Haluk Levent- Istanbul Kemerburgaz University Seyit Mümin Cilasun- Atılım University Binnur Balkan- Bilkent University ERF Workshop on The Political Economy of Contemporary Arab Societies Beirut, Lebanon August 24-25, 2016 www.erf.org.eg

1. CORRESPONDENCE STUDIES ON
GENDER, ETHNICITY AND RELIGIOSITY
DISCRIMINATION IN TURKEY
Binnur Balkan
Bilkent University
Seyit Mümin Cilasun
Atılım University
Haluk Levent
Istanbul Kemerburgaz
University

2. Introduction
• Discrimination is one of the important sources of
inefficiency in different markets.
• We could observe discrimination in labor market,
product markets, housing markets among the
others and there could be multiple steps to
discrimination in these markets.
• For example in the labor market, discrimination
could be observed in
– hiring
– wage setting
– or promotion stages

3. Introduction
• Additionally, people might be discriminated in the
labor market by their
– Age
– Gender
– Race / Ethnicity
– Religion
– Sexual orientation
– or appearance in the labor market and it is possible to
find studies examining all these types of
discrimination in the literature.

4. Introduction
• In this study, we will try to identify hiring stage
labor market discrimination in Turkey
– under gender, ethnicity and religiosity aspects
– by employing a novel approach of correspondence
audits
– through online job application portals, which are
widely used by employers and employees in
Turkey.

5. Correspondence Audits
• In a labor market correspondence audit,
seemingly similar fictional resumes are sent out
to real job openings as pairs.
• After the application process, interview requests
or callbacks from prospective employers are
recorded for the each applicant in the pair.
• The fictitious applicants are very similar except a
single trait, which is the focus of correspondence
audit study.

6. Contribution
• We aim to contribute existing literature in several aspects
with this study.
• Not much ethnicity studies on the natives of the countries,
this study will be one of the very first
• No gender discrimination study in a Muslim country, where
labor market dynamics for women could be quite different
• One of the few study to create a discrimination measure on
the level of religiousness
• Methodological Contribution: In this type of studies, it is
hard to achieve enough observations. We are planning to
solve this problem by monitoring online job application
portal activity.

7. Literature – Gender I
• There is a growing literature on hiring discrimination in terms of gender,
employing correspondence testing method.
• Riach and Rich (2006) -UK
– used a matched pair of applicants and applied to vacancies for engineers,
computer analyst programmers, secretaries and accounting positons
– net discrimination in favor of women in vacancies for computer analyst
programmers, secretaries and accounting positons and in favor of men in
engineering jobs.
• Petit (2007) - France
– prepared separate resumes for males and females, with or without children,
of age 25 or 37.
– sent matched pair applicants to each vacancy for high and five low skill
occupations in administrative and commercial areas often in the financial
sector
– discrimination against young women in high skilled administrative jobs.

8. Literature – Gender II
• Booth and Leigh (2010) - Austria
– focused on female-dominated professions (waitstaff, data-entry, customer service, and sales
jobs)
– a call-back of 1.28 in favor of women.
• Carlsson (2011) - Sweden
– sent matched paired applications for positions of construction workers, sales assistants, IT
professionals, high school teachers, restaurant workers, drivers, accountants, nurses, pre-
school teachers and cleaners.
– female applicants have slightly higher probability to receive a call back compared to men for
the pooled sample for all occupations,
– in male dominated professions male applicants have a slight (insignificant) advantage.
• Zhou et al. (2013) - China,
– sent CVs to accounting, IT, marketing and secretary positions
– statistically significant discrimination in all the jobs
– the level of discrimination is 9% in favor of men for accounting applications
– 20% and 40.2% in favor of women in marketing and secretary applications, respectively.

9. Literature – Ethnicity I
• Most of the ethnicity studies mainly compare the immigrants and non-immigrants in order to
analyze the discrimination in hiring stage.
• Carlsson and Rooth (2007) – Country: Sweden – Minority: Middle Eastern
– sent matched paired applications for positions of construction workers, sales assistants,
IT professionals, high school teachers, restaurant workers, drivers, accountants, nurses,
cleaners and teachers in different branches
– They found that 29 percent of all employers are discriminated against the male with
Arabic sounding names and discrimination is more common in lower level of
occupations
• Drydakis and Vlassis (2010) – Greece – Albenian
– the probability for Albanians to receive an interview is lower than for Greeks by 21.4
percentage points.
• Kaas and Manger (2011) –Germany - Turks
– sent two similar applications, one with a Turkish-sounding and one with a German-
sounding name to each of 528 advertisements for student internships.
– the call back probability for German names is 14 percent higher for all firms
– when the sample is restricted to small firms, probability rises to 24 percent.

