The World’s Income Distribution, By Country

GDP per capita, using PPP:

Via bookofjoe (not his usual thing either).

Why Is Eastern Europe Poorer?

Eastern Europe is generally poorer than Western Europe. This is a problem in an age of common migration because the educated and talented are migrating from Eastern to Western Europe. There’s a brain drain.

New research shows that this goes back about 1,000 years.

When you go back that far, you need to use to use a proxy for human capital. Keywood and Baten use “elite numeracy”. What they record is the frequency with which different countries were capable of recording the date of the birth of the child who later become the ruler. This is an indicator of understanding that some numbers will become important later on and needs to be recorded now.

What they found was that before 1000 A.D., elite numeracy was about the same across Europe (and probably not very good). But after that, and until about 1800 A.D., Western Europe took a large and sustained lead in elite numeracy. They then show that this divergence was related to military threats. In short, leaders in Eastern Europe were scared, and put their money into defense of, rather than education of, their elites.

The macroeconomic patterns we see in the world today may be very old indeed.

Inequality

We have some techniques for measuring the degree of inequality. For example, use of the Gini coefficient is becoming quite widespread. This is useful for thinking about whether the distribution of something is more unequal or less unequal than some other distribution. It isn’t perfect, but it’s a start.

Unfortunately, our mental heuristics† for assessing inequality have not caught up. On the face of it, equality corresponds to a single value of the Gini coefficient, zero, while inequality applies to all other values greater than zero and less than or equal to one (the coefficient is defined over 0 to 1). The thing is, these are point estimates. So, the probability of any distribution’s Gini coefficient hitting any value exactly is … zero. In some sense, we’re never likely to find equality (which is a fairly useful property if you like to complain about the pervasiveness of inequality).

In economic situations the typical heuristic is that the world we observe is too unequal because there are monetary/political/legal/social/cultural forces that have pushed us away from equality, and are capable of sustaining distance between how unequal things are and how equal we’d like them to be.

Now, let me modify that third paragraph with the implication of the second paragraph to get:

In economic situations a more realistic heuristic is that the world we observe is too unequal because there are monetary/political/social/cultural forces that have pushed us away from some more natural level of inequality, and are capable of sustaining distance between how unequal things are and how unequal we can reasonable expect them to be. [I’ve emphasized the modifications between the two paragraphs].

My point in this is that we can still be concerned about inequality while we go and explore the world for how much inequality is actually OK. That’s a premise that lots of people haven’t really considered, but it’s essential for things like, say music, where the inequality of tastes is what makes it worthwhile.

So, where to start? How about with “A Comparison of Wealth Inequality In Humans and Non-Humans”. The paper is behind a paywall, but this is excerpted from the abstract:

In many societies, the statistical distribution of wealth takes a characteristic form: unimodal, skewed to the right, and fat-tailed. …  we present the first description of inequality in material resources in an animal population … the shell distribution for the [hermit] crabs strongly resembles the characteristic form of wealth distribution in human groups. The amount of inequality in the crabs is more than that in some small-scale human groups but less than that in nations. We argue that the shell distribution in the crabs is not simply generated by biological factors such as survival and growth of either crabs or gastropods. Instead, the strong resemblance in the human and hermit crab distributions suggests that comparable factors, not dependent upon culture or social institutions, could shape the patterns of inequality in both groups. …  We also propose that inequality in hermit crabs could provide a baseline for examining human inequality.

For those of you that don’t know, hermit crab exoskeletons are not very serious defensive shells, so they move into harder shells of other creatures that have died. The crabs ability to grow is based on finding a shell that is big enough for them to grow into, but small enough for them to still maneuver. Since mollusks do not stop growing as they age, a hermit crab may go through several shells in its lifetime. Basically, their success as individuals is based on finding natural resources and using them in a rivalrous and excludable manner. And they result is inequality.

Sounds a lot like humans … except that there aren’t monetary/political/legal/social/cultural forces making it happen. This suggests that equality is not the null hypothesis we should be using for assessing human affairs.‡

† Heuristic is a good college level word that you should look up.

‡ Kurt Vonnegut’s short story “Harrison Bergeron” is a satirical look at what might happen if we did.

New Macro Dataset

This morning the BEA released the first county-level GDP data for the U.S. Here’s the news release, and here’s where to find all the numbers.

Annual data is provided for four years, 2015-18.

