Tuesday Growth Links

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Non-economics note: I finished the Souther Reach Trilogy (Annihilation, Authority , and Acceptance) by Jeff VanderMeer. I had been worried about a “Lost” situation, where the story doesn’t tie off nicely at the end, and….the books do not tie off nicely. BUT the writing is hypnotic, and the stories weave together so nicely, that I still recommend the books. If you cannot handle books without neat answers to their mysteries (and I normally cannot) then you should be careful of these books. But if you can give that kind of story a chance, these are a great place to start.

On to links that have been piling up over the last two weeks:

  • Great visualization of the spread of mega-cities over time. When you go to the site, notice that large cities appear first in relatively rich places (Europe, North America) and then slowly spread across the rest of world. Now, most mega-city growth is in particularly poor countries. Remi Jedwab and I have a paper we are working on right now regarding this rise of poor mega-cities. We link it to the change in mortality rates within cities after World War II. Historically, cities were deadly, and their growth was muted by the awful conditions. But with the epidemiological transition, cities became in many ways healthier than rural areas, meaning explosions of population growth, which ultimately let congestion outweigh the positive agglomeration effects of cities.
  • Actual data on the effect of robots! VoxEU post by Guy Michaels and Georg Graetz. They build a new dataset of information on industrial robots in use in 17 countries (OECD) by sector. They find that robot use is associated with higher labor productivity, wages, and total factor productivity, but no effect on labor’s share of output. They also find that robot use lowers the employment of low-skilled workers, and only a marginal effect on medium-skilled workers. They are studying industrial robots, and not necessarily the idealized general-purpose robot that seems to be the big worry of some, so their results are not immediately applicable to the future. But finally studying this in the data is a huge step. Original paper is located here.
  • Tim Harford on Luddites and their modern equivalents. A nice explainer of how Luddites were not anti-technology, and did not think that technology would result in aggregate loses of jobs. They were worried about losing their market power as skilled artisans.
  • This was floating around a lot on my Twitter feed. There was a severe bottleneck in the Y chromosome some time around 4-8 thousand years ago. What does that mean? It means the diversity of Y chromosomes in the human population dropped remarkably in that period, indicating that a relatively small number of men were fathering most children. The diversity of Y chromosomes recovers in most areas in the centuries that follow, indicating that more men are having children. So was it the onset of settled agriculture that led to this bottleneck, with a few males at the top of early agricultural civilizations able to dominate the pool of available females? Was early agriculture as bad for living standards, as has been suggested, so that many men were not healthy enough to have kids or have kids that survived?
  • Dated (from three weeks ago) but excellent post by Cardiff Garcia on the long lags between technology introduction and the effects on labor markets, using “Engel’s pause” in the 19th century to illustrate. Strongest point made here is that we have so few points of evidence regarding the effect of massive technology shifts on labor markets that trying to say anything firm about robots, AI, or anything else is almost impossible.
  • Tim Taylor on Paul Rubin on the mis-use of the idea of competition. The economy involves far more cooperation (implicit or explicit) than we like to give it credit for. Perfect competition is a non-existent, theoretical construct that is useful when writing models and you want to avoid talking about irrelevant things. But that doesn’t mean it is how things actually work, or how they should work. It definitely isn’t true that perfect competition would necessarily make an economy richer in the long run.
  • Many poor people in developing countries are poor in part because they live on really poor agricultural land. About 1.3 billion people are on what Edward Barbier and Jacob Hochard term less-favored agricultural land. Which of course leads to the big question regarding development. Is it better (or even possible) to improve that land, or is it better (or even possible) to get those people to leave those less-favored areas? If it’s the former, then your concern is more with technology and input provision (fertilizer, etc..). If it’s the latter, then your concern is more with property rights and compensating people who have to adapt to additional farmers showing up in their favored areas.
  • A good economic smack-down on trying to use market-based arguments against paying college athletes.
  • Kindle-to-Evernote script. Simple Python script that will suck up your Kindle highlights when you plug it into your computer and e-mail them to your Evernote account, organized nicely by book. Small tweaking necessary/possible to get things to your liking. But I cannot tell you how much I love this script. I want to give it a great big hug for saving me from having to go to my Amazon account all the time for notes.

