of age non-parametrically by including dummies for four age groups which roughly correspond to age quartiles. I find a monotonic decline of clicks in age indicating that employers prefer young domestic workers. Overall, it is reassuring that nationality coefficients remain very stable when controlling for demographic and socio-economic variables.<sup>17</sup>

# **4.1.2 Cross-sector comparison**

As described in section 3, I collect data from three sectors: domestic work (Dom), nanny (Nan) services, and general work (Gen). These professions are very different with respect to the frequency and intimacy of interaction. Domestic workers have access to the personal living space and often live with the employer. The relationship with nannies is even more intimate as they take care of the employer’s children. If employers dislike being around foreigners, we would expect discrimination to be largest in the nanny sector and smallest in the general work sector. To test how employer demand for foreigners varies, I estimate equation 1 separately for each sector. Coefficients reported in Table 2 provide support for this hypothesis. The effect of being Malawian or Zimbabwean is about 50% and 200% larger in the domestic work and nanny sector, respectively, compared to the general work sector. However, this test remains inconclusive since there may be other unobservable differences like reputation of different nationality that vary across sectors.

The coefficients on adding a picture to the profile also show interesting cross-sectoral differences. While the effect is large and highly significant in each sector, it is 30% and 40% larger for the domestic work and nanny sector, respectively, compared to the general work sector. Taken at face value, this indicates that the increased level of familiarity and trust that pictures evoke are more important in sectors with a more intimate employer-employee relationship.<sup>18</sup>

> 17 While we focus on the immigrant status, there are additional interesting results, e.g. on references. 31% of profiles in the domestic work sector mention a reference in the search result. I divide these profiles into three groups: ads that were posted by the employer on behalf of their current worker ( _Employer posts_ ), ads that list the phone number of a reference ( _Refer.phone)_ and those that only lists having a reference ( _Reference_ ). Results in Column 4 show that just mentioning a reference is associated with 3.5% _fewer_ profile clicks whereas providing a reference without a number has no effect. By contrast, job ads posted by current employers receive about 10% more clicks. These results suggest that employers tend to be suspicious and that references need to be credible in order to be effective Abel et al. (2017). In addition, many job seekers claim on their profiles to be ‘hardworking’, ‘reliable’ and ‘trustworthy’. The effect of these claims on the number of clicks is very small and statistically insignificant (results not reported), possibly because these traits are not easily verifiable and may thus be regarded as ‘cheap talk’.

> 18In a seperate analysis, I asked South Africans to rate these pictures according to two metrics: i) physical attractiveness and ii) to what extent the picture reflects the image of a domestic worker. The phycial attractiveness measure was a significant positive determinant of profile clicks whereas the second measure was negatively correlated. While these results warrant further investigation they suggest that some people may review job postings for reasons unrelated to hiring workers.

12