Does Ethnic Discrimination Vary Across Minority Groups? Evidence from a Field Experiment*
| DOI | http://doi.org/10.1111/j.1468-0084.2011.00664.x |
| Author | Andrew Leigh,Alison L. Booth,Elena Varganova |
| Published date | 01 August 2012 |
| Date | 01 August 2012 |
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©Blackwell Publishing Ltd and the Department of Economics, University of Oxford 2011. Published by Blackwell Publishing Ltd,
9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 74, 4 (2012) 0305-9049
doi: 10.1111/j.1468-0084.2011.00664.x
Does Ethnic Discrimination Vary Across Minority
Groups? Evidence from a Field Experiment*
Alison L. Booth†, Andrew Leigh‡ and Elena Varganova
†Economics Department, University of Essex, Wivenhoe Park CO4 3SQ, UK and Research School
of Economics, Australian National University, ACT 0200, Australia (e-mail: albooth@essex.ac.uk)
‡Research School of Economics, Australian National University, ACT 0200, Australia
(e-mail: andrew.leigh@anu.edu.au)
Research School of Economics, Australian National University, ACT 0200, Australia
(e-mail: evarganova@yahoo.com)
Abstract
We conduct a large-scale field experiment to measure labour market discrimination in
Australia, one quarter of whose population was born overseas. To denote ethnicity, we use
distinctively Anglo-Saxon, Indigenous, Italian, Chinese and Middle Eastern names. We
compare multiple ethnic groups, rather than a single minority as in most other studies. In
all cases we applied for entry-level jobs and submitted a CV indicating that the candidate
attended high school in Australia. We find significant differences in callback rates: ethnic
minority candidates would need to apply for more jobs in order to receive the same number
of interviews. These differences vary systematically across ethnic groups.
‘After completing TAFE in 2005 I applied for many junior positions where no experience in
sales was needed – even though I had worked for two years as a junior sales clerk. I didn’t
receive any calls so I decided to legally change my name to Gabriella Hannah. I applied for
the same jobs and got a call 30 minutes later.’
∼Gabriella Hannah, formerly Ragda Ali, Sydney
ÅFor valuable comments, we are grateful to two anonymous referees, Boyd Hunter, Gigi Foster, Steven Haider,
and seminar participants at the 2010 World Conference of the EuropeanAssociation of Labour Economists and the
Society of Labor Economists, theAustralian National University’s Social and Political Theory Seminar, theAustralian
National University Centre forAboriginal Economic Policy Research seminar, the Australasian Labour Econometrics
Workshop, and Monash University. Iktimal Hage-Ali andAmy King put us in touch with Gabriella Hannah, who
is quoted at the start of the paper. Pablo Mateos kindly allowed us to use a beta version of his Onomap software
to impute ethnicity to the names of employers. Mathias Sinning provided invaluable programming assistance and
Susanne Schmidt outstanding research assistance. The background section of this paper uses unit record data from
the Household, Income and Labour Dynamics in Australia (HILDA) Survey.The HILDA Project was initiated and is
funded by theAustralian Government Department of Families, Housing, Community Services and Indigenous Affairs
(FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (MIAESR).The
findings and views reported in this paper, however, are those of the authors and should not be attributed to either
FaHCSIA or the MIAESR. We take very seriously the ethical issues surrounding this research. Our experiment
received approval from the Australian National University’s Human Research Ethics Committee. It involves some
deception of participants – for a thoughtful discussion on the ethics of deception in such field experiments, see Riach
and Rich (2004).
JEL Classification numbers: J71, C93.
548 Bulletin
I. Introduction
How should we measure ethnic discrimination? Among economists, the most common
approach has been to compare labour market outcomes across ethnic groups. But this
method may not provide an accurate answer. If an individual’s ethnicity is correlated with
some unobserved productive trait, then differences in economic outcomes will reflect more
than just discrimination. Similarly, social researchers have often used surveys to measure
the degree of racism in a society. But if respondents know the socially correct response,
then this approach will also provide a biased estimate of true attitudes towards ethnic
groups. When studying labour market outcomes, the problem arises from unobservable
characteristics of ethnic minorities. When analysing social attitudes, the problem stems
from unobservable biases in the reporting of ethnic attitudes.1
In both cases, field experiments can help solve the unobservables problem by creating
a context in which all other factors except ethnicity are held constant. In a context where
the subject is unaware that he or she is participating in an experiment – or in which it is
difficult for the subject to provide a socially acceptable response – it is more likely that the
outcome will provide an accurate measure of racism than with more traditional approaches.
The strengths of field experiments of this type are that they are randomized experiments
that establish causality and provide strong evidence for the existence of discrimination.
Explanations of employer motives generally call for other methods.2So too do explana-
tions as to why some particular ethnic groups might be discriminated against more than
others.
In this article, we present the results of a field experiment that we conducted in order
to estimate discrimination against ethnic minorities in Australia, a country whose immi-
gration policy based on a points system has been admired and adopted by other coun-
tries, including New Zealand and the UK. Unlike many field experiments, looking only
at a single minority group, we take a broader focus: comparing attitudes to Anglo-Saxon
Australians with attitudes to Indigenous Australians (the original inhabitants of the con-
tinent), Italian Australians (a relatively established migrant group), Chinese Australians
(a more recent migrant group), and Middle Eastern Australians (another recent migrant
group). By comparing across these groups, we hope to shed light on how the process of
immigrant assimilation might change over time. However, we would not wish to push
too hard the use of our experiment as a measure of how time in the country matters for
discrimination rates, for there are other conjectures as to how stereotypes are formed. For
instance, Eagly and Kite (1987, p. 452) hypothesise that individuals form stereotypes of
people from particular countries based not so much on direct forms of interaction but rather
1We de fine an ethnic group as comprising individuals who are perceived as having a common heritage consisting
of a common language, culture and ancestry.
2As Arrow (1998, p. 96) notes, without explicit measures for the individual’smarginal productivity, it is impossi-
ble to distinguish between taste-based and statistical forms of discrimination. While in our experiment all applicants
attended school in Australia, and we hold constant their education and experience, it is likely that stereotypes about
productivity still remain. For example, employers might view ethnic minority workers as less productive because
of poor language skills that are not manifest in the application. This might be so even though such beliefs receive
little support in, for example, the HILDA data. Among HILDArespondents who were born in Australia, but whose
parents were born overseas, 98–99% report speaking English ‘very well’ (the highest category in the survey). Since
we cannot give in our fictional CVs precise measures of the applicant’s productivity, we are unable in this study to
separately identify the extent of statistical discrimination.
©Blackwell Publishing Ltd and the Department of Economics, University of Oxford 2011
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