Handy Book of Economic Growth

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

I thought it would be nice to post some overview articles of significant research in economic growth.

  1. Culture, Entrepreneurship, and Growth. Doepke and Zilibotti
  2. Trust, Growth, and Well-Being, Algann and Cahuc
  3. Long-term Barriers to Economic Development, Spolaore and Wacziarg
  4. Family Ties, Alesina and Giuliano
  5. The Industrial Revolution, Clark
  6. Twentieth-Century Growth, Crafts and O’Rourke
  7. Historical Development, Nunn
  8. Institutions and Economic Growth in Historical Perspective, Ogilvie and Carus
  9. What Do We Learn from Schumpeterian Growth Theory? Aghion, Akcigit, and Howitt
  10. Technology Diffusion: Measurement, Causes, and Consequences, Comin and Mestieri
  11. Health and Economic Growth, Weil
  12. Regional Growth and Regional Decline, Breinlich, Ottaviano, and Temple
  13. The Growth of Cities, Duranton and Puga
  14. Growth and Structural Transformation, Herrendorf, Rogerson, and Valentinyi
  15. The Chinese Growth Miracle, Yang Yao
  16. Growth From Globalization? A View from the Very Long Run, Meissner

If I were an enterprising publisher, I would go find some editors. Maybe Philippe Aghion and Steven Durlauf, just to throw some names off the top of my head. I’d have them put these together into a nice volume. Oh, wait

Quick update: I posted this list under the “Papers” page on this site if you want a more permanent place to find them.

More updates: Thanks to Pseudoerasmus for the links on the Yao and Meissner papers.

Friday Growth Links

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Things that I pretend I will have smart things to say about in the future:

  • Lemin Wu on whether we are thinking about Malthusianism correctly. A general point from this paper is that once you stop thinking of output as a single homogenous good, how you choose to weight different goods in your GDP/real wage/utility calculation matters a lot for your conclusions.
  • David Autor will take your job. Or something like that. I lost the thread of this article when I came upon this sentence: “Mr. Autor—who always sports a single gecko-shaped silver earring, his trademark symbol also pasted on his iPhone—says the fear has outpaced reality.”?!?!?
  • Ogilvie and Carus handbook chapter on institutions and economic growth in historical perspective. Whenever economic historians write something called “XXXXX in historical perspective”, the punch line is that “XXXXXX is wrong”. They do not definitively ruin the institutions/growth relationship, but do provide a lot of needed skepticism regarding the relationship. If you are going to argue that institutions matter for growth, then you have to do so in more of a case-by-case basis, and not using crude measures in cross-country regressions. I feel like I’ve heard that before
  • I like this Krugman post from earlier this week. Expanding education is not necessarily the answer to inequality. The idea that education levels are the key to higher wages is very useful for employers. Few people can or will leave work for 2 or 4 years to increase their education once they are working, and so they are willing to accept the low wages they currently have.
  • Ortman, Cabaniss, Sturm, and Bettencourt on settlement scaling and increasing returns in ancient society. They look at pre-Hispanic Mexico and find that the larger the settlement sizes/cities, the larger the monuments they built. Not surprising. But the relationship indicates IRS, which is. A ten-fold increase in settlement size led to a greater than 10-fold increase in the scale of monuments built.
  • Jane Humphries and Jacob Weisdorf look at women’s wages in England from 1260-1850. Female servant wages did not appear to be affected by the Black Death, which is problematic for the theory that the plague led to the emergence of the European Marriage pattern (see here). Women’s wages also did not track with men’s during the run-up to the Industrial Revolution, which may be problematic for the theory that high wages were part of the explanation for adoption of labor-saving technology (see here). Stupid data, always ruining things for everyone.

