Once, Cubans were (maybe) richer than Americans

In light of what we see today, this is hard to believe. However, as a result of Castro’s death, I accidentally became interested in the history of this fascinating island and the more I discover, the more shocked I am at “the path” that Cuba has taken. One of these reasons is provided below by Victor Bulmer Thomas in his Economic History of Latin America since Independence. Now, Thomas uses a different approach than the commonly used Maddison data (he believes the assumptions are too heroic). He uses indicators correlated with GDP per capita to fill in the gaps and he finds that Cuba was generally richer than the United States for most of the 19th century (see below):

cubaus

Now, I am not convinced by the figure Thomas presents. However, I am also skeptical of the levels presented by Maddison (where Cuba is roughly 60% as rich as the US in 1820). In between are some more reasonable estimate (see this great discussion in this book as well as this discussion by Coatsworth).  Moreover, there is the  issue of slavery which distorts the value of using GDP per capita because of high levels of inequality (however, it distorts both ways since the US was also a slave economy up to the Civil War).

Nonetheless, this tells you about the “path not taken” by Cuba.

Household size and growth since 1870 (albeit in Canada)

Two days ago, I posted something on how much we were estimating growth since the 1950s. While organizing another research paper that I am trying to finish, I realized that I could make a follow-up to this based on previous research of mine.

A few months ago, I published (alongside Vadim Kufenko and Klaus Prettner) a short note in Economics Bulletin where we showed that the large differences in household size in Canada that existed up to 1975 led many to overestimate the level of differences between provinces. Moreover, we pointed out that because household size were converging at the same time as incomes, we argued that the rate of convergence from 1945 onwards was slightly overestimated. That paper convinced us to do the same between all the OECD countries (we are assembling the data right now).  But this was an argument about variance, what if we simply plot the “per capita” income of Canada with the “per adult equivalent” income of Canada since 1870.

By using the Maddison dataset combined with the data from my article, it took me a few seconds to get the graph below. What is important to notice in this graph is that, incomes per adult equivalent (measured in 1990 Geary-Kheamis dollars) have increased 40% less than incomes per person. Since adult equivalents are a better measure of living standards (because you capture the economies of scale associated with household size), we can easily say that we have been underestimating the level of improvement in Canada (it is still substantial however).

growthfactors

On 7 million deaths from air pollution

ATTN published a video of An-huld (the really cool guy who made my childhood by being in all my favorite action movies like Predator* and who ended up being the governor of California). In that short clip, Schwarznegger starts by saying that 7 million individuals die from pollution-related illnesses.

That number is correct. But it is misleading.

People see pollution as “all and the same”. But some forms of pollution increase with development (sulfur emissions and some would argue that too much CO2 emissions is pollution as it causes climate change). However, others drop dramatically – especially heavy particules (Pm10) which are a great cause of smog. Julian Simon (the late cornucopian economist who is one my greatest intellectual influence) pointed out this issue and noted that the deadliest forms of pollution are those that relate to underdevelopment.

Back in 2003, Jack Hollander published the Real Environmental Crisis: Why Poverty, Not Affluence is the Environment’s Number One Enemy. Hollander pointed out that simply from the combustion of organic matter (read: firewood and animal manure – literally burning fecal matter) indoors for the purposes of heating, cooking and lighting was responsible for close to 2 millions deaths.

Since then, the WHO came out with a study pointing out that around 3 billion people cook and heat their homes with open fires and stoves that rely on biomass or anthracite-coal. They put the number of premature deaths directly resulting from this at over 4 million people. This is close to 60% of the figure cited by the former President of California (yes, I know he was governor – see here). In other words, 60% of the people who die prematurely as a result of strokes, ischaemic heart diseases, chronic obstructive pulmonary diseases and lung cancers can be attributed to indoor air pollution. That means pollution resulting from the fact that you are so poor that you have to burn anything at hand at the cost of your health.

True, richer countries pollute and there are policy solutions (I have often argued that governments are better at polluting than at reducing pollution, but that is another debate) that should be adopted. But, these forms of pollution do not harm human life as much as those that come with poverty.

* By the way, when you watch Predator, do you realize that there are two future American governors in that movie? I mean, imagine that when Predator came out, some dude from the future told you that two of the main actors would end governing American states. Pretty freaky!

“Watch” the (industrial) revolution!

