Discussion Paper No. 911

COMPARING THE INFLUENCE
OF CONFLICT ON THE PERCEPTIONSOF RICH AND POOR:TESTING THE HYPOTHESISOF ACEMOGLU AND ROBINSON
Eiji Yamamura

July 2014

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Comparing the influence of conflict on the perceptions ofrich and poor: testing the hypothesis of Acemoglu andRobinson

Eiji YAMAMURA,

Abstract
Conflict can cause negative externalities to arise, and this can result in economic
loss. Such externalities are also thought to influence individuals’ perceptions about
economic issues. Acemoglu and Robinson (2000) provide their hypothesis that thepolitical elite extend the franchise to avoid revolution or social unrest. For the
purpose of empirically testing this hypothesis, the present paper explores how thedegree of conflict between rich and poor people is associated with individual
preferences for income redistribution and perceptions regarding income differences.
This paper used cross-country individual-level data covering 26 countries andconsisting of 20,000 observations. After controlling for individual characteristics,
the key findings are as follows: (1) an individual is more likely to prefer income
redistribution policy in countries where people perceive conflict between rich andpoor to be high; (2) an individual is more likely to consider the income difference to
be too large in countries where people perceive conflict between rich and poor to behigh; and (3) after dividing the sample into high- and low-income earners, the above
key findings are only obtained for high-income earners and not for low-income
earners.

JEL classification: D63; D74; H23;
Keywords: Conflict; Income redistribution; Inequality; Perception.
1

1. Introduction
A Kuznetz curve demonstrates that inequality increases and then decreases in
the process of economic development (Kuznetz, 1955). This claim is mainly derived
from historical observations rather than theoretical explanations. The seminal workof Acemoglu and Robinson (2000) provided a theoretical model that suggested thatthe expansion of voting rights leads to redistribution policies. This theory explainsthat democratization triggers the implementation of redistribution policies, which
results in a fall in income inequality. Historical evidence from Western societies
shows that the elite ran oligarchies and enjoyed their benefits at the expense of therest of society. At a later date, these oligarchical political systems were reformed byextending the franchise. However, such political reform is thought to enhanceincome redistribution by increasing the tax on the elite, that is, the wealthy(Meltzer and Richard, 1981). Thus, this reduces the interest of the elite. If this istrue, the elite are opposed to political reform to maintain their interest. This also
raises the question of why the elite would extend the franchise. The main reason for
the transformation from an oligarchy to a democracy is that “the elite extended thefranchise in order to avoid a revolution or social unrest” (Acemoglu and Robinson
2000, p. 1168).
Today, more countries than ever are undergoing democratization. However,income inequality continues to exist and thus there are rich and poor groups withina country. In modern democratic societies, situations similar to oligarchies persist.
That is, social unrest followed by inequality seems to threaten the position of thewealthy 1. Accordingly, conflict between rich and poor is brought to public notice.
Current research has found via statistical methods a positive relationship between
economic inequality and social conflict (Esteban and Ray, 2011; Macours, 2011) 2.
Social conflict possibly leads people to consider income inequality to be higher than
the acceptable level. In this situation, people prefer redistributive policies todecrease the social unrest. The social conflict might inevitably influence perceived
income differences between groups and individuals’ preferences for a redistribution
Between 1990 and 2000 in Rwanda, as an outcome of various conflicts including civil
war and genocide, many people lost their lands and homes, especially those who wereland-rich before the conflict. Wealthier provinces experienced lower, even negative,
economic growth after the conflict (Justino and Verwimp, 2013).
2 A number of theoretical models show relations between inequality and conflictalthough conclusions vary among researchers (Robinson, 2001; Hutter, 2003; De Lucaand Sekeris, 2012).
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policy. Voors et al. (2012) conducted a field experiment and found that exposure toconflict impacts on perceptions such as discount rates. Furthermore, they provided
evidence that those who experienced conflict display altruistic behavior towards
their neighbors.
Some empirical works have examined the determinants of perceived income
inequality (e.g., Tomioka and Outake, 2005; Meagher and Wilson, 2008; Xu andGerand, 2010). A large number of existing works attempt to ascertain thedeterminants of preference for redistribution and to identify the mechanism forsuch a preference (e.g., Ravallion and Lokshin, 2000; Corneo and Grüner, 2002,
Alesina and Angeletos, 2005; Alesina and La Ferrara, 2005; Alesina and Guuliano,
2009; Klor and Shayo, 2010; Luttmer and Singhal, 2011; Dahlberg et al., 2012;
Bjornskov et al., 2013; Yamamura, 2012, 2014). Meager and Wilson (2008)
compared the perceived income differences and preference for redistribution bysuggesting basic statistics. Although empirical works have not been able to provide
sufficient evidence stating how social conflict is jointly associated with the perceived
income difference and preference for redistribution, Acemoglu and Robinson (2000,
2001) developed a theoretical model to clarify the relationship between conflict,inequality and redistribution 3. Thus, it is worthwhile to empirically investigate therelationship in modern society.
The aim of this paper is to explore the influence of the degree of conflict between
rich and poor on not only individuals’ perceived income difference but also on
preference for income redistribution. Furthermore, historical observations showthat social unrest has a large effect on the elite’s preference for democratization andtherefore redistribution. In modern society, inequality has a different influence on
the happiness of the rich and poor (Alesina et al., 2004). In Sweden, the effect ofimmigration on one’s preference for redistribution differs between different income
groups (Dahlberg et al., 2012). Therefore, this paper investigates how the effect ofperceived conflict is different between high- and low-income groups.
For this purpose, the present paper uses data from the International Social
Survey Program (ISSP), which includes more than 20,000 observations. The key
findings of this paper via various specifications estimated by an ordered probit
model are as follows: (1) an individual is more likely to prefer income redistribution
policy in countries where people perceive conflict between rich and poor to be high;There are number of theoretical studies concerning democracy and conflict (e.g.,Przeworski, 2005; Aslaksen and Torvik, 2006; Zhaohui, 2007; Adachi and Nakamura,2008).
3

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(2) an individual is more likely to consider income differences to be too large incountries where people perceive conflict between rich and poor to be high; (3) after
dividing the sample into high- and low-income earners, the above two key finding
are only obtained for high-income earners and not for low-income earners. The
contribution of this paper is that it empirically examines the mechanism proposedby Acemoglu and Robinson (2000) using recent micro-level data from modern
societies.
The remainder of this paper is organized as follows. In Section 2, the testable
hypotheses are presented. Data and the empirical method are explained in Section
3. Section 4 presents the estimation results and their interpretation. The final
section offers some conclusions.

