits to cover their greenhouse gas emissions. Such a policy would make fossil fuel companies pay for their emissions and gradually raise the price of fossil fuels. Higher prices would encourage people and companies to use less fossil fuels, reducing greenhouse gas emissions.

In accordance with the principle that each human has an equal right to pollute, the revenues generated by the sale of permits could finance a global basic income. Every adult would receive [amount bi: $20] per month, thereby lifting 600 million people who earn less than $2 a day out of extreme poverty.

The typical [national: American] would lose out financially [amount lost: $105] per month (as he or she would face around [price increase: 2]% in price increases, which is higher than the [amount bi: $20] per month they would receive).

The policy could be implemented as soon as 100 countries agree to it. Countries that would refuse to take part in the policy could face sanctions (like tariffs) from the rest of the world and would be excluded from the basic income program.
**Do you support the Global Climate Scheme?**
[Section 4.1; Figures 6, 9a, S30;
ICS Support]
Yes; No

[new page] [Two random branches: own; US; Figure S30; gcs-belief, variant-belief]

29. [Branch: US] According to you, what percentage of [belief_nationality: All but US: Americans; US: Europeans] would answer Yes to the previous question (considering that typical [belief_nationality] would lose [belief_loss: $140] per month from the Global Climate Scheme)?
The respondent who is closest to the correct value will get [amount lotteries: $100].
Percentage of [belief_nationality] in favor of Global Climate Scheme

30. [Branch: own] According to you, what percentage of [nationality: fellow citizens] would answer Yes to the previous question?
The respondent who is closest to the correct value will get [amount lotteries: $100].
Percentage of [nationality: fellow citizens] in favor of Global Climate Scheme

## Cap & Share non-universal

[Four random branches: low; mid; high; high_color; Section 4.1; Figures 6, S30; ics_support]

31. [Branch: low] Below is a map showing a possible set of countries that would participate in the Global Climate Scheme previously described.

These countries include India, the European Union, as well as all Africa, Latin America, South-Asia and South-East Asia.

Collectively, these [nb countries low: 145] countries account for [emissions low without: 40] % of global emissions (if [ics country: the U.S.] joined them, [emissions low with: 40] % of global emissions would be covered).

32. [Branch: mid] Below is a map showing a possible set of countries that would participate in the Global Climate Scheme previously described.
These countries include China, India, as well as all Africa, Latin America, South-Asia and South-East Asia.

Collectively, these 119 countries account for 56% of global emissions (if [ics_country: the U.S.] joined them, [emissionsapan: 70]% of global emissions would be cov-ered).

33. [Branch: high] Below is a map showing a possible set of countries that would par-
ticipate in the Global Climate Scheme previously described.

These countries include China, India, [text countries high: the European Union,
Japan, the United Kingdom], Canada, South Korea, as well as all Africa, Latin Amer-
ica, South-Asia and South-East Asia.

Collectively, these [nb countries high: 153] countries account for [emissions high without: 71]% of global emissions (if [ics_country: the U.S.] joined them, [emissions_high_with: 86]% of global emissions would be covered).

34. [Branch: high_color] Below is a map showing a possible set of countries that would participate in the Global Climate Scheme previously described.

These countries include China, India, [text countries high: the European Union,
Japan, the United Kingdom], Canada, South Korea, as well as all Africa, Latin Amer-
ica, South-Asia and South-East Asia.

Collectively, these [nb countries high: 153] countries account for [emissions_highWithout: 72]% of global emissions (if [ics_country: the U.S.] joined them, [emissions_high_with: 86]% of global emissions would be covered).

Note that a provision would prevent the Global Climate Scheme from harming low-
and middle-income countries: this is why countries like China, Mexico, or Egypt are
in white on the map (they would neither win nor lose financially).

35. Do you support [ics_country: the U.S.] joining the Global Climate Scheme, in case it
is adopted by the above countries? [Section 4.1; Figures 6, S30; ics_support]
Yes; No

Warm glow – realism

36. [Two random branches: with or without this informational text.] To ensure that you have attentively read the description below, we will ask some comprehension questions later in the survey: those who get correct answers can win $100.

In several international organizations, **countries have agreed to demonstrate some degree of solidarity in addressing global challenges.**

Negotiations are ongoing to implement specific mechanisms for sustainable development.

Here are a few examples:

In 2025, to reduce carbon emissions from shipping, **the International Maritime Organization adopted an international levy on excess emissions from maritime fuel, that should partly finance low-income countries.**

Since 1970, **developed countries have agreed to contribute 0.7% of their GDP in foreign aid** and development assistance.

In international climate negotiations, **developed countries have committed to finance climate action in developing countries.** In 2009, they committed to provide $100 billion per year by 2020. In 2023, all countries agreed to set up a fund to help vulnerable countries cope with loss and damage from climate change. In 2024, the $100 billion goal was increased to $300 billion per year by 2035.

In 2021, 136 countries adopted a minimum tax rate of 15% on multinational profits.

In 2024, under the leadership of Brazil, **the G20 considered the introduction of a global tax of 2% on the wealth of billionaires.**

In 2024, the UN General Assembly adopted the Pact for the Future, which foresees a reform of the UN Security Council to limit the power of its five permanent member and expand it to new members.