What I read on the plane rides to and from DC this week.

  • Medieval Technology and Social Change, Lynn White Jr. Probably best known for the “plows changed social structure” thesis. This is incredibly readable, and is less a definitive argument regarding technology and social change than a very nicer primer on the basic idea.
  • Mohammed and Charlemagne, by Henri Pirenne. A classic on the influence of Islam on the West. The first part of the book establishes that despite all the invasions of Huns, Goths, and the like, the areas of the Roman Empire remained fundamentally “Roman” throughout. The true disruption of Roman culture didn’t take place until Islam restructured the Mediterranean world. Like White’s book, very readable.
  • Annihilation, by Jeff VanderMeer. Fiction. First of a trilogy about unnamed scientists exploring the mysterious Area X. It sets up so much, I hope he can pull off a meaningful conclusion. Please don’t be like Lost. Please don’t be like Lost. Please don’t be like Lost….

For Chris Blattman, who needs kids book suggestions. These should work for 4-6 year olds, and were approved by my 11 and 9 year old as books they enjoyed a lot.

  • Magic Treehouse books. Kids explore different times, places, ideas in each book. As a bonus, they do companion non-fiction “Fact Tracker” books with more information on the topic.
  • Junie B. Jones. Barbara Park absolutely nails exactly how little kids talk and act. I loved reading these to my girls.
  • Roald Dahl. These are definitely too advanced for 4-6 year olds to read themselves, but we found they could start paying attention long enough to listen to a whole chapter. You have to stop sometimes to explain what is going on, or remind them the next night what is happening in the book, but reading James and the Giant Peach is soooooo much better then reading If You Give a Mouse a Cookie again, and again, and again.
  • Fancy Nancy. Shorter and good for helping them start to read. I resisted early on, but Fancy Nancy (including her many sequels) kind of grows on you. Perhaps that is just a coping mechanism.

Geography is Kinda-Sorta Destiny

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

I spent last weekend in Orlando with my wife and kids at Universal Studios. This had two effects. The first was to confirm everything I hate about large groups of people. The second was that it allowed me to read a number of books. So this is another post that is partly a book review.

I read Why the West Rules–for Now: The Patterns of History, and What They Reveal About the Future by Ian Morris. This is a book I was surprised I hadn’t already read. But nevertheless, I finally got around to it on the plane.

By itself, Morris’ book is fine. I think it falls in a grey area: it gets a little dense for a popular book, but isn’t thorough enough for an academic one. Parts of it are like reading a history textbook, where it becomes a list of events and names without a lot of context. I do like his summary of what drives history. “Change is caused by lazy, greedy, frightened people looking for easier, more profitable, and safer ways to do things. And they rarely know what they’re doing.”

The larger theme of the book is interesting. Morris stakes out a position that geography is really why the West “rules” at this point. Somewhat fixed characteristics like soil and general weather patterns ensured that Western Europe and China were bound to be relatively rich compared to most of the world. The additional advantages of western Europe were the relatively easy access they had to the geographic bonanza of the New World (which itself was due to the particular fact that Native Americans died from European diseases and not vice versa).

Given my not-overwhelming recommendation of Morris’ specific book, let me offer you some additional books that make the case for geography and/or biology being a major factor in economic development.

  1. Plagues and Peoples by William McNeill
  2. Guns, Germs, and Steel: The Fates of Human Societies by Jared Diamond
  3. The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor by David Landes. (Not the whole book, but the early chapters focus on geography)
  4. The European Miracle: Environments, Economies and Geopolitics in the History of Europe and Asia by Eric Jones. (Probably my favorite in this list)

I could go on, but I run into the “wedding invitation” problem. If I recommend another book in which geography features strongly, like Empire of Cotton, I feel compelled to recommend the other 10 books that I find similar in scope or quality. Pretty soon we’re talking about a long list. So stick with these for now as your entree to the world of geography as a determinant of development.

