“The Institutional Causes of China’s Great Famine, 1959-1961,” X. Meng, N. Qian & P. Yared (2011)

Nancy Qian, along with a big group of coauthors, has done a great amount of interesting empirical work in recent years on the economics of modern China; among other things, she has shown that local elections actually do cause policy changes in line with local preferences and that the state remains surprisingly powerful in the Chinese economy. In this paper with Xin Meng and Pierre Yared, she considers what is likely the worst famine in the history of mankind, China’s famous famine following the Great Leap Forward. After a agricultural production shock in 1959, a series of misguided policy experiments in the mid-1950s (like “backyard steel” production, which produced worthless metal), and an anti-Rightist purge which ended a brief period of less rigid bureaucracy, 30 million or so people would die from hunger over the next two years, with most deaths among the young and the very old. To put this in relative context, in the worst-hit counties, the birth-cohorts that should have been born or very young in 1960 and 1961 are today missing more than 80% of their projected members.

What is interesting, and what we have known since Sen, is that famines generally result from problems of food distribution rather than food production. And, indeed, the authors show that total grain production in caloric terms across rural parts of China is a multiple of what is necessary to hold off starvation during the height of the productivity shock. What is interesting and novel, though, is that provinces with higher historic per-capita grain production had the highest mortality, and likewise counties with the highest per-capita production as measured by a proxy based on climate also have the largest number of “missing” members in their birth year cohort in the 1990 census. This is strange – you might think that places that are living on the edge in normal times are most susceptible to famine.

This is where politics comes into play. The Chinese government “sent down” many competent bureaucrats during the anti-Rightist purges in the late 1950s, limiting the ability of the government to use flexible mechanisms for food procurement. The food system at the time involved the central government collecting a set amount of grain from each region, then returning stocks to communal kitchens. Now, local leaders had a strong incentive to understate how much was produced in a given year so that they could use the remainder for local power purposes. Because of limited communication technology and ineffective bureaucracy, the optimal mechanism (not specified formally, but apparently done so in an earlier version) for the central government involved pre-setting fixed production goals for every region. Here is the problem: imagine you wish the city, rural area 1 and rural area 2 to have the same expected consumption, with the city producing no food, and rural area 1 producing 1 ton per capita per year and rural area 2 producing 1.4 tons per capita. This gives total consumption of .8 tons per capita if the government sets in advance a fixed “tax” of .2 tons per capita from 1 and .6 tons per capita from region 2. Now a productivity shock lowers production everywhere by 10 percent. The city still gets its .8 tons per capita (since the “tax” is fixed), but area 1 now gets .9*1-.2=.7 tons per capita, and area 2 gets 1.4*.9-.6=.66 tons per capita. That is, the lack of flexibility in the system is more likely to push the productive regions into famine than other regions.

Now, this is not the whole story. Alternative explanations, already suggested in the literature, also are quantitatively important. Places with more anti-Rightist purges before the famine saw higher mortality (see this 2011 APSR by Kung and Chen), as did places with earlier adoption of communal dining halls or larger increases in backyard steel production, both proxies for “zealous” adherence to the Great Leap Forward. I would really like to see some attempt at a decomposition here: if you buy that local political leadership, the central government quota system, and political punishment of counterrevolutionary areas were all important, and that weather shocks alone were not, how many of the deaths should we ascribe to each of those factors? This seems an important question for preventing future famines. It seems that a further fleshing out of how these results relate to the old theory of the firm debates about flexibility of local managers under imperfect and partially unverifiable reporting can help us understand what was going on with the CCP policy choices; I’m thinking, for instance, of explicitly showing whether it is true that loss of members of the bureacracy (i.e., an increase in the cost of monitoring) necessarily incentivizes more rigid allocation rules. Theory here could help to quantify how important this mechanism might be.

2011 working paper (IDEAS version). This paper is R&R at ReStud currently. Qian has a couple other working papers that caught my eye. First, a paper with Duflo and Banerjee on Chinese transportation infrastructure finds very little impact on relative incomes of (quasi-random) access to a good transportation network, and suggests in a short model (which is less convincing…) that relative immobility of capital might be causing this. The techniques in the paper are similar to those used by Ben Faber in his very nice paper showing Krugman’s home market effect: if you are small and poor, being connected with a big productive place may not be good for you due to increasing returns to scale. Qian also has a 2013 paper with Nathan Nunn on food aid which suggests, pretty convincingly, that food aid in civil war zones prolongs conflicts; the mechanism, roughly, is that local armies can easily steal the aid and hence have less reason to sue for peace. The identification strategy here is quite nice: the US government buys wheat for price stabilization reasons, then gives much of this away to impoverished countries. The higher the price of wheat, the less the government surplus is, hence the less is given away.