Led by the Prime Minister of Barbados and supported by the UN Secretary Gen-
eral, the Bridgetown initiative seeks a new financial system that would drive fi-
nancial resources towards climate action and sustainable development. [Section 5.2;
*Figure 9b*; *info_solidarity*]

37. According to you, how likely is it that international policies involving significant transfers from high-income countries to low-income countries will be introduced in the next 15 years? [Section 5.2; Figures 9b, S31; *likely_solidarity*]
*Very unlikely; Unlikely; Likely; Very likely*

38. Do you support or oppose the following policies?

[Only in PL, SA: (As some items refer to “developed countries”, note that we consider [Saudi Arabia] to be a developed country in this question.)] [Section 6.1; Figures 10, S32-S34; *solidarity_support*]
[Item order is randomized]

* Institutions like the World Bank investing in many more sustainable projects in lower-income countries, and offering lower interest rates (the Bridgetown initiative)

* Developed countries financing a fund to help vulnerable countries cope with loss and damage from climate change

* Expanding the UN Security Council (in charge of peacekeeping) to new permanent members such as India, Brazil, and the African Union, and restricting the use of the veto<fnref n="47" />

* Raising the globally agreed minimum tax rate on profits of multinational firms from 15% to 35%, closing loopholes and allocating revenues to countries where sales are made

* Debt relief for vulnerable countries by suspending repayments until they are better able to repay, promoting their development

* An international levy on carbon emissions from shipping, funding national budgets in proportion to population

* An international levy on carbon emissions from aviation, raising ticket prices by 30% and funding national budgets in proportion to population

<footnote n="47">⁴⁷In Russia, due to a mistake in the questionnaire, this item was not asked to the control group. Therefore, results are based on the treated group for this item in Russia.</footnote>
* Developed countries providing $300 billion a year (0.4% of their GDP) to finance climate action in developing countries

* Developed countries contributing at least 0.7% of their GDP in foreign aid and development assistance

* A minimum tax of 2% on the wealth of billionaires, in voluntary countries

*Strongly oppose; Somewhat oppose; Indifferent; Somewhat support; Strongly support*

NCQG

*[Two random branches: Full; Short; ncqg_fusion, variant_ncqg]*

39. [Branch: Full] At international climate negotiations, developing countries call for larger provision of "climate finance": the financing of climate action from developed countries in developing countries. [developed note: (Note that we consider Saudi Arabia to be a developed country in this question.)]

There are two kinds of climate finance: grants (that is, donations) and loans. In 2022, $26 billion was provided as grants and the rest as loans, for a total of $116 billion.

In 2009, developed countries agreed to mobilize $100 billion per year in climate finance by 2020. In 2024, they committed to raise this goal to $300 billion by 2035. None of the goals specify which share should be provided as grants.

Below are different positions on the amount of climate finance that should be provided in 2035, all expressed in grant-equivalent terms (that is, not counting loans):

- $0: There should be no contributions from developed countries to climate action in developing countries.

- $26 billion (0.04% of developed countries' GDP): The current amount, consistent with the old (2020) goal.

- $100 billion (0.14% of GDP): The old (2020) goal, if all climate finance were provided as grants.

- $300 billion (0.43% of GDP): The new (2035) goal, if all climate finance were provided as grants.
- $600 billion (0.86% of GDP): The goal called for by India, a position shared by most developing countries.

- $1,000 billion (1.43% of GDP): The goal called for by Climate Action Network (a network of NGOs including Greenpeace, Oxfam, and WWF).

- $5,000 billion (7.14% of GDP): The goal called for by Demand Climate Justice (a network of NGOs including 350.org and the World Council of Churches)

**If you could choose the amount of climate finance provided by developed countries to developing countries in 2035, what amount would you choose (in grant-equivalent terms)?**

[Section 6.1; Figure S36; ncqg_full]

[Item order is randomly reversed or not]

$0; $26 billion; $100 billion; $300 billion; $600 billion; $1,000 billion; $5,000 billion

40. [Branch: Short] "Climate finance" designates the financing of climate action from developed countries in developing countries. [developed note: (Note that we consider Saudi Arabia to be a developed country in this question.)]

**There are two kinds of climate finance: grants (that is, donations) and loans. The large majority is currently provided as loans.**

In 2009, developed countries agreed to mobilize $100 billion per year in climate finance. In 2024, they committed to triple this goal by 2035. None of the goals specify which share should be provided as grants.

At international climate negotiations, developing countries call for larger provision of climate finance, particularly in the form of grants.

**If you could choose the level of climate finance provided by developed countries to developing countries in 2035, what would you choose?**

[Section 6.1; Figure S35; ncqg]

[Item order is randomly flipped or not]

Stop all provision of climate finance.;

Reduce the provision of climate finance.;

Maintain current contributions ($26 billion per year in grants, that is 0.04% of developed countries' GDP, and $80 billion in loans, or 0.1% of GDP).;
Meet the newly agreed goal by tripling grants and loans ($100 billion in grants, or 0.15% of GDP).;

Increase climate finance to a level between what developed countries have agreed and what developing countries are asking for ($300 billion in grants, or 0.45% of GDP).;

Increase climate finance to match what developing countries are asking for ($600 billion in grants, or 0.9% of GDP).;

Increase climate finance to match what NGOs are asking for (at least $1,000 billion per year in grants, that is 1.4% of GDP, is what Greenpeace, Oxfam, WWF, and the World Council of Churches ask for).

Wealth tax depending on sets of countries

[Three random branches: Global; HIC; Int'l; Section 4.2; Figures 7, S37; wealth_tax_support]

41. [Branch: Global] Imagine an international tax on individuals with net worth above [wealth_threshold: $1 million].

Only wealth above [wealth_threshold: $1 million] would be taxed, at a rate of 2%. Each country would retain 70% of the revenues it collects, while 30% would be pooled at the global level to finance public services in low-income countries (in particular, access to drinking water, healthcare, and education in Africa).

Say we are in 2030. Imagine that all other countries in the world adopt this policy. Do you support [country_name: the United States] adopting this international tax on millionaires?