Morris and these other authors are often accused of “geographic determinism”. This is often slung about as a kind of epithet, implying that the author means that world economic history had to come out *exactly* like it did because of geography. This bothers people because it seems to exonerate western Europeans from all the awful things they did along the way to becoming rich. It can also be easily twisted into arguments about how Europeans are superior to other races or groups of people.

But that is setting up straw men in place of what these authors actually say. The mistake is to think that by asserting geography matters, this denies any role for human agency. Geography sets the budget constraint, affecting the slope (i.e. relative cost of land versus labor) and intercept (i.e. how many people land can support). But people set the utility function, making the choices about production, consumption, and innovation. To say that geography matters for development is to say that incentives matter, that’s all. Geography creates some subtle, and some not so subtle, differences in the constraints facing people, and they react accordingly. They look for easier, more profitable, and safer things to do within their given geographic conditions.

It is also a mistake to think that geography implies that relative development levels must be constant over time. Certain geographic characteristics are fixed, for all intents and purposes; North American is closer to Europe than to China. But nearly all other characteristics that we could lump under “geography” change over the course of human history. Think of the climate, with little ice ages and the Medieval warm period. And technological changes can make geographic characteristics change in their influence on development. Think of oil.

Geography doesn’t say that some populations are supposed to be rich, that they deserve to be rich, or that they will always be rich. It says that it isn’t terribly surprising that they are rich right now. Imagine that we could rewind and rerun human history over and over and over again. Each time, set the clock back to 15,000 BC and then let things go. Each time, it would be different as all the millions of coin flips in history came up heads or tails. Geography means the coins are not fair. Europe, blessed with productive agricultural land, lots of internal waterways, access to oceans, etc. etc.. comes up heads 55% of the time. Africa, with tough agricultural conditions, a bad disease environment, and a lack of natural transport networks comes up heads only 45% of the time. Over those thousands of versions of history, it would tend to be the case that Europeans would be relatively rich.

So when these authors say “geography matters”, take that as a statement similar to saying that a coefficient in a regression “matters”. It’s a statistical statement that the coefficient on geography is significant, not that the R-squared of the regression is 100%.

The Industrial Revolution and Modern Development

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

I’m not an economic historian, but like most growth economists I am an avid consumer of economic history. Maybe it’s our version of “physics envy”. Regardless, it isn’t always obvious why growth economists look backwards so much for motivation, examples, and inspiration. Let me try to give an example of the usefulness of economic history by looking at recent “big theories” of the British Industrial Revolution (IR).

If you have any interest in learning about the IR, then you could do a lot worse than reading the following two books:

Mokyr’s theory is that there was a unique intellectual environment created in Britain during the Enlightenment, and that this generated cultural conditions that valued innovation as a valuable activity in and of itself, as well as a supply of trained engineers that took advantage of these conditions. What made the IR British was its adoption of science and reason as tools of economic progress.

Allen’s theory has to do with relative factor prices. The IR was British because Britain had a unique combination of high wages (persisting after the Black Death) and low fuel costs (due to cheap coal) that made labor-saving and fuel-using innovations (e.g. the steam engine) profitable. Other countries failed to adopt, or lagged in adopting, because they had different relative prices for labor and fuel.

There is some sense that these two have set up competing explanations of the Industrial Revolution, diametrically opposed. Mokyr does tend to downplay the “coal made the IR” idea. Allen does tend to downplay the notion that Britain was unique in its potential for innovation. But there is more subtlety to their arguments than that. The theories do not contradict each other, because they are fundamentally concerned with explaining different phenomenon.

There are two different questions about the IR in Britain that we want to answer. First, why did several particularly important innovations take place in Britain, and not in other places? Second, of all the innovations available, why were they adopted first (or with greater speed) in Britain than in other areas of Europe?

