Labor productivity: Adjusting national incomes for taxes, hours worked, and labor participation rate
Today I'm going to take a look at some less conventional measures of economic power that have special importance for a robot-fueled, automatized future economy.
One of the most common tools to measure the strength of an economy is per capita income, and although the United States is the richest country in the world in terms of GDP, there are a few other countries that eclipse it in terms of PPP income per capita. However, most or all of these are tiny countries like Luxembourg and/or large oil exporters like UAE or Norway, which makes them less useful as models for other economies to follow. Another complication in measuring per capita income is the difference between before and after tax income. Most developed countries have higher tax rates than the United States, so when looking at gross income, countries like Germany and the Netherlands are very close to the US, and Norway is actually a ways above it. The income per capita picture changes in favor of the US when you deduct taxes:
From this perspective, we see the superiority of the United States take a hit, as it comes in second, just behind Germany and just ahead of Norway for after-tax income per hours worked per worker. Now you may be thinking this is still a pretty good showing for the United States, and that is a fair point. But keep in mind that this is after-tax income. People in the US still have to pay for their own medical care, and often have to pay more for education as well. We also see the effects of parental leave in the long hours that Americans work. In the US, the overall "mean standard of living" as measured by gini-adjusted HDI has been surpassed by several of the other countries on these charts. However, less work is not always better. Studies show that better educated people tend to work more and live healthier lives.
For labor force participation, unlike hours worked, lower numbers often mean that there are large groups of people who are living on very low incomes. For my final chart, I further adjusted the income data, this time for the labor force participation rate, and compared the after tax income with and without this adjustment. This time I used the average participation rate of the 14 countries as a baseline for adjustment.
In this chart, the red bars are higher than the blue for countries that have lower labor force participation rates, representing greater efficiency. Here we see relatively minor changes among most countries, with notable gains seen in Italy, France, and Greece - interestingly all countries that have been heavily hit by recent financial crises. Perhaps this is the result of industrial capacity that goes unused in those places. I also noticed that high labor productivity seems to be a reflection of past economic greatness as much as recent growth. Countries that have experienced huge economic gains in the past half century, such as the Nordic countries, have barely caught up with the old european powers in this measure of economic efficiency, despite having slightly higher standards of living.
I imagine that this type of metric is a rough proxy for the level of automation of economies. It strikes me that the future is nearly certain on a few points: economies will continue to grow, we will see fewer hours worked per worker, and automation will increase. In these charts, the economies with the highest standards of living seem to be efficient in the sense of high income per hours worked, but not quite as efficient in the sense that they to do also tend to have high labor force participation. Therefore policies that increase labor force participation, but decrease hours worked per person should be congruent with the development of robotic economies.
The OECD uses a similar metric of "GDP per hour worked": http://stats.oecd.org/Index.aspx?DatasetCode=LEVEL. There seem to be discrepencies between my numbers and theirs, such as Italy being more efficient than the UK in my data, but less efficient in theirs. I thought that maybe this was due to my data being post-tax and theirs being total GDP, and according to this list on wikipedia, Italy pays more in taxes than the UK. However, according to the OECD, where I got my raw data from, Italian household income takes less of a hit from taxes than UK income. This may be due to Italy's tax burden being shouldered more by corporations?
Sources: http://data.worldbank.org/indicator/SL.TLF.CACT.ZS
https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(PPP)_per_capita
https://data.oecd.org/hha/household-disposable-income.htm
All data is for 2014.
One of the most common tools to measure the strength of an economy is per capita income, and although the United States is the richest country in the world in terms of GDP, there are a few other countries that eclipse it in terms of PPP income per capita. However, most or all of these are tiny countries like Luxembourg and/or large oil exporters like UAE or Norway, which makes them less useful as models for other economies to follow. Another complication in measuring per capita income is the difference between before and after tax income. Most developed countries have higher tax rates than the United States, so when looking at gross income, countries like Germany and the Netherlands are very close to the US, and Norway is actually a ways above it. The income per capita picture changes in favor of the US when you deduct taxes:
I quickly threw this particular chart together from two different data sources, the IMF and OECD, and the green and red colors measure two different things, per capita gdp and after tax income, respectively. There are better, similar charts available elsewhere, but if you can see past the sloppiness, take note that some countries take a bigger hit from taxes than others, with the United States taking a commanding lead above the rest after taxes. Norway on the other hand takes a big hit. These differences are a result of the U.S. having lower tax rates than most developed countries. What the chart shows is that people in the US generally have more money to spend, but sometimes have to spend their income on things that the government takes care of in other countries. The next chart is after tax GDP adjusted for hours worked, with Germany, the OECD country with the least hours worked per worker per year, as the baseline. I am not trying to predict the GDP given x number of hours worked, rather, the idea behind this chart is to give a visual representation of the relative efficiency of the labor forces of each country.
From this perspective, we see the superiority of the United States take a hit, as it comes in second, just behind Germany and just ahead of Norway for after-tax income per hours worked per worker. Now you may be thinking this is still a pretty good showing for the United States, and that is a fair point. But keep in mind that this is after-tax income. People in the US still have to pay for their own medical care, and often have to pay more for education as well. We also see the effects of parental leave in the long hours that Americans work. In the US, the overall "mean standard of living" as measured by gini-adjusted HDI has been surpassed by several of the other countries on these charts. However, less work is not always better. Studies show that better educated people tend to work more and live healthier lives.
For labor force participation, unlike hours worked, lower numbers often mean that there are large groups of people who are living on very low incomes. For my final chart, I further adjusted the income data, this time for the labor force participation rate, and compared the after tax income with and without this adjustment. This time I used the average participation rate of the 14 countries as a baseline for adjustment.
In this chart, the red bars are higher than the blue for countries that have lower labor force participation rates, representing greater efficiency. Here we see relatively minor changes among most countries, with notable gains seen in Italy, France, and Greece - interestingly all countries that have been heavily hit by recent financial crises. Perhaps this is the result of industrial capacity that goes unused in those places. I also noticed that high labor productivity seems to be a reflection of past economic greatness as much as recent growth. Countries that have experienced huge economic gains in the past half century, such as the Nordic countries, have barely caught up with the old european powers in this measure of economic efficiency, despite having slightly higher standards of living.
I imagine that this type of metric is a rough proxy for the level of automation of economies. It strikes me that the future is nearly certain on a few points: economies will continue to grow, we will see fewer hours worked per worker, and automation will increase. In these charts, the economies with the highest standards of living seem to be efficient in the sense of high income per hours worked, but not quite as efficient in the sense that they to do also tend to have high labor force participation. Therefore policies that increase labor force participation, but decrease hours worked per person should be congruent with the development of robotic economies.
The OECD uses a similar metric of "GDP per hour worked": http://stats.oecd.org/Index.aspx?DatasetCode=LEVEL. There seem to be discrepencies between my numbers and theirs, such as Italy being more efficient than the UK in my data, but less efficient in theirs. I thought that maybe this was due to my data being post-tax and theirs being total GDP, and according to this list on wikipedia, Italy pays more in taxes than the UK. However, according to the OECD, where I got my raw data from, Italian household income takes less of a hit from taxes than UK income. This may be due to Italy's tax burden being shouldered more by corporations?
Sources: http://data.worldbank.org/indicator/SL.TLF.CACT.ZS
https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(PPP)_per_capita
https://data.oecd.org/hha/household-disposable-income.htm
All data is for 2014.
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