Trump understands this, Merkel certainly does not

Immigration and Redistribution

by Alberto Alesina, Armando Miano, Stefanie Stantcheva

First the expected biases and overestimates.

We find strikingly large biases in natives' perceptions of the number and characteristics of immigrants: in all countries, respondents greatly overestimate the total number of immigrants, think immigrants are culturally and religiously more distant from them, and are economically weaker – less educated, more unemployed, poorer, and more reliant on government transfers – than is the case.

Prevalence is where?

While all respondents have misperceptions, those with the largest ones are systematically the right-wing, the non-college educated, and the low-skilled working in immigration-intensive sectors.

It's not the numbers, it's who they are.

Support for redistribution is strongly correlated with the perceived composition of immigrants – their origin and economic contribution – rather than with the perceived share of immigrants per se. 

But then again just thinking about them ...

Given the very negative baseline views that respondents have of immigrants, simply making them think about immigration in a randomized manner makes them support less redistribution, including actual donations to charities. 

Even favorable traits get discounted quickly.

We also experimentally show respondents information about the true i) number, ii) origin, and iii) “hard work” of immigrants in their country. On its own, information on the “hard work” of immigrants generates more support for redistribution. However, if people are also prompted to think in detail about immigrants' characteristics, then none of these favorable information treatments manages to counteract their negative priors that generate lower support for redistribution.

Which will show up in election results and compound the political landscape

via MR