Primary Outcomes (explanation)
The main idea is to measure the eﬀect of the IAT feedback on job-counselors behavior and related labor market outcomes of Afro-descendant individuals. We will use administrative records and a follow-up survey to create the relevant indicators. The ﬁrst source is the placement data in the job-centers centralized by the UAESPE. In this case, it would be necessary to identify for each resume in the system, the job-counselor (or at least in the employment center) who handles each case. From this data, we can measure both the referral rate and labor market participation of Afro-descendant individuals.
The second alternative is to search for job applicants in the Integrated Contribution Settlement Worksheet (PILA). As has been done in the past, if a person appears in the PILA it indicates that they have a formal job since they are making their contributions to social security (see for example Attanasio et.al, 2007 and Attanasio et.al, 2017).
At this point, it is necessary to clarify that the ﬁnal eﬀect on employability does not only depend on the intermediation of the counselor, and is limited by the additional frictions in the supply and demand of work in Colombia. The short time frame for the labor market intermediation of a small sample size of Afro-descendant clients presents challenges for measuring impacts on job placement. That is why it is especially important to incorporate a simulation exercise that can provide information on behavior related to the responsibilities of job counselors and linked to long-run employment outcomes.
For the latter, we will collect data through an online work session with the job-counselors that seeks to closely replicate the activities that they carry out at the time of receiving a new job seeker (we closely follow works such as Van Borm et.al, 2021). In this case, in a controlled manner, each counselor participating in the study will be assigned a group of resumes containing the most relevant information from the hypothetical job seekers. Each job-counselor will receive 7 random CVs where we control for variables such as gender, race, education, and experience. The race of the candidate is revealed through the photo on the CV. The photos are composites of publicly available images rather than photos of individuals. After brieﬂy reviewing the 7 CVs, the counselors will receive 3 random diﬀerent job posts and will have to refer 3 from their 7 CVs. In the last activity, they will receive 3 posts for training courses and will have to refer 3 CVs to each course.
Alesina, A., Carlana, M., La Ferrara, E., & Pinotti, P. (2018). Revealing Stereotypes: Evidence from Immigrants in Schools. NBER Working Paper Series(25333).
Attanasio, O., Guarín, A., Medina, C., & Meghir, C. (2017). Vocational training for disadvantaged youth in Colombia: A long-term follow-up. American Economic Journal: Applied Economics, 131-143.
Attanasio, O., Kugler, A., & Meghir, C. (2011). Subsidizing vocational training for disadvantaged youth in Colombia: Evidence from a randomized trial. American Economic Journal: Applied Economics, 188–220.
Van Borm, H., Burn, I., & Baert, S. (2021). What Does a Job Candidate's Age Signal to Employers? Labour Economics.