Statistical Discrimination or Prejudice? A Large Sample Field Experiment

Abstract

A model of racial discrimination provides testable implications for two features of statistical discriminators: differential treatment of signals by race and heterogeneous experience that shapes perception. We construct an experiment in the U.S. rental apartment market that distinguishes statistical discrimination from taste-based discrimination. Responses from over 14,000 rental inquiries with varying applicant quality show that landlords treat identical information from applicants with African-American and white sounding names differently. This differential treatment varies by neighborhood racial composition and signal type in a way consistent with statistical discrimination and in contrast to patterns predicted by a model of taste-based discrimination.

Ethnic and gender discrimination in the rental housing market: Evidence from a meta-analysis of correspondence tests, 2006–2017

“…Thus "positive response" is a subgroup of "simple response", but, as some studies have reported only one type of responses and as these different types of responses do not represent the same thing, it is maybe rather wise not to mix corresponding odd-ratio. Indeed, despite its practicality, comparing simple response rates may not be the best way to determine discrimination and might tend to underestimate it, "to the extent that majority rates could include more positive responses than minority rates" (Ewens et al, 2014). Fortunately, our database has more positive responses ratios than simple ones because it seems to become the norm in this literature despite the fact that it is easier for authors to record simple response rates for each ethnic group than positive response rates that require large sorting.…”

“…We included data from 25 studies, covering 14 countries: France (Acolin et al, 2016, Bunel et al, 2017, Bunel et al 2016, Le Gallo et al, 2017, Canada (Hogan, Berry, 2011), Czech Republic (Bartoš et al, 2016), Slovakia (Sacherová, 2016), Finland (Öblom and Antfolk, 2017), Denmark (Herby and Nielsen, 2015), Germany (Auspurg et al, 2017, Team BR Data andSpiegel Online, 2017), Italy (Baldini and Federici, 2011), Norway (Andersson et al, 2012), Spain (Bosch et al, 2010, Bosch et al, 2015, Sweden (Ahmed et al, 2010, Ahmed and Hammarstedt, 2008, Carlsson and Eriksson, 2013, Iceland (Björnsson et al, 2017), Israel (Sansani, 2017) and finally USA (Carpusor and Loges, 2006, Ewens et al, 2014, Friedman et al, 2010, Hanson and Hawley, 2011, Hanson and Santas, 2014, which are countries very similar in terms of development, whether human or economic.…”

“…Another large scale experiment was conducted at the same time by Ewens et al (2014) and also provides evidence from discrimination against Black people in USA. By sending 14 000 single inquiries to private landlords in 34 major US cities between September and October 2009, they find a level of discrimination relatively close to Hanson and Hawley (2011): positive response rate for Black sounding names applicants is 9.3% points lower than for White when no signal inquiries were sent.…”

Gender bias in public long-term care? A survey experiment among care managers

“…Field experiments show that individuals who are identical except for a group characteristic (gender, race, etc.) are treated differently in the housing market (Andersson et al, 2012;Carlsson and Eriksson, 2014;Ewens et al, 2014) and in the labor market (Bertrand and Mullainathan, 2004;Carlsson and Rooth, 2007). A critique of field studies made by Heckman (1998) is that 1 Balsa et al (2005) use a cross-section of black and white patients, and find that the probability of being diagnosed with depression and mental health problems is reduced for black patients relative to white patients.…”

“…4 This can be true if CMs regard informal care as a free resource, because, as long as informal care is provided, the benefit of doing so outweighs the cost, or if the CMs are only concerned about the health of patients.5 This closely follows the four-stage process of matching tenants to apartments inEwens et al (2014).6 As will be made clear later, we are considering four groups defined by the gender of the patient and gender of the patient's child, i.e., g i ∈ {FatherSon, FatherDaughter, MotherSon, MotherDaughter}.7 Phelps (1972) assumes the same utility function for employers hiring workers with unobservable quality. Please cite this article in press as: Jakobsson, N., et al, Gender bias in public long-term care?…”