Yes; No

42. [Branch: HIC] Imagine an international tax on individuals with net worth above [wealth_threshold: $1 million].

Only wealth above [wealth_threshold: $1 million] would be taxed, at a rate of 2%. Each country would retain 70% of the revenues it collects, while 30% would be pooled at the global level to finance public services in low-income countries (in particular, access to drinking water, healthcare, and education in Africa).

Say we are in 2030. [hic_tax: Imagine that all other high-income countries (such as the European Union, Japan, and Canada) adopt this policy and some middle-income countries (such as China) do not.]
Do you support [country_name: the United States] adopting this international tax on millionaires?

Yes; No

43. [Branch: Int'l] Imagine an international tax on individuals with net worth above [wealth_threshold: $1 million].

Only wealth above [wealth_threshold: $1 million] would be taxed, at a rate of 2%. Each country would retain 70% of the revenues it collects, while 30% would be pooled at the global level to finance public services in low-income countries (in particular, access to drinking water, healthcare, and education in Africa).

Say we are in 2030. [intl_tax:<fnref n="48" /> Imagine that some countries (such as the European Union) adopt this policy and others (such as Japan, Canada, and China) do not.]

Do you support [country_name: the United States] adopting this international tax on millionaires?

Yes; No

## Scenarios & radical tax

[Scenario A & B are randomly interverted.]

44. Consider two possible scenarios for the world for the next 20 years.

### Scenario A:

Most countries implement coordinated policies to limit global warming to +2°C and reduce inequality. The world greatly reduces greenhouse gas emissions and is on track to meet its climate target. Taxes on millionaires fund the installation of heat pumps, the thermal insulation of buildings, and improved public transportation. Yachts and private jets are phased out worldwide. Cars are all electric by 2045, and they are about the same price as internal combustion cars nowadays. By 2045, environmental regulations gradually double the price heating fuel or gas, air travel, and beef. As a result, people fly half as much, eat half as much meat, and use more pub-

<footnote n="48">⁴⁸Excluded countries are China, Japan, and Canada. As for included countries, on top of Brazil, they are: the EU and the UK for Switzerland, Saudi Arabia, and the U.S.; the EU for Russia and the UK; and France, Germany, Spain, and the UK (except one's own country) for EU countries.</footnote>
lic transportation in 2045 than they did in 2025. Despite higher prices for polluting goods, the overall purchasing power is preserved, thanks to a decrease in sales tax that reduces the prices of non-polluting goods.

**Scenario B:**

Since 2025, no additional policies are implemented to address climate change or in-equality. People maintain the same lifestyles as in 2025. For example, most people continue to drive cars with internal combustion engines. Greenhouse gas emissions are stable. Global warming is expected to reach +3°C by 2100 and higher levels beyond that date. A warmer climate will cause more frequent and more severe droughts, heatwaves, wildfires, and floodings.

Apart from the elements described, the two scenarios are the same (for example, in terms of unemployment or crime).

**Which scenario do you prefer for the future?** [Section 6.2; Figures 11, S38; sustainable_future]

*Scenario A; Scenario B*

[new page] [Two random branches: top1; top3; Section 6.2; Figures 11, S39-S40; top_tax_support, variant_top_tax]

45. [Branch: top1] Currently, 2 billion people live in acute poverty, with less than [lcu_250: $250][periodicity: per month].

The Sustainable Development Goals, adopted by all countries in 2015, aim to alleviate poverty and give access to healthcare, education, drinking water, and sanitation for all by 2030. Due to lack of funding, the world is not on track to meet these poverty reduction goals.

**Poverty reduction could be funded by a global tax on individual income above**
**[lcu_120k: $120,000][periodicity_tax: per year].**

**The tax rate would be 15% for every [currency: dollar] over [lcu_120k: $120,000]**
**of income after existing taxes.**

For example, a single person earning [lcu_130k: $130,000][periodicity_tax: per year] after taxes would pay [lcu_1500: $1,500] in additional taxes, or 15% of [lcu_10k: $10,000] = [lcu_130k: $130,000] – [lcu_120k: $120,000]. Meanwhile, a married couple
earning [lcu_200k: $200,000][periodicity_tax: per year], [lcu_100k: $100,000] for each
of them, would go untaxed.

This tax would apply to the richest 1% of the world's population. [tax_country_name:
In the United States], it would affect the richest [affected_top1: 8]% and redistribute
[transfer_top1: 3]% of GDP to lower-income countries.

Do you support or oppose such a global tax on the richest people to finance global poverty reduction?

Strongly oppose; Somewhat support; Strongly support; Somewhat oppose; Indifferent

46. [Branch: top3] Currently, 3 billion people live in deep poverty, with less than [lcu_400: $400][periodicity: per month].

The Sustainable Development Goals, adopted by all countries in 2015, aim to al-
leviate poverty and achieve access to healthcare, education, drinking water, and
sanitation for all by 2030. Due to lack of funding, the world is not on track to meet
these poverty reduction goals.

Poverty reduction could be funded by a global tax on individual income above
[lcu_80k: $80,000][periodicity_tax: per year].

The tax rate would be 15% for every [currency: dollar] over [lcu_80k: $80,000] of
income after existing taxes, 30% over [lcu_120k: $120,000], and 45% over [lcu_1M:
$1 million].

For example, a single person earning [lcu_90k: $90,000][periodicity_tax: per year] af-
ter taxes would pay [lcu_1500_top3: $1,500] in additional taxes, or 15% of [lcu_10k_top3:
$10,000] = [lcu_90k: $90,000] - [lcu_80k: $80,000]. Meanwhile, a married couple
earning [lcu_150k: $150,000][periodicity_tax: per year], [lcu_75k: $75,000] for each of
them, would go untaxed.

