Here is the introduction to an interesting paper. It covers some similar to ground to some of my recent and upcoming posts but uses data on immigrant groups to Denmark:
Stereotypes, that is, people’s beliefs about groups1, are often assumed to be exaggerated and inaccurate (Jussim, 2012). However, whether this is so is rarely examined. The existing body of research reveals that stereotypes are usually fairly accurate and rarely ex- aggerate real differences (Jussim, 2012; Jussim et al., 2015). Demographic stereotypes tend to be among the more accurate. As far as we know, only one prior (pi- lot) study has examined stereotype accuracy in Den- mark (Kirkegaard & Bjerrekær, 2016a). The study was small (N = 48 after quality control), had a strongly unrepresentative sample but was preregistered. It found that stereotypes were fairly accurate (median correlational accuracy score = .51), but the results are hard to generalize to the overall population. The present study is a replication and expansion of the prior study using a large, nationally representative sample.
Please forgive any odd formatting. Through the miracle of the modern US service economy I am without internet except for my phone and will remain so at least through the weekend. It also means that I only went through the paper on my phone. Still, I am not seeing anything obviously wrong with the paper. I like that they made their data available, were crystal clear on methodology, and pre-registered what they were going to be doing before they did it. My only quibble is that their “large” sample only contained 484 observations once they cleaned up the data. There is wrong with 484 observations. I often work with much less, but I wouldn’t call that a large sample.
Here is the abstract, which I think is more clear after you read the introduction reproduced above.
A nationally representative Danish sample was asked to estimate the percentage of persons aged 30-39 living in Denmark receiving social benefits for 70 countries of origin (N = 766). After extensive quality control procedures, a sample of 484 persons were available for analysis. Stereotypes were scored by accuracy by comparing the estimates values to values obtained from an official source. Individual stereotypes were found to be fairly accurate (median/mean correlation with criterion values = .48/.43), while the aggregate stereotype was found to be very accurate (r = .70). Both individual and aggregate-level stereotypes tended to underestimate the percentages of persons receiving social benefits and underestimate real group differences. In bivariate analysis, stereotype correlational accuracy was found to be predicted by a variety of predictors at above chance levels, including conservatism (r = .13), nationalism (r = .11), some immigration critical beliefs/preferences, agreement with a few political parties, educational attainment (r = .20), being male (d = .19) and cognitive ability (r = .22). Agreement with most political parties, experience with ghettos, age, and policy positions on immigrant questions had little or no predictive validity. In multivariate predictive analysis using LASSO regression, correlational accuracy was found to be predicted only by cognitive ability and educational attainment with even moderate level of reliability. In general, stereotype accuracy was not easy to predict, even using 24 predictors (k-fold cross-validated R2 = 4%). We examined whether stereotype accuracy was related to the proportion of Muslims in the groups. Stereotypes were found to be less accurate for the groups with higher proportions of Muslims in that participants underestimated the percentages of persons receiving social benefits (mean estimation error for Muslim groups relative to overall elevation error = -8.09 %points). The study was preregistered with most analyses being specified before data collection began.
I imagine they separated Muslim groups because those are relatively recent and numerous in a country like Denmark, and despite laws to the contrary, often stereotyped. But not necessarily discriminated against:
It can be seen that even the most extreme nationalists in this sample are still not biased against Muslim groups in their ratings because the regression line does not cross 0.
There are a few figures in the article (I will let you look them up) that could have come from my recent posts, even though it looks at welfare by national origin in Denmark and I have been looking at income levels by national origin in the US. Looking at a graph, It seems that countries whose emigrants perform well in the US perform well in Denmark, and those that do poorly in one country do poorly in the other. At a glance the big difference seems to be the lack of Central American immigrants in Denmark in large enough numbers to show up in their graph.
In their conclusion, they find that on aggregate, Danish stereotypes vis a vis how different groups of immigrants to Denmark tend to be dependent on welfare tend to be pretty accurate.
So what does this article plus my posts imply about the economy? The degree to which countries produce emigrants who are culturally well adapted to contribute to the economy can vary dramatically. Immigrants can add to or subtract from productivity. One of the arguments for increased immigration is that the dwindling birth rate in many Western countries means those countries will require an influx of immigrants to keep their economies humming. But the data implies that this only works if immigration is done selectively. Otherwise, immigration can exacerbate issues in the economy.