1. religion and spirituality

Ethnic Diversity and Inter-Group Trust in Turkey
Avital Livny
Carlos III-Juan March Institute
May, 2015
Abstract
The costs of ethnic diversity for economic growth, public goods provision,
and interpersonal trust may be some of the few established “laws” of political
economics. But our ability to correctly estimate the consequences of diversity
depends on the quality of our data, and measures of ethnic group size tend
to suffer from bias, if they exist at all. In the case of Turkey, where ethnicity has political and economic significance but is not formally recognized by the
state, research on ethnicity has suffered from severe data limitiations. As a remedy, I propose a survey-based approach to measuring fractionalization that has
both theoretical and empirical advantages over existing methods and calculate
fractionalization for 570 districts across 66 Turkish provinces using data from
over 115,000 respondents. Using these estimates and measures of coethnic and
non-coethnic trust, I find preliminary evidence in support of contact theory in
the Turkish context: higher levels of diversity correlate with a smaller coethnic
trust premium, indicating that more frequent inter-ethnic interactions may help
promote inter-ethnic tolerance.
Political scientists and economists have repeatedly confirmed the significance of diversity — particularly ethnic diversity — for a number of socio-economic and political
outcomes. More ethnically fractionalized communities tend to suffer from lower rates
of economic growth (Alesina and La Ferrara, 2005; Easterly and Levine, 1997) and
public goods provision (Alesina, Baqir and Easterly, 1999; Habyarimana et al., 2007),
higher rates of civil war (Blimes, 2006) and electoral volatility (Ferree, 2010; Madrid,
2005), more democratic instability (Annett, 2001), and lower levels of generalized
1
trust (Delhey and Newton, 2005; Zak and Knack, 2001). Where scholars remain
divided is on whether diversity supports or undermine inter-group tolerance, with
theoretical and empirical support for contact theory (Lancee and Dronkers, 2011;
Pettigrew, 1998) as well as conflict theory (Giles and Evans, 1986; Putnam, 2007).
Both sides of the debate are confident that ethnic diversity matters, even if they
fundamentally disagree on the direction of its effect.
The ability to estimate the extent of diversity’s effect on growth, public goods, or tolerance depends critically on the quality of data on ethnic-group size. Until now, the
literature has been fairly consistent in calculating ethnic fractionalization — one minus the Herfindahl index of ethnic-group shares — using population estimates derived
from Soviet ethnologists (Easterly and Levine, 1997), from Encyclopedia Britannica
and the CIA World Factbook (Alesina et al.), or from the Library of Congress and
Minorities at Risk Project (Fearon, 2003). But while the number of sources used in
calculating fractionalization has increased over time, their quality remains questionable. Presumably based on official government statistics, they undoubtedly suffer
from bias given the large percentage of countries (nearly two-thirds) that fail to enumerate ethnicity in their national censuses (Mourning, 2008), to say nothing of the
error in contemporary census-taking (Lee and Zhang, 2013).
Given that the political and economic significance of ethnicity in a particular country is likely to be correlated with its formal recognition (and enumeration) by state
authorities, one can expect a paucity of quality data on ethnic diversity in precisely
those places where it is most needed. Consider the case of Turkey, where ethnicity,
despite being of clear political and economic relevance, is not formally recognized by
the state and has not been documented in a national census since 1965. Without
good data on ethnic identity and group size, in their research on ethnicity in contemporary Turkey, scholars have had to rely on fifty-year-old projections from the
last official census (Mutlu, 1996) or data on mother-tongue from the Demographic
and Health Survey (İçduygu, Romano and Sirkeci, 1999; Koç, Hancioğlu and Cavlin,
2008). In the process, they have likely introduced considerable bias into their analyais,
undermining the strength of their results.
As a solution, I propose a new approach to measuring ethnic-group size – using
subjective self-identification from nationally representative surveys — and use it to
estimate fractionalization across a number of geographic units in Turkey — region
(bölge), province (il ), and district (ilçe) — with varying degrees of precision. While
some in the existing literature have previously used survey responses to measure group
size (Gerring et al., 2015; Nunn and Wantchekon, 2011), they have failed to correctly
2
account for the sampled nature of the data (Taplin, 2003). By calculating the standard
error of the sample Herfindahl, I am able not only to report more accurate estimates
but also to conduct significance tests, comparing diversity across space and time.
Using this approach and data from over 115,000 survey respondents, I find statistically significant differences between my survey-based estimates and those derived
from the national census or data on mother-tongue in a large percentage (nearly twothirds) of provinces. Further, with these survey-based estiamtes and data from an
additional 2528 survey respondents, I explore the relationship between diversity and
inter-group tolerance in the Turkish context. I find that ethnic diversity has a substantial and positive impact on tolerance, decreasing the extent to which individuals
trust coethnics more than non-coethnics. Remarkably, the positive effect of diversity
on inter-ethnic trust is particularly sizeable for ethnic Turks who otherwise tend to
be the least tolerant.
The article proceeds as follows. After discussing existing measures of diversity and
introducing my survey-based measurement strategy in Section 1, I present my estimates of ethnic fractionalized in Turkey in Section 2. Section 3 details the current
debate between contact and conflict theory and outlines an empirical strategy for
assessing the impact of diversity on inter-group trust in Turkey. Section 4 presents
the results of my analysis, beginning with some descriptive statistics of how levels of
coethnic and non-coethnic trust vary across demographic categories, and concluding
with evidence of a positive correlation between ethnic diversity and inter-group trust,
including a comparision of contemporary and historical fractionalization. Finally, a
brief conclusion summarizes my findings, discusses their implications, and considers
avenues for future research.
1
Measuring Ethnic Diversity
The existing literature on the costs and benefits of ethnic diversity is lengthy, and
while there is still some discussion of the magnitude and direction of diversity’s effect
on economic development (Alesina and La Ferrara, 2005), public goods (Baldwin and
Huber, 2010), conflict (Fearon and Laitin, 2003), and tolerance (Kasara, 2013), there
is overwhelming consensus around a single measurement strategy: a Herfindahl index
of ethnic-group shares, based on estimates of group size derived from cross-national
references. While the number of these references has increased over time, their quality
remains questionable. Presumably based on official government figures, they would be
3
prone to political manipulation and errors of execution. In place of these estimates, I
propose to use nationally representative survey data to calculate a sample Herfindahl
with the appropriate standard errors.
1.1
Existing Measures
To measure ethnic diversity, the literature commonly uses a standard measure: fractionalization, or one minus the Herfindahl index of ethnic-group shares. This can be
formally defined using the following equation:
F ractionalizationc = 1−
N
X
s2ic
i=1
where sic is the share of the group i (i = 1 . . . N ) in community c. The resulting
number can be easily interpreted as the probability that two randomly selected individuals from community c will belong to different ethnic groups. Fractionalization,
thusly defined, is a function of the number of ethnic groups in a given community and
their relative size. To tabulate the number of groups and their sizes, scholars have
traditionally depended on a number of cross-national referencess: the Russian Atlas
Naradov Mira, the Encyclopedia Britannica, and the CIA’s online World Factbook,
among others. Although the number (and quality) of these sources has increased over
time (Alesina et al., 2003; Fearon, 2003), a number of theoretical and empirical issues
remain.
The first concerns which ethnic groups are included in a particular reference. Adoption of expert- or state-defined group lists goes directly against a growing scholarly
consensus that identities are not objective features of any individual or society but
rather are constructed in a context-dependent way (Nagel, 1994). Given this understanding of identity as mutable, the question of which identities are activated and
how they are defined becomes almost as important as the question of their potential
consequences (Chandra, 2006). As such, no policy expert, state official, or ethnographer can be expected to construct a list of all possible ethnic categories in a given
community. The list can only be created by members of the community itself (Fearon,
2003).
Just as experts would be unable to create a master list of all possible ethnic categories
in a given community, they can not be expected to correctly place individuals into
4
these categories. Again, there is a growing scholarly consensus that there is no such
thing as an objective identity, no fixed sense of membership derived shared history,
language or race. Rather, there is only a process of identification whereby an individual opts to activate her sense of allegiance to a particular group. So just as it is
preferrable to keep the list of possible identity categories open-ended, so too is it important to allow individuals to self-identify into categories of their choosing (Abdelal
et al., 2009). Taken together, this implies that ethnic-group size is best measured
through open-ended self-identification by individuals.