This tax would apply to the richest 3% of the world's population. [tax_country_name:
In the United States], it would affect the richest [affected_top3: 18]% and redistribute
[transfer_top3: 8]% of GDP to lower-income countries.

Do you support or oppose such a global tax on the richest people to finance global poverty reduction?

[Section 6.2; Figures 11, S39-S40; top3_tax_support]
*Strongly oppose; Somewhat support; Strongly support; Somewhat oppose; Indifferent*

47. To show that you are attentive, please select "A little" in the following list: [attention_test]
*Not at all; A little; A lot; A great deal*

Preferred transfer means to LICs

48. Below are different ways to transfer resources to help reduce poverty in a low-income country.

How do you evaluate each of these options?

[Section 6.3; Figures 13, S42-S43; transfer_how] [Item order is randomly flipped or not]

* Transfers to public development aid agencies which then finance suitable projects

* Transfers to the national government conditioned on the use of funds for poverty reduction programs

* Unconditional transfers to the national government

* Unconditional transfers to local authorities (municipality, village chief...)

* Transfers to local NGOs with democratic decision-making processes

* Cash transfers to parents (child allowances), to the disabled and to the elderly

* Unconditional cash transfers to each household

*A wrong way; An acceptable way; A right way; The best way*

Radical redistribution

49. Should governments actively cooperate to have all countries converge in terms of GDP per capita by the end of the century? [Section 6.2; Figures 11, S44; convergence_support]
*Yes; No; I prefer not to answer*

50. If there was a worldwide movement in favor of a global program to tackle climate change, implement taxes on millionaires and fund poverty reduction in low-income countries, to what extent would you be willing to be part of that movement? (Multiple answers possible) [Section 6.2; Figures 11, S45; global_movement]

*I would not support such a movement.; I could sign a petition and spread ideas.; I could*
attend a demonstration.; I could go on strike.; I could donate [amount lottery: $100] to a strike fund.

51. [Except in: RU, SA] Let us call "your political party" the party you voted for in the last election, or the party that represents your views most closely.

**Imagine** there was a **worldwide coalition** of political parties in favor of a common program to tackle climate change, implement taxes on millionaires and fund poverty reduction in low-income countries.

**Would you be more likely to vote for your party if it were part of that coalition?**

[Section 6.2; Figures 11, S46; vote_intl_coalition] [Item order is randomly flipped or not]

Yes, I would be more likely to vote for my party if it joined that coalition (or to vote for another party if only that other party joined the coalition).;

My choice would **not depend** on which parties are part of that coalition.;

No, I would be less likely to vote for my party if it joined that coalition.

52. Some people think that high-income countries should support low-income countries.

Among the different reasons given, which ones do you agree with? (Multiple answers possible) [Section 6.2; Figure S47; why_hic_help_lic] [Order of the first three items is randomized]

High-income countries have a historical responsibility for the current situation in low-income countries.;

In the long run, it is in the interest of high-income countries to help low-income countries.;

Helping those in need is the right thing to do. This is also true at the international level.;

None of the above.

53. [Only in: FR, DE, IT, ES, GB, US] Some people argue that Western countries owe reparations for colonization and slavery to former colonies and descendants of slaves. Reparations could take the form of funding education and facilitating technology transfers, to address unequal opportunities passed down from the past.

**Do you support or oppose reparations of this kind for colonization and slavery?**

[Section 6.2; Figures 11, S48; reparations_support]

Strongly oppose; Somewhat oppose; Indifferent; Somewhat support; Strongly support
[Except in: RU] Custom redistribution

54. What is the [periodicity_text: yearly] income of your household after taxes and social benefits?

This includes all sources of income: salaries, pensions, allowances, welfare benefits, property income, etc.

My household earns ... [text_unit: $ per year] (answer with no comma, no space, no period):

[income_exact]

55. [new page] If you could redistribute income at the global level, what would you do? In this question, we let you choose your preferred parameters for a redistribution of income at the world level.

If you prefer to skip this question, check the corresponding box at the bottom of the page.

The worldwide redistribution of income would take the form of additional policies, taxes, and transfers, on top of existing ones.

These policies would lower the income of the richest (the losers from the redistribution) and increase the income of the poorest (the winners).

Below you will find a graph of the world distribution of after-tax income and three sliders that vary it. The current distribution is in red, and your custom one is in green.

The first two sliders control the proportion of winners and the proportion of losers, among all humans. The third slider controls the degree of redistribution from the richest to the poorest.

If you do not want new policies to reduce global inequality, you can set the third slider to zero.

**You need to move the sliders** (by holding the mouse down on the little squares and moving to the side) to make the green curve evolve: the idea is to move the sliders **until you get a green curve you are satisfied with**.
Examples of income changes after your proposed redistribution:

<table><thead><tr><th>Now</th><th>After</th></tr></thead><tbody><tr><td>0 [text_unit: $ per year]<br>[now_10k] [text_unit]<br>[now_60k] [text_unit]<br>[now_100k] [text_unit]</td><td>[after_0] [text_unit: $ per year]<br>[after_10k] [text_unit]<br>[after_60k] [text_unit]<br>[after_100k] [text_unit]</td></tr><tr><td colspan="2">Your individual income</td></tr><tr><td>[own] [text_unit]</td><td>[after_owned] [text_unit]</td></tr></tbody></table>

[Section 6.4; Figures 14, S50-S57] I am satisfied with my custom redistribution.;
I want to skip this question.

## Well-being (for another project)

[Four random branches: gallup_0; gallup_1; wvs_0; wvs_1; well_being, variant_well_being]

56. [Branch: gallup_0] Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you.

