Category Archives: Economic History

“International Trade and Institutional Change: Medieval Venice’s Response to Globalization,” D. Puga & D. Trefler

(Before discussing the paper today, I should forward a couple great remembrances of Stanley Reiter, who passed away this summer, by Michael Chwe (whose interests at the intersection of theory and history are close to my heart) and Rakesh Vohra. After leaving Stanford – Chwe mentions this was partly due to a nasty letter written by Reiter’s advisor Milton Friedman! – Reiter established an incredible theory group at Purdue which included Afriat, Vernon Smith and PhD students like Sonnenschein and Ledyard. He then moved to Northwestern where he helped build up the great group in MEDS which is too long to list, but which includes one Nobel winner already in Myerson and, by my reckoning, two more which are favorites to win the prize next Monday.

I wonder if we may be at the end of an era for topic-diverse theory departments. Business schools are all a bit worried about “Peak MBA”, and theorists are surely the first ones out the door when enrollment falls. Economic departments, journals and funders seem to have shifted, in the large, toward more empirical work, for better or worse. Our knowledge both of how economic and social interactions operate in their most platonic form, and our ability to interpret empirical results when considering novel or counterfactual policies, have greatly benefited by the theoretical developments following Samuelson and Hicks’ mathematization of primitives in the 1930s and 40s, and the development of modern game theory and mechanism design in the 1970s and 80s. Would that a new Cowles and a 21st century Reiter appear to help create a critical mass of theorists again!)

On to today’s paper, a really interesting theory-driven piece of economic history. Venice was one of the most important centers of Europe’s “commercial revolution” between the 10th and 15th century; anyone who read Marco Polo as a schoolkid knows of Venice’s prowess in long-distance trade. Among historians, Venice is also well-known for the inclusive political institutions that developed in the 12th century, and the rise of oligarchy following the “Serrata” at the end of the 13th century. The Serrata was followed by a gradual decrease in Venice’s power in long-distance trade and a shift toward manufacturing, including the Murano glass it is still famous for today. This is a fairly worrying history from our vantage point today: as the middle class grew wealthier, democratic forms of government and free markets did not follow. Indeed, quite the opposite: the oligarchs seized political power, and within a few decades of the serrata restricted access to the types of trade that previously drove wealth mobility. Explaining what happened here is both a challenge due to limited data, and of great importance given the public prominence of worries about the intersection of growing inequality and corruption of the levers of democracy.

Dan Trefler, an economic historian here at U. Toronto, and Diego Puga, an economist at CEMFI who has done some great work in economic geography, provide a great explanation of this history. Here’s the model. Venice begins with lots of low-wealth individuals, a small middle and upper class, and political power granted to anyone in the upper class. Parents in each dynasty can choose to follow a risky project – becoming a merchant in a long-distance trading mission a la Niccolo and Maffeo Polo – or work locally in a job with lower expected pay. Some of these low and middle class families will succeed on their trade mission and become middle and upper class in the next generation. Those with wealth can sponsor ships via the colleganza, a type of early joint-stock company with limited liability, and potentially join the upper class. Since long-distance trade is high variance, there is a lot of churn across classes. Those with political power also gather rents from their political office. As the number of wealthy rise in the 11th and 12th century, the returns to sponsoring ships falls due to competition across sponsors in the labor and export markets. At any point, the upper class can vote to restrict future entry into the political class by making political power hereditary. They need to include sufficiently many powerful people in this hereditary class or there will be a revolt. As the number of wealthy increase, eventually the wealthy find it worthwhile to restrict political power so they can keep political rents within their dynasty forever. Though political power is restricted, the economy is still free, and the number of wealthy without power continue to grow, lowering the return to wealth for those with political power due to competition in factor and product markets. At some point, the return is so low that it is worth risking revolt from the lower classes by restricting entry of non-nobles into lucrative industries. To prevent revolt, a portion of the middle classes are brought in to the hereditary political regime, such that the regime is powerful enough to halt a revolt. Under these new restrictions, lower classes stop engaging in long-distance trade and instead work in local industry. These outcomes can all be generated with a reasonable looking model of dynastic occupation choice.

What historical data would be consistent with this theoretical mechanism? We should expect lots of turnover in political power and wealth in the 10th through 13th centuries. We should find examples in the literature of families beginning as long-distance traders and rising to voyage sponsors and political agents. We should see a period of political autocracy develop, followed later by the expansion of hereditary political power and restrictions on lucrative industry entry to those with such power. Economic success based on being able to activate large amounts of capital from within the nobility class will make the importance of inter-family connections more important in the 14th and 15th centuries than before. Political power and participation in lucrative economic ventures will be limited to a smaller number of families after this political and economic closure than before. Those left out of the hereditary regime will shift to local agriculture and small-scale manufacturing.