“Patent Alchemy: The Market for Technology in U.S. History,” N. Lamoreaux, K. Sokoloff & D. Sutthiphisall (2012)

It may appear that the world of innovation looks very different today than it used to. Large in-house R&D outfits – the Bell Labs of the past – are being replaced by small firms who sell the results of their research on to producers. Venture capital funding of research appears more and more important, both for providing capital to inventors and to linking the inventors up with potential buyers. Patent trolls hound the innocent, suing them for patent violations they weren’t even aware of. The speed with which patents are evaluated has slowed to a crawl, and the number of patents being granted continues to grow. Many patents are merely defensive, acquired solely to keep someone else from acquiring them.

Lamoreaux et al, building on earlier work by Lamoreaux and Sokoloff as well as Tom Nicholas’ interesting recent research, point out that none of the above is strange. The rise of in-house R&D is a phenomenon that doesn’t show up in great number in America until well into the twentieth century, only becoming dominant after the Second World War. Around the turn of the century, most innovation was done by small, independent inventors, or by small research firms like Edison’s outfit. A series of intermediaries, principally but not always patent lawyers, served both to file the proper paperwork and to link inventors with potential buyers; the authors provide a bunch of juicy historical stories, derived from lawyer diaries during this period, on exactly how such transactions took place. Railroads were frequently being hounded by patent trolls who tried to catch them unaware, and traveling patentbuyers crossed the Midwest and South suing farmers for using unlicensed barbed wire or milk buckets. Patents took an average of three years to be processed by the early 1900s, and the patenting rate was near an all time high. Firms regularly bought patents just so their competitors wouldn’t have them.

This is all to say that, to the extent we are worried about certain aspects of the patent system today, looking to history may be a useful place to begin. “Submarine patents”, acquired by trolls and kept unused until a particularly juicy potential violator has started to earn large profits, don’t appear to have been too prominent at the turn of the century – given how lucrative this business appears, perhaps an investigation of why they only appear in the present would be worthwhile. The role of a patent as a saleable piece of knowledge, allowing non-producers to do useful research and then sell that research to a firm who finds it useful, surely has some role, as Arrow pointed out in his famous 1962 essay. When patents instead simply add transaction costs or result in thickets, discouraging activity by true innovators, something has gone awry. And when something goes wrong in the world, it is rarely the case that history can offer us no useful guidance.

2012 working paper (No IDEAS version). Prof. Sokoloff passed away from cancer at a young age in 2007, so this may become his final published paper – it incorporates a great number of ideas he worked on throughout his career, so that would be a fitting tribute.

“Chinese Economic Performance in the Long Run,” A. Maddison (2007)

Many economists know the rough contours of Western economic history well. Real income of unskilled laborer and farmer households was at no time and in no place more than, at best, three times subsistence income (see Scheidel for a nice summary of this evidence). Peaks in per capita GDP were reached in the heyday of ancient Rome and the early Arab caliphate. Regional regression was nothing strange – Europe in 1000 was using less advanced technology in many cases than the Romans had, credit markets were essentially nonexistent, long-distance or even regional trade had dried up, and no city in Europe existed with a population of even 10,000 people at the turn of the millennium. Living standards begin to rise slowly after the Black Death, first in Renaissance Italy, and then in the Netherlands and England. The Industrial Revolution finally severs the Malthusian noose by the mid-1800s, when living standards for most members of society begin to rise from their historical norm.

But what of China? Before he died, one of Angus Maddison’s final projects was compiling data on historic China. In Chinese culture, the classic periods in history are the Tang and Song dynasties, roughly from the 7th to the 12th centuries, with brief interludes, and perhaps the late Yuan and early Ming, from the late 13 to the late 1400s. Did China escape the Malthusian curse? They also did not. It seems likely that incomes were roughly at subsistence until the Tang dynasty in the 9th century, when income per capita rose perhaps 30 percent. That peak would not be seen again until around 1970!

Now, in a Malthusian world, you can still grow, or be more advanced economically, but that growth is eaten up by population growth. The main pattern in China seems to be a massive shift in population density in the south, meaning south of the Yangtse, after the beginning of the Song dynasty. Woodblock printing, allowing for the dissemination of guides to more productive agriculture, appeared in this era. Chinese agriculture appears to have been much more advanced that that of Europe or India; indeed, more of China’s farmland was irrigated in 1400 than America’s today, and not until the 20th century did Europe reach grain yields seen in China in 1400. If you know your Joseph Needham, you know much of this is driven by Chinese agricultural inventions like the curved mouldboard and the use of crop rotation (not seen in Europe until the eighteenth century!). Population rose ten-fold from 1400 to 1950 despite little change in per capita income. A nontrivial increase in caloric yield per acre of farmland came from the introduction of new world crops like maize and the sweet potato, which appear in China during the Ming dynasty. Nonagricultural rural work also appears to have been much more developed than in medieval Europe, with William Skinner’s “hexagonal trade” existent during nearly all of the post-Tang dynasties. Such trade allowed cities to develop – around 1000, China had almost 100 cities with population above 10,000, as compared to none in Europe!