Estimation of group size through a national census is often considered a superior
method of measurement, since it allows for self-identification. But recent analysis of
censuses from around the world reveals some critical issues with how they tend to
collect data on ethnicity(Mourning, 2008). To begin, less than two-thirds of censuses
include any sort of question on identity, covering those that ask about nationality,
race, or caste, in addition to ethnicity. Ethnicity, specifically, is asked in only 35.6
percent of censuses. Moreover, the enumeration of ethnicity varies considerably by
region — it is included in only 21.1 percent of censues in Africa, 24.3 percent of
those in Europe, and 27.3 percent in South America – and would seem to be least
well-documented precisely where it has the most political and economic relevance.
But even where ethnicity is asked in national censuses, there are reasons to question
the quality of the data. Beyond basic concerns with enumerator error (Lee and Zhang,
2013), there is also evidence that many countries restrict the groups with which
individuals may self-identify, using a closed list with no outside options. Mourning
(2008) finds that over one-third of censuses that include some measure of identity
employ a closed-list system, while a little under one-third define a set list of categories
along with the option of writing in an additional “Other” category. Only 31 percent
employ an entirely open-ended system, allowing individuals to write in whatever group
they choose to identify with. All told, only 39 percent of censuses include a measure
of identity that is at least somewhat open-ended, a strikingly low figure.
1.2
A Survey-Based Measurement Strategy
There are both theoretical and empirical reasons to question the quality of the data
on ethnic-group size published in the Encyclopedia Britannica or Atlas Naradov Mira.
Evidence indicates that they fall far short of the ideal method of measuring ethnic
5
identification: self-reported answers to an open-ended question. Moreover, crossnational references tend to only report only national-level population estimates, overlooking potentially significant variation across sub-national units. I propose to address both of these concerns simultaneously by estimating a fractionalization index
using data from surveys designed to elicit the most reliable information on ethnicity,
by asking respondents open-ended, subjective questions about how they choose to
self-identify (Simpson and Akinwale, 2007).
The use of survey responses to calculate fractionalization is not entirely new, used
originally by Nunn and Wantchekon (2011) and most recently by Gerring et al. (2015).
But existing examples have failed to properly consider and account for the sampled
nature of the survey data. Rather than producing a Herfindahl index of ethnic-group
shares for the entire population, a survey dataset produces a sample Herfindahl which
is, at best, an estimate of the population statistic. As with other population estimates,
a standard error of the sample Herfindahl should be calculated. In his 2003 article,
Taplin derives the variance of a sample Herfindahl (H) to be
M
X
2
σH
=
ai + 2
i−1
M X
X
bij − (E (H))2
i=1 j=1
i=1
where
ai = πi + 7 (n − 1) πi2 + 6 (n − 1) (n − 2) πi3 + (n − 1) (n − 2) (n − 3) πi4 /n3
bij = (n − 1) (n − 2) (n − 3) πi2 πj2 + (n − 1) (n − 2) πi πj (πi + πj ) + (n − 1) πi πj /n3
and the expected value of the Herfindahl is derived to be
M
X
E (H) =
i=1
πi2 +
M
X
πi (1 − πi ) /n
i=1
where M is the number of groups, πi is the proportion of group i in the sample, and
n is the sample size.
By acknowledging that a fractionalization index based on survey data is a measure of
diversity in the sample and is therefore only an estimate of diversity in the population as a whole, this method is able to properly account for how varying sample sizes
6
impact the precision of the survey-based estimate. This supports the calculation
of fractionalization indices within nested sub-national units that acknowledges the
smaller sample sizes in smaller units. Moreover, it has the added bonus of supporting
signifincance testing when comparing two different diversity estimates, something a
traditional Herfindahl is unable to do (Taplin, 2003). Add to this the fact that estimates of ethnic-group share are derived from open-ended subjective self-identifications
and the result is a measure of ethnic diversity that has considerable advantages over
existing measures, particularly where census data is absent or known to be biased.
2
Ethnic Diversity in Turkey
Despite being of considerable political, economic, and historical relevance, ethnicity
has remained largely ignored by the Turkish state. While the Ottoman Empire was
known for centuries as a place of ethnic pluralism (Barkey, 2005; Kymlicka, 1992),
coexistence turned to conflict as the empire began to collapse, and many minority
communities emigrated, whether by choice or by force (Karpat, 1985a; McCarthy,
1983). When the Turkish Republic emerged from the ashes of the collapsed empire,
the mood changed yet again — a singular focus on the Turkish-Sunni nation-state
meant a denial of ethnic and religious differences in favor of an illusion of homogeneity
(Deringil, 1998; Kirişci, 1998; Yavuz, 2001), resulting in a paucity of data on identity. As a solution, my survey-based method offers an updated view of ethnicity and
diversity in contemporary Turkey.
2.1
Ethnicity in Contemporary Turkish Studies
In the existing literature, the significance of ethnic identity for socio-economic and
political outcomes in Turkey has most often been assumed or inferred rather than directly tested (for some notable exceptions, see Güneş-Ayata and Ayata, 2002; Hazama,
2003, 2007). This is mostly due to a paucity of data on identity itself: religious denomination and ethnicity have been excluded from the national census since 1965,
and government officials have asked that questions pertaining to ethnicity be left off
of major survey instruments, including the Demographic and Health Survey and the
World Values Survey. With no formal estimates of group size, scholars have had to resort to statistical projection (Mutlu, 1996) or to rely on data on mother tongue from
the DHS (İçduygu, Romano and Sirkeci, 1999; Koç, Hancioğlu and Cavlin, 2008).
7
Much as in the broader political science literature, scholars of identity in Turkey have
repeatedly noted just how constructed ethnic categories are in the Turkish case (Ergin, 2014; Somer, 2002, 2005; Yavuz, 2001; Yeğen, 2009), making it difficult to accept
that a fifty-year-old census or language-choice could have much of anything to say
about ethnicity in the country today.
Better, but far more rare, is a calculation of group-size based on ethnic self-identification.
Thus far, all those that have been published report variation only at the national or
regional (bölge) level (Aras et al., 2009; KONDA Research and Consultancy, 2006;
Ağirdir, 2008; KONDA Research and Consultancy, 2011), making more fine-grained
analysis impossible. And given the geographic concentration of some of Turkey’s
ethnic minorities in the South and Southeast, it seems likely that ethnic fractionalization will vary considerably across provinces (il ) and districts (ilçe), not to mention
cities and neighborhoods. Although Turkey ranks as fairly homogenous when put in
cross-national comparison — with a fractionalization index of 0.299 by one measure,
ranking 113th out of 159 countries (Fearon, 2003), and an index of 0.320 by another,
ranking 197th out of 215 (Alesina et al., 2003) — some of its subnational units are
likely to emerge as considerably more diverse.
2.2
Measuring Ethnic Identity and Ethnic Diversity in Turkey
To measure ethnicity in Turkey, I rely on nationally representative surveys conducted
by KONDA Research and Consultancy. While questions pertaining to ethnicity have
not been part of the DHS and WVS in Turkey, KONDA has included a question on
ethnic identity in its monthly KONDA Barometer, a nationally-representative faceto-face survey, since March, 2010. All told, the combined KONDA Barometer dataset
includes data on ethnicity for a total of 117,815 respondents in 4264 neighborhoods
and villages in 570 districts in 66 provinces across all 12 of Turkey’s geographical
regions.
The question on ethnicity used in the KONDA Barometer has been consistent throughout, making it possible to combine 45 surveys into a single dataset. Further, it asks
about respondents’ subjective self-identifcation and is phrased with care so as to make
it more likely that they will respond honestly: “We are all citizens of the Republic of
Turkey, but we may have different ethnic roots. As far as you know or feel, what is
your identity?” 1 Answers are transcribed verbatim and later coded as either Turkish,
1
In Turkish: “Hepimiz Türkiye Cumhuriyeti vatandaşıyız, ama değişik etnik kökenlerden olabiliriz;
Siz kendinizi, kimliğinizi ne olarak biliyorsunuz veya hissediyorsunuz? ”
8
Ethnic Diversity
.350709 - .621988
.193094 - .350709
.119523 - .193094
.07662 - .119523
.037625 - .07662
.003407 - .037625
No data
Figure 1: Ethnic Fractionalization across Provinces (NUTS-2)
Source: KONDA Barometer (2010-14).