Indeed, we see all of these outcomes in Venetian history. Trefler and Puga use some nice techniques to get around limited data availability. Since we don’t have data on family incomes, they use the correlation in eigenvector centrality within family marriage networks as a measure of the stability of the upper classes. They code colleganza records – a non-trivial task involving searching thousands of scanned documents for particular Latin phrases – to investigate how often new families appear in these records, and how concentration in the funding of long-distance trade changes over time. They show that all of the families with high eigenvector centrality in the noble marriage market after political closure – a measure of economic importance, remember – were families that were in the top quartile of seat-share in the pre-closure Venetian legislature, and that those families which had lots of political power pre-closure but little commercial success thereafter tended to be unsuccessful in marrying into lucrative alliances.

There is a lot more historical detail in the paper, but as a matter of theory useful to the present day, the Venetian experience ought throw cold water on the idea that political inclusiveness and economic development always form a virtuous circle. Institutions are endogenous, and changes in the nature of inequality within a society following economic development alter the potential for political and economic crackdowns to survive popular revolt.

Final published version in QJE 2014 (RePEc IDEAS). A big thumbs up to Diego for having the single best research website I have come across in five years of discussing papers in this blog. Every paper has an abstract, well-organized replication data, and a link to a locally-hosted version of the final published paper. You may know his paper with Nathan Nunn on how rugged terrain in Africa is associated with good economic outcomes today because slave traders like the infamous Tippu Tip couldn’t easily exploit mountainous areas, but it’s also worth checking out his really clever theoretical disambiguation of why firms in cities are more productive, as well as his crazy yet canonical satellite-based investigation of the causes of sprawl. There is a really cool graphic on the growth of U.S. sprawl at that last link!

“Organizing Venture Capital: The Rise and Demise of American Research and Development Corporation, 1946-1973,” D. Hsu & M. Kenney (2005)

Venture capital financing of innovative firms feels like a new phenomenon, and is clearly of great importance to high tech companies as well as cities that hope to attract these companies. The basic principle involves relatively small numbers of wealthy individuals providing long-term financing to a group of managers who seek out early-stage, unprofitable firms, make an investment (generally equity), and occasionally help actively manage the company.

There are many other ways firms can fund themselves: issuance of equity, investment from friends or family, investment from an existing firm in a spinoff, investment from the saved funds of an individual, or debt loans from a bank, among others. Two questions, then, are immediate: why does anyone fund with VC in the first place, and how did this institutional form come about? VC is strange at first glance: in a stage in which entrepreneur effort is particularly important, why would I write a financing contract which takes away some of the upside of working hard on the part of the entrepreneur by diluting her ownership share? Two things are worth noting. VC rather than debt finance is particularly common when returns are highly skewed – a bank loan can only be repaid with interest, hence will have trouble capturing that upside. Second, early-stage equity finance and active managerial assistance appear to come bundled, hence some finance folks have argued that the moral hazard problem lies both with the entrepreneur, who must be incentivized to work hard, and with the VC firm and their employees, who need the same incentive.

Let’s set aside the question of entrepreneurial finance, and look into history. Though something like venture capital appeared to be important in the Second Industrial Revolution (see, e.g., Lamoreaux et al (2006) on that hub of high-tech, Cleveland!), and it may have existed in a proto-form as early as the 1700s with the English country banks (though I am not totally convinced of that equivalence), the earliest modern VC firm was Boston’s American Research and Development Corporation. The decline of textiles hit New England hard in the 1920s and 1930s. A group of prominent blue bloods, including the President of MIT and the future founder of INSEAD, had discussed the social need for an organization that would fund firms which could potentially lead to new industries, and they believed that despite this social goal, the organization ought be a profit-making concern if it were to be successful in the long run.

After a few false starts, the ARD formed in 1946, a time of widespread belief in the power of R&D following World War II and Vannevar Bush’s famous “Science: the Endless Frontier”. ARD was organized as a closed-end investment trust, which permitted institutional investors to contribute. Investments tended to be solicited, were very likely to be made to New England firms, and were, especially in the first few years, concentrated in R&D intensive companies; local, solicited, R&D heavy investment is even today the most common type of VC. Management was often active, and there are reports of entire management teams being replaced by ARD if they felt the firm was not growing quickly enough.