More recently, industrialization gets a late start. The 1800s are a giant disaster for China, with wars against Europeans, Russians and Japanese (China lost essentially all of these), the Taiping rebellion that kills tens of millions in the nation’s heartland, Muslim rebellions in the Northwest, and a near complete lack of institutional modernization of the type seen in Japan. By 1890, only 10 miles of rail are found in the whole country, and modern industry makes up only one-half percent of the economy. Despite some fits and starts during the Republican era (especially in Shanghai and Japanese-controlled Manchuria), by the end of World War 2 and the Chinese Civil War, per capita income is no higher than it was during the Tang dynasty. Perhaps the non-vilification of Mao in today’s China has to do with the fact that, even with near-complete autarky, the Great Leap Forward and the Cultural Revolution, per capita income still nearly doubled during the Maoist era, and the industrial share of GDP rose up to match the agricultural share. That is, despite all of the human rights disasters, the Maoist economic performance was simply unheard of in Chinese history. Nearly all of this growth came from capital deepening and (especially) increases in labor supply and the human capital embodied in that labor supply; literacy rose from 20 percent to about 80 percent. And, of course, the economic history since 1976 is well-known – in only three years of the past 37 has GDP per capita grown slower than six percent, an unprecedented streak in the history of the globe.

http://browse.oecdbookshop.org/oecd/pdfs/product/4107091e.pdf (Full PDF version of the published book – big thumbs up to the OECD for making these public. If you are a Chinese speaker, prepare to be annoyed by Maddison’s habit of using Wade-Giles transliteration, i.e., Cheng Ho instead of Zheng He, Yung-lo Emperor instead of the Yangle Emperor, Kwangtung for Guangdong, Tseng Kuo-fan for Zeng Guofan. Speaking of Maddison, his historic income tables (.XLS) are a great way to while away a rainy afternoon. Who knew Australia was once the world’s richest place, or that Sri Lanka was historically a particularly wealthy part of Asia, or that Venezuela was wealthier per capita than all of Western Europe in the middle of the 20th century?)

“Diffusing New Technology Without Dissipating Rents: Some Historical Case Studies of Knowledge Sharing,” J. Bessen & A. Nuvolari (2012)

The most fundamental fact in the economic history of the world is that, from the dawn on mankind until the middle of the 19th century in a small corner of Europe, the material living standards of the average human varied within a very small range: perhaps the wealthiest places, ever, were five times richer than regions on the edge of subsistence. The end of this Malthusian world is generally credited to changes following the Industrial Revolution. The Industrial Revolution is sometimes credited to changes in the nature of invention in England and Holland in the 1700s. If you believe those claims, then understanding what spurred invention from that point to the present is of singular importance.

A traditional story, going back to North and others, is that property rights were very important here. England had patents. England had well-enforced contracts for labor and capital. But, at least as far as patents are concerned, recent evidence suggests they couldn’t have been too critical. Moser showed that only 10% or so of important inventions in the mid-1800s were ever patented in the UK. Bob Allen, who we’ve met before on this site, has inspired a large literature on collective invention, or periods of open-source style sharing of information among industry leaders during critical phases of tinkering with new techniques.

Why would you share, though? Doesn’t this simply dissipate your rents? If you publicize knowledge of a productive process for which you are earning some rent, imitators can just come in and replicate that technology, competing away your profit. And yet, and yet, this doesn’t appear to happen in many historical circumstances. Bessen (he of Bessen and Maskin 2009, one of my favorite recent theoretical papers on innovation) and Nuvolari examine three nineteenth century industries, American steel, Cornish steam engines and New England power weavers. They show that periods of open sharing on invention, free transfer of technology to rivals, industry newsletters detailing new techniques, etc. can predominate for periods a decade and longer. In all three cases, patents are unimportant in this initial stage, though (at least outside of Cornwall) quite frequently used later in the development of the industry. Further, many of the important cost reducing microinventions in these industries came precisely during the period of collective invention.

The paper has no model, but very simply, here is what is going on. Consider a fast growing industry where some factors important for entry are in fixed supply; for example, the engineer Alexander Holley personally helped design eight of the first nine American mills using Bessemer’s technology. Assume all inventions are cost reducing. Holding sales price and demand constant, cost reductions increase industry profit. Sharing your invention ensures that you will not be frozen out of sharing by others. Trying to rely only on your own inventions to gain a cost advantage is not as useful as in standard Bertrand, since the fixed factors for entry in a new industry mean you can’t expand fast enough to meet market demand even if you had the cost advantage. There is little worry about free riding since the inventions are natural by-products of day-to-day problem solving rather than the result of concentrated effort: early product improvement is often an engineering problem, not a scientific one. Why would I assume sales price is roughly constant? Imagine an industry where the new technology is replacing something already being produced by a competitive industry (link steel rail ties replaced iron ties). The early Bessemer-produced ties in America were exactly this story, initially being a tiny fraction of the rail tie market, so the market price for ties was being determined by the older vintage of technology.