Kurdish/Zaza, Arab, or Other. Across all respondents, 82.3 percent self-identify as
ethnically Turkish, 13.5 percent as either Kurdish or Zaza, 1.6 percent as Arab, and
2.6 percent as Other.2
To estimate ethnic diversity from these survey data, I estimate both the sample
Herfindahl and its standard error at the province-, district-, and neighborhood-level.
Because the number of survey respondents is smaller at lower levels, estimates of diversity are less precise for neighborhoods and more precise for districts and provinces.
Across provinces, I find considerable variation in diversity, ranging from a high of 0.622
in Tunceli to a low of 0.003 in Niğde, with an average of 0.181 (σ = 0.164). Across
districts, the average is a bit smaller (µ = 0.146) with a similar standard deviation
(σ = 0.164). The two distributions are illustrated in Figures 1 and 2.
The province-level estimates derived from the KONDA Barometer can be directly
compared to two measures commonly used in the existing literature: fractionalization
based on mother-tongue data from 8094 female respondents in the 2003 DHS (Koç,
Hancioğlu and Cavlin, 2008), and that based on the results of the the 1965 census
(TürkStat).3 The 1965 census data produces province-level fractionalization indices
2
Remarkably, despite considerable differences in data sources, these sample averages are not so
different from estimates of group-size derived from DHS data on mother tongue — 82.6 percent
Turkish, 14.5 percent Kurdish, and 1.9 percent Arab (Koç, Hancioğlu and Cavlin).
3
Unfortunately, the census projections estimated by Mutlu (1996) can not be used to calculate
fractionalization as it only includes the size of the Kurdish population and estimates of all ethnicgroup shares are required for the Herfindahl.
9
Ethnic Diversity
.320869 - .660494
.182702 - .320869
.094055 - .182702
.022068 - .094055
0 - .022068
0-0
No data
Figure 2: Ethnic Fractionalization across Districts (NUTS-3)
Source: KONDA Barometer (2010-14).
that average to 0.149 (σ = 0.197), compared to an average of 0.191 (σ = 0.163)
in the DHS-based indices. While seemingly similar to my survey-based estimates,
these cross-provincial averages may very well conceal significant differences within
provinces. To get a better sense of how these three measures compare, Figure 3
displays the survey-based estimates (bounded by 95 percent confidence intervals) and
the DHS- and census-based indices across the 57 provinces for which all three are
available. It reveals is significant differences between the survey-based estimates and
the two existing measures.
Generally speaking, the survey-based estimates tend to be considerably larger than
the fractionalization indices produced by either the 1965 census or the DHS language
data, particularly in provinces with more diversity. Indeed, the DHS language-based
fractionalization indices fall within the bounds of the survey-based estimates only
36.9 percent of the time. They are significantly larger than the survey-based estimates in 27.7 percent of cases and are signifcantly smaller in the remaining 35.4
percent. For its part, the census produces measures of diversity even more distinct
from those estimated by the survey data: census-based fractionalization indices fall
within the bounds of the survey-based estimate only 21.1 percent of the time. They
are significantly larger in 17.5 percent of cases and are significantly smaller in the
remaining 61.4 percent. This is not entirely surprising given that migration that has
significantly altered the demograophic composition of most Turkish provinces since
1965. Still, it makes it clear that migration has served to increase diversity in a large
majority of cases.
10
.6
Ethnic Fractionalization
.2
.4
N
Zo C igd
ng oru e
Tr uld m
ab ak
N Ozon
ev rd
Ka
se u
h
Af ram Rhir
yo a Ay ize
nk nm di
ar ar n
K ahi as
Ka irsesar
st Si hir
am va
o s
Usnu
G Mak
Baires us
l u
Dikes n
Kaeni ir
z
Koyserli
ny i
M
Ku u a
g
Satah la
ka ya
ry
B
A ur a
Santal sa
m ya
TeBursun
ki du
r r
Ki Ar dag
r tv
Amklar in
e
Ca E asyli
D na dirna
iya kk e
rb ale
Es Toakir
ki ka
M seh t
Ananisir
Is ka a
Koparra
t
Ga Icaea
ziazm li
Ist nt ir
an ep
Er Habul
Gu zurtay
m Ad um
us an
Mhana
er e
M Vsin
al an
a
Er Stya
zin iir
c t
K an
SaMar ars
nl di
i n
E ur
Tulazfa
nc ig
eli
0
Survey Estimate
DHS Estimate
Confidence Interval
1965 Census
Figure 3: Comparison of Ethnic Diversity Estimates, across Provinces (NUTS-2)
Source: Heceteppe University (2003); KONDA Barometer (2010-14); TürkStat (1945).
3
Contact, Conflict, and Inter-Ethnic Trust
Using these survey-based estimates of ethnic fractionalization in Turkey, I seek to
adjudicate between two leading theories on the relationship between diversity and
inter-group relations: contact theory, which posits that diversity and inter-group
interactions support more tolerance, and conflict theory, which warns that contact
breeds bias. The relationship between diversity and inter-group bias, broadly speaking, and whether inter-ethnic interactions are most valuable for members of the ethnic
majority or minority, more specifically, are questions that can be addressed by analyzing individual-level survey responses to questions of coethnic and non-coethnic
trust, in combination with district-level data on ethnic diversity.
11
3.1
Diversity and the Coethnic Trust Premium
One of the longest-standing debates in the study of ethnicity and ethnic diversity
is that between contact and conflict theories. On the one hand, contact theory argues that the inter-mixing of distinct groups will help to dispel prejudices and breed
tolerance through more frequent interaction (Pettigrew, 1998); on the other, conflict
theory suggests that these interactions will increase hostility (Giles and Evans, 1986).
Thus far, empirical evidence has been unable to settle the debate, with mixed support
for both theories. While Lancee and Dronkers (2011) find a positive association between diversity and inter-group trust in the Netherlands, Robert Putnam (2007) has
found that diversity undermines both in-group and out-group trust in the American
case. The relationship between diversity and bias in Turkey also remains an open
question: although Saraçoğlu (2009) finds that proximity to Kurdish migrants breeds
prejudice among Turks, a study by SETA and Pollmark (Aras et al., 2009) uncovers
significant bonds of friendship and family between Kurds and Turks across Turkey.
Despite these disagreements, where the two sides of the debate tend to converge is
in their conceptualization and measurement of inter-group relations. Much like in
studies of the costs and benefits of group identity, research on bias and tolerance has
increasingly focused on interpersonal trust, which tends to be more robust among
members of the same group (Dawes, de Kragt and Orbell, 1988; Yamagishi and Kiyonari, 2000) and significantly lower across group boundaries (Habyarimana et al.,
2009; Heap and Zizzo, 2009). The concern is that, so long as trust remains confined
to in-group members, the ability to live and work together successfully will not cross
group boundaries, so that inter-ethnic coexistence becomes a function of how much
individuals trust those outside of their own group, relative to how much they trust
their own group members. By directly comparing levels of non-coethnic trust to coethnic trust, the resulting metric — known as the coethnic trust premium (Robinson,
2013; see also Charnysh, Lucas and Singh, 2015) — reflects the degree of bias and
the potential for coexistence.4
Many existing studies of inter-ethnic trust, including those conducted in Turkey,
have focused on out-group (non-coethnic) trust alone, believing this one measure to
be sufficient (Aras et al., 2009; Çelebi et al., 2014; Dixon and Ergin, 2010). But in
finding that Kurds trust Turks more than Turks trust Kurds, for example, they are
4
Note that the trust premium, by definition, reflects both types of trust. In the ideal case, the
premium would be small because non-coethnic trust is high enough to match the level of coethnic
trust (as opposed to coethnic trust being as small as the level of non-coethnic trust).
12
unable to say whether Turks indeed suffer from more inter-ethnic bias or whether they
are simply less trusting overall, of Kurds and Turks alike. In order to say something
definitive about bias, non-coethnic trust must be measured relative to a baseline:
namely, coethnic trust.
Once bias is defined in terms of the coethnic trust premium, a number of questions
about inter-ethnic relations in Turkey immediately follow. Most basically, variation
in the coethnic trust premium across demographic groups — gender, age, education,
but also ethnic identity and identification — is an obvious starting point. Existing
research has found that Turkish men tend to hold more negative views of Kurds
(Dixon and Ergin, 2010), that education is associated with less support for Kurdish
ethno-politics (Sarigil, 2010), that members of the ethnic-Turkish majority have less
favorable views of ethnic minorities than vice versa (Aras et al., 2009), and that
nationalism is associated with more anti-Kurdish bias among Turks, and religiosity
with less (Dixon and Ergin, 2010). But it is not yet clear whether these differences
exist in the coethnic trust premium or merely reflect differences in trust, of both
coethnics and non-coethnics. Beyond these individual-level factors, I am interested
in how environment — namely, ethnic diversity — might impact inter-ethnic trust,
which calls for a hierarchical model that takes into account both individual-level
variables and fractionalization at the district-level.
