Summary: We analyze labor discrimination in Peru, a fast-growing country where much anecdotal evidence suggests the presence of discriminatory practices in everyday life. Using surnames (indigenous/white) as a proxy for race, we sent 4820 fictitious CVs in response to 1205 real job vacancies for professional, technical, and unskilled jobs in Lima. Overall, whites receive more callbacks than indigenous applicants, and beautiful applicants receive more callbacks than homely-looking ones. The magnitude and significance of the racial and beauty gaps in callbacks substantially vary by job category. In particular, better looks only seem to matter in getting more callbacks for professional jobs.An short interview with Francisco is here.
I am currently reading this fascinating book by Uri Gneezy & John List. They talk extensively about field experiments, and one of the topics they cover is discrimination.
An insights from the book is that providing more information to the buyer reduces the price he pays - less informed costumers usually pay higher prices. Let's see how:
The authors give the example of a person who wants to buy a camera lens. In the first store he enters he asks for the best lens available for the camera he is carrying, and the seller suggests a specific lens and tells the price, around $700. As the buyer shops around he gathers more information about the lens he needs up to a point when he enters a store asking for the specific type (name and model) and the price asked is much lower, around $300. From the seller's perspective a more informed consumer knows the "true" price of a product. In short, a more informed consumer pays less, in general.
In the lens case the higher price the initial sellers wanted to charge was based on the consumer's degree of information only. The seller does not have any hard feelings towards the buyer. The seller just wanted to maximise profits. That is also the case when an airline charges higher prices for flight during week-days versus week-ends, passengers looking for flights during week-days have a less elastic demand, think for instance about company executives. Uri and Jhon call that economic discrimination, as opposed to animus-based discrimination.
The policy implications for the two examples are different: in the case of the camera lens the implication is: provide more information to the buyer. In the case of the labor market in Peru is: if you are looking for a job and you are "homely-looking" or have an indigenous last name, provide less information about those characteristics to the possible employer.
The implications of policy are different because in the first case we see the situation from the perspective of the buyer of the camera, who wants to pay a lower price. In the second case we might be seen the situation from the perspective of the job seeker, the labor seller, who wants to get paid a higher wage, or be hired.
An implication of Francisco and Gustavo's paper is that providing less information to the buyer - the potential employer - can reduce discrimination, and that implication contrast with Uri and John's. Precisely because we are looking at the situation from different perspectives.
Economic discrimination is generally accepted, because it is motivated by profits only - doctors, for example, practice it often. Non-economic discrimination, or animus-based, is not socially accepted because it might be motivated by feelings and prejudices.
A draft of Francisco and Gustavo's paper is here. The field of field experiment is incredibly captivating.
Short reviews of The Why Axis are here and here.