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Policy Misperceptions, Information, and the Demand for Redistributive Tax Reform: Experimental Evidence from Latin American Countries

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Abstract

Why do individuals' preferences for redistribution often diverge widely from their material self-interest? Using an original online survey experiment spanning eight countries and 12,000 respondents across Latin America, one of the most unequal regions in the world, we find significant evidence for an under-explored explanation: misconceptions regarding the distributional effects of current tax policy. Treated respondents who are informed that an increase in the value added tax (VAT) is regressive are significantly more likely to prefer policy reforms that make the tax more progressive. Treatment effects are driven by the large fraction of respondents who underestimate the regressivity of the VAT, even though their misperceptions are linked to fundamental views about the world. These respondents are disproportionately right-leaning and more likely to attribute success to individual effort than luck. Despite the deep-rooted nature of respondents'misperceptions, treatment effects are largest among individuals who hold these views of the world. These findings contribute both to understanding the political economy of redistribution and the potential for information interventions to shift support for fiscal adjustment policies protecting the most vulnerable.
IDB WORKING PAPER SERIES Nº IDB-WP-1385
Policy Misperceptions,
Information, and the Demand for
Redistributive Tax Reform:
Experimental Evidence from
Latin American Countries
Martin Ardanaz
Evelyne Hübscher
Philip Keefer
Thomas Sattler
Inter-American Development Bank
Institutions for Development Sector
Fiscal Managment Division
December 2022
December 2022
Policy Misperceptions,
Information, and the Demand for
Redistributive Tax Reform:
Experimental Evidence from
Latin American Countries
Martin Ardanaz (Inter-American Development Bank)
Evelyne Hübscher (Central European University)
Philip Keefer (Inter-American Development Bank)
Thomas Sattler (University of Geneva)
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Policy misperceptions, information, and the demand for redistributive tax reform: experimental evidence from Latin
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Includes bibliographic references.
1. Tax auditing-Latin America. 2. Value-added tax-Latin America. 3. Fiscal policy-Latin America.
4. Taxation-Latin America. 5. Income distribution-Latin America. 6. Economic surveys-Latin America.
I. Ardanaz, Martin. II. Hübscher, Evelyne, 1975- III. Keefer, Philip. IV. Sattler, Thomas. V. Inter-American
Development Bank. Fiscal Management Division. VI. Series.
IDB-WP-1385
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Copyright © 2022
Policy Misperceptions, Information, and the Demand for
Redistributive Tax Reform: Experimental Evidence
from Latin American Countries
Martin Ardanaz (Inter-American Development Bank)
Evelyne ubscher (Central European University)
Philip Keefer (Inter-American Development Bank)
Thomas Sattler (University of Geneva)
Abstract
Why do individuals’ preferences for redistribution often diverge widely from their
material self-interest? Using an original online survey experiment spanning eight coun-
tries and 12,000 respondents across Latin America, one of the most unequal regions
in the world, we find significant evidence for an under-explored explanation: miscon-
ceptions regarding the distributional effects of current tax policy. Treated respondents
who are informed that an increase in the value added tax (VAT) is regressive are sig-
nificantly more likely to prefer policy reforms that make the tax more progressive.
Treatment effects are driven by the large fraction of respondents who underestimate
the regressivity of the VAT, even though their misperceptions are linked to fundamen-
tal views about the world. These respondents are disproportionately right-leaning and
more likely to attribute success to individual effort than luck. Despite the deep-rooted
nature of respondents’misperceptions, treatment effects are largest among individuals
who hold these views of the world. These findings contribute both to understanding
the political economy of redistribution and the potential for information interventions
to shift support for fiscal adjustment policies protecting the most vulnerable.
JEL Classification: D72, D90, H20, H30
Keywords: taxes, redistribution, survey experiment
Ardanaz and Keefer: Inter-American Development Bank, martina@iadb.org and pkeefer@iadb.org.
ubscher: Central European University, huebschere@ceu.org. Sattler: University of Geneva,
thomas.sattler@unige.ch. This research significantly benefited from the comments of Per Andersson,
Guillermo Cruces, and Ricardo Perez Truglia. We are extremely grateful to LAPOP for its administra-
tion of the survey and, particularly, to Oscar Castorena. We are indebted to the extraordinary research
assistance of Miguel Purroy. The findings and interpretations in this paper are those of the authors and do
not necessarily reflect the views of the Inter-American Development Bank or the governments it represents.
1
1 Introduction
A large literature seeks to understand why individuals’ support for redistributive tax policies
often diverges from their material self-interest. Previous research examines this puzzle in the
United States and other advanced economies, but it is at least as profound in other regions,
such as Latin America, where the challenge of inequality looms large. Two prominent lines of
inquiry focus on voter ignorance regarding their place in the income distribution and the ex-
tent of inequality in society (see especially Stantcheva (2021) for the most recent advances).
Slemrod (2006) though, observed that individuals also have significant misconceptions re-
garding the incidence of current tax policies and asks whether these misconceptions have a
causal effect on preferences for progressive tax reform. Are individuals who incorrectly be-
lieve that a tax is progressive less supportive of reforms to make the tax more progressive? Is
information about the distributional impact of tax policy effective at shifting citizen support
for progressive reforms? We address these questions with experimental data from an original
online survey spanning eight countries and 12,000 respondents across Latin America.
The analysis addresses two gaps in understanding of the cognitive processes that shape
voter support for economic policy reforms. One concerns the informational obstacles that
voters must surmount before they are willing to support a specific policy reform. The other
relates to the sources of policy misperceptions and how they can be corrected. Voter support
for a specific policy reform, such as one to make the tax code more progressive, depends on
whether they have sufficient information to convince them that a problem exists, but also
to convince them that a specific policy reform will solve the problem and make them better
off. Their support for a specific solution should therefore depend on their beliefs about
its effectiveness, even if they are fully convinced of the problem and the need for a policy
response of some kind.1
1For example, if they believe that tax rates on the richest are already high, they are more likely to believe
that the redistributive benefits of more progressive rates are outweighed by other negative effects that they
might associate with higher tax rates. Moreover, individuals, experts and non-experts alike, may struggle to
draw conclusions about the effects of large and unusual changes in public policy on the income distribution.
They are likely to be more certain estimating the effects of more incremental and common policy shifts.
2
Previous research demonstrates that individuals often underestimate the magnitude of
inequality and that this affects their support for redistributive reforms in general. For ex-
ample, Stantcheva (2021) and Kuziemko et al. (2015) demonstrate with evidence from the
United States that when individuals are made aware of the problem with information about
inequality in society and of their own position on the income distribution, they are signif-
icantly more likely to support greater redistribution in general. However, this same infor-
mation has smaller and more ambiguous effects on their support for specific progressive tax
reforms.
We resolve this ambiguity by providing individuals with information that is relevant
to their evaluation of the effectiveness of a specific reform to make the value added tax
(VAT) more redistributive, by describing the incidence of the current VAT. Individuals who
receive information about the regressivity of the current VAT are far more likely to support
progressive tax reform that exempts poorer deciles from paying the VAT. The magnitude
of the effect is similar to that uncovered by Kuziemko et al. (2015) when looking at the
shift in support for greater redistribution in general among those who are informed that
inequality is a significant problem. Treatment effects are driven by individuals who have
misconceptions about the incidence of the VAT that lead them to believe that the VAT is
already progressive, or that make them uncertain about the incidence of the VAT.
The other gap in understanding cognitive processes relates to the sources of policy misper-
ceptions. Misconceptions can be rooted in factual knowledge gaps, but also in ideology-driven
beliefs about the way the world operates. Prior research suggests that misconceptions that
are rooted in ideology may be difficult to shift with simple information treatments (Luttmer
and Singhal, 2011). However, not all ideological beliefs are equally deeply held and it may
be that some, which turn out to be important for public policy preferences, are more sus-
ceptible to revision when new information is presented. In fact, our evidence on mechanisms
indicates that policy misconceptions among respondents seem to be tied more strongly to
ideologically rooted beliefs than to gaps in factual knowledge. Nevertheless, a relatively
3
simple information intervention has a significantly stronger effect on the policy preferences
of these respondents.
In the experiment, respondents are asked to elicit preferences over three possible reforms
to the VAT: one that exempts no poor households from the tax increase, one that exempts
the poorest 30 percent of households and asks the remaining households to pay more, or
one that exempts the poorest 50 percent of households, raising taxes even more on the
remaining households. These options are carefully constructed to hold constant the amount
of tax revenue that each option collects. Treated respondents receive accurate information
about how much more poorer households in the region pay as a share of their income in VAT
payments compared to richer households.
The data also permit us to analyze mechanisms in detail. We identify which respondents
have misconceptions about the incidence of the VAT (that is, those who incorrectly believe it
is progressive). We can also identify the characteristics of respondents who believe that the
VAT is flat or progressive and of those who believe it is regressive. Their main distinguishing
features are linked to their views about the world, reflected in their political ideology and
other beliefs. For example, right-leaning respondents are more likely to hold the incorrect
belief that richer households devote the same or a larger share of their income than the poor
to VAT payments.
The experiment yields three main results. First, learning about the regressivity of current
tax policy has a large impact on support for progressive tax reform. Second, treatment
effects are much stronger among those who incorrectly perceive the progressivity of current
tax policy. Third, policy misperceptions are greatest among those who categorize themselves
as right-leaning; treatment effects are significantly stronger among this group.
These results add to the findings of a rich literature examining preferences for redistri-
bution. Stantcheva (2021) find that informing individuals about the severity of inequality in
society increases support for redistributive tax reforms in general.2Kuziemko et al. (2015)
2Fehr, Mollerstrom and Perez-Truglia (2022) report results from a two-year survey experiment in Ger-
many that correcting respondents systematic under-estimation of their true place in the world’s income
4
examine a multi-dimensional information treatment that, among other things, informs re-
spondents about their income relative to others.3Though the treatments have a statistically
and economically large effect on preferences for redistribution in general, their impact on
preferences for specific progressive tax reforms is substantively small, about one-tenth of
the difference between the preferences of liberal and conservative respondents.4Our treat-
ment, information on the incidence of the current VAT, has as large an effect on respondent
preferences for a specific progressive tax reform as the effects that Stantcheva (2021) and
Kuziemko et al. (2015) estimate when examining the effects of information about inequality
on preferences for redistribution in general.5
Both Bartels (2005) and Slemrod (2006) observed widespread misconceptions regarding
the progressivity of specific tax policies in the United States. Slemrod (2006) analyzes data
from a large survey of Americans and finds that many believed that a new sales or flat tax
would be more progressive than the current income tax and those who held this belief were
significantly more likely to support the sales/flat tax alternatives. Slemrod (2006) closes
with a question for future research to which we respond: whether these misconceptions are
distribution does not affect support for policies related to global inequality.