Open source invention is nothing unusual, nor is it something new. It has long coexisted with the type of invention for which patents may (only may!) be more suitable vectors for development. Policies that gunk up these periods of collective invention can be really damaging. I will discuss some new research in coming weeks about a common policy that appears to provide exactly this sort of gunk: the strict enforcement of non-compete agreements in certain states.

2012 Working Paper (IDEAS version)

Game Theory and History, A. Greif & Friends (1993, 1994)

(This post refers to A. Greif, “Contract Enforceability and Economic Institutions in Early Trade: The Maghribi Traders’ Coalition”, AER 1993, and A. Greif, P. Milgrom & B. Weingast, “Coordination, Commitment and Enforcement: The Case of the Merchant Guild,” JPE 1994.)

Game theory, after a rough start, may actually be fulfilling its role as proposed by Herbert Gintis: unifier of the sciences. It goes without saying that game theoretic analysis is widespread in economics, political science (e.g., voter behavior), sociology (network games), law (antitrust), computer science (defending networks against attacks), biology (evolutionary strategies), pure philosophy (more on this in a post tomorrow!), with occasional appearances in psychology, religion (recall Aumann’s Talmud paper), physics (quantum games), etc. But history? Surely game theory, particularly the more complex recent results, has no place there? Yet Avner Greif, an economic historian at Stanford, has shown that games can play a very interesting role indeed in understanding historical events.

Consider first his Maghribi traders paper. In the 11th and 12th century, a group of Judeo-Arabic traders called the Maghribis traded across the Mediterranean. Two institutional aspects of their trade are interesting. First, they all hired agents in foreign cities to carry out their trade, and second, they generally used other Maghribi merchants as their agents. This is quite different from, for instance, Italy, where merchants tended to hire agents in foreign cities who were not themselves merchants. What explains that difference, and more generally, how can long distance traders insure that traders do not rip you off? For instance, how do I keep them from claiming they sold at a low price when actually they sold at a high one?

To a theorist, this looks like a repeated reputational game with imperfect monitoring. Greif doesn’t go the easy route and just assume there are trustworthy and untrustworthy types. Rather, he assumes that there are a set of potential agents who can be hired in each period, that agents are exogenously separated from merchants with probability p in each period, and that merchants can choose to hire and fire at any wage they choose. You probably know from economics of reputation or from the efficiency wage literature that I need to offer wages higher than the agent’s outside option to keep him from stealing; the value of the continuation game, then, is more than the value of stealing now. Imagine that I fire anyone who steals and never hire him again. How do I ensure that other firms do not then hire that same agent (perhaps the agent will say, “Look, give me a second chance and I will work at a lower wage”)? Well, an agent who has cheated one merchant will never be hired by that merchant again. This means that when he is in the unemployed pool, even if other merchants are willing to hire him, his probability of getting hired is lower, since one merchant will definitely not hire him. That means that the continuation value of the game if he doesn’t steal from me is lower. Therefore, the efficiency wage I must pay him to keep him from stealing is higher than the efficiency wage I can pay someone who hasn’t ever stolen, so I strictly prefer to hire agents who have never stolen. This allows the whole coalition to coordinate. Note that the fewer agents there are, the higher the continuation value from not stealing, and hence the lower the efficiency wage I can pay: it is optimal to keep the set of potential agents small.

What of the Italian merchants? Why do they not hire only each other? Maghribi merchants tended to be involved only in long distance trade, while Italian merchants were also involved in real estate and other pursuits. This means the outside option (continuation value after cheating if no one hires me again) is higher for Italian merchants than Maghribi merchants, which means that hiring merchants at the necessary efficiency wage will be relatively more expensive for Italians than Maghribis.

A followup by Greif, with Milgrom and Weingast, considers the problem of long distance trade from the perspective of cities. Forget about keeping your agent from ripping you off: how do you keep the city from ripping you off? For instance, Genoans in Constantinople had their district overrun by a mob at one point, with no compensation offered. Sicilians raised taxes on sales by Jews at one point after they had brought their goods for sale. You may naively think that reputation alone will be enough; I won’t rip anyone off because I want a reputation of being a safe and fair city for trade.

But again, the literature of repeated games tells us this will not work. Generally, I need to punish deviations from the efficient set of strategies, and punish those who themselves do not punish deviators. In terms of medieval trade, to keep a city from ripping me off, I need not only to punish the city by bringing it less trade, but I also need to make sure the city doesn’t make up for my lost trade by offering a special deal to some other trader. That is, I need to get information about violation against a single trader to other traders, and I need to make sure they are willing to punish the deviating city.

The merchant guild was the institution that solved this problem. Merchant guilds were able to punish their own members by, for example, keeping them from earning rents from special privileges in their own city. In the most general setting, when a guild orders a boycott, cities may be able to attract some trade, but less than the efficient amount, because only by offering a particularly good deal to the merchants who come during a boycott will entice them to come and to credibly believe the city will not steal.

