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Gender inequality in paid work persists, in the form of a gender wage gap, occupational sex segregation and a “glass ceiling” for women, despite substantial institutional change in recent decades. Two classes of explanations that have been offered as partial explanations of persistent gender inequality include economic theories of statistical discrimination and social psychological theories of status-based discrimination. Despite the fact that the two theories offer explanations for the same phenomena, little effort has been made to compare them, and practitioners of one theory are often unfamiliar with the other. In this article, we assess both theories. We argue that the principal difference between the two theories lies in the mechanism by which discrimination takes place: discrimination in statistical models derives from an informational bias, while discrimination in status models derives from a cognitive bias. We also consider empirical assessments of both explanations, and find that while research has generally been more supportive of status theories than statistical theories, statistical theories have been more readily evoked as explanations for gender inequalities in the paid labor market. We argue that status theories could be more readily applied to understanding gender inequality by adopting the broader conception of performance favored by statistical discrimination theories. The goal is to build on the strong empirical base of status characteristic theory, but draw on statistical discrimination theories to extend its ability to explain macro level gender inequalities.

This article deals with the impact of ethnic origin on individual employability, focussing on the first stage of the hiring process. Deeply, the authors’ goal is to fathom whether there is a preference for native job candidates over immigrants, decomposing the discrimination against minority groups into its statistical and taste-based components by means of a new approach.

The authors built up a data set by means of an ad hoc field experiment, conducted by sending equivalent fictitious CVs in response to 1000 real online job openings in Italy. The authors developed the discrimination decomposition index using first- and second-generation immigrants.

The authors’ main result is that both first- and second-generation immigrants are discriminated compared to Italians. In between the two categories, second-generation candidates are discriminated especially if their ethnicities are morphologically different from those of natives (i.e. Chinese and Moroccans). This last finding is a clear symptom of discrimination connected to taste-based reasons. On the other hand, first-generation immigrants of all nationalities but Germans are preferred for hard-work jobs.

The authors develop the discrimination decomposition index to measure the proportion of the two kinds of discrimination (statistical and taste-based) over the total one and apply a probit model to test the statistical significance of the difference in treatment between the three groups of natives, first-generation and second-generation immigrants.

Purpose – Research has shown that employers often disfavor racial minorities − particularly African Americans − even when whites and minorities present comparable resumes when applying for jobs. Extant studies have been hard pressed to distinguish between taste-based discrimination where employers' racial animus is the key motivation for their poor treatment of minorities and variants of statistical discrimination where there is no assumption at all of racial animus on the part of the employer. This chapter proposes a test of these theories by observing whether employers use employee referrals as a “cheap” source of information to help assess applicant quality.Methodology/approach – Unique quantitative data encompassing the entire pool of 987 candidates interviewed by one company in the western United States during a 13-month period are used to test our arguments.Findings – We find that employers in this setting are making use of the cheap information available to them: Consistent with statistical discrimination theory, minority referrals are more likely to receive a job offer than non-referred minority applicants, and are not disfavored relative to referred whites.Originality/value of the chapter – Both statistical and taste-based theories of discrimination propose similar observable outcomes (lower rates of disfavored minority hiring). While different mental processes are being invoked by taste-based and statistical discrimination theories, the theories are extremely difficult to distinguish in terms of observable behaviors. Especially for the purpose of designing legal remedies and labor market policies to ameliorate the disparate treatment of minority groups, differentiating between these theories is a high priority.

The purpose of this paper is to explore the mechanisms underlying hiring discrimination against transgender men.

The authors conduct a scenario experiment with final-year business students in which fictitious hiring decisions are made about transgender or cisgender male job candidates. More importantly, these candidates are scored on statements related to theoretical reasons for hiring discrimination given in the literature. The resulting data are analysed using a bivariate analysis. Additionally, a multiple mediation model is run.

Suggestive evidence is found for co-worker and customer taste-based discrimination, but not for employer taste-based discrimination. In addition, results show that transgender men are perceived as being in worse health, being more autonomous and assertive, and have a lower probability to go on parental leave, compared with cisgender men, revealing evidence for (positive and negative) statistical discrimination.

Targeted policy measures are needed given the substantial labour market discrimination against transgender individuals measured in former studies. However, to combat this discrimination effectively, one needs to understand its underlying mechanisms. This study provides the first comprehensive exploration of these mechanisms.

This study innovates in being one of the first to explore the relative empirical importance of dominant (theoretical) explanations for hiring discrimination against transgender men. Thereby, the authors take the logical next step in the literature on labour market discrimination against transgender individuals.

Sexual orientation and employment bias is examined in Cyprus by implementing an experiment for the period 2010-2011. The design is aimed at answering three main questions. Do gay males and lesbians face occupational access constraints and entry wage bias than comparable heterosexuals? Do gay males and lesbians benefit from providing more job-related information? Does the differential treatment between gay male/lesbian and heterosexual applicants disappear as the information of the applicants increases? The paper aims to discuss these issues.

The author sent applications to advertised vacancies and experimented with two information sets the “sexual orientation” and “information” of the potential applicants.

