correspondence studies on gender, ethnicity and religiosity discrimination in turkey

CORRESPONDENCE STUDIES ON GENDER, ETHNICITY AND RELIGIOSITY

DISCRIMINATION IN TURKEY

Binnur BalkanBilkent University

Seyit Mümin CilasunAtılım University

Haluk LeventIstanbul Kemerburgaz

University

Introduction

• Discrimination is one of the important sources ofinefficiency in different markets.

• We could observe discrimination in labor market,product markets, housing markets among theothers and there could be multiple steps todiscrimination in these markets.

• For example in the labor market, discriminationcould be observed in– hiring– wage setting– or promotion stages

Introduction

• Additionally, people might be discriminated in thelabor 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 ofdiscrimination in the literature.

Introduction

• In this study, we will try to identify hiring stagelabor 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 inTurkey.

Correspondence Audits

• In a labor market correspondence audit,seemingly similar fictional resumes are sent outto real job openings as pairs.

• After the application process, interview requestsor callbacks from prospective employers arerecorded for the each applicant in the pair.

• The fictitious applicants are very similar except asingle trait, which is the focus of correspondenceaudit study.

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 tosolve this problem by monitoring online job applicationportal activity.

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 financialsector

– discrimination against young women in high skilled administrative jobs.

Literature – Gender II• Booth and Leigh (2010) - Austria

– focused on female-dominated professions (waitstaff, data-entry, customer service, and salesjobs)

– 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 forthe 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.

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 withArabic sounding names and discrimination is more common in lower level ofoccupations

• 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.

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).

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.

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.

Turkey: Lordoğlu & Aslan

• “While making the job contract and speaking about date ofstart, I told that I would like to use my off-days onweekdays. When asked for its reason, I told that I wanted topay visits to my brother who is a political prisoner on theseoff-days. They told me that they would contact me back.But after a while I realized that it wouldn’t be possible tostart working”.

• “On my CV, I stated English and Russian as my foreignlanguages. When the manager who had learned that Ispeak these languages was about to hire me, I told him thatI also speak Kurdish as a third language if it is accepted bythem. He folded the job application form; gave it back tome and told me that they had nothing to do with Kurds”.

Turkey: Lordoğlu & Aslan

• “I applied for a job to work as a security personnel. Wewere 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’tsmoke or drink alcohol but as I am an Alevit, I don’tperform the namaz or fast. Later I learned that theother four applicants were all hired. I wasn’t. The factthat I was from Tunceli made them question me onthese issues. The deputy governer who was helping meto get a job stated the situation exactly like this. I don’tapply to such positions anymore…”

MethodologyCorrespondence Audits Again

• In a labor market correspondence audit,seemingly similar fictional resumes are sent outto real job openings as pairs.

• After the application process, interview requestsor callbacks from prospective employers arerecorded for the each applicant in the pair.

• The fictitious applicants are very similar except asingle trait, which is the focus of correspondenceaudit study.

MethodologyCorrespondence 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


TEMPLATES APPLICATION DATA COLLECTION ANALYSIS

Turkish Man / Woman

Interview Req / Callback

Application Request

Analysis

NoneKurdish Man /

Woman


• 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

MethodologyStep 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.


• 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.


• For the surnames, we have chosen some of theheavily used surnames in Turkey.

• That common surnames do not signal anygeographical, ethnic or religious affiliation sincethey are commonly used by the different groupsof society.

• Another benefit of using commonly usedsurnames, it makes harder for recruiters to searchcandidates online if they have such intentions.


• 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.

MethodologyStep 2: Occupation /Position Selection

• In order to achieve desired number ofapplications, we choose the occupations andpositions according to number of vacancies.

• We focus on entry level jobs, which does notrequire much of experience or referencesfrom the previous employers.

• We focus on two different type of positions,one is for high school graduates and the otherone is for college graduates.

MethodologyStep 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

MethodologyStep 3: Resume Qualities Selection

MethodologyStep 4: Creating online applicant accounts

• Online applicant accounts are created in one of theTurkey’s heavily used job search sites.

• First, a name – surname combination is assigned to aphone number – email account. To do that, emailaccounts are created for all the fictitious surname –name combinations.

• Resumes and email information are person specific inorder to avoid detection of fictitious accounts.

• However, given the job first sites do not have anydetection mechanism for phone numbers, every tenapplicant from the same group share a mobile numberin our study.

MethodologyStep 5: Composing Fictional Resumes

• Fictional resumes are formed with therandomly assigned names and resumecharacteristic on our job application portal.

• Since it is important to assign comparablecharacteristics to all matched pairs, werandomly assign everything in each resume.

• The only ground rules were ethnicity – birthplace compatibility and age – educationcompatibility in our resume creation step.

MethodologyStep 6: Sending resumes to chosen vacancies

• At this stage of the project, online job search portalswill be browsed regularly and a matched pairs ofresumes will be sent to chosen vacancies. Vacancychoice will depend on occupation – position selection.

• At the first stage, one resume from each of thefollowing group will be sent out to job openings:– Turkish man– Kurdish man– Turkish woman– Kurdish woman

• The following step will focus on religiosity.

MethodologyStep 7: Recording callbacks from prospective employers

• Assigned phones and mails will be monitoredregularly.

• Moreover, job search sites will be monitoredand any activity on the applications will berecorded. This step will also constitute ourmethodological contribution.

• In the end, the employers will be notified thatthe applicant is interested in other jobs at themoment.

correspondence studies on gender, ethnicity and religiosity discrimination in turkey

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