2. Hypotheses
The opportunity cost of theft is low for people with a low wage rate. That is, even
if they are arrested and then sent to prison, the reduction of their income during theperiod is not so large and therefore the economic damage is low. Hence, incomparison with revenue from theft, its cost is smaller if the wage rate issufficiently low. Furthermore, poor people have emotional hostility towards the rich
if the conflict between rich and poor is high. This in turn also provides poor people
with an incentive to commit theft against the rich. Therefore, when conflict between
rich and poor is high, poor people are likely to engage in criminal behavior: poor
people break into the homes of rich people. Even if there is no economic motivation,
poor people’s hostility possibly causes them to commit violent crimes against therich. Naturally, rich people are threatened by such possibilities and are thenexposed to the danger of criminal acts, for example, attacks by poor people.
Therefore, income inequality is thought to lead to conflict between the rich and poor,
resulting in a negative externality on rich people. Under the condition that suchexternality does not exist, rich people do not prefer income redistribution because
the tax burden reduces their disposable income. However, assuming that thenegative externality of income inequality leads to a large cost, such as the risk oftheft or violent crime, rich people attempt to reduce the externality. For instance, if
income inequality decreases, the externality becomes small. Therefore, rich people
prefer redistribution policies when the externality is sufficiently large. Here,

Hypothesis 1 is advanced:
4Hypothesis 1:
An individual is likely to prefer income redistribution if he (she) lives in a country
where the conflict between rich and poor is high. This tendency is remarkable forindividuals with a high income.
An individual’s happiness is observed to be negatively associated with the income
level of others (Luttmer, 2005). If this holds true, larger inequality leads rich people
to feel happier. However, social unrest rises as inequality increases, leading to anegative influence on rich people’s happiness (Acemoglu and Robinson, 2000). Thus,
this externality is regarded as the cost of inequality for rich people. Inequality is the
optimum level when the marginal benefit of inequality is equal to its marginal cost.
At the optimum level of inequality, the conflict between rich and poor is also at an
optimum level. In other words, when the conflict is higher than the optimum level,
inequality is perceived to be larger than the optimum level. This inference leads to

Hypothesis 2.
Hypothesis 2:
An individual is likely to think that the income difference is too large if he (she)lives in a country where the conflict between rich and poor is high. This tendency isremarkable for individuals with high incomes.

3. Data and Methods
3.1. Data
ISSP data, which provides individual-level data, are used in the present paper.
ISSP surveys have been conducted several times since the 1980s. The theme of ISSP
surveys changes each year; ISSP 2009, which was conducted in August 2008,
focused on the issue of social inequality. Thus, ISSP 2009 provides valuable data to
examine the hypotheses proposed in the previous section. ISSP 2009 covers 26
countries and in each country respondents are asked various questions concerning
demography, social status, education level, economic condition and subjective
perception. The total sample size of ISSP 2009 includes over 20,000 observations,and is regarded as a sufficient sample size for statistical analysis 4. The majority of
The original sample consisted of 54,733 observations. However, data regarding the
key variables were not available for all for all respondents. Hence, the sample size used54

respondents are aged 18 years and older 5. Sampling procedures differed amongindividual countries: some were simple sample and others were multi-stage
stratified random samples. The mode of interview also differed among countries:
some were face-to-face interviews, paper-and-pencil or postal surveys. In general,
the fieldwork to collect the sample was conducted between 2008 and 2010 6.
The variables used in the regression estimations are shown in Table 1, which
provides definitions and basic statistics (mean, standard deviation).
One ISSP question concerning conflict (a key variable in the present study)
asked:“There are conflicts between poor and rich people. In your opinion, in yourcountry, how much conflict is there between poor and rich people?” To answer thequestion, respondents could choose one of four responses ( which are regarded as aproxy for the degree of perceived conflict), ranging from 1 (there are no conflicts) to
4 (very strong conflicts).
When the effect of individually perceived conflict on perceived income differences
is examined, the causality between them is ambiguous because the perceived
conflict is considered an endogenous variable. That is, those who perceived that thedifference is large are likely to perceive conflict to be high. This inevitably causes
endogeneity bias. To avoid such bias, this paper uses the degree of perceived conflictin the country of residence, rather than the individual’s trust level. The averagevalues within each country are calculated and these values are used as a measure of
the degree of conflict.
For the purpose of capturing the economic condition of a country of residence,
GINI (Gini coefficient before tax and transfers), GDP and POP (population) are used.
GINI data were sourced from World Bank data 7. GDP and POP data were collectedfrom the University of Pennsylvania’s Center for International Comparisons, Penn
World Table 7.1 8. This paper used 2008 data from these sources, being the year
when the ISSP 2009 was conducted. The information regarding individualin the estimation was reduced to 20,000.
5 Respondents from Finland, Norway, and Sweden are aged 15–74, 19–0, and 17–79,
respectively. Those of Japan are aged 16 years and older.
6 Fieldwork in Italy was conducted between 2011 and 2012.
7 See http://data.worldbank.org/indicator/SI.POV.GINI?page=1 (accessed on June 12,2013).
8 The data are available at the website of Penn World Table
https://pwt.sas.upenn.edu/php_site/pwt71/pwt71_form.php (accessed on August 25,2013).
6