This is all to say that strong guilds may be in the best interest of cities since they allow the city to solve its commitment problem. The historical record confirms many examples of cities encouraging guilds to come trade, and encouraging the strengthening of guilds. Only a reputational model like the above one can explain such city behavior; if guilds are merely extracting rents with monopoly privilege, cities would not encourage them all. Both of these papers, I think, are quite brilliant.

1993 AER (IDEAS version) and 1994 JPE (IDEAS version). Big thumbs up to Avner for having the final published versions of these papers on his website.

Learning and Liberty Ships, P. Thompson

(Note: This post refers to “How Much Did the Liberty Shipbuilders Learn? New Evidence for an Old Case Study” (2001) and “How Much Did the Liberty Shipbuilders Forget?” (2007), both by Peter Thompson.)

It’s taken for granted now that organizations “learn” as their workers gain knowledge while producing and “forget” when not actively involved in some project. Identifying the importance of such learning-by-doing and organizational forgetting is quite a challenging empirical task. We would need a case where an easily measurable final product was produced over and over by different groups using the same capital and technology, with data fully recorded. And a 1945 article by a man named Searle found just an example: the US Navy Liberty Ships. These standardized ships were produced by the thousand by a couple dozen shipyards during World War II. Searle showed clearly that organizations get better at making ships as they accumulate experience, and the productivity gain of such learning-by-doing is enormous. His data was used in a more rigorous manner by researchers in the decades afterward, generally confirming the learning-by-doing and also showing that shipyards which stopped producing Liberty ships for a month or two very quickly saw their productivity plummet.

But rarely is the real world so clean. Peter Thompson, in this pair of papers (as well as a third published in the AER but discussed here), throws cold water on both the claim that organizations learn rapidly and that they forget just as rapidly. The problem is two fold. First, capital at the shipyards was assumed to be roughly constant. In fact, it was not. Almost all of the Liberty shipyards took some time to gear up their equipment when they began construction. Peter dug up some basic information on capital at each yard from deep in the national archives. Indeed, the terminal capital stock at each yard was three times the initial capital on average. Including a measure of capital in the equation estimating learning-by-doing reduces the importance of learning-by-doing by half.

It gets worse. Fractures were found frequently, accounting for more than 60% of ships built at the most sloppy yard. Speed was encouraged by contract, and hence some of the “learning-by-doing” may simply have been learning how to get away with low quality welding and other tricks. Thompson adjusts the time it took to build each ship to account for an estimate of the repair time required on average for each yard at each point in time. Fixing this measurement error further reduces productivity growth due to learning-by-doing by six percent. The upshot? Organizational learning is real, but the magnitudes everyone knows from the Searle data are vastly overstated. This matters: Bob Lucas, in his well-known East Asian growth miracle paper, notes that worldwide innovation, human capital and physical capital are not enough to account for sustained 6-7% growth like we saw in places like Korea in the 70s and 80s. He suggests that learning-by-doing as firms move up the export-goods quality ladder might account for such rapid growth. But such a growth miracle requires quite rapid on the job productivity increases. (The Lucas paper is also great historical reading: he notes that rapid growth in Korea and other tigers – in 1991, as rich as Mexico and Yugoslavia, what a miracle! – will continue, except, perhaps, in the sad case of Hong Kong!)

Thompson also investigates organizational forgetting. Old estimates using Liberty ship data find worker productivity on Liberty ships falling a full 25% per month when the workers were not building Liberty ships. Perhaps this is because the shipyards’ “institutional memory” was insufficient to transmit the tricks that had been learned, or because labor turnover meant good workers left in the interim period. The mystery of organizational forgetting in Liberty yards turns out to have a simpler explanation: measurement error. Yards would work on Liberty ships, then break for a few months to work on a special product or custom ship of some kind, then return to the Liberty. But actual production was not so discontinuous: some capital and labor transitioned (in a way not noticed before) back to the Liberty ships with delay. This appears in the data as decreased productivity right after a return to Liberty production, with rapid “learning” to get back to the frontier. Any estimate of such a nonlinear quantity is bound to be vague, but Peter’s specifications give organizational forgetting in Liberty ship production of 3-5% per month, and finds little evidence that this is related to labor turnover. This estimate is similar to other recent production line productivity forgetting estimates, such as that found in Benkard’s 2000 AER on the aircraft industry.

How Much did the Liberty Shipbuilders Learn? (final published version (IDEAS page). Final version published in JPE 109.1 2001.

How Much did the Liberty Shipbuilders Forget? (2005 working paper) (IDEAS page). Final paper in Management Science 53.6, 2007.

“When the Levee Breaks: Black Migration and Economic Development in the American South,” R. Hornbeck and S. Naidu (2012)

Going back at least to Marx, surplus labor particularly in the countryside has been considered the enemy of labor-saving technological progress. With boundless countryside labor, either because of force (serfdom, slavery, etc.) or other limited opportunities for migration, landowners can lack the incentive to adopt new labor-substituting technologies that they might otherwise adopt. This story anecdotally applies to the American South. From 1940 to 1970, a second “Great Migration” of African-Americans fled the South toward industrial cities in the North with high labor demand. Simultaneously, the South began adopting farming technology that had been much more common in the North and Midwest. These African-American workers were often part of a paternalistic relation with their employers which imposed relatively large moving costs on potential migrants before 1940. But is there any cause and effect here? Was the industrial boom in the heartland the cause of modernization in the South?