3Their work builds on earlier contributions. For example, in Cruces, Perez Truglia and Tetaz (2013) and
Fernandez-Albertos and Kuo (2018), individuals who are told that their relative income is lower than they
believed demand more redistribution. Similarly, in Karadja, Mollerstrom and Seim (2017) individuals who
learn they are richer relative to others demand less redistribution. In contrast to these findings, Hoy and
Mager (2021) examine data from a survey experiment involving 10,000 participants in ten middle and upper-
income countries and conclude that informing individuals that their position in the income distribution is
lower than they thought does not increase support for redistribution.
431.1 percent of treated respondents, versus 30.21 control respondents prefer higher tax rates on the
richest 1 percent; 79 percent of treated respondents, versus 74 percent of control respondents, prefer higher
tax rates on millionaires.
5In contrast to our findings, Douenne and Fabre (2022) find that respondents do not change their
perceptions of the progressivity of a carbon tax policy when told “this reform would increase the purchasing
power of the poorest households and decrease that of the richest”. We attribute the difference to greater
familiarity with the VAT, the complexity surrounding the incidence of a carbon tax, and the fact that our
information treatment, though substantially lighter than others in the literature, is more detailed and entails
more comprehension checks than their treatment. Numerous studies find strong effects of similar information
treatments on estate taxes, which evidently do not generalize to other taxes with broader incidence. Bastani
and Waldenstrom (2021) find that information about the aggregate importance of inherited wealth and its
implications for the inequality opportunity in Sweden leads to a significant increase in support for estate
taxation among Swedish respondents. Kuziemko et al. (2015) and Sides (2016) also find a dramatic effect
of their information treatment on preferences for a higher estate tax. In Kuziemko et al. (2015), more than
50 percent of treated respondents prefer it compared to 17 percent of control respondents. We focus on a
different and fiscally more important tax with much broader incidence than the estate tax.
5
causally related to tax policy preferences.6
To capture redistributive policy preferences, Alesina, Miano and Stantcheva (2022) and
Alesina, Stantcheva and Teso (2018) ask subjects to manipulate income tax rates paid by
each quintile, holding total income tax revenues constant, allowing the subjects to observe
how their manipulation would change each quintile’s actual after-tax income. We follow their
practice of holding total tax revenues constant. Also holding constant total tax revenues,
de Bresser and Knoef (2022) find that on average, respondents prefer a more redistributive
tax system, giving rise to the same conjecture advanced by Slemrod (2006), that knowledge
of the incidence of the current tax system increases support for redistributive tax reform.
We experimentally evaluate this conjecture.7
Our analysis also contributes to research investigating the effects of information on bias
in individual tax preferences. Sausgruber and Tyran (2011) examine the tax-shifting biases
of individuals - their preference that sellers rather than buyers pay taxes. Tax-shifting bias
is unrelated to the distributional issues of concern here, but their treatment is similar. They
inform individuals about the effects of the two types of taxes on market prices and incomes
and show that this information reduces tax-shifting bias. We find that information about
the true incidence of the VAT also shifts preferences regarding redistributive tax reform.
Other research specifically explores bias against redistributive tax reform, focusing es-
pecially on ideologically induced bias. A repeated finding is that information predicted to
increase support for redistribution has larger treatment effects among right-leaning respon-
dents.8We are able to investigate the mechanisms behind this relationship. Specifically, we
6He also notes that sales and flat taxes could, in principle, be designed in such a way as to make them
more progressive. Respondents to our survey are given unambiguous information about the progressivity of
different tax options.
7Hoy (2022) also exploits experimental evidence from Latin America to document widespread misper-
ceptions of progressivity of fiscal policy and that information about the actual progressivity (regressivity) of
fiscal policy in respondents’ countries increases (decreases) their willingness to pay taxes.
8Boudreau and MacKenzie (2018) inform Californian survey respondents about the true level of inequal-
ity in the state and then elicit their preferences for an increase in the (progressive) state income tax or the
(regressive) state sales tax. Among Republicans, this information significantly raises support for the pro-
gressive reform, an increase in the income tax rates for high earners; it has no effect on Democrats. Among
Democrats, the information reduces support for a regressive increase in the sales tax; it has no effect on
Republican support for a sales tax increase. Results in Karadja, Mollerstrom and Seim (2017) are similarly
6
can show that treatment effects are strongest among those who misperceive the incidence
of the VAT, and right-leaning respondents are among those who are most likely to have
incorrect perceptions.
Finally, the experimental design incorporates common features of the policy environment.
In particular, respondents are asked to assess the VAT reform options in the context of a
government that confronts the need for a large fiscal adjustment and resorts to the VAT to
extricate itself. The analysis therefore contributes to the literature on the political economy
of fiscal adjustments. Alesina et al. (2021) account for the strategic choices that govern-
ments make to reduce the electoral costs of austerity (see ubscher and Sattler (2017)).
They conclude that tax-based austerity measures have large electoral costs that are signifi-
cantly greater than spending-based measures. Consistent with this, Ardanaz, Hallerberg and
Scartascini (2020) show fiscal adjustments in Latin America and the Caribbean are mostly
tax-based and rely fundamentally on increasing the tax rates and the bases of indirect taxes
such as the VAT.9Our survey results indicate that efforts to make VAT adjustments more
progressive might soften the negative electoral impact that previous studies document.
The remainder of the paper is organized as follows. Section 2 introduces the experiment’s
policy environment and stylized facts regarding the VAT in Latin America. Section 3 presents
the survey experiment in more detail and associated data. Section 4 describes the empirical
strategy and Section 5 reports the main results and robustness tests. Section 6 provides
insights on the transmission mechanisms driving the results. Section 7 concludes.
driven by respondents who are more right-wing and believe more strongly that economic success is a product
of effort rather than luck. Sides (2016) also demonstrates that treatment effects on support for a higher
inheritance tax are strongest among right-leaning respondents.
9In a survey of five European countries, ubscher, Sattler and Wagner (2021) also find that tax increases
reduce government popularity, but less than spending cuts.
7
2 Value Added Taxes in Latin America
Two features of the VAT make it particularly relevant for this study. First, it is a key feature
of tax policy in Latin America and a common tool that governments use to respond to fiscal
crises. Hence, fiscal crisis frames the three reform options that the respondents consider:
“How should governments raise tax revenues in response to a fiscal crisis?” In addition,
significant technical advances allow for countries of the region to develop a “personalized
VAT” one that allows poor households to be exempted from VAT payments or to have those
payments be refunded to them. Hence, the three policy options that we describe, exempting
different deciles of poor households, are not foreign to the survey respondents.
The VAT is the single most important source of revenue for Latin American governments
and is highly salient for households.10 Because of its ease of implementation it is also a
favored instrument for fiscal adjustment, despite widespread agreement among experts that
it is regressive.11 Indeed, the incremental upward adjustments of the VAT in response to
repeated crises is one factor that contributes to the limited redistributive effect of fiscal
policy and persistent inequality in the region (Lustig, Pessino and Scott, 2014).
Survey respondents could be confused by the vignettes, or not take them seriously, if
they believed that exempting VAT households from the VAT was impossible or impractical.
However, the region has made substantial progress towards a personalized or compensated
VAT, aimed precisely at making the VAT more progressive. Though the details vary from
country to country, Argentina, Ecuador and Bolivia all return VAT payments to certain poor
households that have made purchases using debit cards issued to them by the government.
Uruguay goes further and exempts poor households from paying the VAT if they use the
10VAT taxes account for about a third of total revenue collection in a typical Latin American country,
and its contribution to the overall tax take is three times as large as that of the personal income tax.
11When individuals are ranked according to their current per capita income, VAT is regressive since the
poor save less than the rich. However, when a lifecycle or intertemporal criterion is used to measure welfare,
the VAT tends to be proportional (Metcalf, 1994; Gasparini, 1998). Informality generally makes the VAT less
regressive: lower-income families are more likely to make part purchases in informal businesses at lower prices
than those of larger and more formal businesses (for example, supermarkets) (Bachas, Gadenne and Jensen,
2021). However even the attenuating effect of informality on VAT regressivity depends on assumptions about
the pass-through of taxes to informal sector prices.
8
government debit card that they have been issued. Colombia’s VAT compensation scheme
currently reaches around two million poor households and benefits are delivered through the
financial system, largely based on previously existing infrastructure for the payment of other
social programs.12
3 Survey Experiment
To explore respondent attitudes towards a more progressive VAT, in March 2022 we con-
ducted an online survey in eight countries in Latin America: Argentina, Brazil, Chile, Colom-
bia, Costa Rica, Guatemala, Mexico, and Peru. In each country, we collected the answers of
1,500 respondents for a total of 12,000 responses. The survey was administered by the Latin
American Public Opinion Project (LAPOP), which, in turn, uses a standing online panel
from two different survey providers (Netquest and Offerwise).13
The survey is divided into three sections. Respondents first answer questions about
their nationality, gender, age, region, confidence and trust, views on the tax administration,
knowledge about who decides tax policy, political participation and alignment, time prefer-
ences, risk preferences, and perceptions of their location in the income distribution. In the
third section, respondents answer questions about their education, occupation, income and
the characteristics of their household.
The second, main part of the survey elicits information about their preferences regarding
three possible tax reforms, which vary in their degree of progressivity. In addition, treated
respondents receive information about the incidence of the VAT. Respondents are from
different countries but all receive the same reform options and treated respondents receive the
same information about incidence. This reinforces the experimental design. To ensure that
the options and incidence information are plausible and realistic, we base them on aggregate
data from household consumption surveys from across the different countries. Necessarily,
12See Barreix et al. (2022) and Rastelleti (2021) for further discussion.
13The survey was pre-registered at https://osf.io/wd6tb.
9
they more closely reflect the tax parameters of some countries than others. However, our
estimates control for country fixed effects. We further report in the robustness section that
treatment effects vary little across countries.