On which step of the ladder would you say you personally feel you stand at this time? [well_being_gallup_0]

Worst possible 0; 1; 2; 3; 4; 5; 6; 7; 8; 9; Best possible 10

57. [Branch: gallup_1] Please imagine a ladder, with steps numbered from 1 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you.

On which step of the ladder would you say you personally feel you stand at this time? [well_being_gallup_1]

Worst possible 1; 2; 3; 4; 5; 6; 7; 8; 9; Best possible 10

58. [Branch: wvs_0] All things considered, how satisfied are you with your life as a whole these days? [well_being_wvs_0]

Completely dissatisfied 0; 1; 2; 3; 4; 5; 6; 7; 8; 9; Completely satisfied 10
59. [Branch: wvs_1] All things considered, how satisfied are you with your life as a whole these days? [well_being_wvs_1]

Completely dissatisfied 1; 2; 3; 4; 5; 6; 7; 8; 9; Completely satisfied 10

Comprehension

60. Comprehension question: one respondent with the expected answer will get [amount lottery: $100].

How would gasoline prices change as a result of the Global Climate Scheme?
Gasoline prices would... [Figure S58; gcs_comprehension] [Item order is randomly flipped or not]

increase; not be affected; decrease

Synthetic questions

61. To what extent do you agree or disagree with the following statement? "My taxes should go towards solving global problems." [Section 6.2; Figures 11, S59-S60; my_tax_global_nati
Strongly agree; Agree; Neither agree nor disagree; Disagree; Strongly disagree

62. Which group of people do you advocate for when you vote?<sup>49</sup> [Section 6.2; Figures 12, S61; group_defended]

Sentient beings (humans and animals); Humans; [country adjective plural: Americans]; People from my community (for example my region, my religion, my gender...); My family and myself

Feedback

63. Do you feel that this survey was politically biased? [Figure S62; survey biased]
*Yes, left-wing biased; Yes, right-wing biased; No, I do not feel it was biased*

64. The survey is nearing completion. You can now enter any comments, thoughts, or suggestions in the field below. [Figure S63; Random answers can be found on bit.ly/fields2025; comment_field]

(Back to Section par:flow.)

<footnote n="49"><sup>49</sup>In Russia and Saudi Arabia, the question was worded as follows: "Which group do you advocate for? For example, if you were the richest person on Earth, which group would you predominantly help with your money?". In Russia, the item *Russians* had to be replaced with *My compatriots*.</footnote>
# C Survey Sources and Features

## C.1 Sources Regarding Plausible Global Policies

Table S1 provides references showing that the “plausible global policies” I test (Section 6.1) are (similar to proposals) debated in international negotiations.

<table><caption>Table S1: Proposals similar to the “plausible global policies” in international negotiations.</caption><thead><tr><td>Proposal</td><td>Appearance in international negotiations and source</td></tr></thead><tbody><tr><td>A minimum tax of 2% on the wealth of billionaires, in voluntary countries</td><td>Proposal by Zucman (2024) in a report commissioned by the Brazilian presidency of the G20.</td></tr><tr><td>Raising the globally agreed minimum tax rate on profits of multinational firms from 15% to 35%, closing loopholes and allocating revenues to countries where sales are made</td><td>In the context of OECD/G20 discussions to address Base Erosion and Profit Shifting (BEPS), a similar proposal has been proposed by the Independent Commission for the Reform of International Corporate Taxation (ICRICT 2020): taxing corporate income through formulary apportionment at a 25% rate.</td></tr><tr><td>Expanding the UN Security Council (in charge of peacekeeping) to new permanent members such as India, Brazil, and the African Union, and restricting the use of the veto</td><td>The Pact for the Future was adopted by the UN General Assembly. It includes “Action 39. We will reform the Security Council, recognizing the urgent need to make it more representative, inclusive, transparent, efficient, effective, democratic and accountable (...) we agree on the following guiding (...) Enlarge the Security Council (...) increase representation of developing countries (...) The question of the veto is a key element of Security Council reform. We will intensify efforts to reach an agreement on the future of the veto, including discussions on limiting its scope and use” (UN 2024).</td></tr><tr><td>Developed countries contributing at least 0.7% of their GDP in foreign aid and development assistance</td><td>This commitment has been made at the UN in 1971 and renewed ever since, e.g. in the SDG 17.2 (UN 2017; UNGA 1971). In 2024, developed countries contributed 0.33% of their GNI in Official Development Assistance (OECD 2025).</td></tr></tbody></table>
(continued)

Debt relief for vulnerable countries by suspending repayments until they are better able to repay, promoting their development

Institutions like the World Bank investing in many more sustainable projects in lower-income countries, and offering lower interest rates (the Bridgetown initiative)

Developed countries financing a fund to help vulnerable countries cope with loss and damage from climate change

Developed countries providing $300 billion a year (0.4% of their GDP) to finance climate action in developing countries

An international levy on carbon emissions from shipping, funding national budgets in proportion to population

An international levy on carbon emissions from aviation, raising ticket prices by 30% and funding national budgets in proportion to population

At the Financing for Development conference, all countries (except the U.S.) have “recognize[d] the need to assist developing countries in attaining long-term debt sustainability through coordinated policies aimed at fostering debt financing, debt relief, debt restructuring and sound debt management” (FfD4 2025).

The Bridgetown Initiative (2025) has been initiated by the government of Barbados and endorsed by the UN Secretary-General (UN 2023). It includes different proposals, including the rechanneling and new issuance of Special Drawing Rights to recapitalize Multilateral Development Banks.

The COP27 “decide[d] (...) to establish a fund for responding to loss and damage” (COP27 2022), to which $768 million have been pledged as of April 7, 2025.

