We have no idea — same analysis, different results

In a recent paper, Akira Igarashi and James Laurence look at anti-immigrant attitudes in the UK and Japan. Like my 2019 paper in JEMS, they and how they highlight the limited research on non-Western countries, but they analysis they do is much more similar to what Sjoerdje van Heerden and I did in Urban Studies. Them like us relied on panel data to get a better handle on changing attitudes to immigrants. Them like us looked at the share of foreigners in the area (this relates to theoretical expectations that individual attitudes to immigrants reflect changes in the share of foreigners in the area; we refer to the same theories). We both used fixed-effect panel models. They find that “increasing immigration harms attitudes towards immigrant”, while we report that “a larger change in the proportion of immigrant residents is associated with more positive views on immigrants among natives” — yes, the exact opposite!

Need another example? Several studies examine the impact of sudden exposure to refugees on attitudes to immigrants and votes for radical-right parties. Such sudden exposure happened for example in Austria and Germany in 2015. In separate analyses, Andreas Steinmayr 2020 finds a clear increase in support for the radical-right, as we find in the work by Lukas Rudolph and Markus Wagner. Max Schaub, Johanna Gereke and Delia Baldassarri, by contrast “record null effects for all outcomes”. Same situation, same strategy to obtain the results.

We could now start the detective work, examining the small differences in modelling, ponder about the impact of how we define neighbourhoods, invoke possible differences between the countries (are the Netherlands an expectation, when the UK and Japan yield the same results? — not likely). Or we could admit how little we know, how much uncertainty there is in what we do, how vague our theories are in the social sciences that we can come to quite different conclusions in quite similar papers. I guess what we can see here is simply a scientific search for answers (it’s not like our research output would otherwise disagree so clearly). It’s probably also a call for more meta-level research: systematic analyses that synthesize what we do and don’t know, because even though individual papers sometimes contradict, we know quite a lot!

Heerden, Sjoerdje van, and Didier Ruedin. 2019. ‘How Attitudes towards Immigrants Are Shaped by Residential Context: The Role of Neighbourhood Dynamics, Immigrant Visibility, and Areal Attachment’. Urban Studies 56 (2): 317–34. https://doi.org/10.1177/0042098017732692.

Igarashi, Akira, and James Laurence. 2021. ‘How Does Immigration Affect Anti-Immigrant Sentiment, and Who Is Affected Most? A Longitudinal Analysis of the UK and Japan Cases’. Comparative Migration Studies 9 (1): 24. https://doi.org/10.1186/s40878-021-00231-7.

Rudolph, Lukas, and Markus Wagner. 2021. ‘Europe’s Migration Crisis: Local Contact and Out‐group Hostility’. European Journal of Political Research, May, 1475-6765.12455. https://doi.org/10.1111/1475-6765.12455.

Ruedin, Didier. 2019. ‘Attitudes to Immigrants in South Africa: Personality and Vulnerability’. Journal of Ethnic and Migration Studies 45 (7): 1108–26. https://doi.org/10.1080/1369183X.2018.1428086.

Schaub, Max, Johanna Gereke, and Delia Baldassarri. 2020. ‘Strangers in Hostile Lands: Exposure to Refugees and Right-Wing Support in Germany’s Eastern Regions’. Comparative Political Studies, September, 001041402095767. https://doi.org/10.1177/0010414020957675.

Steinmayr, Andreas. 2020. ‘Contact versus Exposure: Refugee Presence and Voting for the Far-Right’. The Review of Economics and Statistics, May, 1–47. https://doi.org/10.1162/rest_a_00922.

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. https://doi.org/10.1080/1369183X.2015.1133279.

Now Published: How attitudes towards immigrants are shaped by residential context

Sjoerdje van Heerden and I have just learned that our paper “How Attitudes towards Immigrants Are Shaped by Residential Context: The Role of Neighbourhood Dynamics, Immigrant Visibility, and Areal Attachment” is now available at Urban Studies. This is the first publication coming out of the SNIS project on attitudes to foreigners.

In the paper, we check whether we can find any evidence for the ‘defended neighbourhood’ thesis, using panel data from the Netherlands and fixed-effect models. It turns out, we find no evidence of such effects in the Netherlands in recent years. The analysis looks at how proportional changes in residential context are associated with changes in attitudes towards immigrants. Following the reasoning that the majority population need to perceive immigrants, we paid particular attention to immigrant visibility. What is more, the unit of analysis is the neighbourhood, as close as possible as people experience it. We have put a lot of thought in choosing the right level, and went with the four-digit postcodes in the Netherlands. From what we gather, this largely corresponds to the perception of neighbourhoods people have, and not an artificial unit that happens to be ‘available’ in the data.

Following the ‘defended neighbourhood’ hypothesis, we focus on proportional change, not absolute numbers as researchers typically do when using cross-sectional data. A larger change in the proportion of immigrant residents is associated with more positive views on immigrants among natives — not what a defended neighbourhood would look like. Indeed, it is particularly a change in the proportion of visible non-Western immigrants that is associated with changes in attitudes.

Heerden, Sjoerdje van, and Didier Ruedin. 2017. “How Attitudes towards Immigrants Are Shaped by Residential Context: The Role of Neighbourhood Dynamics, Immigrant Visibility, and Areal Attachment.” Urban Studies Online First. https://doi.org/10.1177/0042098017732692.

Estimating party positions on immigration: Assessing the reliability and validity of different methods

ppqa_23_3.coverIt’s been in the making for a long time, but I’m happy to announce that Laura Morales and my paper on estimating party positions on immigration is now available from Party Politics. In the paper we provide a systematic assessment of various methods to position political parties on immigration based on their electoral platforms. We do this for Austria, Belgium, France, Ireland, the Netherlands, Spain, Switzerland, and the UK, between 1993 and 2013. There high levels of consistency between expert positioning, manual sentence-by-sentence coding, and manual checklist coding; and poor or inconsistent results with the CMP/MARPOR, Wordscores, Wordfish, and the dictionary approach. An often-neglected method – manual coding using checklists – offers resource efficiency with no loss in validity or reliability. Now there is really no excuse any more for using old CMP data and pretend that they really were about immigration… (with the new subcodes in the most recent codebook things will probably improve for the CMP/MARPOR positions).

We’ve started this as an internal project for the SOM project (hence 7 of the 8 countries), simply because we (thought we) needed party positions on immigration over time. Wary of the time it takes to manually code party manifestos, we tried a few methods. There are two more we have tried but not pursued to the same extent, namely using a dictionary of keywords and Wordfish estimates on the entire text of the party platforms (i.e. without manually selecting the parts of the manifestos that are about immigration). These are not ‘dead’ yet, but we need further tests to ensure we know what they measure.

There’s an 102-page supplement available from the journal’s website.