So why have you never of ARD, then? Two reasons: returns, and organizational structure. ARD’s returns over the 50s and 60s were barely higher, even before fees, than the S&P 500 as a whole. And this overstates things: an investment in Digital Equipment, the pioneering minicomputer company, was responsible for the vast majority of profits. No surprise, then, that even early VCs had highly skewed returns. More problematic was competition. A 1958 law permitted Small Business Investment Corporations (SBICs) to make VC-style investments at favorable tax rates, and the organizational form of limited partnership VC was less constrained by the SEC than a closed-end investment fund. In particular, the partnerships “2 and 20″ structure meant that top investment managers could earn much more money at that type of firm than at ARD. One investment manager at ARD put a huge amount of effort into developing a company called Optical Scanning, whose IPO made the founder $10 million. The ARD employee, partially because of SEC regulations, earned a $2000 bonus. By 1973, ARD had been absorbed into another company, and was for all practical purposes defunct.

It’s particularly interesting, though, that the Boston Brahmins were right: VC has been critical in two straight resurgences in the New England economy, the minicomputer cluster of the 1960s, and the more recent Route 128 biotech cluster, both of which were the world’s largest. New England, despite the collapse of textiles, has not gone the way of the rust belt – were it a country, it would be wealthier per capita than all but a couple of microstates. And yet, ARD as a profitmaking enterprise went kaput rather quickly. Yet more evidence of the danger of being a market leader – not only can other firms avoid your mistakes, but they can also take advantage of more advantageous organizational forms and laws that are permitted or created in response to your early success!

Final published version, in Industrial and Corporate Change 2005 (RePEc IDEAS).

“The Rise and Fall of General Laws of Capitalism,” D. Acemoglu & J. Robinson (2014)

If there is one general economic law, it is that every economist worth their salt is obligated to put out twenty pages responding to Piketty’s Capital. An essay by Acemoglu and Robinson on this topic, though, is certainly worth reading. They present three particularly compelling arguments. First, in a series of appendices, they follow Debraj Ray, Krusell and Smith and others in trying to clarify exactly what Piketty is trying to say, theoretically. Second, they show that it is basically impossible to find any effect of the famed r-g on top inequality in statistical data. Third, they claim that institutional features are much more relevant to the impact of economic changes on societal outcomes, using South Africa and Sweden as examples. Let’s tackle these in turn.

First, the theory. It has been noted before that Piketty is, despite beginning his career as a very capable economist theorist (hired at MIT at age 22!), very disdainful of the prominence of theory. He, quite correctly, points out that we don’t even have any descriptive data on a huge number of topics of economic interest, inequality being principal among these. And indeed he is correct! But, shades of the Methodenstreit, he then goes on to ignore theory where it is most useful, in helping to understand, and extrapolate from, his wonderful data. It turns out that even in simple growth models, not only is it untrue that r>g necessarily holds, but the endogeneity of r and our standard estimates of the elasticity of substitution between labor and capital do not at all imply that capital-to-income ratios will continue to grow (see Matt Rognlie on this point). Further, Acemoglu and Robinson show that even relatively minor movement between classes is sufficient to keep the capital share from skyrocketing. Do not skip the appendices to A and R’s paper – these are what should have been included in the original Piketty book!

Second, the data. Acemoglu and Robinson point out, and it really is odd, that despite the claims of “fundamental laws of capitalism”, there is no formal statistical investigation of these laws in Piketty’s book. A and R look at data on growth rates, top inequality and the rate of return (either on government bonds, or on a computed economy-wide marginal return on capital), and find that, if anything, as r-g grows, top inequality shrinks. All of the data is post WW2, so there is no Great Depression or World War confounding things. How could this be?

The answer lies in the feedback between inequality and the economy. As inequality grows, political pressures change, the endogenous development and diffusion of technology changes, the relative use of capital and labor change, and so on. These effects, in the long run, dominate any “fundamental law” like r>g, even if such a law were theoretically supported. For instance, Sweden and South Africa have very similar patterns of top 1% inequality over the twentieth century: very high at the start, then falling in mid-century, and rising again recently. But the causes are totally different: in Sweden’s case, labor unrest led to a new political equilibrium with a high-growth welfare state. In South Africa’s case, the “poor white” supporters of Apartheid led to compressed wages at the top despite growing black-white inequality until 1994. So where are we left? The traditional explanations for inequality changes: technology and politics. And even without r>g, these issues are complex and interesting enough – what could be a more interesting economic problem for an American economist than diagnosing the stagnant incomes of Americans over the past 40 years?

August 2014 working paper (No IDEAS version yet). Incidentally, I have a little tracker on my web browser that lets me know when certain pages are updated. Having such a tracker follow Acemoglu’s working papers pages is, frankly, depressing – how does he write so many papers in such a short amount of time?