3.1 Tax policy reform preferences
Respondents are shown three policy options for raising tax revenues in response to a fiscal
crisis. Governments can raise the VAT rate for all households; they can exempt the bottom
30 percent of households from the increase and impose a higher percentage point increase on
the top 70 percent; or they can exempt the bottom 50 percent and impose an even higher
increase on the upper 50 percent.
Two key parameters vary across the reform options: the amounts by which tax rates will
increase, and the fraction of the population that is exempted from the increased tax rates.
We set these parameters to ensure that all reform options increase total VAT collection by
the same amount. We do this using estimates from household expenditure survey data of
VAT payments across the income distribution. 14
The baseline adjustment option raises the standard VAT rate by one percentage point
for all households, enough to finance a 4 percent increase in total VAT revenues.15 This is
the All Pay option. The Top 70% Pay option redistributes to the poorest 30 percent. The
tax rate therefore rises by more than one percentage point on the 70% who pay, such that
their VAT payments rise by 5 percent, ensuring that the VAT reform still yields an increase
of 4% in VAT revenues for the government. The Top 50% Pay option exempts the poorest
50 percent of voters from paying the higher VAT. The tax rate rises by more than in the Top
70% Pay option and the 50% of households who pay it therefore see a 6 percent increase
in their VAT payments, enough to yield a 4 percent net increase in VAT payments to the
14The potential impact of fiscal adjustment itself on income inequality is ambiguous and not mentioned
to respondents. Potential heterogeneity in respondent beliefs about this should not introduce bias into the
experiment since the adjustment is identical across all options.
15For example, if the VAT rate goes from 24 to 25 percent, household payments rise by an average of four
percent.
10
government. These trade-offs are made clear to respondents.
The three policy options are therefore:
Option 1 - All pay: 4% increase in VAT payments, no exemptions.
Option 2 - Top 70% pay: 5% increase in VAT payments by top 70%, poorest 30% are
exempted.
Option 3 - Top 50% pay: 6% increase in VAT payments by top 50%, poorest 50% are
exempted.
We calculate the incidence of the current VAT and the key parameters of the three
VAT reform options using micro-data taken from household consumption surveys in ten
Latin American countries, based on IDB (2022).16 For households in each income decile,
the survey data allow us to compute both the VAT that the households pay and household
income, yielding VAT payments as a fraction of household income. For example, in Argentina
households in the poorest decile pay 20.9 percent of their income in VAT payments while
households in the richest decile pay only 8 percent.
As previously discussed, the two key parameters that vary across the three policy options
are the fraction of households exempted from an increase in the VAT and the magnitude of the
increase on the non-exempt that is needed to ensure that every policy option yields the same
total revenues, regardless of how many poor households are exempted.17 To find out exactly
how much higher the tax rate would be, we first calculate total household consumption in
every decile from survey data. We then calculate how much each decile’s total VAT payments
would rise with a one percentage point increase in the standard VAT rate, which is a typical
policy response in times of fiscal adjustment across the region (David and Leigh, 2018).18
16Argentina, Bolivia, Brazil, Chile, Colombia, the Dominican Republic, Honduras, Mexico, Peru, and
Uruguay.
17The poorest decile consumes far less than 10 percent of total household consumption and therefore its
VAT payments at any given rate are far less than 10 percent of total VAT payments. Hence, if the poorest
decile is exempted from an increase in the VAT, the amount that the remaining households will have to pay
is something less than 10 percent higher than they would have had to pay if no decile were exempted.
18VAT exemptions and rate reductions for particular goods proliferate in most Latin American coun-
tries. The survey data are detailed enough to allow us to assign shares of household consumption to the
corresponding rates. However, to avoid complicating the options we present to the respondents, we do not
11
When no decile is exempted, the All Pay reform option raises total VAT tax revenues
by approximately 4 percent.19 For each of the other two options, Top 70% Pay and Top
50% Pay, we then calculate the additional amount by which the VAT tax rate would have
to rise to ensure that total VAT tax receipts to the government still rise by 4 percent after
the bottom three (“70% Pay”) or bottom five deciles (“50% Pay”) are exempted.20
To increase the salience of the policy options and reduce the cognitive burden on respon-
dents, we tell them how much more households will pay in taxes under the new rates, not
the new rates themselves. That is, respondents see the percentage increase in monthly VAT
payments for an average household under each policy option. The increased VAT payments
are simply the product of the tax rate established for each policy option and total household
consumption in all non-exempt deciles. Our vignettes inform respondents of these increases:
5% in the case of the Top 70% Pay option, and 6% in the Top 50% Pay option.
All respondents see the three policy alternatives and are then asked to evaluate three
pairwise comparisons: Option 1 against Option 2; Option 1 against Option 3; Option 2
against Option 3. The order in which respondents see these vignettes is randomized. In each
comparison, respondents indicate on a 5-point scale if they are more likely to vote for the
government if the government implemented Option xvs. Option y. A value of 1 indicates
most support for Option x, 5 indicates most support for Option y, and 3 indicates that the
respondent is indifferent between Option xand Option y.
After respondents completed these comparisons, they are guided to a new screen that asks
them to choose their most preferred option among the following four alternatives: Option
1, Option 2, Option 3, or an additional Option 4, which suggests that the government does
not adjust the VAT to address the fiscal crisis.
mention reduced rates. Our policy options incorporate only increases in the standard VAT rate, not the
reduced rates.
19While in practice the exact number varies from country to country depending on their prior VAT tax
rate and base, the cross-country variation is trivial, lending credence to the use of a common figure across
the experiment.
20As is standard in this type of analysis, we assume that household consumption is inelastic with respect
to the changes in the VAT tax rate and that households bear the full burden of the tax (see Lustig (2018)
and IDB (2022)).
12
3.2 Information treatment
The hypothesis motivating the study is that individuals’ reluctance to embrace progressive
tax reforms can be traced to their uncertainty about the progressivity of the existing tax
system. Therefore, before choosing between the policy options, the survey includes an in-
formation treatment that tells respondents randomly assigned to the treatment group the
distributive impact of the VAT in a typical Latin American country.
To build the treatment, we again use the tax incidence analysis described above providing
information on the fraction of monthly income devoted to VAT payments by different income
groups. Thus, our treatment involves telling respondents about the incidence of the VAT
across the income distribution and, specifically, that lower income households devote a higher
share of their income to VAT payments than higher income households, as shown by Figure
1. We highlight the fact that the poorest households pay up to 23% of their income on the
VAT and the richest households pay only 11% of their income on VAT payments. To increase
salience and comprehension, the information is presented both verbally and graphically.21
Figure 1: Impact of VAT on income deciles; averages across selected countries in Latin
America
0
.05
.1
.15
.2
.25
Share of income paid on VAT
1 2 3 4 5 6 7 8 9 10
Income decile
21Appendix Figure A1 shows a screenshot from the survey with the actual graph shown to the treatment
group. In order to generate a common treatment across countries, the figure presents average values across
the countries in our sample, thus representing the distributive impact of VAT in a typical or representative
country in Latin America.
13
Treatment length or content could affect attrition in the treatment group relative to
the control group, potentially biasing responses. However, attrition was nearly the same in
treatment and control groups, on average 6.2% of respondents in the control group and 6.6%
in the treatment group. The difference is entirely insignificant, whether or not we control
for country fixed effects and respondent characteristics (see Table 1).22
Table 1: Survey attrition rate by treatment status
Outcome: D(Dropped out from the survey)
(1) (2) (3)
Treated 0.004 0.004 0.001
(0.006) (0.006) (0.003)
Observations 12,985 12,985 12,371
Country Fixed Effects No Yes Yes
Individual controls No No Yes
Mean Dep Var (Control) .0622 .0622 .0171
Notes: This table presents the estimates of the effect of being treated on sur-
vey attrition. The outcome is a dummy taking the value of 1 if the individual
dropped out from the survey. Individual controls include sex, age, household size,
the education level, the income level, employment and formality status, whether
the participant is retired, and a subsidies reception dummy. Standard errors are
clustered at the country level.
3.3 Control variables
The survey collected a wide range of household and respondent characteristics that might
influence their support for more progressive tax reform. These included basic data about
education, age, gender, household size, and employment status. In addition, respondents
provided information that allow us to place their actual and perceived location in the income
distribution, as well as their attitudes on key issues. These are all balanced across treatment
and control groups. We include them to identify empirical regularities in the data that link
22In their work, using more intensive treatments, Kuziemko et al. (2015) and Stantcheva (2021) experi-
enced overall attrition rates of 15% and 19%-20%, respectively. In Kuziemko et al. (2015), treated individuals
were 11.3 percentage points less likely to finish the survey and in Stantcheva (2021) the treated were between
two and six percentage points less likely. In our experiment, the treated are 0.4 percentage points less likely.
14
this research to prior work, yield surprising new regularities, or, most importantly, help to
estimate heterogeneous treatment effects that are useful to explore mechanisms.
Actual and perceived position in the income distribution. Substantial theoretical and
empirical attention has been given to household income as a determinant of redistributive
preferences. If respondents are only motivated by their material self-interest, respondents
in the top half of the income distribution should prefer the All Pay option over the other
two; those in the fourth or fifth deciles should prefer the Top 50% Pay option over the other
two; and those in the first, second or third deciles should prefer either of the redistributive
options over the first.
Two questions capture households’ actual and perceived location in the income distri-
bution. First, prior to entering the VAT portion of the survey, respondents were asked to
imagine a staircase with ten steps, with the poorest located on the first step and the richest
on the tenth step. Their self-location on the staircase constitutes their perceived location
in the income distribution. Second, we derived their actual location by asking them, at the
end of the survey, for their household income. Specifically, we computed the thresholds for
each income decile in the survey countries using Latin American household survey data from
Soci´ometro-IDB and SEDLAC. Respondents were asked to place themselves in one of the 10
income categories.23
The 10-step scales allowed us to group respondents into the three income groups that
are relevant for the fiscal policy questions: the lower 30% group including respondents who
classify themselves into the first three income percentiles; the middle 40-50% group including
respondents who classify themselves into the fourth and fifth income percentiles; and the
top 60% group including respondents who classify themselves into sixth through the tenth
percentiles.