COP29 adopted the NCQG and “decide[d] to set a goal, (...) with developed country Parties taking the lead, of at least USD 300 billion per year by 2035 for developing country Parties for climate action” (UNFCCC 2024).

The International Maritime Organization recently adopted a draft standard and feebate on carbon emissions from shipping (IMO 2025). While countries still have to agree on the allocation of the revenue, a group of countries including China and Brazil proposed to allocate 30% for developing countries; Norway proposed to let the Green Climate Fund manage the revenue; and Germany that the revenue be used to “strengthen the green transition, in particular in the SIDS and LDCs.”

While more narrow in scope, in 2025, a “new aviation solidarity coalition on premium flyers (first- and business-class tickets, and private jets) has been launched by France, Kenya, Barbados, Spain, Somalia, Benin, Sierra Leone and Antigua & Barbuda. It will be supported by the European Commission, and the Global Solidarity Levies Task Force (...) The coalition aims to improve domestic revenue mobilization of developing countries and support international solidarity.”
## C.2 Country-specific Features and Policies' Costs

In the survey, various features are tailored to country-specific characteristics. The workbook at github.com/bixiou/robustness_global_redistr/raw/main/questionnaire/sources.xlsx contains all such features as well as their sources. In particular, it includes the following spreadsheets:

* Quotas: targets for each category based on frequencies among the adult population, as well as their sources (namely official statistical agencies) and the definition of regions. The coding of regions and urbanicity is done in Qualtrics based on zip codes; with the zipcode correspondences exported in the repository folder data_ext/zipcode_urbanity_region using code in data_ext/code_robustness/zipcodes.

* Income, income_raw: brackets used in the income question (10), and associated sources and computations. I use household-level income Russia and the U.S.; equal-split income for Saudi Arabia; and equivalised income (i.e. standard of living, accounting for family composition) for other countries. Data sources are Eurostat for EU countries, Rosstat for Russia, WID for Saudi Arabia, Census Bureau for the U.S., and LIS for the other countries.

* Policies, policies.sources, policies.leaning, policies party, policies.leaning party: respectively the policies used in the conjoint experiment (Question 23), the source of each policy (i.e. the political program from which they come), their political leaning (classified manually as 0 if the policy is consistent only with a left-wing program, 2 for a right-wing one, and 1 otherwise), the party that proposed each policy, and their political leaning based on the party that proposed each policy.

* Elections: results at the last election (used in Questions 16-18) including abstention share among citizens, as well as classifications of the parties: whether they are major (i.e. obtained more than 5% of votes), and their political leaning (Left, Center-right or Right, Far right).

* Figures, features: country-specific figures used in the questionnaire, as detailed below.

Table S2 reports the figures used for each country for the National or Global Climate Scheme; the top income tax; and the revenue allocation of a wealth tax. Below, I detail the methodologies used for these and other questions.
<table><caption>Table S2: Country-specific features of the questionnaire.</caption><thead><tr><th>Question; Feature</th><th>FR</th><th>DE</th><th>IT</th><th>PL</th><th>ES</th><th>GB</th><th>CH</th><th>JP</th><th>RU</th><th>SA</th><th>US</th></tr></thead><tbody><tr><td>26 NCS amount_expenses (LCU/m.)</td><td>35</td><td>65</td><td>35</td><td>235</td><td>35</td><td>35</td><td>35</td><td>10k</td><td>5500</td><td>510</td><td>125</td></tr><tr><td>28 GCS net cost ($/month)</td><td>17</td><td>48</td><td>18</td><td>39</td><td>13</td><td>24</td><td>14</td><td>48</td><td>30</td><td>101</td><td>88</td></tr><tr><td>28 GCS amount_lost (LCU/month)</td><td>15</td><td>45</td><td>15</td><td>150</td><td>10</td><td>20</td><td>15</td><td>7000</td><td>2500</td><td>400</td><td>90</td></tr><tr><td>28 GCS amount_bi (LCU/month)</td><td>20</td><td>20</td><td>20</td><td>85</td><td>20</td><td>15</td><td>20</td><td>3500</td><td>3000</td><td>130</td><td>35</td></tr><tr><td>28 GCS price_increase (%)</td><td>1</td><td>2</td><td>1</td><td>2</td><td>1</td><td>1</td><td>1</td><td>2</td><td>2</td><td>3</td><td>2</td></tr><tr><td>10 Income type: net/gross</td><td>n</td><td>n</td><td>n</td><td>n</td><td>n</td><td>g</td><td>g</td><td>g</td><td>n</td><td>g</td><td>g</td></tr><tr><td>46 Income period: month/year</td><td>m</td><td>m</td><td>m</td><td>m</td><td>m</td><td>y</td><td>y</td><td>y</td><td>m</td><td>m</td><td>y</td></tr><tr><td>46 80k $PPP lcu_80k</td><td>5k</td><td>5k</td><td>4.5k</td><td>13k</td><td>4k</td><td>60k</td><td>85k</td><td>8M</td><td>200k</td><td>10k</td><td>80k</td></tr><tr><td>45 120k $PPP lcu_120k</td><td>7.5k</td><td>7.5k</td><td>7k</td><td>20k</td><td>6k</td><td>90k</td><td>130k</td><td>12M</td><td>300k</td><td>15k</td><td>120k</td></tr><tr><td>46 1M $PPP lcu_1M</td><td>60k</td><td>60k</td><td>60k</td><td>150k</td><td>50k</td><td>700k</td><td>1M</td><td>100M</td><td>2.5M</td><td>130k</td><td>1M</td></tr><tr><td>24 Wealth tax revenue ($ bn)</td><td>48</td><td>43</td><td>11</td><td>1</td><td>6</td><td>14</td><td>15</td><td>26</td><td>21</td><td>4</td><td>514</td></tr><tr><td>24 Wealth tax revenue (% GNI)</td><td>1.6</td><td>0.9</td><td>0.5</td><td>0.2</td><td>0.4</td><td>0.4</td><td>1.8</td><td>0.5</td><td>1</td><td>0.4</td><td>1.9</td></tr><tr><td>LCU per dollar (on Apr. 2, 2025)</td><td>.926</td><td>.926</td><td>.926</td><td>3.87</td><td>.926</td><td>.773</td><td>.9</td><td>149</td><td>84.3</td><td>3.75</td><td>1</td></tr></tbody></table>