Naidu and Hornbeck (two of the best young economic historians in the world; more on this shortly) examine this by looking at the 1927 flood of the Mississippi river. During this flood, large number of black workers in the Delta were forced to move to Red Cross camps, where networks formed that led many of the workers to head to cities like Chicago; blatant abuse of the Red Cross system by white planters certainly served as an additional incentive. In the Delta, mule use as well as tractors for transportation of cotton to the gin was very limited.

Imagine that the cost of black labor increases, as happened during the flood due to the ease of labor moving North from the aid camps. In a simple model where black labor, white labor and capital are substitutes, the one-time increase in black wages increases capital use, decreases land value (due to the loss of exploitable black labor paid less than MP due to moving cost), and increases white labor (which was assumed to be part of a national labor market already). The authors examine this model using a difference-in-difference applied to counties which were flooded and other non-flooded counties in the Delta.

Flooded counties lost 14% of their black population after the flood. Flooded counties adopt mules and horses at a higher rate than non-flooded counties by 1930, and quickly replace these farm animals with tractors. The use of tractors causes average farm size to rise in flooded counties over the next 30 years; large average farm size, worldwide, is highly correlated with productive farming. Profits of one large landowner with accessible records sees no change in profits despite the modernization of inputs. There are many robustness checks, but overall this is a convincing case that the South modernized when labor costs were relieved from their artificially low pre-flood level.

August 2012 NBER Working Paper (IDEAS page)

(P.S.: If this type of work interests you, take a quick peek at some of the other work the coauthors have been doing. Hornbeck’s recent AER shows in great detail the slow economic adjustment to the Dust Bowl’s short-run effects, with great relevance to current climate change policy, and his 2010 QJE with Greenstone and Moretti which uses large industrial plant “contests” to study local knowledge spillovers is the state of the art on the question. Naidu has a forthcoming AER on how pseudo-slavery relations (roughly, labor contracts enforced in criminal courts in 19th century Britain) were used to smooth labor market risk, as well as a great 2011 paper showing clear-as-day evidence that someone aware of secret coup plotting in the US during the Cold War was using that knowledge to profit in the stock market. Naidu also does some cool evolutionary game theory work with the always-great Sam Bowles.)

“Why was it Europeans Who Conquered the World?,” P. Hoffman (2012)

Talk about an ambitious title! Take it as given that, by the eighteenth century, Europeans had a huge advantage in gunpowder-based technology and tactics, and that this was the primary reason they were able to colonize large swaths of the globe. Why was it that Europeans had such an advantage? The substance gunpowder did not originate in Europe, as is well-known. But Europeans did not even originate certain important tactics, like volley fire with layers of infantry. Nonetheless, from 1600-1800, weapons manufacturing productivity, firing rate, and naval firepower had all increased at an annual rate in Europe which far exceeded the rate of total economic growth or total productivity growth anywhere in the world up to that point. Why?

A common story is that competition in Europe was important. There were many small states who fought often, and hence better and better technology was selected. And Europeans were belligerent indeed! From 1500-1800, the Austrians were at war with a power 24% of the time, the English 53 percent, and the Spanish 81 percent of the time. The problem with the competition thesis, Hoffman points out, is that we have other similar entities: the Chinese were constantly fighting nomads in the north and west, the Japanese were in frequent warfare until the Tokagawa in 1600, and the small states of India were no peaceful assembly before the conquests of the British East India Company. So why, then, Europe?

Hoffman’s explanation is the following. Technology improves from learning by doing. It improves faster the more and the longer you practice, and disseminates easier when costs of dissemination are low. In war, then, gunpowder improves rapidly when countries fight, and when their fighting involves heavy expenditure. Countries go to war when the expected gain from fighting exceeds the expected cost (and they fight rather than settling immediately based on their expectations of the outcome because arbitrary transfers are not easy when the “prize” for winning is something like glory). Countries differ in their variable costs of war because of, for instance, differential abilities to extract tax revenue, and they differ in their benefits from winning war; Indian states may have, for example, had lower benefits from winning war because interdynastic conflict was frequent compared to Europe, and hence the winner of a war may have been sacked by his brother before even having a chance to bask in the glory of victory. Note that “death and destruction” was not a cost of war for most states in this period; indeed, from 1500-1790, not a single European monarch was deposed due to loss in battle in anything but a civil war! Shall we call this the original agency problem?