3.2
Measuring the Coethnic Trust Premium in Turkey
To measure the coethnic trust premium in Turkey, I rely on the results of another
nationally representative survey administered by KONDA Research in Consultancy
in September, 2012. A total of 2528 face-to-face interviews were conducted in 142
neighborhoods and villages across 91 districts in 29 provinces across all 12 geographic
regions. Sampling was based on both neighborhood/village population and educational attainment, as defined by the Address Based Population System (Adrese Dayal
Nüfus Kayıt Sistemi ), as well the outcome of the 2011 general elections. Further, age
and gender quotas were applied to the 18 surveys conducted within each neighborhood/village. (For a full set of descriptive statistics, see Appendix Table A1.)
As part of the survey, respondents were asked about their level of trust in a number
of different groups. The list of groups was introduced with the following phrase —
“I would like to ask you how much you trust people from various groups” 5 — with
5
In Turkish: “Size çeşitli gruplardan insanlara ve kurumlara ne kadar güvendiğinizi soracağım”.
13
Coethnic Trust Premium
.405 - 1.083
.377 - .405
.332 - .377
.2505 - .332
.182 - .2505
.085 - .182
Figure 4: Coethnic Trust Premium across Regions (NUTS-1)
Source: KONDA Barometer (2012).
five possible responses for each — “Trust completely”, “Trust somewhat”, “Neither
trust nor distrust”, “Do not trust very much”, or “Do not trust at all”.6 In addition
to their level of trust in people they meet for the first time, members of their family,
friends and neighbors, respondents were asked about their trust in “People of the
same ethnicity” 7 and in “People of a different ethnicity”.8
For ease of interpretation, both of these two measures of trust were recoded — 1 if
respondents reported that they trust completely or somewhat, 0 if they neither trust
nor distrust, and −1 if they do not trust very much or at all. Vis-à-vis coethnics,
35.0 percent of respondents trust, 29.8 percent neither trust nor distrust, and 35.2
percent do not trust, for an average trust level of −0.002. As for non-coethnics, only
20.4 percent trust, 28.8 percent neither trust nor distrust, and 78.7 percent do not
trust, for an average of −0.305. In other words, coethnic trust is considerably higher
than non-coethnic trust.
I calculate the coethnic trust premium by subtracting non-coethnic trust from coethnic trust. Since both measures of trust are measured on a scale from [−1, 1],
the coethnic trust premium varies from [−2, 2]. Across all respondents, 12.7 percent trust coethnics but not non-coethnics, 11.4 percent trust them only one unit
more, 71 percent trust them both equally, 3.3 percent trust coethnics one unit less
6
In Turkish: “Tamamen güvenirim”, “Biraz güvenirim”, “Ne güvenirim, ne güvenmem”, “Pek güvenmem”, or “Hiç güvenmem”.
7
In Turkish: “Sizden aynı etnik gruptan – Türk, Kürt, Çerkes vs. – insanlara”.
8
In Turkish: “Sizden farklı bir etnik gruptan insanlara”.
14
than non-coethnics, and 1.6 percent trust non-coethnics but not coethnics, for an
average coethnic premium of 0.303.9 Although I will consider variation in the trust
premium across demographic groups below, here I will just note the variation across
geographic regions (Figure 4): while the coethnic trust premium on average is largest
in Northeastern Anatolia (1.083), it is smallest in the Eastern Black Sea (0.085).
4
Ethnic Diversity and Inter-Ethnic Trust in Turkey
Using these survey responses on coethnic and non-coethnic trust, I am able to calculate the average coethnic trust premium across a variety of demographic categories, including gender, age, education, as well as ethnicity and primary identification. When
these individual-level data are combined with district-level data on fractionalization, I
am able to draw some preliminary conclusions about the relationship between ethnic
diversity and inter-ethnic trust, including how diversity interacts with ethnicity to
promote tolerance of non-coethnics.
4.1
Inter-Ethnic Trust across Demographic Categories
To examine differences in inter-ethnic trust across demographic groups, I calculate
the average coethnic trust premium for each group, along with the standard error of
these calculations. Finding a statistically significant difference in the trust premium
across groups would indicate that one group has more in-group favoritism. But to
understand why this is the case, it is important to compare their relative levels of
coethnic and non-coethnic trust so as to see whether differences in the trust premium
are driven by high levels of the former or low levels of the latter.
As an initial basis of comparison, I estimate the average coethnic trust premium
across three dimensions: gender, age, and education.10 Differences in coethnic and
9
Among respondents with a premium of 1, 57.7 percent neither trust nor distrust coethnics but
do not trust non-coethnics, while 42.3 percent trust coethnics but neither trust nor distrust noncoethnics; among those with no trust premium, 44.5 percent do not trust either group, 30.9 neither
trust nor distrust either group, and 24.6 percent trust both groups; and finally, among those with
a premium of -1, 61.5 percent do not trust coethnics and neither trust nor distrist non-coethnics.
10
Recall that the sample was engineered to be balanced with regards to gender, as well as across
three age-categories — 18-28, 29-43, and 44 and up. There is less balance in the sample across
the three education categories: 54.2 percent of respondents report have less than a high school
education, 29.5 percent have a high school education, and 16.4 percent are university-educated.
15
Age Categories
Education Levels
-.4
-.2
0
.2
.4
Male vs. Female
Coethnic Trust
Non-Coethnic Trust
Trust Premium
Figure 5: Inter-Ethnic Trust across Demographic Categories
Notes: Coethnic trust, non-coethnic trust and the coethnic trust premium across gender categories
(male, female), age categories (18-28, 29-43, 44+), and education levels (less than high school, high
school, university). All data from KONDA Research and Consultancy, 2012.
non-coethnic trust and in the trust premium across groups are illustrated in Figure 5.
Across gender lines, I find that women are significantly less trusting of coethnics than
men: whereas men, on average, positively trust coethnics, women actually distrust
them, on average. Similarly, women are significantly less trusting of non-coethnics.
This is entirely consistent with existing literature which finds that women tend to
be less trusting of others, both in Turkey (Çelebi et al., 2014) and beyond (Buchan,
Croson and Solnick, 2008; Croson and Buchan, 1999). Still, overall, women are no
different than men in the size of their coethnic trust premium. That is, although they
trust coethnics and non-coethnics less, the degree to which they trust the former more
than the latter is identical to that of men. This finding highlights the importance of
comparing non-coethnic trust to a baseline when estimating bias across subgroups.
16
Moving onto age, I find that younger Turks are more trusting of both coethnics and
non-coethnics and that older Turks have the lowest levels of both coethnic and noncoethnic trust. Interestingly, middle-aged respondents have lower levels of coethnic
trust — on par with that of older respodents — but higher levels of non-coethnic trust
— on par with that of younger respondents. As a result, they have a smaller coethnic
trust premium relative to younger and older respondents, whose trust premiums are
roughly similar. Still, these differences are not statistically significant.
The most significant differences that I find are based on education. Respondents
who did not graduate high school have the lowest level of trust in both coethnics
and non-coethnics, but their level of trust in non-coethnics is so low that it results
in a significantly larger coethnic premium. Meanwhile, respondents with only a high
school education have middle levels of trust in both coethnics and non-coethnics,
resulting in a middle-level trust premium. Finally, those with a university education
have the highest levels of trust in both coethnics and non-coethnics — particularly
the latter — and have a significantly smaller coethnic trust premium. So while
Sarıgil (2010) has found that education is associated with significantly lower levels
of support for Kurdish ethno-politics, I am able to confirm and expand upon this
finding: education is a strong predictor of inter-ethnic bias in Turkey.
