Hiring now: Postdoctoral Researcher (4 years, 70% FTE)

We’re now hiring a postdoctoral researcher (4 years, 70% FTE) for a project on overcoming inequalities and ethnic discrimination in the labour market. The project is jointly with Wassilis Kassis. You’ll be working at the University of Neuchâtel, and will be joined by a doctoral students by the end of the year. Full advert here: http://nccr-onthemove.ch/wp_live14/wp-content/uploads/2018/03/IP26-Jobs-NCCR-Phase-II-UNINE-PD.pdf

This position is one of the many currently advertised at the NCCR on the move: http://nccr-onthemove.ch/jobs/ — come and join us!

Discrimination not declining

A new meta-analysis draws on correspondence tests in the US to show that levels of ethnic discrimination in hiring do not seem to have changed much since 1989. This persistence in racial discrimination is bad news, and indeed Eva Zschirnt and I have shown the same result across OECD countries a year ago. While policies have changed, especially in the European Union, looking at the ‘average’ from correspondence tests suggests that they may not have been effective — and that is bad news.

Correspondence tests are widely accepted as a means to identify the existence of ethnic discrimination in the labour market, and as field experiments they are in a relatively good position to make the causal claims we typically want to make. It turns out that most correspondence tests have not paid sufficient attention to heterogeneity, which — as David Neumark and Judith Rich demonstrate — means that they likely over-estimate the degree of discrimination. Unfortunately, most old studies did not vary the groups in a way that this could be fixed post-hoc. If we throw these out of the meta-analysis, we probably no longer have sufficient studies to make claims about changes over time.

Meta-analyses are no doubt an important tool of science, but there’s always a delicate balance to be struck: are the experiments included really comparable? Here we’re looking at field experiments in different countries, different labour markets, different jobs, and different ethnic groups. We can control for these factors in the meta-analysis, but with the limited number of studies we have, this might not be sufficient to silence critics. With correspondence tests, we only cover entry-level jobs, and despite much more fine-graded studies going into the field recently, we don’t have a tool to really identify why discrimination takes place.

Neumark, David, and Judith Rich. 2016. ‘Do Field Experiments on Labor and Housing Markets Overstate Discrimination? Re-Examination of the Evidence’. NBER Working Papers w22278 (May). http://www.nber.org/papers/w22278.pdf.

Quillian, Lincoln, Devah Pager, Ole Hexel, and Arnfinn H. Midtbøen. 2017. ‘Meta-Analysis of Field Experiments Shows No Change in Racial Discrimination in Hiring over Time’. Proceedings of the National Academy of Sciences, September, 201706255. doi:10.1073/pnas.1706255114.

Zschirnt, Eva, and Didier Ruedin. 2016. ‘Ethnic Discrimination in Hiring Decisions: A Meta-Analysis of Correspondence Tests 1990–2015’. Journal of Ethnic and Migration Studies 42 (7): 1115–34. doi:10.1080/1369183X.2015.1133279.

Image: CC-by CharlotWest

Did I just find these “missing” papers in the meta-analysis on hiring discrimination?

When Eva Zschirnt and I were working on the meta-analysis on ethnic discrimination in hiring, I also run one of these tests for publication bias (included in the supplementary material S12). According to the test, there are a couple of studies “missing”, and we left this as a puzzle. Here’s what I wrote at the time: “Given that studies report discrimination against minority groups rather consistently, we suspect that a study finding no difference between the minority and majority population, or even one that indicates positive discrimination in favour of the minority groups would actually be easier to publish.” (emphasis in original).

We were actually quite confident not to have missed many studies. One way is to dismiss the assumptions between the tests for publication bias. Perhaps a soft target, but who are we to say that there are no missing studies?

Here’s another explanation that didn’t occur to me at the time, and nobody we asked about it explicitly came up with it. It’s just a guess, and will remain one. David Neumark has suggested a correction for what he calls the “Heckman critique” in 2012. We were aware of this, but I did not connect the dots until reading David Neumark and Judith Rich‘s 2016 NBER working paper where they apply this correction to 9 existing correspondent tests. They find that the level of discrimination is often over-estimated without the correction: “For the labor market studies, in contrast, the evidence is less robust; in about half of cases covered in these studies, the estimated effect of discrimination either falls to near zero or becomes statistically insignificant.”

This means that the “Heckman critique” seems justified, and at least in the labour market some of the field experiments seem to overstate the degree of discrimination. Assuming that this is not unique to the papers they could re-examine, the distribution of effect sizes in the meta-analysis would be a bit different and include more studies towards the no discrimination end. I can imagine that in this case, the test for publication bias would no longer suggest “missing” studies. Put different, these “missing” studies were not missing, but reported biased estimates.

The unfortunate bit is that we cannot find out, because the correction provided by David Neumark has data requirements not all existing studies can meet. But at least I have a potential explanation to that puzzle: bias of a different kind than publication bias and the so-called file-drawer problem.

Neumark, D. (2012). ‘Detecting discrimination in audit and correspondence studies’, Journal of Human Resources, 47(4), pp. 1128-157

Neumark, David, and Judith Rich. 2016. “Do Field Experiments on Labor and Housing Markets Overstate Discrimination? Re-Examination of the Evidence.” NBER Working Papers w22278 (May). http://www.nber.org/papers/w22278.pdf.

Zschirnt, Eva, and Didier Ruedin. 2016. “Ethnic Discrimination in Hiring Decisions: A Meta-Analysis of Correspondence Tests 1990–2015.” Journal of Ethnic and Migration Studies 42 (7): 1115–34. doi:10.1080/1369183X.2015.1133279.

Planning a Field Experiment? Read These First

Are you planning to run a field experiment, perhaps even on discrimination in hiring decisions? As a complement to our meta-analysis of existing field experiments on ethnic discrimination in hiring, you could do worse than reading two recent working papers by my co-author Eva Zschirnt: In one, she outlines the history of field experiments in much more detail than a journal article can do, in the other she collects ethical considerations in a single place.

Zschirnt, Eva. 2016a. ‘Measuring Hiring Discrimination – A History of Field Experiments in Discrimination Research’. NCCR On the Move Working Paper Series 7 (May): 1–32.
———. 2016b. ‘Revisiting Ethics in Correspondence Testing’. NCCR On the Move Working Paper Series 8 (May): 1–26.
Zschirnt, Eva, and Didier Ruedin. 2016. ‘Ethnic Discrimination in Hiring Decisions: A Meta-Analysis of Correspondence Tests 1990–2015’. Journal of Ethnic and Migration Studies 42 (7): 1115–34. doi:10.1080/1369183X.2015.1133279.

Ethnic discrimination in hiring decisions: a meta-analysis of correspondence tests 1990–2015

Eva Zschirnt and I have undertaken a meta-analysis of correspondence tests in OECD countries between 1990 and 2015. It is now available on the website of JEMS. We cover 738 in 43 separate studies conducted in OECD countries between 1990 and 2015. In addition to summarizing research findings, we focus on groups of specific tests to ascertain the robustness of findings, emphasizing (lack of) differences across countries, gender, and economic contexts. Discrimination of ethnic minority and immigrant candidates remains commonplace across time and contexts.