characteristics sourced from ISSP data was matched with country characteristics
such as the degree of perceived conflict, GINI, GDP and POP. Thus, we were able toinvestigate how the characteristics of the residential country influence anindividual’s preference for income redistribution and perceived income difference.
With respect to individual characteristics, PRDIST are proxies for preferences
for income redistribution. A question from the ISSP 2009 asked respondents about
their degree of agreement with the statement that government should reduceincome inequality: there were five response options, ranging from “1 (strongly
disagree)” to “5 (strongly agree)”. PRDIST represents the values the respondents
chose. Figure 1 illustrates the distribution of PRDIST, and shows that the numberof respondents who chose 1, 2 or 3 is distinctly smaller than those who chose 4 or 5.
This implies that the shape of the histogram is skewed towards the right. In the
ISSP 2009, respondents were also asked about their degree of agreement with thestatement that income differences in their country are too large. There were five
response options, ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
DIFINCOM represents the values the respondents chose. The distribution of
DIFINCOM is demonstrated in Figure 2; the larger values show that more people
chose those responses. Thus, most people perceive the income difference to be toolarge. Considering Figures 1 and 2 shows that people are more inclined to preferredistribution and perceive the income difference to be too large.
It is plausible to argue that political ideology is one of determinants concerning
preferences for redistribution and so should be controlled for when preferences forincome redistribution are estimated (Alesina and Giuliano, 2009; Yamamura, 2012).
The ISSP contains the following question: “Where on the following scale would you
say your political views lie?” There are five response options: “1 (Liberal)” to “5(Conservative)”. Based on the responses to that question, a proxy was constructed tocapture political ideology effect. Political views are captured by dummies: CONSV_5
equals 1 when the response is 5, otherwise 0; CONSV_2, CONSV_3, and CONSV_4
are defined in the same manner.

3.2. Econometric Framework and Estimation Strategy
Table 2 shows that respondents belonging to a higher income group are lessinclined to prefer redistribution and to perceive the income difference to be larger.
Hence, relative income level is associated with an individual’s perception. In Figure
3, the vertical axis shows the average preference for redistribution (PRDIST) withina country. In Figure 4, the vertical axis shows the average perceived difference in7

income (DIFINCOM) within a country. In Figures 3 and 4, the horizontal rows show
the average perceived conflict (CONFLICT) within a country. A cursory examinationof Figure 3 reveals a positive association between CONFLICT and PRDIST.
Similarly, Figure 4 shows a positive association between CONFLICT and
DIFINCOM. These are in line with the hypotheses raised in Section 2. However,these relationships are observed when individual characteristics are not controlled.
A closer examination calls for a regression analysis using individual-level data
matched with the characteristics of one’s country of residence.
For the purpose of examining the hypotheses proposed the previous section, theestimated function of the baseline model takes the following form:

PRDIST(or DIFINC)ik = α1 CONFLICTk + α2GINIk + X’Β+εi
X: Vector of characteristics of country’s and individual’s characteristics
Β: Vector of coefficients of country’s and individual’s characteristics,
where PRDIST(or DIFINC)ik represents the dependent variable for individual i andcountry k. Regression parameters are represented by α. As explained earlier, values
for PRDIST and DIFINC range from 1 to 5 and an ordered probit model was used to
conduct the estimations. The error term is represented by εi. It is reasonable toassume that the observations may be spatially correlated within a country, as thecountry of one agent may well relate to the preference of another in the same
country. To control such spatial correlation in line with this assumption, the Statacluster command was used and z-statistics were calculated using robust standard
errors. The advantage of this method is that the magnitude of spatial correlation
can be unique to each country.
Regarding the control variables included in X, GDP and POP are included tocapture the economic condition of each country. Furthermore, according to the“prospect of upward mobility” (POUM) theory (Bénabou and Ok, 2001), people who
expect to move up the income scale are unlikely to support a redistribution policy
even when they are currently poor. Hence, the sign for GDP is likely to become
negative when PRDIST is the dependent variable. In contrast, people do not
perceive the income difference as high. Hence, the coefficient of GDP is likely to
become negative when DIFINCOM is assessed. If inequality increases social
problems such as crime, then inequality leads people to perceive the income
difference to be large and prefer redistribution. Thus, the coefficient of GINI ispredicted to be positive in the estimation when PRDIST and DIFINCOM aredependent variables.
Turning to the economic condition of individuals, people tend to compare their
8

income with that of surrounding people (Luttmer, 2005). As exhibited in Table 2, an
individual’s income position seems appropriate to capture the income effect. Hence,
the relative income levels in each country are considered. For this purpose, threedummy variables are constructed: HIGHINCOM (respondents belong to the 25th
percentile income group), MIDINCOM (respondents belong to the income groupbetween the 25th and 75th percentiles), and LOWINCOM (respondents belong to
the 75th percentile income group). In addition, to capture wealth level, dummy
variables to measure savings, stocks and bonds are constructed: NOSTOC,
SAMLSTOC, MEDSTOC, LARSTOC and TOPSTOC. Furthermore, dummy
variables are created to measure home or apartment: DEBTHOM, NOSHOM,
SMALHOM, MEDHOM, LARGHOM and TOPHOM. Previous studies controlled forindividuals’ demographic and social status characteristics (e.g., Ravallian and
Lokshin, 2000; Corneo and Gruüner, 2002; Ohtake and Tomioka, 2004; Alesina and
La Ferrara, 2005; Rainer and Seidler, 2008; Alesina and Giuliano, 2009; Yamamura,2012a). Thus, this paper incorporates AGE, SCHOOL, MALE, MARRI, and DIVO
as independent variables. Perceptions about inequality and income difference arethought to depend not only on economic conditions but also on individuals’ politicalviews. For the purpose of capturing political views, CONSV_2–CONSV_5 areincluded and CONSV_1 (liberal view) is the reference group. Liberal views are
generally considered to support left-wing policies such as political income
redistribution. Accordingly, the coefficients of CONSV_2–CONSV_5 are expected tobe negative. In addition, the absolute value of the coefficient CONSV_5 is expected
to be the largest among them. In addition, types of employment should beconsidered. Public sector employees would not like to lose their jobs as a result of agovernment downsize. Hence, public sector workers are thought to have a positive
view about the role of government because they are likely to keep their jobs. With
the aim to capture such an effect, respondents’ jobs are captured by incorporating
WOKGOV, WOKPUB, WOKFIRM, WOKSELF, WOKOTHE and WOKNO.

