Does immigration explain most of the inequality in the OECD states?

Economics Economics Questions
1

Hi all. This is my first post in the Mises community.

I am fishing for resources and leads (and thoughts) for my Masters dissertation at the LSE.

I will be exploring a theory I have about how immigration might be the main factor in explaining differing levels of inequality in the OECD states.

As it turns out immigrants tend to mostly enter the workforce from the bottom (unskilled labor) and the top (specialists, investors, billionaires) and would therefore tend to pull at the income distribution curve at both ends.

I produced a scatter chart of the OECD states comparing Gini-scores and migration levels and found a somewhat obvious correlation. There are a few outliers, but those appear to be countries that have a different composition of immigrants than the other OECD states.

To my surprise it seems that the immigration variable has not been properly studied before and it is proving to be quite a challenge to find material to support or refute my theory.

Thus far one of the best hints I’ve gotten ponted me towards german journalist Olaf Gerseman who wrote about the subject in a book of his and apparently proved that if you factor in immigration it turns out that inequality becomes the same among developed nations.

If it turns out my theory is correct I’m hoping that would be important news for libertarians, as it would serve to prove that the “problem” with inequality has nothing (or very little) to do with e.g. whether a country has a strong or weak welfare system.

Also, it appears that over time immigrants tend to slowly move closer to locals in wages and education, so the individuals move up the inome ladder, effectively lifting themselves up from the bottom of the inequality curve. I’ve found data from the US that shows that by the second generation immigrants have become completely normalized with regards to education. So looking at the progression of the individual inequality starts to not seem like such a big problem.

Here’s a link to an image of the scatter chart showing how inequality tends to rise as the inflow of migrants rises. http://imgur.com/0h8iX1A

I would really appreciate any comments, suggestions or reccomended readings.

2

Your research looks cool.

I don’t think I can see clearly the positive correlation just looking at the data, do you have a plot showing the correlation?

And how’s that possible to have negative number of migrants per 1000 pop? There’s a data point below zero.

edit: I see you are considering net migration rates, immigrants to X country less emigrants from X country, and then dividing by mid year population…

Looking at the net migration rates here http://upload.wikimedia.org/wikipedia/commons/2/2e/Net_migration_rate_world.PNG I could not identify an OECD country with negative rates, but maybe your data is not for the same period.

edit: Latvia is a member of OECD, I didn’t know that.

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That scatter chart is just something I drew up rather quickly using statistics from Wikipedia (Not very academic, I know, but it will do for now). It will get more accurate as my research progresses. For the time being, only consider it a rough guide.

Here’s a Wikipedia article with a list of countries by migration rate http://en.wikipedia.org/wiki/List_of_countries_by_net_migration_rate

The OECD countries certainly don’t all align on a straight line, but it still does appear that as countries move up in migration rate they also tend to move up in inequality. I’ve made this additional drawing showing this tendency, and also how the majority of OECD countries form a cluster in an area of low migration and low inequality. http://imgur.com/Zlmsv0x

The reason why the effects of increased migration are not the same for all countries is probably a difference in composition of the migrants.

For instance, Luxembourg is an obvious outlier, with a very high migration rate but a fairly low Gini score. A closer look at the composition of the income of migrants into Luxembourg also seems to reveal that they seem to be similar in composition to the locals with regards to wages.

Meanwhile a country like Portugal might experience a more drastic effect from immigrants (despite having a fairly modest migration rate at 3 per 1000) since it might tend to attract migrants at the furthest extremes of the income scale: very low wage manual laborers from Africa and Latin America on one hand, and specialists and wealthy riterees on the other.

Of course there are also other factors at work, but I’m guesstimating that the migration rate might explain about half the variance in gini scores among OECD states.

The country with a negative migrant outflow is Poland, where there are more people moving out than in.

It is also worth noting that the higher the migration rate, the higher the cumulatie effect over time as there’s exponential growth involved. If two countries start of with a [stagnant] base population of 100.000 and one has an annual migration rate of 1:1000 and the other 5:1000, by year 20 the first country will have 2.000 immigrants or 2% of the population while the latter country will have around 10.500 immigrants or about 10,5% of the population, making the wage-inequality effect that much stronger.

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But your plot does not look well-centered.

You should try to put the origin of the axis at the average gini coef and the average migration rate for your set, to see how countries are deviating from these averages according to their particular figures.

If they’re concentrated in the first and third quadrants, there you have a positive correlation.

I’m ballparking by looking at the graph that your average migration is around 2.5 and your average gini is around 3, and putting the origin of axis there I guess you can see some positive correlation.

Anyways, I was never really good with scatter plots.

5

Thanks for the input. Truth be told numbers aren’t my strongest side, but I’ll fiddle around with the figures and see what comes out.

If anyone might recall any relevant studies or figures, that would also be very much appreciated.

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Hmm, I’m no statistician, but I don’t see a correlation on that graph either.

You’d also have to compare it with a graph measuring the correlation between inequality and welfare spending. The closest I could find with a quick search is this graph relating inequality to tax revenue as a percentage of GDP. It seems like a better correlation than what you got. However, the Gini scores seem to be a bit different than what you have.

7

It does indeed seem that Gini scores fluctuate quite a bit. I re-did my scatter chart with the latest available data on Wikipedia and got a slightly different picture.

Here’s a new scatter chart with a regresson line. In this chart I have excluded a few outliers, namely Luxembourg (outlier), Chile (outlier), Turkey + Mexico (low GDP), and Estonia + Poland (negative migration rates). http://imgur.com/Evzm8wq

It seems to be a somewhat strong correlation and I’m fairly confident that when I account for the different compositions of immigrants the slope of the regresson line will start to get steeper.

Of course I will eventually have to do some broader statistical analysis, adjusting e.g. for factors such as levels of taxation. I will also have to look at long-term averages of Gini and Migration to have numbers that better describe the “normal” condition of countries.

8

I should also add that the R squared is a mere 0,1038. However, as I account for other variables -composition of immigrants in particular- I expect to see a stronger correlation.