**Climate Scheme.** In the Climate Schemes, I assume a carbon price of $95/tCO₂, corresponding to the price in 2025 for an emissions trajectory compatible with a global warming peaking at +1.8°C before 2100.<fnref n="50" /> After 2025, the decline in emissions is estimated to almost balance out the carbon price increase, in the sense that the GDP share of carbon pricing revenue would be roughly constant over the thirty years following the initial phase-in, before plummeting as net-zero approaches (Fabre 2024a). In other words, the cost of climate schemes provided to the respondents reflects the direct monetary costs expected from a carbon price aligned with the Paris Agreement.

In the National Climate Scheme, the average increase in expenditures is equal to the carbon price multiplied by the country's emissions per capita,<fnref n="51" /> and corresponds to the equal cash transfer each person would receive (Question 26). Relative to the country's GDP per capita, this translates into the price increase reported in the Global Climate Scheme (GCS). To compute the amount lost, i.e. the net cost of the GCS for the average person in the country (Question 28), I subtract the equal cash transfer from the increase in expenditures.

<footnote n="50">⁵⁰More precisely, I use the price trajectory of the integrated assessment model IMAGE in the scenario SSP2-2.6, as given by the IIASA.</footnote>

<footnote n="51">⁵¹I use territorial CO₂ emissions from non-LULUCF by country from Gütschow et al. (2021). I use the same source to estimate the emissions covered by the different scenarios in the International Climate Scheme.</footnote>
In case of a strictly equal per adult allocation of carbon price revenue, the global ba-
sic income would amount to $45 per month, corresponding to the world average emis-
sions multiplied by the carbon price. However, to prevent highly emitting middle-income
countries from losing financially, the GCS departs from the egalitarian allocation by of-
fering them a waiver from the mutualization of revenue, thereby lowering cash transfers
in other countries (Fabre 2024b). When the country coverage is *global*, as is implicitly the
case in questionnaires for Russia, Saudi Arabia, and the U.S., this results in a global ba-
sic income of $36 per month. In European countries and Japan, the cash transfer is even
lower, at $22 per month, since I implicitly assume a *high* country coverage (cf. Figure 5)
that excludes countries with the greatest emissions per capita. As I conservatively use low
figures for the cash transfer, the GCS question could somewhat underestimate acceptance
of a global, egalitarian cap-and-trade in high-income countries.

**Global Income Distribution.** To estimate the global income distribution, I use the dis-
tributions of disposable income by country in 2019 constructed by Fisher-Post & Gethin
(2023) (FPG).<fnref n="52" /> I inflate all generalized percentiles by real GDP growth observed between
2019 and 2024 (using IMF data), factor in country-specific inflation until 2022 and convert
values from LCU to 2022 PPP dollars (using FPG), and finally assume that all countries
experienced the same inflation as in the U.S. in 2023 and 2024 (using IMF data).

To aggregate country distributions, I compute the global cumulative distribution func-
tion and interpolate it at each thousandile. I obtain the global distribution of disposable
income at purchasing power parity (PPP) in 2024.

I use this distribution for the custom redistribution task, after converting back to LCU
(Section 6.4, Question 55). I also use it to calibrate the top income tax schedules so that
they raise an amount equivalent to the poverty gap (Section 6.2, Questions 45-46). Then,
I use country-level data to estimate the share of GDP collected as well as the share of the
population affected by each tax in each country. Finally, I compute the poverty gaps and
the tax revenue in every country in proportion to GDP, and aggregate them at the global
level after converting national disposable income back to market exchange rates (using
World Bank's PPP conversion factors for 2022). I find that the top 1% tax collects 1.8%
of global nominal income, while the top 3% tax collects 4.8% of global nominal income.
These amounts are higher than the respective poverty gaps: 1.3% of global nominal in-
come for a $250 per month poverty line, and 3.2% for a $400 per month poverty line.

<footnote n="52">⁵²The data is available on Amory Gethin's website.</footnote>
While the cost of poverty reduction declines relative to tax revenue once one accounts for market exchange rates, closing the poverty gap actually requires extra revenue due to imperfect targeting and administrative costs (Sahoo et al. 2025). Therefore, the tax schedule calibrations are consistent with the poverty reduction objectives.

**Wealth Tax Revenue.** To estimate the revenue from a global tax on wealth above $5 million at a rate of 2% (Section 3.2, Questions 24-25), I use the distribution of net wealth by country in current dollar for 2022 from the World Inequality Database. I assume that the taxable base is reduced by 30% due to tax avoidance and asset depreciation. I report expected tax revenue as a share of countries' 2023 GNI (from the World Bank). I also report the absolute revenue after converting them into LCU.

**Sustainable future; aviation levy.** I assume a carbon price of $300/tCO$_2$. Given natural gas footprint at .1807 tCO$_2$/MWh, this carbon price would double a gas price of $54/MWh, which is a midpoint between U.S. and European prices. Similarly, the prices of beef and flights would double, assuming that beef costs $10/kg and emits 33 kgCO$_2$/kg, and aviation emits 3 kgCO$_2$/e per dollar of flight. A 30% increase in flight prices corresponds to a carbon price of $100/tCO$_2$, or to a $300/t levy which does not account for the warming effect of contrails (Lee et al. 2021).