Mokyr’s theory is very much an answer to the first question, and provides a sound answer to the second. Newcomen and Watt and Arkwright and Darby and Hargreaves were all British. Perhaps more important than these noted innovators, according to Mokyr, is the small army of highly skilled engineers that patiently but steadily made improvements to the steam engine, spinning jenny, coke smelting, and other technologies. What set Britain apart from China (where most of the big innovations had occurred earlier) or France (which quickly had knowledge of the big innovations) were those engineers. Without them, you have curiosities. With them, you have industrialization. Britain led the IR because the Enlightenment took hold and produced both the original innovators and that army of engineers.

Allen’s theory is very much an answer to the second question, but is relatively weak on the first. That is, we can use factor prices to understand why Britain adopted the steam engine or spinning jenny first, but they don’t explain why those things were invented in Britain. Allen suggests that those same factor prices played a role in inducing innovation, but that is shakier ground. Anton Howes just posted a reaction to Allen’s work that focuses precisely on that failure.

So Mokyr’s theory is more comprehensive, but it lacks a compelling explanation for the failure of other countries to follow Britain quickly into industrialization. Allen’s work is really a theory of growth and development, articulated with examples from the British IR. We can easily adopt his concepts for other time periods and places, whereas Mokyr’s work is far more context-specific. Thus Allen’s theory is more relevant than Mokyr’s to thinking about the general process of development. The second question above – why do some places fail to adopt or lag in adopting new innovations? – is in some sense the central question of development.

Research on development has been focusing a lot lately on the distribution of productivity across firms (see my reading list on misallocation). In China, India, or Mexico, for example, the ratio of labor productivity of the top firms to bottom firms is on the order of 10-1 or more. Even in the U.S. there are productivity gaps of something like 2-1 between the best and worst firms. Not all firms use the best techniques. Poor countries have particularly bad distributions, with the vast majority of their firms using low productivity technologies.

If we could understand that distribution, we could understand a lot about the gap in income per capita between poor and rich countries. So far, most of the explanations hinge on firms facing some implicit distortion to factor costs, which makes them choose a sub-optimal level of inputs. Firms that may be very productive perhaps face high distortions, making factors expensive, and leading them to be too small. Firms that are unproductive face low distortions, making factors cheap, leading them to be too big.

What this literature could learn from Allen is that the choice of technology itself is in play when factor prices are distorted. In particular, distortions that change the costs of materials relative to capital or labor could be instrumental in keeping firms from adopting leading technologies in poor countries. Cheap labor may make a firm inefficiently large in a poor country, yes. But it also removes the incentive to adopt a capital-using, labor-saving high technology production technology, even if the firm has full knowledge of the technology.

This isn’t a brand new idea by Allen. Hicks talked about it in 1932. Hayami and Ruttan talked about induced innovation and the choice of technology with respect to agriculture in developing countries long ago. Banerjee and Duflo’s chapter on distortions considers the role of borrowing constraints (i.e. expensive capital) in generating a fat tail of small labor-intense firms in India. Daron Acemoglu‘s theory of directed technical change is basically induced innovation based on differentials in factor prices.

Allen, though, provides a clear and compelling story about the power of factor prices in technology adoption. Think of his work as a “proof of concept” that induced innovation has a lot of explanatory power for differences between rich and poor countries. It is an excellent example of how studying economic history can produce insights into modern questions about development and growth. Factor price differences created decades-long lags in technology adoption across Europe, perhaps we shouldn’t be surprised at decades-long delays in adoption in developing countries. Relative factor prices may be a worthwhile avenue to explore, possibly as the lever on which institutions (hypocrite!?) or geography push to generate differences in living standards.

[I appear to have slighted Mokyr’s work here in favor of Allen, but right now someone else is reading his book and gleaning from it some idea about culture and development that I missed completely. From the growth economist’s perspective, the purpose is not to decide who’s right in these economic history debates, it is to mercilessly steal all the good ideas.]