Next, I assess differences in coethnic and non-coethnic trust and in the trust premium
across four ethnic groups: Turk, Kurd/Zaza, Arab, and Other. The results, illustrated
in Figure 6, indicate that Turks are indeed less trusting of non-coethnics than either
Kurds or Arabs (although the small number of ethnic-Arabs respondents makes it
difficult to know whether they are statistically significantly different from any other
group). But in addition to being less trusting of non-coethnics, ethnic Turks are also
less trusting of members of their own ethnic group, with coethnic trust levels that are
slightly negative, on average. In contrast, coethnic trust among Kurds and Arabs is
positive, on average. So too is non-coethnic trust among the small number of Arab
respondents. While non-coethnic trust among Kurds is still negative, on average, it
is significantly higher than that among Turks.
Taken together, these variations in coethnic and non-coethnic trust across ethnic
groups result in some significant differences in the size of the coethnic trust premium.
Although small in number, Arab respondents all report trusting coethnics and noncoethnics equallty, resulting in a trust premium of zero. After them, Kurdish respondents and those that fall under the “Other” umbrella-category have a similar, positive
trust premium. Despite this similarity in the size of the trust premium, there are
interesting differences between the two groups: for Kurds, the smaller trust premium
17
.4
.2
0
-.2
-.4
Turk Kurd Arab Other
Coethnic Trust
Turk Kurd Arab Other
Non-Coethnic Trust
Turk Kurd Arab Other
Trust Premium
Figure 6: Inter-Ethnic Trust across Ethnic Groups
Notes: Coethnic trust, non-coethnic trust and the coethnic trust premium across self-reported
ethnicity (Turkish, Kurdish, Arab, Other). All data from KONDA Research and Consultancy,
2012.
reflects their high levels of trust in both coethnics and non-coethnics; for Others, the
smaller trust premium reflects their low levels of trust in both. Finally, the largest
coethnic trust premium is found among Turks, driven primarily by their low levels
of non-coethnic trust relative to their middling levels of coethnic trust. Further, the
difference in trust premiums between Turks and the three other categories is statistically significant, indicating that Turks trust their coethnic relative to non-coethnics
significantly more than any other ethnic group.
Finally, I compare differences in inter-ethnic trust along another important dimension of identity, namely, primary identification. Previous research has found that
identification with a common, national identity can reduce inter-ethnic bias, both in
Turkey (Bilali, 2014; Dixon and Ergin, 2010) and beyond (Robinson, 2013). Similarly,
18
.4
.2
0
-.2
-.4
Citizen Ethnicity Religion
Coethnic Trust
Citizen Ethnicity Religion
Non-Coethnic Trust
Citizen Ethnicity Religion
Trust Premium
Figure 7: Inter-Ethnic Trust by Primary Identification
Notes: Coethnic trust, non-coethnic trust and the coethnic trust premium across self-reported
primary identification (Turkish citizen, ethnicity, religion). All data from KONDA Research and
Consultancy, 2012.
an emphasis on a common religious identity may also be able to bridge inter-ethnic
differences, as it has in the case of voter support for the AKP (Yavuz and Özcan,
2006). In the survey instrument, identification was measured by asking “Which of the
following best describes you? Which of your identities comes first?” 11 Respondents
could choose between “Turkish citizenship” (65.3 percent), “My ethnic identity” (9.1
percent), or “My religion/sect” (25.6 percent).12
From the existing literature, the expectation is that identification with one’s ethnic
11
In Turkish: “Sizi en iyi aşağıdakilerden hangisi ifade eder? Hangi kimliğiniz hepsinden önce
geliyor? ”.
12
In Turkish: “Türkiye vatandaşlığı”, “Etnik kimliğim – Türk, Kürt, Çerkes gibi ”, or
“Dinim/Mezhebim”. Again, note that the mention of ethnicity was treated with sensitivity.
19
Kurdish
-.4
-.2
0
.2
.4
Turkish
Cit Eth Rel
Cit Eth Rel
Coethnic Trust
Cit Eth Rel
Cit Eth Rel
Non-Coethnic Trust
Cit Eth Rel
Cit Eth Rel
Trust Premium
Figure 8: Inter-Ethnic Trust by Primary Identification and Ethnicity
Notes: Coethnic trust, non-coethnic trust and the coethnic trust premium across self-reported
primary identification (Turkish citizen, ethnicity, religion) and ethnicity (Turkish, Kurdish). All
data from KONDA Research and Consultancy, 2012.
identity should be associated with the highest level of coethnic trust, the lowest levels
of non-coethnic trust, and the largest coethnic trust premium. But looking at the
data, I find only minimal support for this expectation (Figure 7). While those who
identify, first and foremost, with their ethnicity do indeed have the highest levels of
coethnic trust, they also have the highest levels of non-coethnic trust. This results in
a lower coethnic trust premium, on average, although the difference is not statistically
significant. Further, far from building inter-ethnic bridges, an emphasis on a common
identity — whether citizenship or religion — is associated with the lowest levels of
non-coethnic trust and the largest coethnic trust premiums.
This finding raises an additional question, namely whether differences in inter-ethnic
trust based on primary identification are driven by any particular ethnic group(s).
20
Indeed, Çelebi et al. (2014) have found that ethnicity increases out-group bias among
Turks while a strong national identity is associated with less bias among Kurds. Yet,
those results are only minimally supported here (Figure 8). While I find that Turks
who identify with their ethnicity do have significantly lower levels of non-coethnic
trust, they also have lower levels of coethnic trust, resulting in a similar coethnic
trust premium as Turks with other primary identities. In sharp contrast, Kurdish
respondents who identify primarily with their ethnicity have some of the highest
levels of both coethnic and non-coethnic trust, and have the smallest trust premiums
in the sample. In addition, Kurds who identify primarily with their religion have
above-average levels of non-coethnic trust and a smaller-than-average trust premium.
4.2
Ethnic Diversity and Inter-Ethnic Trust
The existing literature remained deeply divided on the question of ethnic diversity
and inter-ethnic trust, both in terms of theory and empirical evidence. To gain
some traction on the relationship between diversity and coexistence in the Turkish
case, I calculate the correlation between ethnic fractionalization and average levels
of inter-ethnic trust across the 91 districts sampled in the survey. (For a list of all
districts, along with their levels of trust and diversity, see Appendix Table A2.) In line
with conflict theory, I find a weak but positive relationship between fractionalization
and coethnic trust across districts (r = 0.111). But in support of contact theory, I
find another, positive and much stronger correlation between fractionalization and
non-coethnic trust (r = 0.343). Most telling is the negative correlation between
fractionalization and the coethnic trust premium (r = −0.231), illustrated in Figure
9, which indicates better inter-ethnic relations, overall, in more diverse locales.
Although the bivariate association between diversity and inter-ethnic trust is statistically and substantively significant, it is possible that the two are not directly related
but, rather, that some other factor simultaneously increases (or decreases) both diversity and coethnic trust. One possible confounder is wealth: Turkey’s most diverse
regions also tend to be among its poorest (İçduygu, Romano and Sirkeci, 1999) and
economic shocks are thought to encourage individuals to bind together and build
trust networks, regardless of kinship ties (Durante, 2009). To test for this possibility,
I estimate Ordinary Least Squares (OLS) regressions of the coethnic trust premium
across districts and include fractionalization in addition to GDP per capita measured
at the province-level for the closest available year (2001). I find no significant change
21
1.5
Coethnic Trust Premium
1
Pasinler
Edremit/Balikesir
Selcuklu
Karacabey
Civril
Sariyer
Odemis
0
.5
Buyukcekmece
Kars Merkez
Nilufer
Seferihisar
Muratpasa
Balikesir
Kutahya
Ondokuzmayis
MerkezMerkez
Nigde Merkez
Bornova
Ilkadim
Kirikhan
Gevas
Gaziemir
Eregli/Zonguldak
Gonen/Balikesir
Yildirim
Bayrampasa
Dortyol
Sultanbeyli
Viransehir
Karaisali
Bandirma
Tekkekoy
Iznik
CigliBahcelievler
Akcaabat
Kecioren
Yenimahalle
Tavsanli
Kemer/Antalya
Mamak
Elmadag Sahinbey
Iskenderun
Zeytinburnu
Kucukcekmece
Yuregir
Odunpazari
Saraykoy Umraniye
Sisli
Etimesgut
Sivas Merkez
Cankaya Kagithane Sehitkamil
Siverek
Tepebasi
Denizli Merkez Sincan
Erdemli
Tavas
Muradiye
Fatih
Kadikoy
Kavak Merkez
Carsamba
BeyogluGungoren
Trabzon
Eyup Malatya
Bagcilar
Merkez
Dosemealti
Inegol
Polatli
Gaziosmanpasa Buca
Giresun
Bismil Merkez CorluUrla
MaltepeKayapinar
Yenisehir
Akdeniz
Ordu Merkez
Pendik
Cayirova
Marmaraereglisi
Sanliurfa Merkez
-.5
Sancaktepe
0
.1
.2
.3
.4
Ethnic Fractionalization
.5
.6
Figure 9: Trust Premium and Ethnic Diversity, across Districts (NUTS-3)
Notes: Bivariate association between the coethnic trust premium and ethnic fractionalization across
districts (NUTS-3). All data from KONDA Research and Consultancy, 2012.
in the bivariate association between diversity and trust with the inclusion of the income measure (Table 1). Further, I see that income is only correlated with coethnic
trust, the measure shown to be least affected by diversity.