I don’t know how I missed such a valuable article, but O’Grada and Kelly have this fascinating piece on the price of watches in England from the early 18th century to the early 19th century in the Quarterly Journal of EconomicsStarting from Adam Smith’s quote that the price of watches had fallen 95% over roughly one hundred years, they collected prices of stolen watches reported in court records.  They find that Smith was wrong. The drop was only 75% (see the sarcasm here).

watch-prices

Why is this interesting? Because it shows something crucial about the industrial revolution. This was a complex good to build which required incredible technical advances – many of which could be considered general purpose technologies which could then be used by other industries for their own advances (on the assumption that other entrepreneurs noticed these technologies). But, more importantly, it provides further evidence against the pessimistic view of living standards in Britain at the beginning of the Industrial Revolution. These “new” goods became incredibly cheaper. Along with nails, glass, pottery and shipping , watches did not weigh heavily in the cost of living of the British. However, they did weigh heavily as industrial prices which meant that costs of production were falling progressively which augured well for the beginning of the industrial revolution*.

Literally, you can watch the industrial revolution in that paper! (sorry, bad pun)

* By the way, I use the term because it is conventional but a revolution is a clean break. The British industrial revolution was not saltation as much as it was a steady process of innovation from the early 18th century up to the mid 19th century. The real “revolution” in my eyes is that of the late 19th century. The technological changes from 1870 to 1890 are the most momentous in history and if there was any technological revolution in the past, this was it.

Did the Thirty Glorious Years Actually Exist?

Okay, I am going for a flashy title here. I should have asked whether the Thirty Glorious were as glorious as they are meant to be. This is a question that matters in debates about both inequality and the often-bemoaned growth slowdown.

In the past (say before 1950), labor force participation was quite low (relative to today) by virtue of large family sizes and most married women not working. However, when they were at-home, these married women produced something. That something was simply not included in our national accounts. When they entered the labor force, they produced less of that something. However, since it had never been measured, we never subtracted that something from the actual output generated from their increased participation.

Even before the 1950s, this mattered considerably as growth tended to be heavily underestimated (by 0.3 percentage points from 1870 to 1890, overestimated by 0.38 points from 1890 to 1910 and by 0.06 percentage points from 1910 to 1930).This was at a time when variations between the household economy and the market economy were small. Imagine the importance of overestimates since the 1950s! In a short comment reply to Emily Skarbek last year, I pointed out that adjusting for the size of the household economy meant that 1/7th of Canada’s economic growth from 1960 to 1997 (see image below and this was before one additional surge of labor participation resulting from daycare and unemployment policy reforms).

SEcularStagnation2

Recently, I found an old book in my library. It is Kenneth Boulding’s Structure of a Modern EconomyIn it, he makes this exact same argument. Basically, actual output today is overestimated relative to output in the past. And there are many, many, many other articles on this. In all cases, the rate of growth is heavily reduced. In a way, that means that the Thirty Glorious are less glorious (which makes the growth stagnation argument seem more defensible).

And you know what? This is consistent with attempts to correct inequality measures. Most of the attempts made to correct inequality for age, number of workers per household, the size of household and prices, they generally increase very modestly the income growth of the bottom centiles and decrease appreciably the actual level of growth of incomes at the top. While these corrections reduce the level of inequality (and the growth thereof), they also reduce the growth rate of incomes.

Is it possible that the correction to make inequality measures more comparable over time are allow us to see the point about overestimating growth since the 1950s? It means that the Thirty Glorious aren’t that glorious (at the very least, they’re overestimated). It also means that someone who could follow some of the proposed corrections to national income accounts (generally, the best source for this is the Review of Income and Wealth) for every year since 1929 (starting date of the US national accounts which could be extended by using Kuznets’s national income measures from 1913 to 1929) could propose the “actual output” of the country and see how glorious the 1945-1975 period was. That is the work of economic historians to do!

On immigration, trade, and inequality: why nobody should care (that much)

Recently, I read snippets from George Borjas’s book, We Wanted Workers (I got distracted and reverted to reading Leah Platt Boustan’s Competition in the Promised Land).On its heels came this article by Dani Rodrik in Foreign Policy. Both work make the same case, that free movement of goods and people may imply some negative effects on inequality. Borjas argues that immigration increases inequality while Rodrik argues that low-skilled workers are displaced.

Both arguments are not convincing.

First of all, immigration will always increase inequality in one area. This is by definition. Unless the migrants follow the same distributional pattern as the host population, inequality will increase. If somebody from Cuba enters the United States at the tenth percentile, he increases inequality by swelling the ranks of low earners. If somebody from China enters the United States at the 90th percentile, he increases inequality by swelling the ranks of the high earners. However, from a global perspective (world population), inequality has actually dropped since the migrant has a greater income than in the past. After all, bringing a Haitian to the US may increase US inequality measures but the ten-fold increase in his income (this number comes from my colleague Ben Powell) means that worldwide inequality drops.

To be honest, I know that Borjas is probably aware of this point, but many of those who spin his work don’t get it. Borjas’s argument is little more sophisticated. His claim is that low-skilled workers (high school dropouts) see their wages go down while everybody else (high school graduates and university graduates) gains from immigration. This increases inequality because they are left behind economically. But this is where his argument is alike that of Rodrik and where it misses the target dramatically.