Tax incidence misperceptions. We expect treatment effects to be strongest among those
who have incorrect perceptions of the incidence of tax policy. Therefore, before introducing
23The distribution of respondents for these two variables is in Appendix B, Figure B1.
15
our experiment, we asked respondents whether they believe rich households spend a higher,
the same, or lower fraction of their income on VAT compared to poor households.24 Only 35
percent of our sample is aware that poor households tend to pay a higher fraction of their
income in VAT than the rich.25
Attitudinal controls. The survey collected additional information that is particularly use-
ful for understanding mechanisms. We asked respondents where they located themselves
ideologically, on a 10 point scale from left to right; right-leaning respondents were signifi-
cantly more likely to underestimate the regressivity of the VAT.
Individuals’ support for redistribution can also depend on whether they believe that
success in life depends on one’s own efforts. Those who believe this is the case turn out to
have the misconception that the VAT is progressive.26
Beliefs about the potential for upward mobility in society might also affect support for
progressive tax reform, and perceptions about the progressivity of the VAT. Respondents
therefore indicated which of four statements they most agreed with, from “almost all children
from poor households have the same opportunities as children from rich households” to
“almost no child from a poor household has the same opportunities as children from rich
households.” Again, these beliefs are strongly associated with misconceptions about the
incidence of the VAT.
24The exact question wording is as follows: “Over the course of a year, all households will have dedicated
a certain percentage of their income to paying VAT for the goods and services they purchased. What do you
think is the percentage of income paid by poor households and rich households on VAT? Do you think that
rich households spend a higher percentage of their income paying VAT, or a lower percentage, compared to
poor households?” Respondents choose one of five possible answers: 1) Rich households spend a much higher
percentage of their income in VAT payments; 2) Rich households spend a higher percentage; 3) Rich and
poor households spend about the same percentage; 4) Poor households spend a higher percentage; and 5)
Poor households spend a much higher percentage of their income in VAT payments.
25Krupnikov et al. (2006) argue that survey data on respondents’ factual knowledge, in their case knowl-
edge of the incidence of the estate tax, likely underestimate knowledge. When they offer one dollar to
respondents who correctly answer the question about estate tax incidence, the number of correct responses
increase by more than 30 percent. Although we do not reward respondents for correct answers on the in-
cidence of the VAT, the possible inaccuracy of responses does not bias our experimental results. Random
assignment of respondents into treatment and control groups ensures balance in the number of respondents
who accurately and inaccurately respond to the question regarding VAT tax incidence.
26The exact question wording is as follows: “With which of statements A or B are you more in agreement?
A. People’s incomes are the product of their individual efforts; or B. People’s incomes are the product of
factors outside of their control?”
16
Respondents had an opportunity to indicate which two potential problems in their coun-
try, out of a list of 14, most concerned them. The list was randomly reordered for each
respondent. From these choices, we constructed a dummy variable to indicate those respon-
dents who were most concerned about inequality and poverty. They were more in favor of
progressive tax reform, and more likely to say that the VAT was regressive.
Finally, the survey also asked various questions related to trust in others and in gov-
ernment. These did not have systematic effects on either preferences for tax reform nor
misconceptions regarding the incidence of the VAT.
4 Empirical Strategy
We examine whether the information treatment has a significant effect on VAT reform pref-
erences by estimating an empirical specification with the following form:
yic =αc+θ1T reatedi+θ2Xi+εic (1)
The variable yic captures the VAT reform options preferred by respondent iin country c.
There are different versions of the variable, capturing respondent preferences across binary
comparisons of the three options All Pay,70% Pay, or 50% Pay.T reatediis an indicator
variable that equals 1 if the respondent ireceived the information treatment, and 0 otherwise.
The coefficient of interest, θ1, captures the average differential change between those who
received the information treatment and those who did not.
We include a complete set of country fixed effects αcto control for any source of cross-
country heterogeneity. The term Xiin equation (1) represents control variables. The group
of basic socioeconomic controls consists of the respondent’s actual position in the income
distribution, education, age, gender, employment status, whether the worker is informal or
retired, whether the respondent receives any government subsidy, and household size. Some
specifications also control for respondents’ attitudes: their perceived location in the income
17
distribution, whether they consider inequality and poverty as main problems in their country,
trust in the current government, beliefs about the determinants of economic success (luck vs.
effort), beliefs about the life opportunities of poor children, previous knowledge about who
decides tax policy, and political alignment (left vs. right ideological dimensions). Finally,
εic is the clustered error term that allows correlation within countries.
To investigate the heterogeneity of the information treatment based on respondent’s
characteristics, we use an augmented version of the main specification, equation (1). We
estimate the following equation:
yic =αc+θ1T reatedi+θ2(T reatedi×Zi) + θ3Zi+µic, (2)
The coefficient of interest in this equation is θ2, which captures the differential effect on tax
policy preferences of those who received the information treatment that also share charac-
teristic Zi.
5 Results
5.1 Graphical evidence
Before examining respondent support for redistribution we confirm in Figure C1 in Appendix
C that the treatment and control groups are balanced with respect to all observable variables.
This is unsurprising given the random assignment of respondents to treatment and control
groups. The analysis provides reassurance that the two groups are likely to be balanced as
well with respect to unobservable characteristics.
Simple comparisons of respondent support for the various reform options reveals a sig-
nificant preference for the redistributive over the non-redistributive reform options. This
preference is stronger among treated respondents. Figure 2 describes these differences. Sub-
figure 2(a) shows that more respondents favor the options that include a compensation
18
component, Options 2 (70% Pay) and 3 (50% Pay), than Option 1 (All Pay).
More specifically, respondents first made a pairwise comparison between Option 1, All
Pay and Option 2, 70% Pay, on the 5-point scale described in the previous section, where 1 or
2 expressed support for the first option, 4 or 5 for the second, and 3 reflects indifference. The
columns Support for O1/O2are the shares of respondents who prefer All Pay or 70% Pay,
respectively. The shares for the other two pairwise comparisons are computed similarly. The
fraction of respondents who prefer the more redistributive options over the non-redistributive
option is between 10 and 15 percentage points. When respondents choose between the two
redistributive options, they slightly favor Option 2, which exempts the bottom 30%, over
Option 3, which exempts the bottom 50% of the income distribution. Between 20% and 25%
of the respondent are indifferent between the various options.
Respondents then indicated their preferred policy from among any of the three options
plus the added option of no VAT reform at all, despite the fiscal stringencies that the
government confronts. Subfigure 2(b) reports the responses to this question. Option 1,
All Pay, receives less support than the other two options. The most redistributive option,
Option 3, 50% Pay, receives more overall support than all other options, including 70% Pay,
which differs from the pairwise comparisons in subfigure 2(a). We also find that only a small
share of respondents, about 7%, favors no fiscal adjustment.27
27We do not attach a strong interpretation to the fact that more respondents prefer an uncompensated
tax hike to doing nothing. It is possible that the framing of the vignette, emphasizing that serious fiscal
problems threaten economic stability, employment, and family incomes, could account for weak support for
no action. Experimenter demand, though, is another plausible explanation, since all of the focus of the
section is on VAT policy changes.
19
Figure 2: Support for fiscal adjustment options, in %
(a) Pairwise comparisons
0
5
10
15
20
25
30
35
40
45
Support for All Pay
Indifferent
Support for 70% Pay
All vs. 70% Pay
0
5
10
15
20
25
30
35
40
45
Support for 70% Pay
Indifferent
Support for 50% Pay
70% vs. 50% Pay
0
5
10
15
20
25
30
35
40
45
Support for All Pay
Indifferent
Support for 50% Pay
All vs. 50% Pay
Untreated
Treated
(b) Direct comparison of all options
0
5
10
15
20
25
30
35
All Pay
70% Pay
50% Pay
No adjustment
Untreated
Treated
All options
Figure 2 also summarizes how the information treatment, which manipulates respon-
dents’ knowledge about the regressive impact of the VAT, affects their policy preferences.
It compares the average policy preference for the treated (red bar) with those for the non-
treated (gray bar). For all three pairwise comparisons, information about the regressive
impact of the VAT increases support for a policy that compensates citizens in lower income
brackets. The increase in support is most pronounced for Option 3, 50% Pay which proposes
20
an increase in VAT of 6% for citizens who belong to the upper half (top 50%) of the income
distribution while exempting the bottom half. This result is consistent across both outcome
variables in panels (a) and (b) of Figure 2. The share of respondents that are indifferent
remains almost identical between treated and untreated respondents.
5.2 Regression results: average treatment effects
Table 2 further examines the treatment effect using a series of OLS regression models with
country fixed effects.28 We use different outcome variables for the analysis of the pairwise
comparisons in columns (1) to (6): the original, 5-scale categorical variable where higher
values indicate greater support for the option mentioned first in the top row29 and a dummy
version that takes the value 1 if the respondent supports the option mentioned first in the top
row. In columns (7) to (10), the outcome variables are dummy variables that take the value
1 if the respondent chose the option listed on top of the column and 0 otherwise. Finally,
Panel A simply regresses the respective outcome variable on the treatment dummy; Panel B
does the same but includes a series of socioeconomic control variables; and Panel C includes
variables capturing a respondent’s subjective perceptions, beliefs and knowledge in addition
to the socioeconomic controls.30
This is a version of the table just above, but with stars indicating statistical significance
The results confirm the graphical analysis of Figure 2. The information treatment has a
consistent and statistically significant impact on support for the different adjustment options.
The negative signs on the coefficients in the Treated row of 2 indicate that respondents who
were informed about the regressive impact of the VAT are less likely to choose Option 1,
All Pay, over Option 2, 70% Pay or over Option 3, 50% Pay (columns (1)-(2) and (5)-
(6)). In column 6, information reduces support for the least redistributive option by 3.4
28The summary statistics of all relevant variables are in Appendix Table B1.
29For example, for the comparison of ‘Option1to2’, higher values indicate greater support for Option 1.
30The results for the control variables are in the Appendix, Table C1.