My interpretation of the positive correlation between ethnic diversity and inter-ethnic
trust is that more interaction between members of different ethnic groups breeds more
understanding and tolerance. This would imply that any increase in ethnic intermixing through internal migration bodes well for the future of inter-ethnic relations
in Turkey. But is also possible that the correlation between diversity and coexistence
is not reflective of day-to-day interactions but is instead indicative of a long-standing
culture of tolerance in places that are now and have always been relatively diverse
(Jha, 2013). If contemporary diversity reflects historical diversity, and if ethnic trust
22
Table 1: Inter-Ethnic Trust, Ethnic Diversity, and Income
Diversity
Coethnic Trust
(1)
(2)
0.113
0.138
(0.125) (0.126)
Non-Coethnic Trust
Trust Premium
(3)
(4)
(5)
(6)
∗∗
∗∗
∗∗
0.610
0.625
-0.502
-0.492∗∗
(0.116)
(0.117)
(0.117) (0.118)
lira_2001
Log GDP Per Capita
Constant
Adjusted R2
Observations
-0.025
(0.030)
-0.000
2518
-0.069
(0.048)
-0.042
(0.045)
0.502 -0.429∗∗
(0.365) (0.028)
0.000
0.010
2518
2518
-0.107
(0.342)
0.010
2518
-0.028
(0.045)
0.404∗∗
(0.029)
0.007
2515
0.620†
(0.344)
0.007
2515
Notes: The dependent variables are the degree of (i) coethnic trust and (ii) non-coethnic trust and
(iii) the size of the coethnic trust premium. The independent variables are (i) ethnic fractionalization
at the ilce-level and (ii) the natural logarithm of GDP per capita in 2001. OLS regressions. Coefficient
is statistically different from 0 at the ** .01, * .05, and † .10 level.
is more strongly correlated with the latter, then we can conclude that inter-mixing
matters for coexistence, but only in the long-run.
To test for this possibility, I begin by calculating fractionalization indices for each
village and administrative unit, using estimates of ethno-religious group size from
the Ottoman census in 1881 (Karpat, 1985b). Although the geographic overlap between Ottoman-era administrative units and contemporary ones is not entirely clear,
a rough match is possible: out of the 570 contemporary districts for which ethnic
fractionalization has been estimated, 186 can be linked to an Ottoman administrative unit with the same name. Among these are 30 districts for which trust data
are also available.13 In a first test, I estimate the correlation between contemporary
13
These districts are Akcaabat, Balıkesir Merkez, Bandırma, Büyükçekmece, Çarşamba, Denizli
Merkez, Edremit/Balıkesir, Ereğli/Zonguldak, Gevas, Giresun Merkez, Gönen/Balikesir, İnegöl,
Karacabey, Karaisal, Küçükçekmece, Kütahya Merkez, Malatya Merkez, Muradiye, Niğde Merkez,
Ödemiş, Ordu Merkez, Pasinler, Şanlıurfa Merkez, Saraykoy, Seferihisar, Sivas Merkez, Siverek,
Tavas, Trabzon Merkez, and Urla.
23
1.5
Pasinler
1
Coethnic Trust Premium
Pasinler
Edremit/Balikesir
Karacabey
Odemis Odemis
Edremit/Balikesir
Karacabey
Buyukcekmece
Buyukcekmece
Sanliurfa Merkez
-.5
0
.5
Seferihisar
Seferihisar
Balikesir
Balikesir
Kutahya
Merkez
Kutahya
Merkez
Merkez
Merkez
Nigde Merkez
Nigde Merkez
Gevas
Gevas
Eregli/Zonguldak
Eregli/Zonguldak
Gonen/Balikesir
Gonen/Balikesir
Karaisali
Karaisali
Bandirma
Bandirma
Akcaabat
Akcaabat
Kucukcekmece
Kucukcekmece
Saraykoy
SivasSaraykoy
Merkez
Siverek
Sivas Merkez
Siverek
Denizli
Denizli
Merkez
Merkez
Tavas
Tavas
Muradiye
Muradiye
Carsamba
Carsamba
Trabzon Merkez
Trabzon Merkez
Malatya Merkez Inegol
Malatya Merkez
Inegol
Giresun
Merkez
Urla
Sanliurfa Merkez
Giresun
Urla
Ordu
Merkez
OrduMerkez
Merkez
0
.1
.2
.3
Diversity
Contemporary Diversity
.4
.5
.6
Historical Diversity
Figure 10: Trust Premium and Diversity, Contemporary and Historical, across Districts (NUTS-3)
Notes: Bivariate associations between the coethnic trust premium and ethnic fractionalization in
2010-14 and between the trust premium and ethno-religious fractionalization in 1881. Data from
KONDA Research and Consultancy, 2012 and Karpat, 1985b.
ethnic fractionalization and ethno-religious fractionalization in 1881. If diversity impacts coexistence only in the long-term, then places that are fractionalized today (and
enjoy higher levels of inter-ethnic trust) should also have been fractionalized in 1881.
Instead, I find that the two are only weakly correlated — r = 0.186 in the larger
sample (N = 186), r = 0.024 in the smaller one (N = 30) — indicating that locales
that were once more diverse are not particularly likely to be diverse today.
Despite the weak correlation between historical and contemporary diversity, it is still
possible that Ottoman-era fractionalization is a better predictor of inter-ethnic trust
than contemporary measures. To test for this possibility, I estimated the correlation
between fractionalization in 1881 and my three measures of inter-ethnic trust. I find
24
only a weak association in all three cases — r = 0.086, r = 0.095, and r = 0.010,
respectively — far weaker than the correlations between contemporary diversity and
trust, even when restricting the sample to those districts for which both measures
of fractonalization are available (r = 0.225, r = 0.545, and r = 0.201, respectively).
Figure 10 illustrates the difference in the two trends: while the relationship between
fractionalization in 1881 and the coethnic trust premium (solid gray line) is essentially
flat, the relationship between contemporary fractionalization and the trust premium
(dashed black line) is clearly negative.
4.3
Ethnicity, Diversity, and Inter-Ethnic Trust
Having shown that diversity at the district level is associated with higher levels of
inter-ethnic trust and that members of Turkey’s ethnic minorities tend to have higher
levels of trust, it seems fair to ask whether the relationship between diversity and
tolerance is driven by the larger numbers of minorities living in more diverse communities. In order to answer this question, I need to estimate a hierarchical model
of inter-ethnic trust that takes into account both individual-level variables — i.e.,
ethnicity — and district-level ones — i.e., ethnic fractionalization. As a first test, I
want to see whether including the individual-level measures of ethnicity will weaken
or eliminate the association I have found between diversity and trust. Additionally,
I want to assess whether a diverse environment is more or less important to an individual’s trust level depending on her ethnicity, and whether an her ethnicity has
a different effect on her level of trust depending on the diversity of her community.
In other words, I will want to estimate the interaction between ethnicity and ethnic
diversity.
To estimate this interaction, I begin by creating three binary indicators of ethnicity
— one for Turkish respondents, one for those who are Kurdish, and one for Arabs.