This model looks a lot like a micro theory tournament plus diffusion of inventions gained from learning by doing. Solve for the equilibrium, as Hoffman does, and you will see that rapid progress in arms technology requires that there is a lot of war using a lot of resources among combatants geographically close enough for technology to transfer easily, and conditions for that to happen are that countries for which gunpowder is effective in war are evenly matched in their ability to raise an army, and that the prize for winning (measured in glory or whatever) is high compared to the costs of battle (measured in the cost of raising revenue for an army, etc.). The Ottomans in this period had too little ability to raise revenue for war. The Chinese were unified internally and fought externally mostly with cavalry, since guns were not terribly effective against steppe nomads. Japan was unified by 1600, hence had no incentive to fight internally and improve their weapons technology, and the fixed cost of invading China or Korea was seen to be too high after some late 16th century adventures. In India, interdynastic battles were so frequent that the benefit of total warfare, as opposed to light skirmishes, was too limited, and hence even though war was frequent, it was at such a low level that there was limited learning-by-doing.

An interesting hypothesis. As invention is my own field of research, I am a bit skeptical of the learning-by-doing mechanism, however. Despite what schoolkids are taught, necessity is absolutely not the mother of invention. We need many things, but we only invent very few of them. Rather, technological feasibility tends to be the important constraint on technological improvement. My hunch is that a detailed investigation of specific microinventions in European military technology would show that they rely heavily on complementary developments in private industry, in scientific research, or in “common” engineering. Indeed, I would suspect that many of the important inventions come from places not known for their belligerence; Hoffman even mentions an important Swiss cannon foundry whose technology was critical to French artillery in the 1700s. Such importation from non-military external sources is not uncommon: later on, we have the American engineer Hiram Maxim inventing an early machine gun, and the Dutchman Fokker playing the most important role in airplane technology in World War I. The ability of the UK and Germany to procure these inventions has less to do with the frequency of war in those countries, but instead simply results from the fact that Western Europe and America had, by this time, developed large amounts of non-military engineering talent.

March 2012 working paper (no IDEAS version). This paper was published in the September 2012 issue of the Journal of Economic History. If you find it interesting, Hoffman recently published a book Why the West Rules – For Now which has come highly recommended to me by a well-known historian of this era. [CORRECTION: As noted by Mark Schaffer below, Why the West Rules is by Ian Morris, not Philip Hoffman. Nonetheless, it is still a great book!]

“Directed Technical Change,” D. Acemoglu (2002)

If I increase the supply of something, its price should go down. And if I decrease the supply, its price should rise. Some markets do not seem to follow this pattern, however, with skilled labor in the US since 1970 being a famous example. As the percentage of college-educated workers has risen the U.S., the premium paid to the college educated has also risen. How can this be? One hypothesis is skill-biased technical change: the innovation that has occurred over the past few decades, computers included, has been complementary with the skills of educated workers. When might we expect innovation to complement certain factors?

An old and incorrect answer, previously discussed on this site, is that innovation will replace “expensive” factors of production. If labor is dear, for instance, firms will try to invent machines to replace labor. This intuition is wrong: in competitive markets, all factors are paid their marginal products, so saying labor is “dear” is just like saying labor is productive. And you might imagine we’d want to develop innovations that are complementary to our most productive factors!

Daron Acemoglu has a nice paper from a few years back – already very highly cited – dealing with these issues. Take a good produced using two factors with a CES production function; that is, the way in which factors are substituted for one another does not depend on how much of each factor we are already using. Let each factor have its marginal productivity improve by technology multipliers A1 and A2, and let innovations (which increase A1 or A2) be developed in any structure where the amount of new innovation responds in the natural way to the social value created by improving the technology multiplier. Acemoglu uses a monopoly innovator, but broader assumptions here about how social value is captured will not change the basic point.

The social value of innovations in each factor are increasing in the price paid to the factor and the total quantity of that factor used. If one factor is, say, skilled labor, then my incentive to create innovations improving the productivity of skilled labor depends both on how much skilled labor will be used, and on how productive the marginal skilled labor already is (since my invention is a multiplier on the existing marginal product). Imagine now that I increase the relative supply of skilled labor, exogenously. Will I see more or less skilled labor-augmenting invention? On the one hand, there is more skilled labor, so I can sell my innovation to a bigger market, but on the other hand this extra labor has a lower marginal product, so there is less productivity to enhance. Which effect dominates? With CES production, there is a simple rule. If the two factors are gross substitutes, an increase in the relative supply of a factor will increase the incentive to develop innovations augmenting that factor, and vice versa for gross complements. That is, with gross substitutes, an increase in the supply of one factor will not affect the relative factor prices (read: relative marginal products) very much, so the effect of an increased amount of that factor which I can augment dominates the effect of lower marginal product on that factor.