21
Table 2: Main effects VAT experiment
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay Preferred Choice
Cat D Cat D Cat D All Pay 70% Pay 50% Pay No Adj
Panel A: Baseline
Treated -0.049*** -0.017*** -0.050** -0.017 -0.112*** -0.034*** -0.039** 0.022 0.025** -0.008
(0.014) (0.005) (0.020) (0.012) (0.021) (0.007) (0.015) (0.014) (0.010) (0.004)
Panel B: Baseline + socioeconomic controls
Treated -0.050*** -0.017*** -0.050** -0.016 -0.114*** -0.035*** -0.040** 0.022 0.027** -0.008
(0.013) (0.005) (0.021) (0.012) (0.022) (0.008) (0.015) (0.014) (0.010) (0.005)
Panel C: panel B + knowledge/beliefs/perceptions
Treated -0.051*** -0.017*** -0.051** -0.016 -0.114*** -0.035*** -0.040** 0.022 0.027** -0.008
(0.013) (0.005) (0.020) (0.012) (0.021) (0.008) (0.014) (0.014) (0.009) (0.005)
Observations 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152
Mean Dep. Var. 3.094 0.317 2.934 0.389 3.107 0.326 0.277 0.308 0.338 0.076
Mean Dep. Var. (control) 2.931 0.326 3.091 0.398 2.949 0.344 0.297 0.297 0.326 0.080
Country FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Notes: This table presents the results of the main treatment effects. All vs. 70% Pay measures respondents’ preferences
for option 1 over option 2. Cat means that it is the categorical measure, which takes values from 1-5, where 5 is a greater
preference for option 1. Dis an indicator variable that takes values of 1 if option 1 was preferred, and 0 otherwise. All Pay in
column 7 is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise. The same logic for columns 8, 9
and 10. All Pay being the least redistributive option and 50% Pay the most redistributive. No Adj means no action. Treated
is an indicator variable that takes values of 1 if it received the treatment of experiment 1, and 0 otherwise. Clustered standard
errors at the country level are reported in parentheses. * is significant at the 10% level, ** is significant at the 5% level, *** is
significant at the 1% level.
percentage points from a base of 34% in the control group, a 10% decrease. There is some
indication that the treated respondents are also less likely to choose Option 2,70% Pay, over
Option 3, 50% Pay (column (3), although this result is not robust across definitions of the
dependent variable (column 4). In line with these results from the pairwise comparisons,
support for Option 1, All Pay, is lower and support for Option 3, 50% Pay, is higher among
treated respondents for the simultaneous comparison of all options (columns (7)-(10)). The
treatment does not affect support for Option 2, 70% Pay, or Option 4 (no fiscal adjustment).
A standard concern regarding information interventions is whether their effects are sub-
stantively important. One way to see that they are is by comparing them with other respon-
dent characteristics that are known to be electorally important. Three such characteristics
are political alignment, concern for inequality, and beliefs about the relative opportunities
of children from poor and rich households.
Treated respondents are more likely to prefer option 3, 70% Pay over option 1, All Pay.
22
The effect size is larger than a one standard deviation leftward shift in political alignment,
which increases the probability of supporting 70% Pay by 2 percent. Treatment effects are
similar to the impact of concerns about inequality and poverty and are half as large as
the effect of believing that poor children have fewer opportunities than rich children: these
respondents are 8 percent more likely to prefer 70% Pay over option 1, All Pay.
Among the control variables, ideology and beliefs have the strongest consistent impact
on a respondent’s fiscal attitudes (see Appendix C, Table C1). Three variables—political
alignment, concern for inequality and perceptions of poor child opportunity—stand out.
Compared to left-leaning respondents, those on the right are more likely to support the less
redistributive options, i.e. Option 1, All Pay, over Option 2, 70% Pay, and Option 2, 70%
Pay, over Option 3, 50% Pay. Their preferences are transitive, as they also prefer Option
1, All Pay, over Option 3, 70% Pay. Respondents who do not indicate that inequality
and poverty are among their two greatest concerns are similar to right-leaning respondents.
Respondents who agree more with the statement that children from poor households have the
same opportunities as children from rich households also express significantly less support
for the more redistributive reform options.
Respondents’ actual location in the income distribution, based on respondent reports of
the income decile to which their household belongs, exhibits a counter-intuitive relationship
with preferences for redistribution. Contrary to their material interests, respondents in the
bottom 30% of the income distribution are more likely to support less redistributive options
than those in the top 50% group (the reference category in our analysis). The same is true
for the respondents in the fourth and fifth decile of the income distribution.
When we compare respondents’ actual location in the income distribution, based on
household income information that they provide at the end of the survey, with their perceived
location, based on information they provide at the beginning, significant inconsistencies
emerge. In line with previous research (Cruces, Perez Truglia and Tetaz, 2013; Karadja,
Mollerstrom and Seim, 2017), respondents have difficulty placing themselves in the income
23
distribution.31 Hence, we also ask how perceived location in the income distribution is related
to preferences for redistributive tax reform.
These coefficient estimates yield more intuitive results. Respondents who perceive them-
selves to be the bottom three deciles or in the fourth and fifth deciles of the income distri-
bution are more likely to choose the most redistributive Option 3, 50% Pay, over Option
1, All Pay. These results are robust to whether or not the specification controls for actual
location in the income distribution. However, even perceived income is not correlated with
preferences across other policy comparisons (e.g., 70% Pay vs. All Pay).32
5.3 Robustness checks
There are three possible concerns with the foregoing results. One is that treatment effects
could be the product of experimenter demand; another is that they are the spurious product
of respondents’ lack of attention; a third is that results are driven country-specific circum-
stances, such as levels of informality or VAT tax rates, that cloud interpretation or limit
external validity.
Two features of the the experiment attenuate concerns about experimenter demand bias.
First, we would expect stronger experimenter demand effects from treatments in prior re-
search; these treatments nevertheless have small effects on preferences for specific reforms to
reduce inequality. This is the case for the three-part intervention in Kuziemko et al. (2015),
for example. The first part told respondents their exact position in the income distribution;
the second, how much larger their income would be if growth had been more evenly shared;
and the third told respondents that pre-tax family incomes grew faster when top tax rates
31As Appendix B, Figure B1 shows, respondents tend to place themselves closer to the middle of the
income distribution than their actual income would suggest. That is, poor respondents perceive themselves
as less poor and rich respondents perceive themselves as less rich than they really are.
32Misperceptions regarding one’s location in the income distribution are in any case likely to be related
to unobserved characteristics and beliefs that influence demand for redistributive policies.Weisstanner and
Armingeon (2022) note that perceptions of location in the income distribution are endogenous; they also find,
in their study of Swiss respondents, that perceived income is only associated with redistribution preferences
among center-right, not left-leaning respondents.
24
were higher. Nevertheless, the treatment had an economically small effect on preferences for
tax rates on the rich. Our treatment, which only informed respondents that VAT payments
by poor households constitute a larger share of their incomes, has an economically large
effect on preferences for a more progressive VAT.
Second, any experimenter demand bias elicited by the treatment is likely to be small
compared to the potential bias elicited by text seen by both control and treated respondents.
All respondents, both treated and control, are told the following: “We wanted to know your
opinion about three options that governments have to collect more revenues through the value-
added tax. Two of these seek to protect the poorest households from the impact
of the increase, by collecting more revenues from the other households. Hence,
all respondents are encouraged to pay attention to the welfare of poor households. Treated
households are only told, in addition, that the VAT affects poor households more than
rich, with technical information about the incidence of the tax across income deciles. If
experimenter demand effects were strong, they would be more likely to be elicited by the
bold-faced statement, read by all respondents, attenuating rather than enhancing treatment
effects.
Respondents possible lack of attention is especially relevant because our interpretation of
the results depends on whether respondents actually understood the key features of each of
the policy alternatives. We introduced two attention check questions that capture respondent
comprehension of the distributive effects of the reform options. One asked respondents to
identify the policy option that makes the poorest pay more; the other asked the option that
makes the richest deciles pay more. Close to 70% of the sample understood at least one of
the attention check questions (see Table C2 in Appendix C). When we restrict the analysis
to this particular sample, we obtain larger treatment effects, as Table C3 in Appendix C
shows. The treatment effect remains unchanged for the comparison of Options 2 and 3, but
it increases by 19% for the comparison of Options 1 and 3 and by 76% for the comparison
of Options 1 and 2.
25
Finally, the countries in our sample may vary in ways that influence how respondents
interpret or react to the treatment. For example, the countries exhibit significant variations
in their VAT tax rates, potentially affecting the salience of the treatment, and in their levels
of informality, which could affect perceptions of incidence (e.g., if respondents believe that
the poor buy from vendors who evade the VAT). Such variations do not affect the internal
validity of our estimated treatment effects, but could raise questions about their external
validity and interpretation. In fact, the point estimates of the treatment effects are roughly
constant across the sample countries.
Figure C7 in Appendix C summarizes the treatment effects for every country across the
three outcome variables in Table 2. We do not expect significant treatment effects at the
country level, since the experiment was not powered to reveal them. However, in nearly every
case the point estimates are close in magnitude to and statistically indistinguishable from the
point estimates of the total treatment effects. In addition, to check that no particular country
is driving the results, we drop one country at a time from the estimation sample. Figure C8
in Appendix C shows the treatment effects when the observations from the different countries
are excluded one-by-one. The results are stable and similar across the different subsamples.
6 Mechanisms: The Role of Tax Incidence Mispercep-
tions
The rich data from the survey allow us to explore the mechanisms linking misperceptions
of VAT incidence to opposition to progressive tax reform. Two key conclusions emerge
from this exploration. First, the effects of the information treatment are strongest among
respondents with misperceptions regarding incidence. Second, misperceptions appear not to
be a cognitive phenomenon: education is not correlated with beliefs about the progressivity
of the VAT. Instead, policy misperceptions are correlated with individuals’ world views:
they are consistently higher among right-leaning respondents, respondents who believe that
26
poor children have similar opportunities as children in rich households, and respondents
who believe that effort is more important than luck in determining household incomes.
It is intuitive that misperceptions about the progressivity of the VAT might be strongest
among individuals with these beliefs. Less intuitive and more remarkable is the finding that
information that corrects these misperceptions is sufficient to overcome these beliefs and
change respondents’ preferences regarding progressive tax reform.
6.1 Misperceptions about the incidence of VAT
We first examine how respondents’ prior beliefs about the distributive impact of the VAT
influences policy choices. Table 3 regresses the outcome variables on PerceptVAT, a vari-
able that takes higher values for those respondents who incorrectly perceive that the VAT
is progressive, and on the interaction of PerceptVAT with the treatment variable.33 The
coefficient estimates of PerceptVAT are positive, indicating that untreated respondents who
incorrectly believe that rich people pay a greater share of their income on the VAT than
poor people are significantly more likely to support Option 1, All Pay, which does not com-
pensate poor people. The effect is most pronounced when this option is compared to the
most redistributive Option 3, 50% Pay.