10. Literature – Ethnicity II
• Baert et al. (2011) - Belgium – Turks
– compared to natives, applicants with Turkish sounding name are equally often
invited to a job interview if they apply for occupations for which vacancies are
difficult to fill,
– but they have to send twice as many applications for occupations for which
labour market tightness is low.
• McGinnity and Lunn (2011) – Ireland – African, Asian, German
– applicants with Irish names are over twice as likely to be called to interview as
are candidates with an African, Asian or German name
– discrimination rate does not vary between these minority groups.
• Booth et al. (2012) – Australia – Indigenous, Italian, Chinese and Middle Eastern
– ethnic minority applicants need to apply for more jobs in order to receive the
same number of interviews.
– Italians (a more established migrant group) discriminated less than Chinese
and Middle Easterners (who have arrived more recently).

11. Literature – Ethnicity III
• Midtbøen (2016) – Norway - Pakistani
– second generation of immigrants
– applicants with Norwegian names on average are 25 percent more likely to receive
a call back for a job interview than applicants with Pakistani names.
– the effect of ethnic background on employment probabilities is larger among men
than women and larger in the private sector than in the public sector.
• Arai et al. (2016) – Sweeden – Arabic
– contrary to what is often assumed about the interaction of gender and ethnicity,
Arabic men face stronger discrimination than Arabic women.
• Maurer-Fazio (2012) – China - Mongolian, Tibetan, and Uighur (different than the
aforementioned studies, not immigrants)
– found significant differences in the callback rates by ethnicity and
– these differences vary systematically across ethnic groups.
– state-owned firms are significantly discriminates less than privately-owned firms.

12. Literature – Religion
• The effect of religion on hiring discrimination is hard to study since most of the time religion and
ethnicity are intertwined.
• Banerjee et al. (2009) - India
– the role of caste and religion in India’s software and call-center sectors.
– sent 3160 fictitious résumés in response to 371 job openings.
– no discrimination against Muslims.
• Wright et al. (2013) - New England, US
– applicant from any religion received about one-quarter fewer callbacks compared to the control
group (had no religious identification in his/her résumé)
– discrimination is more evident for Muslims. They received one-third fewer callbacks compared to
control group
– discrimination is also evident for atheists, Catholics and pagans.
• Wallace et al. (2013) - American South
– applicants who expressed a religious identity were 26 percent less likely to receive a callback.
– While, Muslims, pagans, and atheists suffered the highest levels of discrimination, Catholics
experienced moderate levels, evangelical Christians encountered little and Jews received no
significant discrimination.

13. Turkey: Lordoğlu & Aslan
• “While making the job contract and speaking about date of
start, I told that I would like to use my off-days on
weekdays. When asked for its reason, I told that I wanted to
pay visits to my brother who is a political prisoner on these
off-days. They told me that they would contact me back.
But after a while I realized that it wouldn’t be possible to
start working”.
• “On my CV, I stated English and Russian as my foreign
languages. When the manager who had learned that I
speak these languages was about to hire me, I told him that
I also speak Kurdish as a third language if it is accepted by
them. He folded the job application form; gave it back to
me and told me that they had nothing to do with Kurds”.

14. Turkey: Lordoğlu & Aslan
• “I applied for a job to work as a security personnel. We
were five in total. We were interviewed individually.
The questions I was asked were about whether I pray,
fast, smoke or drink alcohol. I told them that I don’t
smoke or drink alcohol but as I am an Alevit, I don’t
perform the namaz or fast. Later I learned that the
other four applicants were all hired. I wasn’t. The fact
that I was from Tunceli made them question me on
these issues. The deputy governer who was helping me
to get a job stated the situation exactly like this. I don’t
apply to such positions anymore…”

15. Methodology
Correspondence Audits Again
• In a labor market correspondence audit,
seemingly similar fictional resumes are sent out
to real job openings as pairs.
• After the application process, interview requests
or callbacks from prospective employers are
recorded for the each applicant in the pair.
• The fictitious applicants are very similar except a
single trait, which is the focus of correspondence
audit study.

