To elicit discrimination towards entrepreneurs we send 8.000 CV's in response to 2.000 vacancies. We randomly assign if (1) a person was self-employed or worked for a company and (2) whether motivation section in CV is provided. To assess if the entrepreneurial discrimination is statistically based, we apply for the similar occupations with different skill-levels: High (Skill level 4) or low(skill level 2) skill level job according to International Standard Classication of Occupations (2008). Namely, we send resume on the next vacancies in Skill level 4: Finance Managers (1211), Advertising and Public Relations Managers (1222), Information and Communications Technology Services Managers (1330). In skill level 2: Accounting Associate Professionals (3313); Conference and Event Planners (3332); Information and Communications Technology Operations Technicians (3511).
To assess racial discrimination we send 4.000 CV's in the response of 1.000 vacancies.We randomly vary the Slavic and ethnic minorities sounding names for the resumes with equal quality e.g. Alexey Lebedev vs. Ansar Juraev. Also, we vary if the person has work experience (on average 1.5 year) or (s)he recently graduated. We choose a broad range of occupations in different industries with the highest demand and that requires or does not face-to-face interaction with clients. Thus, we chose next six occupations for this part of experiment: Advertising and Marketing Professionals (2431, skill level 4), Real Estate Agents and Property Managers (3334, skill level 3), General Office Clerks (4110, skill level 2), Answering Service Operator (4223, skill level 2), Receptionists (general) (4226, skill level 2), Messengers, Package Deliverers and Luggage Porters (9621, skill level 1).
Computer software for correspondence study.
We develop a computer program for this experiment. It contains three main functions:
1. Resumes generating
3. E-mail Responses tracking
CV characteristics database and CV Generation. To create the resumes, we analyzed a large number of real CVs posted online. With the help of these CVs, we created a database for resumes' sections. We also made a database of names, surnames, and middle names based on most popular Slavic and ethnic minorities names.
All the resumes contain the following sections: Heading (name, mobile telephone, e-mail, birth date); Work experience; Education; Professional skills; Personal qualities; Advanced training, Language Skills. The program randomly chooses gender of the applicant and construct their full name from corresponding part of names database (according to the type of CV). Next, it takes randomly lines from every section (according to the type of CV) in order to create a resume. The formatting of the resumes is also chosen at random. All the characteristics of the resume stored in MySQL database with unique CV identifier number.
All this helps us to address the Heckman critique (Heckman, 1998) as suggested by Carlsson et al. (2014). Thus, it gives us the possibility to interpret the ratios as suggested by Neumark (2012) and to estimate wage differentials in lines with Lanning (2013).
Mailing. We apply within-subject design: For each vacancy, computer program sends four types of the resumes in random order.
All applications contain a cover letter, where candidates express an interest in the posted job advertisement. The exact wording of the cover letter is chosen from a set of cover letters at random.To make the application realistic and targeted to specific vacancy the program contains an electronic form that is filled for every vacancy. The form contained following lines: job vacancy, email of a recipient, web source and the name of contact person (if given). This information is used to generate the cover letter.
E-mail Responses tracking. The program automatically tracks the responses on e-mails that are unique for each resume.
Call-back tracking. The unique phone number is assigned to each treatment and job
skill level. We plan to track phone calls on each type of treatment and job skill level. That
allows us to have clear results with respect to the main treatments. To get the detailed
picture of the characteristics of resume, we plan to match the call-back and corresponding