provide direct evidence for hiring discrimination based on ethnicity: job applications with native names receive between 14 and 50 percent more positive callbacks than applications with non-native names in the US, Germany and Belgium. However, identifying discrimination is one thing; tackling it is another.To combat labour market discrimination effectively, we need to understand its underlying mechanisms. As reviewed by Guryan & Charles (2013), the leading explanations for labour market discrimination still go back to the theoretical models of taste-based discrimination, as introduced by Becker (1957), and statistical discrimination, as introduced by Phelps (1972) and Arrow (1973). In the model of taste-based discrimination, members of the majority experience a disutility from interacting with minority workers and are willing to pay a financial price to avoid such interactions. Becker (1957) describes three sources of discriminatory tastes: employers, co-workers and customers. Statistical discrimination occurs when employers examine statistics about a group's average performance to predict a particular applicant's productivity as a time-efficient and profit-maximising response to imperfect information about the actual productivity of the individual job candidate.As reviewed by Guryan & Charles (2013), most papers attempting to answer the question whether taste-based or statistical discrimination is a more appropriate explanation for unequal treatment in the labour market have conducted indirect assessments: they have measured whether particular patterns in economic data square predictions of the model being tested. The problem with this literature is that testing between the two models is only convincing to the degree that a particular pattern is explicable exclusively by one model, a challenge that is, as shown by Guryan & Charles (2013), rarely met. Recent work, however, has attempted to test more essential arguments of the taste-based model or the statistical discrimination model in explaining labour market discrimination (see Bertrand

No abstract

During the last decade, economists have attempted to identify Sticky Floors in the labour market, thereby building on the seminal work by Booth et al. (2003). Sticky Floors can be described as the pattern that women are, compared to men, less likely to start to climb the job ladder. Thereby Sticky Floors complement the well-known concept of Glass Ceilings which implies that women are less like to reach the top of the job ladder. 1 Evidence for the existence of Sticky Floors has been found in countries such as Italia (Filippin and Ichino, 2005), Spain (Gradín and del Río, 2009), Thailand (Fang and Sakellariou, 2011) and the United States (Baker, 2003). In Belgium, the country where the present study is accomplished, Deschacht et al. (2011) conclude, based on their discrete time event history analysis of the Panel Study of Belgian Households data (1994-2001), that women near the top face fewer obstacles to promotions than women in the lower-and mid-career levels. In addition, Belgium is one of the 12 European countries in which Christofides et al. (2013), investigating the gender wage gap across 24 EU member states, found evidence for Sticky Floors. From a policy perspective, it is important to determine the nature of the phenomenon of Sticky Floors in order to design adequate policy actions. Based on the mentioned literature, however, it is unclear whether Sticky Floors result from gender differences in human capital, preferences and behaviour at the employee side or from preferences (and unequal treatment) at the employer side. In our study, we contribute to the literature by investigating the importance of employer preferences (and thereby discrimination) in explaining Sticky Floors, keeping employee characteristics constant. 2 More concretely, we aim at answering the question whether unequal treatment of equally productive male and female job candidates by employers is heterogeneous by whether or not