The negative coefficient on the interaction term reveals that the information treatment
significantly moderates the impact of misperceptions, especially when the respondents com-
pare the least and most progressive options. Figure 3 shows the marginal effect of the
information treatment on support for the least and most progressive options among respon-
dents with different perceptions regarding the impact of the VAT. The strongest treatment
effects are observed among those who misperceive the impact of the VAT. For those who
(correctly) believe that poor people pay a greater share of their income on VAT than rich
people, the point estimate for the treatment variable is negative, but it is not statistically
33The misperceptions variable takes a value of 1 if the respondent believes that richer households spend a
higher or similar percentage of their income on VAT payments relative to poorer households and 0 otherwise.
27
Table 3: Heterogenous effect - Misperception of VAT incidence
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay Preferred Choice
Cat D Cat D Cat D All Pay 70% Pay 50% Pay No Adj
Treated * PerceptVAT -0.098 -0.028 -0.097** -0.043 -0.111** -0.040** -0.028 0.008 0.022 -0.002
(0.061) (0.020) (0.038) (0.023) (0.042) (0.017) (0.017) (0.019) (0.021) (0.012)
Treated 0.014 0.001 0.013 0.010 -0.040 -0.009 -0.021 0.016 0.011 -0.007
(0.048) (0.015) (0.023) (0.013) (0.041) (0.015) (0.019) (0.016) (0.015) (0.009)
PerceptVAT 0.185** 0.053** 0.194*** 0.055** 0.220*** 0.066*** 0.065*** 0.008 -0.068** -0.005
(0.066) (0.018) (0.047) (0.022) (0.044) (0.009) (0.013) (0.014) (0.021) (0.010)
Constant 2.811*** 0.291*** 2.966*** 0.362*** 2.807*** 0.301*** 0.255*** 0.292*** 0.370*** 0.083***
(0.044) (0.012) (0.030) (0.012) (0.031) (0.007) (0.008) (0.008) (0.015) (0.006)
Observations 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152
R-squared 0.014 0.013 0.008 0.009 0.019 0.016 0.018 0.005 0.011 0.005
Mean Dep. Var. 3.094 0.317 2.934 0.389 3.107 0.326 0.277 0.308 0.338 0.076
Mean Dep. Var. (control) 2.931 0.326 3.091 0.398 2.949 0.344 0.297 0.297 0.326 0.080
Country FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Notes: This table presents the results of heterogeneous treatment effects. All vs. 70% Pay measures respondents’ preferences
for option 1 over option 2. Cat means that it is the categorical measure, which takes values from 1 to 5, where 5 is a greater
preference for option 1. Dis an indicator variable that takes values of 1 if option 1 was preferred, and 0 otherwise. Same logic
for the dependent variables in columns 3 to 6. All Pay in column 7 is an indicator variable that takes values of 1 if option 1
was chosen, and 0 otherwise. The same logic for columns 8, 9 and 10. All Pay being the least redistributive option and 50%
Pay the most redistributive. No Adj means no action. Treated is an indicator variable that takes values of 1 if it received
the information treatment, and 0 otherwise. PerceptVAT is an indicator variable equal to 1 if respondent believes that rich
households spend a higher or similar percentage of their income on VAT payments relative to poor households, and 0 otherwise.
Clustered standard errors at the country level are reported in parentheses. * is significant at the 10% level, ** is significant at
the 5% level, *** is significant at the 1% level.
significant. For those who (incorrectly) believe that rich people pay a greater share of their
income on VAT, the point estimate is considerably larger and the 95% confidence interval
does not span the zero line. In short, the treatment effect is driven by misinformed people
who change their attitude towards compensated fiscal adjustment when they learn that their
beliefs about the incidence of the VAT across income groups are wrong.
28
Figure 3: Treatment Effects by Perception about VAT Incidence
-.2
-.15
-.1
-.05
0
.05
Treatment effect
Correct Incorrect
Perception VAT
(a) All vs. 50% Pay
-.06
-.04
-.02
0
.02
Treatment effect
Correct Incorrect
Perception VAT
(b) D(All vs. 50% Pay)
Notes: This figure presents the impact of the information treatment on support for the more redistributive option 3, 50% Pay,
conditional on the respondent’s perception of the impact of the VAT. The results are based on models (5) and (6) in Table
3. All vs. 50% Pay is a categorical variable that measures preferences for option 1 over option 3. D(All vs. 50% Pay )
is an indicator variable that takes values of 1 if the respondent prefers option 1 more, and 0 if he/she prefers option 3 more.
Perception VAT is an indicator variable that takes the value 1 if the respondent (incorrectly) believes that richer households
spend the same or a higher percentage of their income on VAT relative to poorer households, and 0 otherwise.
6.2 Drivers of misperceptions
In the next step, we examine the determinants of tax incidence misperceptions. Table
4 examines to what extent these misperceptions correlate with cognitive and ideological
factors, including education, political alignment (left vs. right), concerns about inequality,
and beliefs about the sources of poverty and individual success. Beliefs and ideology, rather
than cognitive factors (education), appear to drive misperceptions. The positive coefficient
on political alignment in Table 4 shows that people on the center/right tend to be more
likely to believe the rich pay more than the poor. In contrast, people who think inequality
and poverty are a significant concern are more likely to believe that the poor pay more than
the rich in VAT, as the negative coefficient on concern for inequality in Table 4 shows. We
would therefore expect that the information treatment should mostly affect people on the
center and right of the ideological spectrum since the perceptions of VAT incidence of those
on the left are more consistent with its actual distributive impact. Similarly, the treatment
should affect respondents who believe that inequality is the main problem less than those
29
who believe other issues to be more salient. This is because the perceptions of the latter
about the VAT impact is less accurate than the perceptions of the former.
Table 4: Determinants of VAT misperceptions
(1) (2) (3) (4) (5)
Perception of VAT impact
Educated 0.005 -0.009 -0.007 -0.015 -0.015
(0.016) (0.016) (0.015) (0.015) (0.015)
PoliticalAlign 0.027*** 0.027*** 0.026*** 0.026*** 0.022***
(0.004) (0.004) (0.004) (0.004) (0.003)
Bottom30Actual -0.053*** -0.036** -0.043**
(0.014) (0.014) (0.013)
B40and50Actual -0.005 0.002 -0.001
(0.016) (0.015) (0.015)
Bottom30Perceived -0.095*** -0.083*** -0.070***
(0.009) (0.007) (0.008)
B40and50Perceived -0.022 -0.017 -0.012
(0.012) (0.011) (0.010)
KnowledgeTaxes -0.001
(0.010)
ConcernIneqPov -0.044***
(0.010)
TrustGov 0.021
(0.018)
BeliefsLuck -0.028***
(0.007)
PoorChildOpportunity -0.092***
(0.017)
Constant 0.499*** 0.526*** 0.542*** 0.553*** 0.654***
(0.019) (0.021) (0.023) (0.025) (0.028)
Observations 12,152 12,152 12,152 12,152 12,152
R-squared 0.039 0.041 0.043 0.044 0.054
Mean Dep. Var. 0.580 0.580 0.580 0.580 0.580
Country FE Yes Yes Yes Yes Yes
Notes: This table presents the determinants of respondents’ misperceptions about VAT. BottomXXActual and BottomXXPer-
ceived identify respondents whose reported income puts them in the bottom XXth percentile and whose perceived income puts
them in the bottom XXth percentile, respectively. Clustered standard errors at the country level are reported in parentheses.
* is significant at the 10% level, ** is significant at the 5% level, *** is significant at the 1% level.
This is what Figures 4 and 5 show.34 Figure 4 illustrates the impact of the information
treatment for respondents who place themselves on different locations on the left-right po-
litical dimension. The treatment does not affect respondents on the left: the marginal effect
for these respondents is zero, which means that treated and untreated respondents from the
34The figures are based on the results in Appendix C, Tables C4 and C5.
30
left, on average, do not differ when they compare Options 1 and 3. In contrast, the infor-
mation treatment has a strong effect on respondents on the right; they are correspondingly
less likely to select the least redistributive Option 1, All Pay, over the most redistributive
Option 3, 50% Pay, when they learn about the regressive impact of the VAT.
Figure 4: Treatment effects by political alignment
-.3
-.2
-.1
0
.1
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
% of observations
(a) All vs. 50% Pay
-.1
-.05
0
.05
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
% of observations
(b) D(All vs. 50% Pay)
Notes: This figure presents the impact of the information treatment on support for the more redistributive option 3, 50% Pay,
conditional on the respondent’s political alignment. The results are based on models (5) and (6) in Table C4. All vs. 50%
Pay is a categorical variable that measures preferences for option 1 over option 3. D(All vs. 50% Pay ) is an indicator variable
that takes values of 1 if the respondent prefers option 1 more, and 0 if he/she prefers option 3 more. Political alignment is the
respondent’s position on the left-right political dimension.
Figure 5 compares treatment effects for respondents with strong and weak concern for
inequality and poverty. The figure shows that the treatment effect is not statistically signif-
icant for respondents who have a strong concern for inequality. In contrast, it is large for
those with a small concern, indicating that respondents who are not much concerned with
inequality are less likely to choose Option 1 over Option 3 when they are informed about
the regressive impact of VAT.
7 Conclusions and Policy Implications
Prior research has found a strong relationship between respondents’ knowledge of their loca-
tion in the income distribution and support for more redistributive policies in general, but
much weaker effects on support for specific measures to redistribute. Our results suggest that
31
Figure 5: Treatment effects by concern about inequality and poverty as problems
-.2
-.1
0
.1
Treatment effect
Weak Strong
Concern Inequality and Poverty
(a) All vs. 50% Pay
-.06
-.04
-.02
0
.02
Treatment effect
Weak Strong
Concern Inequality and Poverty
(b) D(All vs. 50% Pay)
Notes: This figure presents the impact of the information treatment on support for the more redistributive option 3, 50% Pay,
conditional on the respondent’s concern for inequality and poverty. The results are based on models (5) and (6) in table 5.