16. Methodology
Correspondence Audits
• Our pairs will be
– Turkish man vs. Turkish woman for gender study
– Turkish man vs. Kurdish man for ethnicity study
– Turkish man vs. religious Turkish man for religiosity
study
• In order to produce different measures, we will
send group of four resumes to chosen job
openings
– Turkish man, Turkish woman, Kurdish man and
Kurdish woman

17. Methodology
Correspondence Audits
TEMPLATES APPLICATION DATA COLLECTION ANALYSIS
Turkish Man /
Woman
Interview Req /
Callback
Application
Request
Analysis
None
Kurdish Man /
Woman

18. Methodology
Correspondence Audits
• Name and surname selection
• Occupation/position selection
• Resume qualities selection
• Creating online applicant accounts
• Composing fictional resumes
• Sending resumes to chosen vacancies
• Recording callbacks from prospective
employees

19. Methodology
Step 1: Name / Surname Selection
• The name of the applicants is the main source of
variation in correspondence audits.
• In order to identify source of the discrimination
correctly, names should reflect an affiliation to
the group of interest but nothing more than that
to potential recruiters.
• At this point, we designed a survey in the name
selection stage to ensure that we are signaling
the affiliation, which we aim to signal.

20. Methodology
Step 1: Name / Surname Selection
• We gathered commonly used female and male names
for
– Turks
– Kurds
– Religious people
• Then we surveyed people and ask them to assign traits
to our names, which could be religious, ethnic or
gender.
• After the survey, we collected the names, which are
identified with a single group and identified by
majority of our subjects as belonging that single group.

21. Methodology
Step 1: Name / Surname Selection
• For the surnames, we have chosen some of the
heavily used surnames in Turkey.
• That common surnames do not signal any
geographical, ethnic or religious affiliation since
they are commonly used by the different groups
of society.
• Another benefit of using commonly used
surnames, it makes harder for recruiters to search
candidates online if they have such intentions.

22. Methodology
Step 1: Name / Surname Selection
• Finally, we randomly matched surnames and
names to create fictional applicant identities.
• In that way, we could use any name and
surname more than once
• and we were able to choose the strongest
names in each category in terms of their
identity signaling power.

23. Methodology
Step 2: Occupation /Position Selection
• In order to achieve desired number of
applications, we choose the occupations and
positions according to number of vacancies.
• We focus on entry level jobs, which does not
require much of experience or references
from the previous employers.
• We focus on two different type of positions,
one is for high school graduates and the other
one is for college graduates.

24. Methodology
Step 3: Resume Qualities Selection
• Gender discrimination related component
• Ethnicity discrimination related component
• Birth place supporting component
• Education
• Address
• School
• Age
• Prior work experience
Common
Components

25. Methodology
Step 3: Resume Qualities Selection

26. Methodology
Step 4: Creating online applicant accounts
• Online applicant accounts are created in one of the
Turkey’s heavily used job search sites.
• First, a name – surname combination is assigned to a
phone number – email account. To do that, email
accounts are created for all the fictitious surname –
name combinations.
• Resumes and email information are person specific in
order to avoid detection of fictitious accounts.
• However, given the job first sites do not have any
detection mechanism for phone numbers, every ten
applicant from the same group share a mobile number
in our study.

27. Methodology
Step 5: Composing Fictional Resumes
• Fictional resumes are formed with the
randomly assigned names and resume
characteristic on our job application portal.
• Since it is important to assign comparable
characteristics to all matched pairs, we
randomly assign everything in each resume.
• The only ground rules were ethnicity – birth
place compatibility and age – education
compatibility in our resume creation step.

28. Methodology
Step 6: Sending resumes to chosen vacancies
• At this stage of the project, online job search portals
will be browsed regularly and a matched pairs of
resumes will be sent to chosen vacancies. Vacancy
choice will depend on occupation – position selection.
• At the first stage, one resume from each of the
following group will be sent out to job openings:
– Turkish man
– Kurdish man
– Turkish woman
– Kurdish woman
• The following step will focus on religiosity.

29. Methodology
Step 7: Recording callbacks from prospective employers
• Assigned phones and mails will be monitored
regularly.
• Moreover, job search sites will be monitored
and any activity on the applications will be
recorded. This step will also constitute our
methodological contribution.
• In the end, the employers will be notified that
the applicant is interested in other jobs at the
moment.