Economic Outcomes of Immigrants v. Their Stay at Home Counterparts: What the Data Shows


Mike Kimel

Economic Outcomes of Immigrants v. Their Stay at Home Counterparts: What the Data Shows

In this post, I will test whether people from countries with relatively poor economies also tend to do poorly when they relocate to the United States. As an example, GDP per capita for Haiti is much lower than GDP per capita for Hong Kong. Does the available data also say Haitian immigrants to the US generate lower income per capita than immigrants from Hong Kong? In general, as we will see below, the answer is yes.

Data used in this post comes from two sources. The first is GDP per capita, by country, obtained from the World Bank. The post also uses information obtained from the Census Department’s 2014 American Community Survey. In particular, the post uses the 2014 per capita income of immigrants to the US by nation of origin. It also uses the percentage of the immigrants from a given country that have arrived in the US prior to the year 2000. That data is kind of unwieldy to find, but the starting point is here. To be clear, immigrants in this source are foreign born, which is to say first generation only. Only immigrants alive at the time of the survey are included.

There are 72 countries for which there is data on per capita income for that country’s immigrants to the US (from the Census) and for which 2014 GDP per capita is available (from the World Bank). The graph below shows per capita income for those immigrants along the X axis, and GDP per capita along the Y axis.

immigrants1Figure 1

The correlation is 0.7, which is fairly high. That is to say, in general, the poorer a country is, the worse its immigrants fare in the US. This is because on aggregate the skills and culture of people living in poor countries do not command a high price on the world market. Such a combination of skills and culture will also not command a high price in a large open economy like the US. (Yes, there are exceptions. Some will be covered in later posts.)

But… does the problem solve itself? Do immigrants from poor countries who are in the US long enough abandon less successful cultures, develop new skills, and start performing more like natives and less like their stay-at-home former compatriots? Or is something akin to a “water seeking its own level” effect? If so, we would expect that after the shock of immigration wears off, immigrants from country X converge back for better or worse to the same levels of performance we see in country X.

It turns out we can answer that question too. The Census data provides breakdowns for the percentage of the immigrants from each country who arrived before the year 2000. (Arrivals between 2000 and 2009, and from 2010 to 2014 are also provided but are generally not used in in this post.) The third quartile for “arrived before the year 2000″ is 68.3%. That is, for a quarter of the countries in the sample, 68.3% or more of its (living) immigrants to the US arrived before the year 2000. For example, fully 89.5% of live immigrants from Greece, and 74.9% of live immigrants from Cambodia arrived in the US before the year 2000. (Interestingly but not surprisingly, the UK is not in this longest-established quartile in large part because immigration from the UK ramped up heavily in recent years.)

Here’s what the graph looks like for groups of living immigrants with the longest tenure in the US:

immigrants2Figure 2

The correlation between how well the native country does, and how well its immigrants do in the US rises to 0.84 when only the top quartile of most established immigrant groups is used. From this, it would appear that skillsets and cultures not only survive the move to the US, but in general, they may barely change among first generation immigrants. And since parents’ income is often a strong predictor (if not determinant) of a child’s income, it would seem that the effect can continue for generations. What my old econometrics professor used to call casual empiricism also appears to bear this out, at least for those who aren’t shocked by the results.

I would also note one extremely important implication – different groups can have wildly different outcomes without it being the result of racism, discrimination, or randomness.

I will have a few more posts using this data set, as it may provide some insights into the questions I am ultimately interested in answering, namely:

1. What are the factors that contribute to success or failure in a given group?
2. Can we weight the scale toward success, and if so, how?
3. What are the implications of situations in which traits that bias toward failure are resistant to change?
4. With each of the above, how do we avoid trampling on the rights of individuals?

In closing – as always, if you want my data, drop me a line at my first name (mike) dot my last name (kimel – that’s with one m, not two) at gmail dot com. Occasionally I get data requests six or seven years after a post. While I always try to comply with these requests, I reserve the right to change computers, have them stolen, or to drop dead if too much time has elapsed between this writing and a request for data occurs.

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