Hello. You may be interested in how the distribution of income before tax (not wealth) has evolved across time. The 1 % of people with the highest income had around 20 % of the total income before tax both now, and 200 years ago.
The data in this area is pretty shaky. On the graph you have shared specifically:
Although the graph goes back to 1820, there is actually very limited data before WWI, as most countries didnât have income taxes back then (which is the main source of data). In fact, when you click on the individual countries, most of them do not go back before 1900. The US starts in 1913, China starts in 1979, India in 1923, Indonesia in 1984 and Nigeria in 1985. Japanâs series doesnât start until 2008!! Clicking through the countries, it looks like countries with considerably less than half of the current worldâs population had any data before 1900, and I am not sure what extrapolations they had to make to get the âWorldâ figures they use for teh graph.
I would also be very sceptical of income data for developing countries, which tend to have large âinformal economiesâ.
China is an interesting case. There is no doubt that China has experienced enormous economic growth since its economy opened up in the late 1970s. But the graph for China shows the income share of the top 10% growing from 28% of Chinaâs income to 41.7%! Caveats about data reliability still apply, but that is quite a shocking increase in inequality.
More generallyâthere is some evidence that median wages have started to decouple from general productivity growth, with the labour share of income declining over the past ~20-30 years. Economists argue about the data, the causes of this, and whether it is a temporary or lasting change. But some think it is because âsuperstarâ firms with low labour shares have taken a greater market share thanks to globalisation and digitsation. See e.g. Autor et al (2020), and this 2018 OECD working paper.
In any case, I donât think we are going to resolve this disagreement by exchanging data because: (1) data is limited; (2) there are so many different ways to interpret the data and experts genuinely disagree on this; and (3) we can also argue over the extent to which the past predicts the future. I think there is only so much we can learn from the past as I am concerned AI can be different in important waysâi.e. I think it is very plausible that the distributional impacts of automating cognitive labour will be quite different to the impacts of automating physical labour or routine, administrative tasks, but I wonât be able to prove this with data.
The main reason I replied wasnât to get into an argument over data as that can go on for days with no resolution. Rather, I replied because I saw this post already had a fair number of âdisagree-votesâ and only one comment explaining why, so I thought I should at least explain my alternative view.
Thanks for the good points. Here is the same graph for the United States (US). The income before tax of the 1 % of people with the most income was supposedly 20.4 % in 1913, and 20.7 % in 2024. I am sharing data for the US because it covers a long period (111 years), and âhas been the worldâs largest economy since about 1900â until 2015.
Re: betsâI am highly uncertain about AI timelines myself. Amongst the EA/âAI community, I think my timelines would be considered âlongââI expect major advancements in robotics will be needed for AI to displace more than about 20% of the current jobs in developed countries, and I donât expect that could happen within the next 10 years.
Hello. You may be interested in how the distribution of income before tax (not wealth) has evolved across time. The 1 % of people with the highest income had around 20 % of the total income before tax both now, and 200 years ago.
The data in this area is pretty shaky. On the graph you have shared specifically:
Although the graph goes back to 1820, there is actually very limited data before WWI, as most countries didnât have income taxes back then (which is the main source of data). In fact, when you click on the individual countries, most of them do not go back before 1900. The US starts in 1913, China starts in 1979, India in 1923, Indonesia in 1984 and Nigeria in 1985. Japanâs series doesnât start until 2008!! Clicking through the countries, it looks like countries with considerably less than half of the current worldâs population had any data before 1900, and I am not sure what extrapolations they had to make to get the âWorldâ figures they use for teh graph.
I would also be very sceptical of income data for developing countries, which tend to have large âinformal economiesâ.
China is an interesting case. There is no doubt that China has experienced enormous economic growth since its economy opened up in the late 1970s. But the graph for China shows the income share of the top 10% growing from 28% of Chinaâs income to 41.7%! Caveats about data reliability still apply, but that is quite a shocking increase in inequality.
More generallyâthere is some evidence that median wages have started to decouple from general productivity growth, with the labour share of income declining over the past ~20-30 years. Economists argue about the data, the causes of this, and whether it is a temporary or lasting change. But some think it is because âsuperstarâ firms with low labour shares have taken a greater market share thanks to globalisation and digitsation. See e.g. Autor et al (2020), and this 2018 OECD working paper.
In any case, I donât think we are going to resolve this disagreement by exchanging data because: (1) data is limited; (2) there are so many different ways to interpret the data and experts genuinely disagree on this; and (3) we can also argue over the extent to which the past predicts the future. I think there is only so much we can learn from the past as I am concerned AI can be different in important waysâi.e. I think it is very plausible that the distributional impacts of automating cognitive labour will be quite different to the impacts of automating physical labour or routine, administrative tasks, but I wonât be able to prove this with data.
The main reason I replied wasnât to get into an argument over data as that can go on for days with no resolution. Rather, I replied because I saw this post already had a fair number of âdisagree-votesâ and only one comment explaining why, so I thought I should at least explain my alternative view.
Thanks for the good points. Here is the same graph for the United States (US). The income before tax of the 1 % of people with the most income was supposedly 20.4 % in 1913, and 20.7 % in 2024. I am sharing data for the US because it covers a long period (111 years), and âhas been the worldâs largest economy since about 1900â until 2015.
I remain open to bets against short timelines for transformative AI (TAI), or what they supposedly imply, up to 10 k$. Do you see any that we could make?
Re: betsâI am highly uncertain about AI timelines myself. Amongst the EA/âAI community, I think my timelines would be considered âlongââI expect major advancements in robotics will be needed for AI to displace more than about 20% of the current jobs in developed countries, and I donât expect that could happen within the next 10 years.