4. Estimation Results
The estimation results are exhibited in Tables 3, 4, and 5. The results of Table 3
are based on the full sample. After dividing the sample into high- and low-income
groups, Table 4 shows the results using the low-income sample while Table 5 shows
the results using the high-income sample. Furthermore, in each table, columns(1)–(3) present results of PRDIST while columns (4)–(6) present the results of9

DIFINCOM. For a robustness check of the results, various independent variables
are used in different columns. In columns (1) and (4) of each table, all control
variables are incorporated as independent variables (however, the sample size issmaller than in other columns because information about some control variables
was not available). In each table, the coefficients of the independent variables arereported 9.
Table 3 shows that the coefficient of CONFLICT is positive, being statisticallysignificant at the 1 percent level in columns (1)–(3). This is consistent with theprediction concerning the preference for redistribution. In contrast, the coefficient of
CONFLICT is positive and statistically significant in columns (4)–(5). This iscongruent with the prediction concerning the perceived income difference. Turning
to the control variables, the results of the individual-level variables are shown in
Table 3. Consistent with Table 2, HIGHINCOM is negative and statisticallysignificant at the one percent level in columns (1)–(6). That is, high-income earners
are less likely to support a redistribution policy and they consider the income
difference to be small. LARSTOC and TOPSTOC are negative and statisticallysignificant at the 1 percent level in all columns. This is congruent with theprediction that high-income earners do not prefer redistribution and they do not
perceive the income difference to be large. With respect to political views, CONSV_2,
CONSV3, CONSV4 and CONSV5 are negative and statistically significant in all
estimations. This is convincing because conservative people are thought to beagainst progressive policies such as income redistribution. Concerning employment
type, on the condition that WOKGOV is the default variable, WOKPUB, WOKFIRM,WOKSELF and WOKOTHE are negative in columns (1) and (4). Furthermore,
WOKFIRM and WOKSELF are statistically significant. This implies that comparedwith other kinds of employment, government employees are more likely to preferredistribution and perceive the income difference to be large. That is, government
employees consider that it is the government’s role to decrease inequality, thusincreasing the need for government and thereby protecting their jobs.
With respect to Tables 4 and 5, the results for CONFLICT relate to Hypotheses 1
The marginal effects of PRIDST (and DIFINCOM) can be calculated for each value(Greene, 2008, p. 831–835). That is, their marginal effect on the probability that
PRDIST (and DIFINCOM) is 5, their marginal effect on the probability that PRDIST(and DIFINCOM) is 4, their marginal effect on the probability that PRDIST (andDIFINCOM) is 3, their marginal effect on the probability that PRDIST (andDIFINCOM) is 2, and their marginal effect on the probability that PRDIST (andDIFINCOM) is 1. Please note, the results of the marginal effects are not reported
because of space limitations.
109and 2. Table 4 reports that the coefficient of CONFLICT is positive in columns(1)–(6). However, it is interesting to observe that CONFLICT is not statisticallysignificant, with the exception of column (3). Based on this result, the following
argument can be derived: for high-income earners, the perceived conflict is not
associated with a preference for redistribution and perceived income difference. In
contrast, Table 5 shows that the coefficient of CONFLICT is positive andstatistically significant at the 1 percent level in all columns. Therefore, it can beargued that for high-income earners, the perceived conflict is positively associatedwith a preference for redistribution and a perceived income difference. Furthermore,
the coefficient of CONFLICT is approximately 0.70 in columns (1)–(3) of Table 5,
which is two times larger than the coefficient of CONFLICT in columns (1)–(3) of
Table 4. Similarly, the coefficient of CONFLICT is approximately 1 in columns(4)–(6) of Table 5, being four times larger than the coefficient of CONFLICT shownin columns (4)–(6) of Table 5. To sum the various estimated results presented thus
far, the estimation results examined in this section strongly support Hypotheses 1
and 2.
Expressive behavior (Hillman, 2010) explains, to some extent, the reason why
the effect of social conflict has a different effect on an individual’s perceived income
difference and preference for redistribution. According to the expressive voting
hypothesis, individuals vote to express their views regarding particular issues, even
if they do not intend to affect the outcomes of the election (e.g., Tullock, 1971;
Copeland and Laband, 2002; Sobel and Wagner, 2004). As a consequence,individuals vote for a certain policy despite the fact that the actual implementationof the policy would reduce their material utility. High-income earners consider
income inequality to be too large, which expresses their sympathy to low-income
earners. High-income earners’ support for income redistribution is thought toreflect their support for the generosity of the welfare state. These expressions
increase the utility of high-income earners. The estimation results in this paper
were obtained using survey data. Survey responses can be interpreted as expressive
because the responses have no effect on redistribution policies in any way. There isno material loss from expressing generosity regarding the welfare state even when
expressive utility increases by signaling conformity with group-defined equality
norms (Tullock, 1971).

11

5. Conclusions
Conflicts cause negative externalities, which in turn result in economic losses.
Such externalities are also thought to influence individuals’ perceptions about
economic issues. The larger the conflict between rich and poor, the morehigh-income earners are likely to be the target of criminal behavior. For instance,high-income earners are more inclined to fear burglary. Social unrest puts pressure
on high-income earners to reconcile such conflict. Thus, the argument in this paper
is that high-income earners consider inequality to be too large when the conflict
increases to a level that threatens their property and safety. However, high-income
earners support income redistribution policies if the burden of progressive tax issmaller than the cost of the externality of conflict.
To test these inferences, this paper explored how the degree of conflict between
rich and poor is associated with individual preferences for income redistribution as
well as perceived differences in income. Cross-country individual-level data wereused for statistical estimations. After controlling for individual characteristics, thekey findings are as follows: (1) an individual is more likely to prefer an income
redistribution policy in countries where people perceive the conflict between richand poor to be high; (2) an individual is more likely to consider the income
difference to be too large in countries where people perceive the conflict between
rich and poor to be high; (3) after dividing the sample into high- and low-income
earners, the above two finding are only obtained for high-income earners and not for
low-income earners.
The main contribution of the present paper is twofold: first, this paper is the first
to investigate the effect of conflict between rich and poor, not only regarding
perceived income differences but also on preferences for redistribution; second,
these effects differ according to income group. Following previous studies(Yamamura 2012, 2014; Dahlberg et al., 2012), this paper sheds light on differences
in income levels to investigate how socio-economic circumstances affect perceptions
regarding the welfare state. The findings of this paper empirically support the claim
theoretically proposed by Acemoglu and Robinson (2000).