A Few Growth Links

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  1. Kelly and O’Grada on sustained economic growth in England berfore 1700. That growth was slow relative to modern rates, but they argue it was appreciable and associated with increasing human capital and high wages. They give several examples of significant division of labor within industry in this pre-IR era.
  2. Via Chris Blattman. Experimental evidence that participating in trade leads to higher productivity. The modern firm-level trade models generally take productivity of firms as given, and only those who are already productive find trade worth it. The most enthusiastic reading of this is that simply providing firms with information about markets boosts productivity. The least enthusiastic is that experimenters simply paid fixed export cost for firms.
  3. The UN Least Developed Countries Report 2014 is about Growth with Structural Transformation. One of the key messages is “Economic growth is not enough: it must be accompanied by structural transformation..”. Um, name one example of economic growth that did *not* involve structural transformation. Probably more to come from me on this report, but you can all study it at home over the break.
  4. Correlation of pathogen exposure and degree of innovation across primate species. Essentially, being social animals has benefits (cooperation, imitation, and innovation) and costs (infectious diseases). Big question obviously is whether one drove the other.
  5. Gehringer and Prettner on longevity and innovation. A basic scale story. The longer people live, the more incentives they have to invest in capital (physical and human). This expands the scale of the economy, which expands incentives to innovate and earn profits. A relatively optimistic response to population aging through lower mortality rates as opposed to pessimistic worries about stagnation.
  6. Noah Smith (from a long time ago) writes a review of a paper by Acemoglu, Robinson, and Verdier regarding different types of capitalism (think Sweden and the US) and innovation. Upshot is that Sweden’s “soft” capitalism is worse for innovation than US type. More interesting than the particulars of the ARV paper is Noah’s broader comments on writing down models designed to fit existing data. The fact that the data matches your model doesn’t imply your model is right. It means you were smart enough to get the math to work out.
  7. Alex Tabarrok links to CBO report on patenting and TFP growth. Not much of a correlation. Several ways to think about this. First, patents are a very imperfect measure of innovation. Second, TFP is a very imperfect measure of innovation – remember, TFP includes utilization changes, markups, and input changes. It does *not* equal technology, so it is probably not surprising that TFP and patents are not correlated.

New Growth Resources

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First, great reading lists from Anton Howes and Pseudoerasmus on economic history, often from a very broad perspective. These are all books that I (and you, if you’re reading this) should have read already, but I promise I’ll be good next year and get to it.

Also, I put up a new section of maps that I use when I teach economic growth. Will attempt to get around to putting together slides and post those some day too.

The Loss of Skill in the Industrial Revolution

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

There’s a recent working paper by Alexandra de Pleijt and Jacob Weisdorf that looks at skill composition of the English workforce from 1550 through 1850. They do this by looking at the occupational titles recorded in English parish records over that period, and code each observed worker by the skill associated with their occupation. They use the standardized Dictionary of Occupational Titles to infer the skill level for any given occupation. For example, a wright is a high-skilled manual laborer, a tailor is medium-skilled, while a weaver is a low-skilled manual laborer.

de Pleijt and Weisdorf 2014

The big upshot to their paper is that there was substantial de-skilling over this period, driven mainly by a shift in the composition of manual laborers. In 1550, only about 25% of all manual laborers are unskilled (think ditch-diggers), while 75% are either low- or medium-skilled (weavers or tailors). However, over time there is a distinct growth in the the unskilled as a fraction of manual laborers, reaching 45% by 1850, while the low- and medium-skilled fall to 55% in the same period. You can see in their figure 10 that this shift really starts to take place by 1650, while before the traditional start of the Industrial Revolution.

Looking at more refined measures, de Pleijt and Weisdorf find that the fraction of workers classified as “high-quality workmen” – carpenters, joiners, wrights, turners – rose only from 3.9% to 4.9% of the workforce between 1550 and 1850. These are precisely the kinds of workers that Joel Mokyr claims are the crux of the Industrial Revolution in England. They built, improved, adapted, and micro-innovated all the classic inventions of the IR. While they were only between 4-5% of the workers, and this proportion didn’t expand rapidly, given population growth the absolute numbers of these high-quality workmen went up by a factor of 4 between 1700 and 1850 (from about 200K to 850K).