All vs. 50% Pay is a categorical variable that measures preferences for option 1 over option 3. D(All vs. 50% Pay ) is an
indicator variable that takes values of 1 if the respondent prefers option 1 more, and 0 if he/she prefers option 3 more. Concern
for inequality is an indicator variable that takes the value 1 if the respondent answers that s/he is strongly concerned about
inequality and poverty, and 0 otherwise.
misperceptions about the distributional incidence of different policy measures could account
for this. In theory, individuals might reasonably have a difficult time inferring significant
changes in the distribution of income and their position within it from any specific change
in the tax code. However, when they are informed about the general incidence of a salient
tax across all households in the income distribution, their support for more redistributive
tax policies increases.
The effects are large. In addition, they are driven in part by a group of respondents who
might reasonably be considered as hard-to-reach: respondents whose ideologies and view of
the world lead them to assume that the VAT is not regressive and that redistribution is an
inappropriate goal for public policy. In fact, treatment effects are stronger among this group.
These results have policy implications both regarding how to inform citizens about com-
plex fiscal policy reforms with easy-to-interpret facts, but also about how to design fiscal
adjustment packages. More progressive policy responses are more popular, but only when
individuals are informed about how progressive they are.
32
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36
Screen 1
A menudo, los países de América Latina se encuentran con problemas fiscales serios, amenazando la
estabilidad económica, el empleo, y los ingresos familiares. Una opción a la cual los gobiernos recurren
para salir del callejón fiscal es subir los impuestos al consumo - el Impuesto al Valor Agregado (IVA).
El IVA afecta más a los pobres que a los ricos. Como muestra el gráfico abajo, un individuo
perteneciente al 10% de hogares más pobres destina alrededor de 23% de sus ingresos mensuales en
concepto de pagos de IVA. En cambio, un individuo perteneciente al 10% de los hogares más ricos
paga sólo 11% de sus ingresos en concepto de IVA.
Pagos de IVA como porcentaje del ingreso en América Latina
Screen 2
Queremos saber su opinión de tres opciones que tienen los gobiernos para recaudar más a través de del
IVA. Dos de ellas buscan proteger a los hogares más pobres del impacto del aumento, al recaudar
más de los demás hogares.
Opción 1: Aumentar el IVA de manera que el gobierno recaude lo suficiente para evitar la crisis
fiscal. Cada persona pagaría 4% más que ahora en concepto de IVA. Por ejemplo, si una persona
actualmente paga mensualmente 3.000 pesos, después del aumento del IVA pagaría 3.120 pesos.
A Survey Screenshots
Figure A1: Information treatment and VAT adjustment options
Screen 3
Opción 2: Aumentar el IVA de manera que el gobierno recaude lo suficiente para evitar la crisis fiscal.
Sin embargo, el 30% de hogares más pobres no pagaría el aumento de IVA. Cada persona en los
demás hogares pagaría 5% más que ahora. Por ejemplo, si una persona en estos hogares
actualmente paga mensualmente 3.000 pesos, después del aumento del IVA pagaría 3.150 pesos.
Screen 4
Opción 3: Aumentar el IVA de manera que el gobierno recaude lo suficiente para evitar la crisis fiscal.
Sin embargo, en este caso el 50% de hogares más pobres no pagaría el aumento de IVA. Cada
persona en los demás hogares pagaría 6% más que ahora. Por ejemplo, si una persona en estos
hogares paga mensualmente 3.000 pesos, después del aumento del IVA pagaría 3.180 pesos.
Screen 5
Esta tabla resume las opciones.
¿Cuáles hogares pagan?
¿Cuánto paga cada hogar?
Opción 1
Todos los hogares
4% más que ahora
Opción 2
El 70% de hogares con mayores ingresos
5% más que ahora
Opción 3
El 50% de hogares con mayores ingresos
6% más que ahora
B Descriptives
Table B1: Summary statistics
(1) (2) (3) (4) (5)
Average Standard
deviation Min Max Obs.
Panel A: Outcomes
All vs. 70% Pay 2.906 1.351 1 5 12,152
D(All vs. 70% Pay) 0.317 0.465 0 1 12,152
70% vs. 50% Pay 3.066 1.301 1 5 12,152
D(70% vs. 50% Pay) 0.389 0.488 0 1 12,152
All vs. 50% Pay 2.893 1.386 1 5 12,152
D(All vs. 50% Pay) 0.326 0.469 0 1 12,152
Redist - All Pay 0.277 0.448 0 1 12,152
Redist - 70% Pay 0.308 0.462 0 1 12,152
Redist - 50% Pay 0.338 0.473 0 1 12,152
Redist - No Adj. 0.076 0.265 0 1 12,152
Panel B: Controls
Actual - Bottom 30% 0.343 0.475 0 1 12,152
Actual - Between 40% and 50% 0.175 0.380 0 1 12,152
Actual - Top 60% 0.482 0.500 0 1 12,152
Educated 0.516 0.500 0 1 12,152
Age 38.755 13.780 16 99 12,152
Female 0.501 0.500 0 1 12,152
Unemployed 0.324 0.468 0 1 12,152
Informal worker 0.191 0.393 0 1 12,152
Retired 0.050 0.218 0 1 12,152
Government subsidies 0.158 0.365 0 1 12,152
Household size 4.020 2.322 1 12 12,152
Panel C: Knowledge/Beliefs/Perceptions
Perceived - Bottom 30% 0.181 0.385 0 1 12,152
Perceived - Between 40% and 50% 0.533 0.499 0 1 12,152
Perceived - Top 60% 0.286 0.452 0 1 12,152
Knowledge of tax policy 0.457 0.498 0 1 12,152
Concern about inequality and poverty 0.248 0.432 0 1 12,152
Trust in government 0.250 0.433 0 1 12,152
Beliefs in luck 0.244 0.429 0 1 12,152
Poor child opportunities 0.743 0.437 0 1 12,152
Political alignment 5.323 2.225 0 10 12,152
39
Figure B1: Actual and perceived position of respondents in income distribution
40
C Additional Results
Figure C1: Balance between treatment and control
Actual - Bottom 30%
Actual - Between 40% and 50%
Actual - Top 60%
Educated
Age
Female
Unemployed
Informal worker
Retired
Government subsidies
Household size
-.5 0 .5 1
Figure C2: Margin plots - perception VAT (other outcomes)
-.1
-.05
0
.05
.1
Treatment effect
0 1
Perception VAT
(a) All vs. 70%
-.04
-.02
0
.02
.04
Treatment effect
0 1
Perception VAT
(b) D(All vs. 70% )
-.15
-.1
-.05
0
.05
Treatment effect
0 1
Perception VAT
(c) 70% vs. 50%
-.06
-.04
-.02
0
.02
.04
Treatment effect
0 1
Perception VAT
(d) D(70% vs. 50% )
-.08
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Perception VAT
(e) Redist - All Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Perception VAT
(f) Redist - 70% Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Perception VAT
(g) Redist - 50% Pay
-.02
-.01
0
.01
Treatment effect
0 1
Perception VAT
(h) Redist - No Adj.
Notes: This figure presents the marginal effects of the heterogeneous effects. Al l vs. 70% Pay is a categorical variable
that measures preferences for option 1 over option 2. D(All vs. 70% Pay) is an indicator variable that takes values of 1 if
the respondent prefers option 1 more, and 0 if he/she prefers option 2 more. Same logic for variables 70% vs. 50% Pay and
D(70% vs. 50% Pay). ‘Redist - All Pay is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise.
The same logic for panels f, g and h. ‘Redist - All Pay being the least redistributive option and ‘Redist - 50% Pay the most
redistributive. ‘Redist - No Adj. means no action.
41
Figure C3: Margin plots - political alignment (other outcomes)
-.2
-.1
0
.1
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(a) All vs. 70%
-.1
-.05
0
.05
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(b) D(All vs. 70% )
-.3
-.2
-.1
0
.1
.2
Treatment effect
012345678910
Political Alignment
0
10
20
30
40
Percentage of observations
(c) 70% vs. 50%
-.1
-.05
0
.05
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(d) D(70% vs. 50% )
-.1
-.05
0
.05
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(e) Redist - All Pay
-.04
-.02
0
.02
.04
.06
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(f) Redist - 70% Pay
-.05
0
.05
.1
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(g) Redist - 50% Pay
-.04
-.02
0
.02
.04
Treatment effect
0 1 2 3 4 5 6 7 8 9 10
Political Alignment
0
10
20
30
40
Percentage of observations
(h) Redist - No Adj.
Notes: This figure presents the marginal effects of the heterogeneous effects. Al l vs. 70% Pay is a categorical variable
that measures preferences for option 1 over option 2. D(All vs. 70% Pay) is an indicator variable that takes values of 1 if
the respondent prefers option 1 more, and 0 if he/she prefers option 2 more. Same logic for variables 70% vs. 50% Pay and
D(70% vs. 50% Pay). ‘Redist - All Pay is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise.
The same logic for panels f, g and h. ‘Redist - All Pay being the least redistributive option and ‘Redist - 50% Pay the most
redistributive. ‘Redist - No Adj. means no action.
Figure C4: Margin plots - concern inequality and poverty (other outcomes)
-.1
-.05
0
.05
.1
Treatment effect
0 1
Concern Inequality and Poverty
(a) All vs. 70%
-.04
-.02
0
.02
Treatment effect
0 1
Concern Inequality and Poverty
(b) D(All vs. 70% )
-.2
-.1
0
.1
.2
Treatment effect
0 1
Concern Inequality and Poverty
(c) 70% vs. 50%
-.08
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Concern Inequality and Poverty
(d) D(70% vs. 50% )
-.08
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Concern Inequality and Poverty
(e) Redist - All Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Concern Inequality and Poverty
(f) Redist - 70% Pay
-.05
0
.05
Treatment effect
0 1
Concern Inequality and Poverty
(g) Redist - 50% Pay
-.02
-.01
0
.01
.02
Treatment effect
0 1
Concern Inequality and Poverty
(h) Redist - No Adj.
Notes: This figure presents the marginal effects of the heterogeneous effects. Al l vs. 70% Pay is a categorical variable
that measures preferences for option 1 over option 2. D(All vs. 70% Pay) is an indicator variable that takes values of 1 if
the respondent prefers option 1 more, and 0 if he/she prefers option 2 more. Same logic for variables 70% vs. 50% Pay and
D(70% vs. 50% Pay). ‘Redist - All Pay is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise.