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Sobel, Russell S., Wagner, Gary A., 2004. Expressive voting and government
redistribution: testing Tullock’s charity of the uncharitable. Public Choice, 119,143-159.
Tullock, Gordon, 1971. The charity of the uncharitable. Western Economic Journal,
9, 379-392.
Voors, Maarten J., Nillesen, Eleonora E.M., Verwimp, Philip, Bulte, Erwin H.,
Lensink, Robert, Van Soest, Daan P., 2012. Violent conflict and behavior: A field
experiment in Burundi. American Economic Review, 102(2), 941-964.
Xu, Ping, Garand, James C., 2010. Economic context and American’s perception ofincome inequality. Social Science Quarterly, 91, 1220-1241.
Yamamura, Eiji., 2012. Social capital, household income, and preferences for income
redistribution. European Journal of Political Economy, 28(4), 498-511.
Yamamura, Eiji, 2014. Trust in government and its effect on preferences for income
redistribution and perceived tax burden. Forthcoming in Economics of Governance.
Zhaohui, Bi, 2007. Income inequality, redistribution and democratization. Economics
Bulletin, 4(35), 1-10.

17

4
3
Density
2
1
0
1

2

3

4

5

Figure 1. Distribution of views regarding preference for income redistribution

18

5
4
3
Density
2
1
0
1

2

3

4

5

Figure 2. Distribution of views regarding perceived income difference in countryof residence

19

4.5
Preference for Redistribution
3
3.5
4

CyprusUkraineRussiaPortugal
Italy
Hungary
Slovenia
TurkeyCroatia
LatviaBulgaria
IsraelEstonia France
Argentina
PolandChina
SlovakSpain
Finland
South Korea
Austria
IcelandChile
BelgiumSouth Africa
Czech
Germany
TaiwanUK
JapanSweden
Switzerland
Venezuela
Philippines
NorwayDenmark Australia
New Zealand

2.5

United States

1.5

2

2.5
Average Perceived Conflict3

3.5

Figure 3. Association between average perceived conflict and average preference
for income redistribution20

5

Hungary

Perceived Income Difference
3.5
4
4.5

Ukraine
Italy
Portugal

FranceEstonia
SlovakLatviaSlovenia
Bulgaria
Croatia
GermanySouth
AfricaIsraelAustriaPoland
Iceland
TaiwanCzech
China
Argentina
Switzerland Spain Chile
Japan

RussiaTurkeySouth Korea

UK
SwedenAustraliaFinland
Belgium
CyprusNew ZealandVenezuela
United States

Denmark
Norway3

Philippines

1.5

2

2.5
Average Perceived Conflict3

3.5

Figure 4. Association between average perceived conflict and average perceived
income difference in country of residence21

Table 1
Definitions and basic statistics of each variable
Definitions
Country
characteristics
CONFLICTGINICONFLICT is the average value of proxyfor degree of conflict in a country
Question: In all countries, there areconflicts between poor and rich people. In
your opinion, in <country> how muchconflict is there between poor and richpeople?
There are 5 responses, which are regarded
as proxies for degree of conflict:1 (there are no conflicts) – 5 (very highconflicts)
Gini coefficients before taxes and transfers
in 2008 (World Bank)

Mean

Standard
deviation
2.44

0.34

0.45

0.04

GDP

GDP (Millions of US dollars)

34,0698,316

POPPopulation (thousands)

55,33381,046

Degree of agreement with the statementthat the government should reduce income
inequality:
1 (strongly disagree) – 5 (strongly agree)
Degree of agreement with the statementthat income differences in country are toolarge:
1 (strongly disagree) – 5 (strongly agree)
Equals 1 if the respondent’s householdincome is higher than 25th percentile(Group > 25 percentile), otherwise 0.
Equals 1 if the respondent’s householdincome is between 25th and 75th
percentile of household income (25thpercentile > = Group > = 75 the percentile),
otherwise 0
Equals 1 if the respondent’s householdincome is lower than 75th percentile(Group < 75th percentile), otherwise 0
Equals 1 if the respondent’s wealth(savings, stocks, or bonds) is just debt,
otherwise 0
Equals 1 if the respondent has no wealth(savings, stocks, or bonds), otherwise 0

3.61

1.21

Individual
characteristics

PRIDIST

DIFINCOMHIGINCOM
MIDINCOM

LOWINCOM
DEBTSTOCNOSTOC

22

4.08

0.99

0.26

___

0.59

___

0.15

___

0.10

___

0.20

___

Equals 1 if the respondent’s wealth(savings, stocks, or bonds) is larger than 0
but smaller than the expected mean
wealth, otherwise 0
Equals 1 if the respondent’s wealth(savings, stocks, or bonds) is equivalent to
the expected mean wealth using external
information, otherwise 0
Equals 1 if the respondent’s wealth(savings, stocks, or bonds) is larger thanthe expected mean wealth but smaller
than the highest category, otherwise 0
Equals 1 if the respondent’s wealth(savings, stocks, or bonds) belongs to thehighest category (no upper limitation),otherwise 0
Equals 1 if the respondent’s wealth (homeor apartment) is just debt, otherwise 0

0.41

___

0.05

___

0.19

___

0.05

___

0.06

___

NOSHOM

Equals 1 if the respondent has no wealth(home or apartment), otherwise it takes 0

0.18

___

SMALHOM

0.34

___

0.08

___

0.31

___

0.03

___

AGE

Equals 1 if the respondent’s wealth (homeor apartment) is larger than 0 but smaller
than the expected mean wealth, otherwise
0
Equals 1 if the respondent’s wealth (homeor apartment) is equivalent to the
expected mean wealth using external
information, otherwise 0.
Equals 1 if the respondent’s wealth (homeor apartment) is larger than the expected
mean wealth but smaller than the highest
category, otherwise 0
Equals 1 if the respondent’s wealth (homeor apartment) belongs to the highest
category (no upper limitation), otherwise 0
Ages