It’s a really interesting paper, and it’s neat to see how much information you can keep sucking out of these parish records from England. It leaves me with two big questions/ideas. First, does industrialization depend on a concentrated core of skills, rather than a broad distribution of skills? That is, if Mokyr is right about the source of English industrialization, then it’s those extra 650K high-skilled workers that really made all the difference. Industrialization didn’t involve spreading skills all around the (rapidly expanding) population, but in getting together a critical mass of skilled workers. Are we paying too much attention to average human capital levels when we talk about development and growth, and not enough to looking at when/how/if countries achieve that critical mass of skilled workers? Is the overall level of education irrelevant to industrialization?

Second, should we care about de-skilling? In a vacuum, telling someone that the share of unskilled workers in the economy rose from 25 to 40% of all workers would send up red flags. That must be a bad thing, right? Is it? As England added population, much of that new population was unskilled, presumably because there was no longer a demand for certain low- and medium- skilled professions that had been replaced by machines. Could this just mean that the economy was getting more efficient at using the human capital at hand? England didn’t need to waste all that time and effort skilling-up a big mass of workers. They could be used immediately, without much training.

True, real wages didn’t rise between 1550 and 1800 (but from 1800 to 1850 they seem to start taking off, see Clark, 2005). But they also didn’t fall. That is, despite the fact that even before the classic IR the population of England was deskilling, there wasn’t a demonstrable fall in living standards. So doesn’t that imply that England was getting more (output) from less (human capital)? That’s a good thing, right? If England had held the level of human capital constant, then this would have raised real wages per worker. Instead, they chose to lower the amount of human capital while leaving real wages per worker the same. Who’s to say that this is a worse outcome?

If we were talking about innovations that got more output from less energy, then holding output constant while lowering energy consumption would be what everyone hoped to see. Why should human capital be different?

Empirical Institutions Reading List

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The next installment of reading lists for my grad growth and development class this fall has to do with one explanation for the fundamental source of cross-country differences: institutions. “institutions” is a very nebulous concept, and so most of the recent, empirically sound, research on institutions focuses not on “institutions” in general but on some specific type of institution. Almost without fail, this leads to studies of former colonies. This is because they tend to have a very useful quality: a specific institution may have been thrust upon them, or changed arbitrarily.

Empirically, we want to find the causal effect of some specific institution on development (output per worker, wage levels, education levels, what have you). In general, what we call institutions are hopelessly endogenous, so we’re looking for natural experiments where an institution was dropped from the sky, so to speak, on top of some country. If so, we can possibly isolate the independent effect of that institution on development. Colonies make for a good test bed, as one can make a (perhaps) plausible argument that the colonizer exogenously altered, added, or subtracted some specific institution to the colony.

I try to avoid any papers that look at simple cross-country regressions of income per capita on some index of institutions, although I do talk through the Acemoglu, Johnson, and Robinson papers because of their prevalence across the literature. This is because of a point I raised before, which is that one can arbitrarily make an “institutions index” significant in a regression if you simply wiggle around the index values the right way. [I could code the U.S. a 1, Turkey a 0.5, and Zimbabwe a 0, or code them as 10,9, and 0, respectively. I preserve the ordering, but completely change the possible implications in a regression].

The reading list, which is posted under the “Papers” page on this site, thus focuses on recent within-country work related to specific institutions. One exception is the African work by Stelios Michalopoulos and Elias Papaioannou, which covers most of the continent, and tends to look at institutions as a generic concept. The interesting comparison here is the differing results: one paper finds that pre-colonial institutions do have persistent effects on development of ethnic groups, while the other finds that national institutions are not relevant. This just highlights that “institutions” taken as a whole are not necessarily a good predictor of development. Rather, one can find examples of specific institutions that matter.