**NCQG.** The sources used for the New Collective Quantified goal of climate finance for 2035 (Section 6.1, Questions 39-40) are the following: UNFCCC (2024) states the goal itself, OECD (2024) provides figures on past achievements, Earth Negotiations Bulletin (2024) reports the positions of India and other countries, and Climate Action Network (2024); Demand Climate Justice (2025) those of NGOs. Note that the question wordings do not mention the gap between climate finance needs and the official goal identified in official reports (OECD 2024; Songwe et al. 2024), nor that existing plans by Multilateral Development Banks (MDBs) to ramp up climate finance would achieve most of the new goal (MDBs 2024).<fnref n="53" />

<footnote n="53">⁵³According to the OECD (2024), MDBs contributed $81 billion to climate finance in 2022 (both directly through finance provision and indirectly through mobilization of the private sector), with 71% (or $58 billion) attributable to developed countries. Before the NCQG was agreed at COP29, they jointly stated that they will contribute an estimated $185 billion in 2030 (including $65 billion from the private sector). Assuming that this increase of $104 billion is replicated in the period 2030-2035, MDBs would contribute $289 billion in 2035, including $205 attributable to developed countries, that is $147 billion more than in 2022. As (multilateral plus unilateral) developed countries' climate finance totaled $116 billion in 2024,</footnote>
To express the NCQG as a share of developed countries' GDP, I use 2024 data from the World Bank on nominal GDP in high-income countries. This figure —of $70 trillion— is conservative, since it does not account for growth or inflation until 2035.

### C.3 Definition of Keywords

Below are the keywords used to classify the open-ended fields on top-of-mind considerations (Figure S2, Section 3.1, Questions 19-22). The keyword search uses the R function grep1 and ignores case. The special character ^ indicates the start of the string and $ the end.

(Back to Section 3.1.)

* **Money; own income; cost of living; inflation:** money|inflation|price|wage|wealth|income|salar|finance|cost|financial|afford|illionaire|expensive;

* **Relationships; love; emotions:** relationship|husband|wife|love|partner|emotion;

* **Work; (un)employment; business:** business|work|employ|job;

* **Poverty; inequality:** poverty|inequalit|poor|social justice;

* **Global poverty; hunger; global inequality:** global poverty|global inequal|hunger|drinking water|starv;

* **Health; healthcare system:** health|sick|disease|NHS|medica;

* **Criticism of immigration; national preference:** migration|migrant|asylum|refugee|alien;

* **Corruption; criticism of the government:** corruption;

* **Environment; climate change:** environment|climat|pollution|warming|drought;

* **Security; violence; crime; judicial system:** safe|murder|crime|criminal|fraud|rape|terrorism;

* **Discrimination; gender inequality; racism; LGBT:** gender|raci|scrimination|women|xenophob|LGB|machism|antisemit;

<footnote>adding the $147 billion expected in their multilateral finance would achieve three-quarter of the required increase, at $263 billion.</footnote>
* **Rights; democracy; freedom; slavery:** freedom|rights|democracy|dictator;

* **Happiness; peace of mind:** happiness|happy|serenity|peace of mind|tranquility
|inner peace|relax;

* **War; peace:** peace|war|WW;

* **Tax system; welfare benefits; public services:** tax|social benefit|social security;

* **Criticism of far right; Trump; tariffs:** Trump|AfD|populist|far right|radical
right|extreme right|tariff| PiS |fascism;

* **Social division; fake news; (social) media:** social division|social cohesion
|media|fake news;

* **Animal welfare:** animal;

* **Religion; sin; God:** religion| god|self injustice|self-injustice|theism|disbelief;

* **Housing:** hous|apartment|real estate|mortgage;

* **Education:** education|school|exam|universit;

* **Old age; retirement; ageing society:** old age|pension|retire| aging| ageing;

* **Family; children; childcare:** family|child|daughter| son|parent|mother|father
|loved ones|kids;

* **International issues:** world|humanity|foreign|countries|Ukraine|Gaza|Palestin
|Hamas|Israel|Yemen|Sudan|middle east|Iran|geopol;

* **Own country referred:** country|German|Saudi|France|French|Ital|Poland|Polish
|Spain|Spanish| UK|U.K.|Great Britain|England|British|Japan|Russia|America
|U.S.| USA|United States;

* **Nothing; don't know; empty:** ^nothing$|^no$|^.$|^~$|^^do not have$|^^nothing
in particular$|^^None$|^^I don't know$|^^I would not know$;

* **Economy:** econom|growth;

* **Media:** internet|media;
• Trump: Trump;

• Tariffs: tariff|customs dut|custom dut;

• Palestine: Palestine|Gaza;

• Car: car;

• Mental health: mental | mental health;

• Sport: sport|soccer;

• Holiday; travel: travel|vacation|holiday| rest;

• Time; more free time: time|leisure;

• Politics: politic;

• Millionaire; billionaire: illionaire;

• Inflation; cost of living: inflation|rising price|cost of living;

• Abortion: abort;

• Stock; investment: investment|asset|stock;

• Birthrate: birth rate|birthrate;

• Government; president: government|president|PSOE|Sanchez|Sánchez|Liberal
Democratic Party|LDP|Komeito|Tusk|Nawrocki|PO|Macron|Trump|Meloni|Starmer
|Labour;

• Hunger: hunger;

• Stability: stability|stabl;

• Wage: wage|salar;

• Youth: young|youth.

(Back to Section 3.1.)