49.9

15.1

SCHOOLYears of schooling

13.3

4.03

MALE

Equals 1 if respondent is male, otherwise 0

0.51

___

MARRI

Equals 1 ifotherwise 0

respondentismarried,

0.62

___

DIVO

Equals 1 ifotherwise 0

respondentisdivorced,

0.08

___

CONSV_1

Concerning political views, equals 1 if
respondent chooses 1, otherwise 0
1 (Liberal) – 5 (Conservative)
Concerning political views, equals 1 if
respondent chooses 2, otherwise 0
1 (conservative) – 5 ( progressive)

0.09

___

0.35

___

SMALSTOCMEDSTOCLARSTOCTOPSTOCDEBTHOMMEDHOM

LARGHOMTOPHOMCONSV_2

23

Concerning political views, equals 1 if
0.21___
respondent chooses 3, otherwise 0
1 (conservative) – 5 (progressive)
CONSV_4
Concerning political views, equals 1 if
0.31___
respondent chooses 4, otherwise 0
1 (conservative) – 5 (progressive)
CONSV_5
Concerning political views, equals 1 if
0.04___
respondent chooses 5, otherwise 0
1 (conservative) – 5 (progressive)
WOKGOV
Equals 1 if respondent works for
0.26___
government, otherwise 0
WOKPUB
Equals 1 if respondent works for a publicly
0.07___
owned firm, otherwise 0
WOKFIRM
Equals 1 if respondent does not work for
0.52___
government, a publicly owned firm and is
not self-employed, otherwise 0
WOKSELF
Equals 1 if respondent is self-employed,
0.14___
otherwise 0
WOKOTHE
Equals 1 if respondent works for other
0.002
___
than WOKGOV, WOKPUB, WOKFIRM,WOKSELF, otherwise 0. Other works(not )WOKNO
Equals 1 if respondent is not in paid
0.005
___
employment, otherwise 0.
Note:
GINI
is
obtainedfromOECD(http://stats.oecd.org/Index.aspx?DataSetCode=IDD#. accessed on June 27, 2013).
GDP
and
POP
are
from
Penn
World
Table
7.1
(http://www.rug.nl/research/ggdc/data/penn-world-table. accessed on June 27, 2013).
Other variables sourced from ISSP 2009.
Sample is equivalent to that used in column (1) of Table 3. Question about political
position varies according to country. However, in general it asks “To what degree do you
think yourself politically liberal or conservative?”
CONSV_3

Table 224

Preference for redistribution and perceived income difference:
average values of each income category.
PRIDIST

DIFINCOM

High-income group:Group > 25th percentile.

3.78

4.19

Middle-income group:
25th percentile > = Group > = 75th
percentile.
Low-income group:
75th percentile > = Group

3.82

4.21

4.01

4.29

Table 3
Estimation results based on full sample (ordered probit)
25

Estimation for preference forincome redistribution
Dependent variable: PRIDIST
(1)
(2)
(3)

Estimation for perceived income
difference
Dependent variable: DIFINCOM
(4)
(5)
(6)

0.79***(3.94)

0.74***(3.64)

0.67***(4.37)

0.63**(2.50)

0.59**(2.51)

0.56***(2.67)

GINI

3.13**(2.58)

3.19***(2.61)

2.99**(3.24)

1.66(1.16)

1.79(1.26)

1.75(1.42)Ln (GDP)−0.63**(−2.37)−0.59**(−2.28)−0.58***(−3.33)−0.64***(−2.68)−0.64***(−2.84)−0.63***(−3.51)

Ln (POP)−0.18**(−2.40)−0.17**(−2.30)−0.15**(−2.54)−0.06(−0.90)−0.06(−0.83)−0.07(−1.21)Country
characteristics
CONFLICT

Individual
characteristics
MIDINCOM<Reference group><Reference group>

HIGINCOM−0.18***(−4.55)−0.19***(−4.50)−0.18***(−4.55)−0.22***(−5.32)−0.22***(−5.28)−0.20***(−4.70)LOWINCOM

0.05(1.40)

0.06(1.26)

0.05(1.40)

0.001(0.01)

0.002(0.04)

0.007(0.20)

DEBTSTOC<Reference group><Reference group>

NOSTOC

0.01(0.20)

0.01(0.09)−0.001(−0.04)0.03(0.36)

0.01(0.07)−0.004(−0.06)SMALSTOC−0.07(−1.58)−0.07(−1.44)−0.12***(−2.71)−0.03(−0.49)−0.05(−0.82)−0.10(−1.65)MEDSTOC−0.06(−1.01)−0.07(−1.16)−0.15***(−2.90)−0.10(−1.38)−0.12*(−1.74)−0.19***(−3.24)LARSTOC−0.21***(−4.72)−0.21***(−4.62)−0.25***(−5.68)−0.19***(−2.93)−0.21***(−3.47)−0.25***(−4.05)TOPSTOC−0.32***(3.29)−0.31***(2.94)−0.43***(3.84)−0.35***(−5.35)−0.38***(−5.39)−0.46***(−5.77)DEBTHOM<Reference group>

NOSHOM−0.01(0.01)

0.002(0.03)−0.01(−0.28)0.05(0.61)

0.06(0.63)

0.07(0.88)

SMALHOM−0.06(−0.93)−0.04(−0.70)−0.07*(−1.82)0.01(0.20)

0.03(0.39)

0.02(0.42)MEDHOM

0.02(0.21)

0.04(0.41)−0.02(−0.28)0.09(0.80)

0.10(0.91)

0.07(0.73)LARGHOM−0.09(−0.71)−0.08(−0.78)−0.14(−1.54)−0.01(−0.05)0.01(0.05)−0.02(−0.28)TOPHOM−0.13(−1.13)−0.13(−1.26)−0.24**(−2.35)−0.19(−1.60)−0.18(−1.56)−0.21*(−1.93)<Reference group>

26

AGE

0.003***(2.60)

0.003***(3.04)

0.003***(3.70)

0.007***(5.70)