The GMP (Gross Metropolitan Product) data series will be discontinued. Now you can slice and dice that at the county level if you don’t like the official definitions of metro areas. I do wish the data, as released, had filters for the metro areas.

What trivia did I spot?

• There appear to be 3,112 county entries. This does not match up with the number of counties in the U.S. Still trying to figure out what’s missing.
• There are some entries for independent cities and combination entities (independent cities and their surrounding counties) from Virginia. This makes the undercount above more severe. Again, not a biggie, but I have to figure it out.
• My own small county in rural, southwestern Utah, has a GCP of $1,500M (larger than about 2 dozen countries).
• The smallest county is Issaquena in Mississippi with a GCP of just over $18M.
• The largest is Los Angeles (County) at $711,000M. Its’ just a tad smaller than Pennsylvania, and larger than 44 states.
• New York County, basically Manhattan, has a GCP of $600,000M. I was surprised at how large that is relative to the other boroughs of New York: Kings County (Brooklyn) and Queens are about $85,000M. The Bronx and Staten Island are far smaller. Nassau and Suffolk in the suburbs is about the same size.
• Salt Lake County, where I once lived, which is about half the metropolitan area comes in at $81,000M
• Orleans Parish, where I once lived, it down to $23,000M. It’s not even the largest parish in the state anymore. Even with the surrounding parishes added in, New Orleans is now far smaller than Utah’s Wastach Front.
• Erie County, New York, where I grew up, comes in at $51,600M.
• I also lived for two years in Tuscaloosa County, Alabama. It’s at $8,600M

Infographic: The World’s Money and Markets

This is good but not great. (All my comments are up here because the image is so large, here is the original in its own web page with comments). I have 3 big complaints. There’s also a fourth group of stuff to love because we don’t often see it elsewhere.

• There’s some crossover between different categories, so some things are double-counted. Some examples are:
• Several of the “Biggest Companies” biggest shareholders are listed in the “50 Richest People”.
• The “Fed’s Balance Sheet” includes the USA sub-category under “Currency”. And BTW: which side of the Fed’s balance sheet is shown there, or is it both (or do the visualizers not have that straight in their own heads?)
• There’s some mixing of stocks and flows. For example:
• The category “50 Richest People” (in the world) is followed by “California’s GDP”. But the former is a stock and the latter is a flow. A way to think about this is that they are related by a rate of return. Assume that’s 10%/year to make things simple. Thus, the flow of income coming of the wealth of the 50 richest people is about 2 blocks. When compared to the flow of California’s GDP of 26 blocks (yes, there’s a mistake in the chart there) it doesn’t look so big. Even better, California’s flow of GDP is generated by a stock of wealth that’s 10 times as big, so an appropriate comparison is the 19 blocks for the “50 Richest People” to the 260 blocks of wealth in California.
• But that comparison is insightful because the size of the sub-category “United States” under “Stock Markets” is only 73 blocks. Figure about 10 of those are in California. So somehow, California has 260 blocks of wealth of which just 10 are the market’s net worth of corporations. This tells us that most of what is productive in our world is not in corporations, which begs the question of why on earth so many politicians are so concerned with limiting them.
• They need to be careful about what are assets, what the liabilities are, and what net worth (the difference between the two) is. For example:
• They only have some portions of assets listed (e.g., “Gold”, “Currency”) but then they show a much more inclusive and comprehensive “Global Debt” category. This makes debt look too large.
• They also show capitalization of “Stock Markets” which is a net figure. What are the assets and liabilities associated with that?
• The same thing goes for derivatives. They talk about the zero-sum nature of most of those, but they don’t actually show it.
• This is a good example of the “balanced reporting” and “what passes for expertise” problems from my Why Is Macro So Hard lectures. In the sidebar about derivatives, they quote Dr. Richard Sandor (why does he get a title if it isn’t important to the position he takes?), Warren Buffet, and Jeff Greene. So what you have there is a guy who markets derivatives, a guy who’s rich mostly from non-derivatives, and a guy who got rich from derivatives. Any expertise there on the history of derivatives, why we have them, or why they’re useful??
• Most people who are buggy about money being backed by something think it has to be gold (in Fort Knox!!). The sub-category “Central Banks & IMF” shows how small that component actually is.

Courtesy of: Visual Capitalist, via Newmark’s Door.