The estimations suggest that gay male and lesbian applicants face significant bias than heterosexual applicants. Moreover, both heterosexual and gay male/lesbian applicants gain by providing more job-related information. However, the estimations suggest that the informational premium for sexual orientation minorities could not reduce the discriminatory patterns.

The current results indicate that discrimination against sexual orientation minorities in the Cypriot labour market is a matter of preference, not the result of limited information. One strategy the Cypriot government may employ is to try to affect public opinion and people's attitudes towards sexual orientation minorities.

This is the first nationwide field experiment in the Cypriot labour market and contributes to the literature as it is the first field study on sexual orientation which tries to disentangle statistical from taste-based discrimination in the labour market.

In this chapter, I analyse the ethics of organisations assessing applicants based on group risk statistics; for example, parole boards consider information predicting recidivism risk, and employers want to minimise the risk of selecting lower-productivity employees. The organisational rejection of applicants from risky groups is explored as a form of discrimination to help identify the distinct ethical implications for applicant autonomy from the use of group risk statistics. Contra arguments from Schoeman (1987) and Schauer (2003), I argue that there is a substantive difference between assessing applicants directly through group statistics rather than including ‘individualised’ evidence. This difference impacts on the agency of applicants in the process. As organisations have reason to statistically assess applicants, some considerations for increasing applicant agency in the process are suggested. These include focusing on the nature of the factors used to assess applicants (static or dynamic), the transparency of the process to applicants, and the use of statistics specific to individuals.

Starts out with a survey of various formal theories that have focused on discrimination in the labor market. Argues that Becker’s traditional taste for discrimination model, the various statistical discrimination models and the new cultural communication cost models ultimately yield analytically and observationally equivalent predictions. In particular, these models all imply that we may find occupational segregation across firms. This, in turn, suggests that it is not easy to identify the true causes of discriminatory wage differentials in the labor market and thus that we may have a very hard time sorting out which of these models applies best. Finally, speculates, in the context of Kremer’s model of economic growth, about how changing technologies and structure of production could possibly exacerbate the inequalities predicted by these models of discrimination in the labor market.

This paper discusses the factors to consider when designing studies to measure hiring discrimination against transgender job applicants.

The paper builds on academic literature related to hiring discrimination and transgender employment to build a detailed discussion of the numerous factors and issues inherent in hiring discrimination against transgender job applicants. By isolating and describing a number of relevant considerations, the paper aims to act as a guide for future studies to build upon.

Three types of hiring discrimination studies are discussed: correspondence tests, in-person experiments and student cohort experiments. Three main categories of factors relevant to an experiment’s design are then discussed: the legal context, industry/role factors and transgender population-specific factors. A flow-chart detailing the research design decision-making process is provided.

The discussion within this paper will act as a reference and a guide for researchers seeking to address the dearth of empirical studies in the literature. The list is not exhaustive; while a number of factors relevant to transgender-specific studies are identified, there may be more that could affect an experiment's design.

Hiring discrimination against transgender people has been recorded in many surveys, but there is little empirical measurement of this discrimination. To the author's knowledge, this paper is the first to examine the experimental design decisions related to transgender hiring discrimination. In doing so, it provides contributions for two primary audiences: those researching transgender employment issues but who have never conducted a study measuring hiring discrimination; and those who have previously conducted studies on hiring discrimination, but have not done so with reference to transgender job applicants.

The purpose of this review is to explicate the role of statistics as evidence in employment litigation, especially in regard to statistical proof involving claims of employment discrimination. The use of statistics to uncover discrimination and as a means to criticize or justify varied personnel practices is examined, drawing upon legal, scientific, statistical, and psychological literature. Statistical evidence is scrutinized as potentially persuasive indirect evidence of discrimination, with an emphasis on the utilization of statistical methods under the theories of adverse impact and disparate treatment. In order to explore the historical context and contemporary use of specific statistical techniques in employment discrimination litigation, an extensive investigation of statistics presented in cases filed under Title VII of the Civil Rights Act of 1964 and The Age Discrimination in Employment Act of 1967 is conducted. Criticisms and perceived benefits of statistical analyses in litigation are addressed, as are future trends pertaining to advanced statistical methodology and the acceptance of statistics in the legal arena. Implications for human resource management policies and practices are presented.

The purpose of this paper is to explore the mechanisms underlying hiring discrimination against transgender women.

The authors conduct a scenario experiment in which fictitious hiring decisions are made about transgender or cisgender female job candidates. In addition, these candidates are scored on statements related to theoretical reasons for hiring discrimination given in the literature. The resulting data are analysed by means of a multiple mediation model.

The results suggest that prejudices with respect to the health of transgender individuals mediate unfavourable treatment of them. However, this mechanism is compensated by a beneficial perception concerning transgender women’s autonomy and assertiveness.

Targeted policy measures are needed given the substantial labour market discrimination against transgender individuals measured in former studies. However, to combat this discrimination effectively, one needs to understand its underlying mechanisms. This study provides a first exploration of these mechanisms.

This study innovates in being the first to explore the relative empirical importance of dominant (theoretical) explanations for hiring discrimination against transgender women. Thereby, the authors take the logical next step in the literature on labour market discrimination against transgender individuals.