While I could be lazy and simply say that many other scholars place Borjas at the extreme of the spectrum of academics with regards to the effects of immigration on labor markets. Indeed, there are more scholars who find that low-skilled workers also gain from immigration all things being equal. But, I won’t be lazy. Let me assume, for the sake of argument, that the empirical result is valid. If unskilled workers are displaced, why can’t they find new employment elsewhere. If the effects of immigration are so positive for everybody else, it means that everybody else is substantially richer and they can demand more goods. Are there barriers preventing the unskilled from acquiring jobs? The answer is emphatically yes.

The ability to find a new form of employment following changes in the labor market depends on the frictions that exist on the labor market. Some of them are natural. We have to assume search costs (time, energy, some money) to look for a job and get the training for that job. But there are also barriers that create unnecessary frictions. The rise of occupational licencing is one of those (growing) frictions (see here, here and here). We could also point out that product regulations tend to affect the prices of goods that weigh more heavily in the consumption baskets of lower-income workers (here and here) thus pulling the poorest down. We could also point to the fact that states with right to work laws seem to have enjoyed more limited increases in inequality than the states without such laws (here). We could also underline the fact that housing regulations are making it harder for unskilled workers to move to dynamic areas, thus locking them in low-productivity areas (here). And the list could go on for a few more pages, but I think the point is made: there are tons of factors that make displacement a problem. However, those who worry about it when it comes from changes resulting from trade or immigration are concerned with a minor (and positive in the long-run) variable. In a way, Borjas and Rodrik are (rightfully) concerned about the poorest but they fail to identify the problem like if a doctor was concerned with his patient’s loss of sight rather than concentrating on the brain tumor that caused the loss.

Free trade and open borders generate massive benefits. But there are short-term costs as production methods and resources are being reallocated. Many government policies amplify exponentially these costs and delay reallocation. This creates the inequality they bemoan.

Did 89% of American Millionaires Disappear During the Great Depression?

Over the years, I became increasingly skeptical of using tax data to measure inequality. I do not believe that there is no value in computing inequality with those sources (especially after the 1960s, the quality is much better in the case of the US). I simply believe that there is a great need for prudence in not overstretching the results. This is not the first time I make this point (see my paper with Phil Schlosser and John Moore here) and I think it is especially crucial for anything prior to 1943 (the introduction of tax withholding).

One of my main point is that the work of Gene Smiley which ended up published in the Journal of Economic History has generally been ignored. Smiley had highlighted many failings in the way the tax data was computed for measuring inequality. His most important point was that tax avoidance foiled the measurements of top incomes and how well they could transposed on the overall national accounts.

More precisely, Smiley argued that the tax shelters of the 1920s and 1930s would have affected reporting behavior. As long as corporations could issue stock dividends rather than cash dividends, delaying the payment of dividends until shareholders were in lower tax brackets, there would be avoidance. Furthermore, state and municipal securities were exempted from taxation which meant that taxpayers could shelter income and end up in lower brackets. All this combined to wide fluctuations in marginal tax rates conspires to reduce the quality of the tax data in computing inequality. Rather than substantial increases in inequality, Smiley found that his corrected estimates (which kept tax rates constant) suggested no increase in inequality during the 1920s and a minimal decrease when you exclude capital gains.

Alongside John Moore, Phil Schlosser and Phil Magness, I am in the process of attempting to extend the Smiley corrections to include everything up to 1941 (Smiley had ended in 1929). As a result, I had to assemble the tax data and the tax rates and I was surprised to see that, even without regressions, we can see the problem of relying on the tax data for the interwar period.

The number of millionaires in the tax reports is displayed below. As one can see, it is very low from 1917 to 1924 – a period of high tax rates. However, as tax rates fell in the 1920s, the number of millionaires quintupled. And then, when the Depression started in synchronicity with the increases in top marginal tax rates, it went back down. It went down by 89% from 1929 to 1941. Now, I am quite willing to entertain that many millionaires were wiped out during the Great Depression. I am not willing to entertain the idea that 9 out of every 10 millionaires disappeared. What I am willing to entertain is that the tax data is clearly and heavily problematic for the pre-withholding era.* This is evidence in favor of caution and prudence in interpreting inequality measures derived from tax data.

 

taxreports

I am of those who believe that inequality was lower than reported elsewhere in the 1920s, higher than reported in the 1930s and 1940s. Combined together, these would mean that inequality would tend to follow a L-curve or a J-curve from the 1920s up to the present rather than the U-curve often reported.  I will post more on this as my paper with Moore, Schlosser and Magness progresses.