The same logic for panels f, g and h. ‘Redist - All Pay being the least redistributive option and ‘Redist - 50% Pay the most
redistributive. ‘Redist - No Adj. means no action.
42
Figure C5: Margin plots - beliefs in luck (other outcomes)
-.1
-.05
0
.05
.1
Treatment effect
0 1
Beliefs in luck
(a) All vs. 70%
-.04
-.03
-.02
-.01
0
.01
Treatment effect
0 1
Beliefs in luck
(b) D(All vs. 70% )
-.15
-.1
-.05
0
.05
Treatment effect
0 1
Beliefs in luck
(c) 70% vs. 50%
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Beliefs in luck
(d) D(70% vs. 50% )
-.08
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Beliefs in luck
(e) Redist - All Pay
-.04
-.02
0
.02
.04
.06
Treatment effect
0 1
Beliefs in luck
(f) Redist - 70% Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Beliefs in luck
(g) Redist - 50% Pay
-.03
-.02
-.01
0
.01
Treatment effect
0 1
Beliefs in luck
(h) Redist - No Adj.
Notes: This figure presents the marginal effects of the heterogeneous effects. Al l vs. 70% Pay is a categorical variable
that measures preferences for option 1 over option 2. D(All vs. 70% Pay) is an indicator variable that takes values of 1 if
the respondent prefers option 1 more, and 0 if he/she prefers option 2 more. Same logic for variables 70% vs. 50% Pay and
D(70% vs. 50% Pay). ‘Redist - All Pay is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise.
The same logic for panels f, g and h. ‘Redist - All Pay being the least redistributive option and ‘Redist - 50% Pay the most
redistributive. ‘Redist - No Adj. means no action.
Figure C6: Margin plots - poor child opportunity (other outcomes)
-.2
-.15
-.1
-.05
0
Treatment effect
0 1
Poor child opportunities
(a) All vs. 70%
-.06
-.04
-.02
0
Treatment effect
0 1
Poor child opportunities
(b) D(All vs. 70% )
-.15
-.1
-.05
0
Treatment effect
0 1
Poor child opportunities
(c) 70% vs. 50%
-.06
-.04
-.02
0
.02
Treatment effect
0 1
Poor child opportunities
(d) D(70% vs. 50% )
-.08
-.06
-.04
-.02
0
Treatment effect
0 1
Poor child opportunities
(e) Redist - All Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Poor child opportunities
(f) Redist - 70% Pay
-.02
0
.02
.04
.06
Treatment effect
0 1
Poor child opportunities
(g) Redist - 50% Pay
-.03
-.02
-.01
0
.01
Treatment effect
0 1
Poor child opportunities
(h) Redist - No Adj.
Notes: This figure presents the marginal effects of the heterogeneous effects. Al l vs. 70% Pay is a categorical variable
that measures preferences for option 1 over option 2. D(All vs. 70% Pay) is an indicator variable that takes values of 1 if
the respondent prefers option 1 more, and 0 if he/she prefers option 2 more. Same logic for variables 70% vs. 50% Pay and
D(70% vs. 50% Pay). ‘Redist - All Pay is an indicator variable that takes values of 1 if option 1 was chosen, and 0 otherwise.
The same logic for panels f, g and h. ‘Redist - All Pay being the least redistributive option and ‘Redist - 50% Pay the most
redistributive. ‘Redist - No Adj. means no action.
43
Figure C7: Treatment effects by country (with and without controls)
Treatment
estimate
-.4 -.2 0 .2 -.4 -.2 0 .2 -.4 -.2 0 .2
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay
Total Argentina Brazil Chile Colombia
C. Rica Guatemala Mexico Peru
(a) Without controls
Treatment
estimate
-.4 -.2 0 .2 -.4 -.2 0 .2 -.4 -.2 0 .2
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay
Total Argentina Brazil Chile Colombia
C. Rica Guatemala Mexico Peru
(b) With controls
Notes: Treatment effects, equivalent to the results in Table 2, Panels A (without controls) and C (including socioeconomic
controls and knowledge, beliefs, and perceptions), when all countries are pooled, and by country. Total treatment refers to the
pooled estimation. Outcome variables are the categorical measures described in Table 2. The standard errors are clustered at
the country level for the pooled sample, and are robust for the country specifications. Point estimates with 95% confidence
intervals.
Figure C8: Country Exclusion
Argentina
Brazil
Chile
Colombia
Costa Rica
Guatemala
Mexico
Peru
-.15 -.1 -.05 0 -.15 -.1 -.05 0 -.15 -.1 -.05 0
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay
Excluded country
Treatment effect
Notes: Treatment effects, equivalent to the results in Table 2, Panel A, when countries are excluded one-by-one. Outcome
variables are the categorical measures described in Table 2. Point estimates with 95% confidence intervals
44
Table C1: Main effect - showing controls
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
All vs. 70% Pay 70% vs. 50% Pay All vs. 50% Pay Preferred Choice
Cat D Cat D Cat D All Pay 70% Pay 50% Pay No Adj
Treated -0.051*** -0.017*** -0.051** -0.016 -0.114*** -0.035*** -0.040** 0.022 0.027** -0.008
(0.013) (0.005) (0.020) (0.012) (0.021) (0.008) (0.014) (0.014) (0.009) (0.005)
Bottom30Actual 0.238*** 0.049*** 0.128** -0.001 0.228** 0.035 0.036** -0.023** -0.043** 0.030***
(0.046) (0.012) (0.040) (0.016) (0.067) (0.023) (0.014) (0.009) (0.015) (0.008)
B40and50Actual 0.199*** 0.034** 0.094** -0.001 0.183*** 0.025 0.020* -0.011 -0.023* 0.014
(0.039) (0.010) (0.030) (0.010) (0.037) (0.014) (0.009) (0.011) (0.011) (0.008)
Educated -0.088*** -0.020* -0.063 -0.014 -0.082* -0.018 -0.031*** -0.002 0.032* 0.000
(0.022) (0.010) (0.036) (0.010) (0.043) (0.012) (0.008) (0.015) (0.016) (0.005)
Age 0.000 -0.000 -0.001 -0.001** -0.001 -0.001 0.000 -0.000 -0.001 0.000
(0.001) (0.000) (0.001) (0.000) (0.001) (0.001) (0.001) (0.000) (0.001) (0.000)
Female -0.024 -0.017 -0.024 -0.015 -0.013 -0.018 -0.004 0.027*** -0.022*** -0.002
(0.039) (0.014) (0.015) (0.008) (0.031) (0.010) (0.007) (0.005) (0.006) (0.006)
Unemployed -0.050 -0.014 0.003 0.005 -0.017 -0.002 -0.009 0.004 -0.005 0.010**
(0.033) (0.009) (0.019) (0.006) (0.052) (0.013) (0.009) (0.005) (0.006) (0.003)
InformalWorker -0.084** -0.021** -0.048 -0.014 -0.038 -0.009 -0.014 0.022** -0.005 -0.003
(0.033) (0.007) (0.027) (0.010) (0.035) (0.013) (0.011) (0.008) (0.013) (0.008)
Retired -0.035 0.005 -0.058 -0.014 -0.008 -0.013 -0.013 0.008 0.030 -0.025
(0.090) (0.023) (0.043) (0.010) (0.098) (0.026) (0.034) (0.031) (0.021) (0.015)
GovernmentSub 0.001 0.015 0.053 0.031** -0.029 -0.001 -0.007 0.028 0.001 -0.022*
(0.043) (0.012) (0.038) (0.010) (0.041) (0.012) (0.009) (0.019) (0.014) (0.012)
HouseholdSize 0.011* 0.001 0.002 -0.002 0.016* 0.005 0.002 -0.001 -0.002 0.001
(0.005) (0.002) (0.004) (0.002) (0.008) (0.003) (0.002) (0.002) (0.002) (0.002)
Bottom30Perceived -0.033 -0.016 -0.074 -0.021 -0.096** -0.025* 0.005 -0.028* 0.018* 0.005
(0.037) (0.012) (0.044) (0.014) (0.032) (0.012) (0.013) (0.014) (0.009) (0.007)
B40and50Perceived 0.004 0.000 -0.040 -0.017 -0.067** -0.015 0.003 -0.008 0.005 0.000
(0.017) (0.009) (0.032) (0.010) (0.025) (0.008) (0.007) (0.011) (0.012) (0.003)
KnowledgeTaxes -0.019 -0.003 -0.039 -0.008 -0.042* -0.003 0.007 -0.007 0.008 -0.008
(0.022) (0.008) (0.023) (0.009) (0.019) (0.006) (0.008) (0.010) (0.009) (0.006)
ConcernIneqPov -0.175*** -0.033** -0.066* -0.004 -0.145*** -0.030*** -0.050*** 0.021** 0.044* -0.014**
(0.040) (0.012) (0.031) (0.008) (0.036) (0.008) (0.011) (0.009) (0.019) (0.004)
TrustGov 0.019 0.017 0.071 0.043** 0.053 0.027 0.022 0.013 -0.026 -0.009
(0.052) (0.014) (0.048) (0.013) (0.064) (0.017) (0.013) (0.009) (0.017) (0.008)
BeliefsLuck 0.005 0.011 -0.028 0.003 -0.024 0.001 -0.038** 0.017* 0.009 0.012*
(0.031) (0.006) (0.038) (0.012) (0.035) (0.008) (0.015) (0.007) (0.016) (0.005)
PoorChildOpportunity -0.207*** -0.062*** -0.161*** -0.037*** -0.277*** -0.080*** -0.038*** -0.006 0.054*** -0.009
(0.027) (0.012) (0.018) (0.006) (0.020) (0.009) (0.011) (0.009) (0.011) (0.009)
PoliticalAlignment 0.063*** 0.018*** 0.045*** 0.011*** 0.064*** 0.017*** 0.018*** -0.005** -0.016*** 0.003
(0.013) (0.003) (0.008) (0.001) (0.014) (0.003) (0.003) (0.002) (0.003) (0.002)
Observations 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152 12,152
R-squared 0.045 0.030 0.023 0.015 0.051 0.034 0.034 0.008 0.026 0.012
Mean Dep. Var. 3.094 0.317 2.934 0.389 3.107 0.326 0.277 0.308 0.338 0.076
Mean Dep. Var. (control)