Mismatch in beliefs between job seekers and employers in Iraq

Information treatment.

Employers will reveal their preference for employers after evaluating hypothetical candidates. From employers' choices, I will calculate the likelihood of a woman being hired using the number of business owners who would hire a woman divided by the total number of employers. I will calculate the same rate for men, migrants, non-migrants, and applicants living close or far away from the physical location of businesses.

For job seekers, I will ask them to estimate the likelihood of a woman finding a job in Iraq and the probability of migrants and candidates living close to a vacancy. Then, I will use an information treatment, where half of the sample will randomly receive a message saying: "The hiring rate of men is X1%, and the hiring rate of women is X2%." After receiving (or not receiving) the information treatment, job seekers will evaluate hypothetical vacancies, knowing they will receive three actual vacancies based on their assessment.

2022-12-05

2024-05-31

For employers
1. How interested would you be in hiring Jenna? Use a scale from 0, no interested, to 10, very interested. [=0 not interested; 10= very interested]
2. If you offer Jenna a job, how likely do you think she will accept the offer? Use a scale from 0, no likely, to 10, very likely. [=0 not likely; 10= very likely]
3. Would you offer Jenna the job? [Mark only one]
a. Yes, if she is the only candidate available
b. Yes, even if there are more candidates.
c. No

For Job Seekers
1. How interested would you be in applying for this job? Use a scale from 0, no interested, to 10, very interested. [=0 not interested; 10= very interested]
2. If you apply for this job, how likely do you think the employer would offer you the job? Use a scale from 0, no likely, to 10, very likely [=0 not likely; 10= very likely]
3. Would you apply for the job?
a. Yes, if the job offer is the only one
b. Yes, even if there are more job offers
c. No

1. I will create variable women's likelihood of getting a job = (number of employers offering a job to a hypothetical candidate / total employers).
1.1 Same for host communities' likelihood of getting a job and the likelihood of getting a job for candidates living close to the location of the hypothetical vacancy.

2. I will create variable women's
job application = (number of women who applied for a job to hypothetical vacancies / total applicants).
2.1 For host communities' rate of applying for a job and rate of candidates living close to the location of the hypothetical vacancy.

3. A continuous variable from 1 to 10 showing interest in applying for a job.

4. A continuous variable from 1 to 10 shows the belief in receiving an employer's offer.

The research design consists of three parts: (i) elicit employers' preferences about hiring candidates. (ii) elicit preferences of job seekers about applying to vacancies. (iii) The treatment will randomly reveal employers' hiring rate to half of the job seekers in the data.

This study will use the incentivized resume rating (IRR) method to elicit the preference of employers and job seekers without deception. The IRR works in two steps. First, we build hypothetical resumes from real profiles and construct hypothetical vacancies from real job posts. Second, employers evaluate hypothetical resumes, and job seekers assess hypothetical vacancies.

To avoid deception, employers and job seekers know that they will evaluate hypothetical resumes and vacancies from the experiment's beginning. The IRR is an incentivized method to elicit preferences since employers will receive the three most suitable candidates depending on employers' evaluation. Similarly, we will send job seekers' profiles to the three most suitable vacancies based on the preferences of job seekers.

From eliciting employers' preferences, we will know the general trend in hiring rate by gender, migration status, and physical proximity to the vacancy. We will provide the following messages to the treated group and won't reveal any information for the control group. For example:
1. From our sample of employers, the hiring rate for women is 10%, and for men is 60%.
2. From our sample of employers, the hiring rate for workers from the host communities is 40%, and for candidates returning to the community is 80%.
3. From our sample of employers, the hiring rate for workers close to the vacancy is 80%, and for candidates residing far away is 20%.

First, we will show the first message about the hiring rate by gender. Second, we will deliver the second message about the hiring rate by migration status to candidates living in host communities and job seekers returning to the district. Finally, we will present the hiring rate by distance to the vacancy to candidates living close and far away.

Not available

Randomization was done in the office by computer.

Randomization unit is at the individual level. All job seekers have an equal probability of receiving the information treatment.

Yes

Five sectors and two governorates.

660 Job seekers and 200 employers.

200 employers.
-- 65 females and 65 males receive the hiring rate of women and men (treatment 1).
-- 50 migrants and 50 no-migrants receive the hiring rate of migrants and non-migrants (treatment 2)
-- 50 candidates living close to the location of hypothetical vacancies and 50 candidates living far away from the location receive the hiring rate of candidates living close and far from the location (treatment 3)
-- 65 females, 65 males, 50 migrants, 50 non-migrants, 50 close, and 50 far away do not receive any information treatment.