Abstract
We run a correspondence-field experiment in the Czech Republic to test whether employers reward cognitive abilities in mid/end-career applicants. We send fictitious applications to job advertisements, each vacancy receives one application only; that is, this experiment has a between-subjects structure and this choice is meant to reduce detectability concerns (Balfe et al., 2021). Moreover, while this choice usually limits statistical power, it addresses the concern that matched-pair (within-employer) correspondence may alter behavior and impact mechanism-specific discriminatory behaviors (Lahey, 2016).
Our applications consist in CVs, which are all equivalent in terms of education, work history, and English proficiency, while they have three randomized attributes. First, “Age,” disclosed implicitly via graduation year and evenly assigned from 40 to 55. The other two randomized characteristics are meant to capture different dimensions of cognitive abilities, at different margins. Second, “Certificate of Portuguese language knowledge” with three levels—None, CIPLE: A2 level or DAPLE: C1 level (i.e., certificate no or yes, and, if yes, how advanced); this signal means to capture verbal skills. Third, “Playing chess” as an analytical-skill signal with three levels—None, “Chess enthusiast”, or “Chess enthusiast ranked in in the first quartile of national ranking at Chess.com in 2024” (i.e., chess players no or yes, and, if yes, how good); this signal means to capture analytical cognitive skills and their intensity.
These randomized plausible signals are chosen to disclose different dimensions of cognitive skills and to be productivity-unrelated in most jobs within the Czech context. These features allow us to study how belief-updating about ability—rather than job-match (more on this below)—varies with age.
These fictitious applications will reach employers all over the country and for all kinds of jobs advertised through publicly available database of Public Employment Service of the Czech Republic.
While the above three attributes are randomized and orthogonal to employers’ needs, the reminder of the CVs closely fits employers’ needs. These CVs follow the usual Czech CVs structure, that is, one sheet, where the top panel lists job experience for all applicants, while the bottom panel reports additional qualifications, or hobbies, and a short cover letter-like paragraph. With the help of machine learning techniques, the top panel lists relevant, ad-fitting job experience from the last 10 years for all candidates (as such, the fit of each individual CV does not need to be tested with actual people); this strategy addresses the concern that older applicants would list longer job relevant experience. The short bio reports the usual, vague yet credible positive self-promotion (e.g., “I am reliable, proactive, and my previous employers appreciate my consistent performance”), and it explains that the candidate is seeking for a new job after having recently relocated to the area.
With the help of machine learning, we additionally assign candidates’ address. This address is composed of a randomly drawn, real town and street, as well as a fake number, between 5 and 20 km from the registered place of work or (if not available) address of the employer. While the combination of town and street are real, their combination with number returns a non-existent address—this is done to address potential ethical concerns.
Our applicants are all male. This choice is guided by various reasons; most importantly, concerns with statistical power in different occupations. While previous studies have showed that the response rate—when answering job ads—might generally be high in the Czech labour market, e.g., ~30%, it might vary a lot across occupations (Bartos et al., 2016).
The study wants to clarify whether job-irrelevant cognitive ability, move screening decisions differently for applicants aged 40-55, informing debates on late-career signalling and the limits in the increase of generic cognitive abilities.