0.007***(5.88)

0.006***(5.89)SCHOOL−0.02***(−2.86)−0.02**(−2.43)−0.01**(−2.27)−0.01***(−2.67)−0.01**(−2.52)−0.01**(−2.31)MALE−0.05*(−1.94)−0.07***(−2.81)−0.09***(−4.00)−0.07***(−2.67)−0.09***(−3.20)−0.10***(−3.47)

MARRI

0.01
(0.65)

0.01(0.62)

0.02(0.92)

0.06*(1.86)

0.06*(1.87)

0.06**(2.32)

DIVO−0.01(−0.39)−0.02(−0.55)−0.003(−0.09)0.06(1.35)

0.06(1.52)

0.10***(2.85)CONSV_1<Reference group><Reference group>

CONSV_2−0.30***(−2.81)−0.29***(−2.84)−0.29***(−2.68)−0.26**(−2.50)CONSV_3−0.54***(−4.86)−0.54***(−4.86)−0.49***(−4.13)−0.47***(−4.00)CONSV_4−0.86***(−6.17)−0.87***(−6.19)−0.80***(−6.45)−0.78***(−6.18)CONSV_5−0.50***(−3.01)−0.49***(−3.01)−0.49***(−3.27)−0.46***(−3.16)WOKGOVWOKPUBWOKFIRMWOKSELF
WOKOTHE
WOKNO<Reference group><Reference group>−0.15**(−2.53)−0.14***(−5.97)−0.19***(−4.60)−0.17(−0.44)−0.004(−0.03)0.24***(3.84)−0.04(−0.65)−0.06**(−2.11)−0.13***(−3.51)−0.27(−1.30)0.20*(1.84)
0.24**(2.52)

Marginal effect
0.23***
0.22***
0.22**
0.22**of CONFLICT:(3.52)(4.19)(1.51)*Pr (Y = 5)
(2.66)
Log−18,924−20,267−28,391−16,059−17,155−23,814
pseudo-likeliho
odObservations.
13,716
14,655
20,573
13,777
14,716
20,688
Note: Values without parentheses are coefficients. Values in parentheses arez−statistics calculated using robust standard errors clustered for per country. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

Table 4
Estimation results based on low-income sample (ordered probit)
27

Estimation for preference forincome redistribution
Dependent variable: PRIDIST
(1)
(2)
(3)

Estimation for perceived income
difference
Dependent variable: DIFINCOM
(4)
(5)
(6)

0.32
(1.21)

0.28(0.97)

0.39*(1.85)

0.25(1.08)

0.23(0.98)

0.32(1.45)

GINI

2.43*(1.66)

2.74*(1.83)

3.05***(2.71)

1.56(1.21)

1.69(1.31)

1.61(1.39)Ln (GDP)−0.71***(−3.10)−0.71***(−2.80)−0.60***(−3.59)−0.80***(−3.44)−0.80***(−3.15)−0.60***(−2.98)

Ln (POP)−0.15**(−2.14)−0.14*(−1.78)−0.13**(−2.05)−0.07(−1.15)−0.05(−0.84)−0.06(−1.12)

Country
characteristics
CONFLICT

Individual
characteristics
DEBTSTOC<Reference group><Reference group>

NOSTOC

0.21**(2.06)

0.16*(1.76)

0.07(1.18)

0.04(0.33)−0.02(−0.20)−0.05(−0.57)SMALSTOC

0.05(0.47)

0.01(0.12)−0.09(−1.14)−0.05(−0.73)−0.13*(−1.88)−0.20***(−2.67)MEDSTOC

0.24(1.34)

0.16(0.93)−0.003(−0.03)−0.13*(−1.69)−0.20(−1.16)−0.27**(−2.00)LARSTOC−0.10(−0.85)−0.15(−1.47)−0.25***(−2.62)−0.15(−1.31)−0.24***(−2.70)−0.32***(−4.06)

TOPSTOC

0.02(0.13)

0.04(0.23)−0.13(−0.91)0.29(1.35)

0.11(0.60)−0.05(−0.49)DEBTHOM<Reference group>

NOSHOM−0.31**(−2.28)−0.20*(−1.66)−0.24***(−2.63)−0.18(−1.64)−0.08(−0.97)−0.09(−1.13)

SMALHOM−0.27*(−1.82)−0.15(−1.16)−0.18*(−1.88)−0.14(−1.08)−0.05(−0.44)−0.04(−0.52)MEDHOM−0.24(−1.31)−0.11(−0.69)−0.18*(−1.69)−0.13(−1.00)−0.05(−0.46)LARGHOM−0.49***(−3.18)−0.36***(−2.64)−0.38***(−3.45)−0.30(−1.61)−0.18(−1.13)−0.15(−1.17)TOPHOM−0.15(−0.74)−0.10(−0.47)−0.23(−1.16)−0.56***(−3.39)−0.39***(−2.99)AGE

0.001(0.87)

0.001(0.82)

0.002(1.35)

0.003(1.62)−
0.45***(−3.57)0.003**(1.94)SCHOOL−0.01(−1.10)−0.01(−0.94)−0.01(−0.90)−0.01(−0.73)−0.01(−0.64)−0.01(−0.61)MALE−0.08*(−1.73)−0.07*(−1.74)−0.05(−1.58)−0.09***(−2.63)−0.09***(−2.91)−0.06*(−1.67)<Reference group>

28

−0.04
(−0.35)0.003**(2.05)MARRI

0.08(1.33)

0.11*(1.84)

0.05(0.89)

0.16*(1.96)

0.19**(2.35)

0.13*(1.74)

DIVO

0.04(0.76)

0.08(1.43)

0.06(1.65*)

0.04(0.63)

0.09(1.34)