(“Other” is the excluded category.) Each of these is included in a model of trust, on
its own as well as in interaction with fractionalization, resulting in the following:
T rustij = β0 + β1 T urkishij + β2 T urkishij × F ractionalizationj +
β3 Kurdishij + β4 Kurdishij × F ractionalizationj +
β5 Arabij + β6 Arabij × F ractionalizationj +
β7 F ractionalizationj + µi + ηj + εij
where T rustij is the level of trust for respondent i in district j; F ractionalizationj is
the level of ethnic fractionalization in district j; T urkishij , Kurdishij , and Arabij are
25
Table 2: Inter-Ethnic Trust, Ethnicity, and Ethnic Diversity
Turkish
Coethnic Trust
(1)
(2)
0.073
0.563∗
(0.102) (0.232)
-2.065∗
(0.869)
Turkish × Diversity
Kurdish
0.178
(0.111)
Kurdish × Diversity
Arab
Non-Coethnic Trust
(3)
(4)
-0.027
-0.017
(0.095)
(0.216)
Arab × Diversity
-2.031∗
(0.818)
-0.042
(0.811)
0.510∗
(0.253)
0.144
(0.104)
-1.475
(0.917)
0.317
(0.227)
Trust Premium
(5)
(6)
0.099
0.581∗∗
(0.096) (0.218)
0.142
(0.236)
0.034
(0.105)
-1.473†
(0.862)
-0.002
(0.855)
0.478∗
(0.211)
0.423
(0.550)
-0.837
(1.625)
0.825
(0.513)
0.368
(0.238)
-0.161
(0.214)
-1.059
(1.516)
-0.402
(0.517)
0.222
(1.529)
Diversity
0.042
(0.130)
1.954∗
(0.857)
0.476∗∗
(0.121)
0.520
(0.800)
-0.441∗∗
(0.122)
1.435†
(0.807)
Constant
-0.096
(0.105)
0.001
2506
-0.557∗ -0.401∗∗
(0.230) (0.098)
0.003
0.016
2506
2506
-0.411†
(0.214)
0.015
2506
0.306∗∗
(0.099)
0.007
2503
-0.146
(0.216)
0.010
2503
Adjusted R2
Observations
Notes: The dependent variables are the degree of (i) coethnic trust and (ii) non-coethnic trust
and (iii) the size of the coethnic trust premium. The independent variables are (i) an individual’s
ethnic identity; (ii) ethnic fractionalization in her district; and (iii) an interaction between the two.
OLS regressions. Coefficient is statistically different from 0 at the ** .01, * .05, and † .10 level.
26
binary indicators of the respondent’s ethnicity; T urkishij ×F ractionalizationj . . . are
interactions between ethnicity and diversity; and εij is the error term. The effect of
ethnicity on inter-ethnic trust, conditional on diversity, is the direct effect of ethnicity
(β1 , β3 , or β5 ) plus the effect of ethnicity through diversity (β2 , β4 , or β6 ) multiplied
by the level of diversity in a respondent’s district. The impact of diversity on trust
for a respondent is β7 , plus either β2 , β4 , or β6 depending on her ethnicity.
The full set of estimated models is presented in Table 1. To begin, it is clear that
including measures of ethnicity, on their own, does little to affect the relationship
between diversity and inter-ethnic trust. Only with the addition of interactions between ethnicity and diversity do some interesting patterns emerge. Most importantly,
whereas Turkish respondents have significantly higher coethnic trust premiums, that
difference is diminishing in the extent of diversity in their community. This means
that while a Turkish respondent in a homogenous community is likely to have a largerthan-average coethnic trust premium, a Turkish respondent living in a more diverse
community may not. Similarly, although the trust premium of Kurdish respondents,
on average, is not statistically distinct, it becomes significantly smaller depending on
the level of diversity in their community, with the smallest premiums among Kurds
in the most diverse places.
To understand how diversity affects the size of the coethnic trust premium across
ethnic groups, I calculate the marginal effect of ethnicity on inter-ethnic trust for
each group conditional on the level of diversity (Brambor, Clark and Golder, 2006).
The results of these calculations are presented in Figure 11: while the solid line traces
the effect of being ethnically Turkish on the size of the coethnic trust premium across
levels of fractionalization, the dashed line traces the effect of being Kurdish or Zaza
depending on the level of diversity, and the dotted line, the effect of being Arab.
Whereas identifying as Arab has a pretty consistent effect on one’s inter-ethnic trust
— lowering the coethnic trust premium, regardless of how diverse one’s community
— diversity has a sizeable impact for the other two ethnic groups. For both Turks
and Kurds living in the most homogenous communities, identifying as either Turkish
or Kurdish is associated with a larger coethnic trust premium; but among Turks and
Kurds living in more diverse communities, the effect switches, so that identifying as
either Turkish or Kurdish is associated with a smaller trust premium.
Turning the question around, from the effect of ethnicity conditional on diversity to
the effect of diversity conditional on ethnicity, I can gain an even better understanding
of the importance of diversity for coexistence across ethnic groups. Calculating the
marginal effect of diversity conditional on each of the three ethnicities, I find one sta27
Effect of Ethnicity on Trust Premium
-.5
0
.5
-1
0
.1
.2
.3
.4
Ethnic Fractionalization
Turkish
Kurdish
.5
.6
.7
Arab
Figure 11: Marginal Effect of Ethnicity on Trust, across Levels of Diversity
Notes: The marginal effect of ethnicity (Turkish, Kurdish, Arab) on the size of the coethnic trust
premium, across levels of ethnic fractionalization. All data from KONDA Research and Consultancy,
2012.
tistically significant result: diversity significantly lowers the coethnic trust premium
among all Turkish respondents. Recall that respondents who identify as ethnically
Turkish tend to have the highest coethnic trust premiums, on average, so finding that
diversity breeds tolerance within this community, in particular, is most welcomed.
5
Conclusion
Using the self-reported ethnicity of over 115,000 Turkish respondents and a new
method for estimating ethnic fractionalization from survey data, I have been able
28
to paint a clearer, updated picture of diversity in Turkey today. Together with measures of coethnic and non-coethnic trust, I have used these fractionalization estimates
to provide some preliminary support for the contact theory in the Turkish context.
Although many Turks still trust their coethnics significantly more than their noncoethnics, the size of this coethnic trust premium is not uniform and is considerably
smaller for a number of key subgroups, including those with higher levels of education and members of the Kurdish minority, particularly those that identify primarily
with their ethnic identity. Beyond these individual-level differences, the size of the
coethnic trust premium is decreasing in the ethnic diversity of communities, where
members of different ethnic groups interact more frequently. The benefits of diversity
for inter-ethnic bias are particularly large for members of the Turkish majority who
otherwise suffer from the lowest levels of non-coethnic trust.
A number of implications directly follow from these findings. To begin, given the
strong association between education and inter-ethnic trust, any improvements in
higher education are likely to result in significant benefits for tolerance and coexistence. Further, given the role played by ethnic diversity in ameliorating inter-ethnic
bias, particularly among members of the Turkish majority, internal migration that
increases inter-group interactions is also expected to breed trust. And with migrants
increasingly chosing the Southwest over the traditional Northwest (Akarca and Tansel,
2012), the level of ethnic fractionalization is expected to rise over time. If the patterns
seen here continue, non-coethnic bias should decline, especially among ethnic Turks,
as they are increasingly exposed to those outside their own ethnic group. Governmental and non-governmental organizations that can bolster inter-ethnic interaction
through community activities also stand to make a significant contribution to the
future of coexistence in Turkey.
Despite the results presented here, some important questions remain that should be
used to guide future research. First and foremost, the survey data I have analyzed
asks respondents direct questions about their feelings of inter-ethnic trust. Given the
sensitive nature of ethnic relations in Turkey, there are real reasons to be concerned
about social desirability bias, i.e., respondents answering as they think they should
rather than as they really feel (Fisher, 1993). Moreover, desirability bias could well
explain some of my empirical results: on the one hand, ethnic minorities and respondents with higher levels of education could plausibly be more influenced by desirability
concerns and would therefore be less willing to respond honestly about their true level
of inter-ethnic bias; further, individuals living in more diverse communities may be
less likely to respond honestly either because of socialization or out of fear of retribution were their true beliefs to be made public. If these desirability biases exist and
29
were corrected, the differences I find in inter-ethnic trust across subgroups might very
well disappear.
To address this concern, future research should seek to measure out-group bias in
a way that is less vulnerable to desirability concerns. Two potential solutions include indirect questioning (Ibid.) and list experiments (Glynn, 2013; Sniderman and
Carmines, 1997) which are designed to get at sensitive topics implicitly. Employing
one or both of these methods alongside direct questions would also allow for a direct
comparison of implicit and explicit bias across subgroups and locales. Future reseach
may also want to take variations in ethnic fractionalization at different levels —
across provinces, districts, and neighborhoods — even more seriously, designing samples that include some diverse neighborhoods in homogenous districts and vice versa.