In the short run, before innovations can be created, the now more abundant factor sees its rent (wage) decline. This is the usual substitution effect. But what about in the long run, after technology is created? Here we need to model explicitly the monopolists who create inventions. It turns out that if the elasticity of substitution between factors is sufficiently high, an exogenous increase in the relative supply of one factor will increase the rent received by that factor. That is, the long run factor demand curves will slope up! This is because when the factors are gross substitutes (the elasticity of substitution is at least 1), innovation will be directed toward the now more abundant factor. The higher the elasticity, the more innovation. At some point, there is so much productivity-enhancing innovation directed toward the more abundant factor that even though the marginal units of this factor were relatively unproductive without the innovation, and hence received a lower wage, the response by innovators will be high enough that the now-more-abundant factor is paid even more than it was before the exogenous supply increase. A quick aside: theoretically, the increased elasticity (though not the sign change) of long-run response vis-a-vis short-run response is well known. It is called the Le Chatelier Principle and comes to economics via Paul Samuelson. Milgrom and Roberts have a lovely paper on why Le Chatelier works. The three theorems in this paper are proof positive of the usefulness of monotone comparative statics. Topkis is used to prove a result in two lines that must have taken pages to prove, and in less generality, with earlier techniques.

Consider again the concrete example of skilled labor since 1970. Goods are produced with skilled and unskilled labor. The supply of skilled labor increases, due to the GI Bill and other exogenous factors. This causes the skill premium to fall initially. If the elasticity of substitution is above 2, the long run wage premium to skilled labor will increased due to the effect of incentives to develop technologies augmenting the now larger base of skilled labor. This is one explanation for why you may have seen skill-biased technological change after the 1960s, and why there may have been enough of it to raise the skill premium. (Note that the elasticity of substitution itself is fixed in this model, but you might imagine that certain types of innovations may affect this factor.)

Those interested in Acemoglu’s work may enjoy an empirical paper by a PhD student on the job market this year, Walker Hanlon, applying Acemoglu’s result to the context of the Cotton Crisis, the shift in Britain from using US to using Indian cotton during the US Civil War. He has some nice data showing that even though Indian cotton became relatively abundant, there was a great amount of invention dealing with gins and other techniques for handling idiosyncratic issues in the Indian supply, and that the elasticity of substitution between US and Indian cotton was high enough that, indeed, the relative price of Indian cotton to US cotton rose by the end of the Civil War despite the relative abundance of the Indian cotton.

Final REStud version, Oct 2002 (IDEAS)

“The Three Horsemen of Riches: Plague, War and Urbanization in Early Modern Europe,” N. Voigtlander & H.-J. Voth (2012)

Malthus was, broadly, right in his description of the world before 1800. Almost all income was agricultural income, and agricultural income was dependent largely on a fixed factor of production, land. As production technology became better (which happened at a very slow rate), wages increased, lowering death rates and increasing birth rates, which led to growing population. As population increased, less fertile land was brought into production, lowering per capita income. Per capita income fell until the birth-death ratio was again in steady state, with society at a higher level of population than before the new technology, but no richer overall.

This story is only broadly true, however. We do see regions diverge slightly: Europe becomes twice as rich as China by the 1700s, for instance. In a Malthusian world, how is this possible? Voigtlander and Voth propose an interesting new mechanism – their model is much more complicated than what I present here, but the spirit is the same.

Take as given that increased wages led to greater urbanization (people above subsistence have a taste for goods that can only be produced in cities), and that the Malthusian mechanism above holds, returning us to the subsistence steady state after shocks. Europe is rather unique in the following way: higher levels of urbanization there were quite deadly by world standards. Voigtlander and Voth mention three particular reasons why. First, European cities tended to both be filthy and high density. Human waste was often just tossed onto the street in Europe, whereas in China it was much more common to carry the waste to the countryside for use as fertilizer; partly for this reason, China had relatively high rural mortality, and Europe relatively high urban mortality. Second, geography and political circumstances in the early modern era meant that warfare was much more common in Europe than in other parts of the world. Wars of this era generally just meant increased death by disease rather than mass destruction of capital. Third, urban centers traded more, and common disease resistance across regions in Europe was not as prevalent as in China.

Think of this on a standard Malthusian graph. Putting quantity on the vertical axis and income on the horizontal axis, in the steady state equilibrium, the wage is determined by the intersection of a downward sloping death schedule (higher wages=less mortality) and an upward sloping birth schedule (higher wages=more births). A population shock hits: in this case, the Black Death kills an enormous percentage of Europe’s population beginning in the 1300s. Lower population means a temporarily higher wage in the Malthusian mechanism. The higher wage leads to greater urbanization. In Europe, but not in other regions experiencing negative population shocks, the greater urbanization leads to a higher death rate. That is, the death schedule shifts up and to the right. The new steady state intersection of the birth and death schedules that we return to is at a higher income than before the shock. So long-run incomes have increased following a temporary shock, even in the Malthusian world. A nice trick! Note also the counterintuitive nature of the result: Europe prospers in the centuries after the first plague precisely because of its violent, disease-ridden nature. That means you should be careful to interpret the results as explaining why incomes rose, not as arguing for any increase in welfare.

The authors also attempt to show, via a calibration exercise, how relatively important urbanization, disease spread from trade and disease/killing from war are in allowing Europe to grow. These type of exercises are not really for me, but check it out if you are interested – they assign most of the income gains in Europe to the effects of more frequent warfare made possible by taxing urban workers.

Dec. 2011 Working Paper (IDEAS)