0.13**(2.54)CONSV_1<Reference group><Reference group>

CONSV_2−0.29**(−2.32)−0.26**(−2.40)−0.27***(−2.66)−0.24***(−2.71)CONSV_3−0.44***(−3.08)−0.42***(−3.60)−0.36***(−2.70)−0.32***(−2.78)CONSV_4−0.69***(−4.15)−0.62***(−4.33)−0.69***(−5.26)−0.60***(−5.35)CONSV_5−0.37**(−2.11)−0.36**(−2.46)−0.36*(−1.70)−0.38**(−2.10)WOKGOVWOKPUBWOKFIRMWOKSELF
WOKOTHE
WOKNO<Reference group><Reference group>−0.11(−1.05)0.005(0.12)
0.03(0.45)
0.95(1.58)
0.22(1.62)
0.11(1.22)−0.01(−0.13)0.10(1.63)
0.11(1.45)
0.46(1.26)
0.55***(2.79)
0.10(1.09)

Marginal effect
0.10
0.14*
0.09
0.13
of CONFLICT:(0.97)(1.84)(0.98)(1.45)Pr (Y = 5)Log−2,739−3,068−4,367−2,263−2,534−3,644
pseudo-likeliho
odObservations.
2,074
2,229
3,380
2,082
2,306
3,401
Note: Values without parentheses are coefficients. Values in parentheses arez−statistics calculated using robust standard errors clustered per country. *, **, and ***indicate significance at the 10%, 5%, and 1% levels, respectively.

Table 5
Estimation results based on high-income sample (Ordered Probit)
29

Estimation for preference forincome redistribution
Dependent variable: PRIDIST
(1)
(2)
(3)

Estimation for perceived income
difference
Dependent variable: DIFINCOM
(4)
(5)
(6)

0.97***(4.27)

0.88***(4.08)

0.71***(4.10)

1.09***(3.60)

1.09***(3.40)

0.82***(2.90)

GINI

3.22***(2.66)

3.10***(2.61)

2.56**(2.26)

3.25**(2.10)

3.23**(2.10)

3.00*(1.88)Ln (GDP)−0.63**(−2.26)−0.61**(−2.18)−0.67***(−3.67)−0.58**(−2.14)−0.56**(−2.12)−0.68***(−3.35)

Ln (POP)−0.18**(−2.30)−0.17**(−2.33)−0.14**(−2.46)−0.11(−1.38)−0.10(−1.31)−0.11(−1.64)

Country
characteristics
CONFLICT

Individual
characteristics
DEBTSTOC<Reference group><Reference group>

NOSTOC−0.05(−0.52)−0.04(−0.44)0.02(0.35)

0.11(0.82)

0.12(0.90)

0.18*(1.84)SMALSTOC−0.15(−1.64)−0.14(−1.49)−0.10(−1.55)−0.07(−0.66)−0.05(−0.55)0.01(0.09)MEDSTOC−0.06(−0.80)−0.06(−0.77)−0.08(−1.12)−0.12(−1.09)−0.11(−0.98)−0.04(−0.52)LARSTOC−0.25***(−2.74)−0.25***(−2.70)−0.22***(−3.23)−0.19*(−1.75)−0.19*(−1.73)−0.12(−1.20)TOPSTOC−0.41***(−3.70)−0.41***(−4.06)−0.50***(−5.04)−0.37***(−3.18)−0.38***(−3.17)−0.38***(−3.14)DEBTHOM<Reference group>

NOSHOM

0.15(1.10)

SMALHOM

0.11(0.79)<Reference group>
0.09(1.16)

0.01(0.05)−0.03(−0.25)−0.05(−0.90)MEDHOM

0.14(0.99)

0.10(0.69)LARGHOM

0.08(0.53)TOPHOM
AGE

0.001
0.01)
04

−
( −
0.0

01
06)
0.001

0.
(0.
−

0.0

1
14)
0.02

(0.
−

0.02
(0.28)

(0.
03)
0.11
(0.61)

( −
0.01)
0.11
(0.61)

( −
0.25)
0.03
(0.29)

0.03(0.23)−0.06(−0.61)0.01(0.07)

0.005(0.03)−0.08(−0.60)−0.05(−0.32)−0.10(−0.60)−0.24*(−1.89)−0.21(−1.14)−0.21(−1.12)−0.31*(−1.96)0.01***(2.94)

0.01***(2.69)

0.01***(2.93)

0.01***(5.20)

0.01***(4.71)

0.01***(5.00)

30

SCHOOL−0.01(−1.48)−0.01(−1.22)−0.01(−1.09)−0.01(−1.57)−0.01(−1.42)−0.01(−1.10)MALE−0.07*(−1.91)−0.10**(−2.33)−0.12***(−2.95)−0.10**(−2.20)−0.12**(−2.39)−0.11**(−2.40)MARRI−0.05*(−1.67)−0.06**(−2.14)−0.03(−1.08)−0.05(−1.12)−0.06(−1.23)−0.03(−1.01)

DIVO

0.03(0.26)

0.02(0.21)

0.08(0.98)

0.09(0.66)

0.08(0.60)

0.17*(1.84)CONSV_1<Reference group><Reference group>

CONSV_2−0.37***(−2.97)−0.37***(−3.00)−0.39**(−2.55)−0.35**(−2.33)CONSV_3−0.66***(−4.43)−0.67***(−4.44)−0.60***(−3.33)−0.58***(−3.20)CONSV_4−1.02***(−6.69)−1.03***(−6.61)−0.95***(−5.49)−0.93***(−5.31)CONSV_5−0.64**(−2.51)−0.66**(−2.51)−0.66***(−3.29)−0.61***(−2.80)WOKGOVWOKPUBWOKFIRMWOKSELF
WOKOTHE
WOKNO<Reference group><Reference group>−0.17*(−1.94)−0.13**(−2.36)−0.27***(−3.63)−0.28(−0.53)−0.07(−0.33)0.26***(4.17)−0.07(−0.78)−0.07(−1.10)−0.22***(−2.99)−0.23(−1.39)0.01(0.04)
0.39***(3.65)

Marginal effect
0.23***
0.21***
0.35***
0.30***of CONFLICT:(3.99)(4.00)(3.45)(2.89)Pr (Y = 5)Log
−5,157−5,359−7,419−4,555−4,721−6,391
pseudo−likelih
ood
Observations.
3,610
3,745
5,133
3,621
3,756
5,150
Note: Values without parentheses are coefficients. Values in parentheses arez−statistics calculated using robust standard errors clustered in the country. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

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