By focusing on localized diversity and controlling for the broader environment, the
importance of day-to-day interactions for tolerance, relative to other environmental
factors, could be better identified.
Finally, it is important to note that ethnic groups are not the only source of diversity in
Turkey today. Although smaller in scope, religious-based fractionalization and interreligious relations are no less interesting. In addition to asking respondents about their
ethnic identity and their level of inter-ethnic trust, the KONDA Barometer includes
questions about religious denomination and religious-based trust, both in members
of one’s own religious group as well as in members of other religions. Initial analysis
indicates that many of the same patterns in ethnic diversity and inter-ethnic trust
hold true for religious diversity and inter-religious trust, but more in-depth analysis
will need to test the robustness of these results. Future work might also consider the
intersection between religious and ethnic identities in Turkey, especially whether a
shared religious identity can indeed bridge inter-ethnic divides between members of
the majority and the minority.
30
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Appendix
Table A1: Descriptive Statistics
Mean
Coethnic Trust
-0.0020
Non-Coethnic Trust
-0.31
Trust Premium
0.30
Ethnicity: Turkish
0.84
Ethnicity: Kurdish
0.12
Ethnicity: Arab
0.0068
Ethnicity: Other
0.028
Ethnic Diversity (NUTS-3)
0.21
Gender: Female
0.50
Age: 18-28 Year Olds
0.30
Age: 29-43 Year Olds
0.34
Age: Over 44 Year Olds
0.36
Education: Less than High School
0.54
Education: High School
0.29
Education: University
0.16
Identity: Citizen
0.65
Identity: Ethnicity
0.091
Identity: Religion
0.26
37
σ
N
0.84 2518
0.79 2518
0.79 2515
0.36 2516
0.33 2516
0.082 2516
0.16 2516
0.15
91
0.50 2524
0.46 2525
0.47 2525
0.48 2525
0.50 2518
0.46 2518
0.37 2518
0.48 2487
0.29 2487
0.44 2487
Table A2: Trust and Diversity across Districts
District
Akcaabat
Akdeniz
Bagcilar
Bahcelievler
Balikesir Merkez
Bandirma
Bayrampasa
Beyoglu
Bismil
Bornova
Buca
Buyukcekmece
Cankaya
Carsamba
Cayirova
Cigli
Civril
Corlu
Denizli Merkez
Dortyol
Dosemealti
Edremit/Balikesir
Elmadag
Erdemli
Eregli/Zonguldak
Etimesgut
Eyup
Fatih
Gaziemir
Gaziosmanpasa
Gevas
Giresun Merkez
Gonen/Balikesir
Coethnic Trust
Non-Coethnic
Trust Premium
Diversity
N
-0.263
0.056
0.286
0.000
0.611
0.121
-0.333
-0.167
0.222
-0.083
-0.438
0.333
-0.167
-0.444
-0.667
0.028
-0.056
-0.500
-0.176
0.333
-0.357
0.361
0.333
-0.321
-0.167
0.000
-0.316
-0.127
0.389
0.611
-0.222
-0.286
0.286
-0.579
0.056
0.200
-0.333
0.056
-0.229
-0.722
-0.278
0.222
-0.556
-0.500
-0.333
-0.389
-0.556
-0.611
-0.306
-0.833
-0.500
-0.380
-0.056
-0.429
-0.500
0.056
-0.491
-0.600
-0.235
-0.421
-0.273
-0.056
0.556
-0.667
-0.286
-0.143
0.316
0.000
0.086
0.333
0.556
0.364
0.389
0.111
0.000
0.472
0.062
0.667
0.222
0.111
-0.056
0.333
0.778
0.000
0.204
0.389
0.071
0.861
0.278
0.170
0.433
0.235
0.105
0.145
0.444
0.056
0.444
0.000
0.429
0.005
0.534
0.417
0.339
0.066
0.161
0.262
0.304
0.033
0.239
0.414
0.172
0.223
0.115
0.290
0.323
0.057
0.110
0.096
0.305
0.078
0.044
0.178
0.214
0.000
0.187
0.361
0.365
0.323
0.339
0.270
0.031
0.117
19
18
36
18
18
35
18
18
18
36
16
18
18
18
18
36
18
18
108
18
28
36
18
53
30
17
19
55
18
18
18
7
14
38
Table A2 Cont’d: Trust and Diversity across Districts
District
Gungoren
Ilkadim
Inegol
Iskenderun
Iznik
Kadikoy
Kagithane
Karacabey
Karaisali
Kars Merkez
Kavak
Kayapinar
Kecioren
Kemer/Antalya
Kirikhan
Kucukcekmece
Kutahya Merkez
Malatya Merkez
Maltepe
Mamak
Marmaraereglisi
Muradiye
Muratpasa
Nigde Merkez
Nilufer
Odemis
Odunpazari
Ondokuzmayis
Ordu Merkez
Pasinler
Pendik
Polatli
Sahinbey
Coethnic Trust
Non-Coethnic
Trust Premium
Diversity
N
-0.111
0.102
0.176
0.556
0.000
0.194
0.000
0.389
-0.375
0.167
0.056
-0.263
-0.105
0.056
-0.028
-0.127
0.000
-0.194
-0.286
0.130
-0.667
-0.028
0.381
0.222
0.167
0.382
-0.028
-0.222
-0.486
0.722
-0.278
0.389
-0.097
-0.222
-0.367
0.118
0.278
-0.333
0.056
-0.264
-0.389
-0.750
-0.500
-0.056
-0.263
-0.421
-0.222
-0.514
-0.400
-0.556
-0.278
-0.286
-0.148
-0.400
-0.194
-0.163
-0.296
-0.472
-0.441
-0.278
-0.778
-0.459
-0.778
-0.222
0.333
-0.361
0.111
0.469
0.059
0.278
0.333
0.139
0.226
0.778
0.375
0.667
0.111
0.000
0.316
0.278
0.457
0.273
0.556
0.083
0.000
0.278
-0.267
0.167
0.571
0.519
0.639
0.824
0.250
0.556
-0.027
1.500
-0.056
0.056
0.264
0.340
0.105
0.095
0.363
0.100
0.236
0.265
0.043
0.000
0.537
0.023
0.215
0.157
0.094
0.224
0.386
0.098
0.386
0.180
0.157
0.208
0.228
0.147
0.004
0.139
0.198
0.170
0.102
0.027
0.070
0.198
0.322
0.229
18
50
17
18
18
36
55
36
16
18
19
19
38
18
36
55
36
36
14
54
15
36
45
54
36
34
36
18
37
18
18
18
72
39
Table A2 Cont’d: Trust and Diversity across Districts
District
Sancaktepe
Sanliurfa Merkez
Saraykoy
Sariyer
Seferihisar
Sehitkamil
Selcuklu
Sincan
Sisli
Sivas Merkez
Siverek
Sultanbeyli
Tavas
Tavsanli
Tekkekoy
Tepebasi
Trabzon Merkez
Umraniye
Urla
Viransehir
Yenimahalle
Yenisehir
Yildirim
Yuregir
Zeytinburnu
Coethnic Trust
Non-Coethnic
Trust Premium
Diversity
N
-0.444
0.333
0.083
0.500
0.316
-0.139
-0.053
-0.167
0.125
0.028
0.333
-0.111
-0.333
-0.176
-0.118
0.081
-0.316
0.000
-0.389
0.556
0.250
0.222
0.000
0.000
-0.444
-0.167
0.333
-0.167
-0.333
-0.263
-0.361
-0.842
-0.389
-0.125
-0.194
0.111
-0.500
-0.500
-0.471
-0.471
-0.135
-0.421
-0.250
-0.389
0.167
-0.056
0.222
-0.407
-0.263
-0.722
-0.278
0.000
0.250
0.833
0.579
0.222
0.789
0.222
0.250
0.222
0.222
0.389
0.167
0.294
0.353
0.216
0.105
0.250
0.000
0.389
0.306
0.000
0.407
0.263
0.278
0.433
0.644
0.202
0.210
0.277
0.318
0.127
0.170
0.259
0.043
0.519
0.426
0.012
0.000
0.015
0.171
0.017
0.259
0.132
0.457
0.207
0.236
0.132
0.496
0.465
18
18
36
18
19
36
19
54
16
36
18
18
18
18
18
37
19
36
18
18
36
18
54
19
18
Notes: List of districts (NUTS-3) surveyed, with average levels of trust and diversity, and number
of survey respondents.
40