“Immigration and the Diffusion of Technology: The Huguenot Diaspora in Prussia,” E. Hornung (2014)

Is immigration good for natives of the recipient country? This is a tough question to answer, particularly once we think about the short versus long run. Large-scale immigration might have bad short-run effects simply because more L plus fixed K means lower average incomes in essentially any economic specification, but even given that fact, immigrants bring with them tacit knowledge of techniques, ideas, and plans which might be relatively uncommon in the recipient country. Indeed, world history is filled with wise leaders who imported foreigners, occasionally by force, in order to access their knowledge. As that knowledge spreads among the domestic population, productivity increases and immigrants are in the long-run a net positive for native incomes.

How substantial can those long-run benefits be? History provides a nice experiment, described by Erik Hornung in a just-published paper. The Huguenots, French protestants, were largely expelled from France after the Edict of Nantes was revoked by the Sun King, Louis XIV. The Huguenots were generally in the skilled trades, and their expulsion to the UK, the Netherlands and modern Germany (primarily) led to a great deal of tacit technology transfer. And, no surprise, in the late 17th century, there was very little knowledge transfer aside from face-to-face contact.

In particular, Frederick William, Grand Elector of Brandenburg, offered his estates as refuge for the fleeing Huguenots. Much of his land had been depopulated in the plagues that followed the Thirty Years’ War. The centralized textile production facilities sponsored by nobles and run by Huguenots soon after the Huguenots arrived tended to fail quickly – there simply wasn’t enough demand in a place as poor as Prussia. Nonetheless, a contemporary mentions 46 professions brought to Prussia by the Huguenots, as well as new techniques in silk production, dyeing fabrics and cotton printing. When the initial factories failed, knowledge among the apprentices hired and purchased capital remained. Technology transfer to natives became more common as later generations integrated more tightly with natives, moving out of Huguenot settlements and intermarrying.

What’s particularly interesting with this history is that the quantitative importance of such technology transfer can be measured. In 1802, incredibly, the Prussians had a census of manufactories, or factories producing stock for a wide region, including capital and worker input data. Also, all immigrants were required to register yearly, and include their profession, in 18th century censuses. Further, Huguenots did not simply move to places with existing textile industries where their skills were most needed; indeed, they tended to be placed by the Prussians in areas which had suffered large population losses following the Thirty Years’ War. These population losses were highly localized (and don’t worry, before using population loss as an IV, Hornung makes sure that population loss from plague is not simply tracing out existing transportation highways). Using input data to estimate a Cobb-Douglas textile production function, an additional percentage point of the population with Huguenot origins in 1700 is associated with a 1.5 percentage point increase in textile productivity in 1800. This result is robust in the IV regression using wartime population loss to proxy for the percentage of Huguenot immigrants, as well as many other robustness checks. 1.5% is huge given the slow rate of growth in this era.

An interesting historical case. It is not obvious to me how relevant this estimation to modern immigration debates; clearly it must depend on the extent to which knowledge can be written down or communicated at distance. I would posit that the strong complementarity of factors of production (including VC funding, etc.) are much more important that tacit knowledge spread in modern agglomeration economies of scale, but that is surely a very difficult claim to investigate empirically using modern data.

2011 Working Paper (IDEAS version). Final paper published in the January 2014 AER.

“Information Frictions and the Law of One Price,” C. Steinwender (2014)

Well, I suppose there is no surprise that I really enjoyed this paper by Claudia Steinwender, a PhD candidate from LSE. The paper’s characteristics are basically my catnip: one of the great inventions in history, a policy question relevant to the present day, and a nice model to explain what is going on. The question she asks is how informational differences affect the welfare gains from trade. In the present day, the topic comes up over and over again, from the importance of cell phones to village farmers to the welfare impact of public versus closed financial exchanges.

Steinwender examines the completion of the transatlantic telegraph in July 1866. A number of attempts over a decade had been made in constructing this link; the fact that the 1866 line was stable was something of a surprise. Its completion lowered the time necessary to transmit information about local cotton prices in New York (from which much of the supply was sent) and Liverpool (where much of the cotton was bought; see Chapter 15 of Das Kapital for a nice empirical description of the cotton industry at this time). Before the telegraph, steam ships took 7 to 21 days, depending on weather conditions, to traverse the Pond. In a reduced form estimate, the mean price difference in each port, and the volatility of the price difference, fell; price shocks in Liverpool saw immediate responses in shipments from America, and the prices there; exports increases and become more volatile; and similar effects were seen from shocks to ship speed before the telegraph, or temporary technical problems with the line after July 1866. These facts come from amazingly well documented data in New York and UK newspapers.

Those facts are all well and good, but how to explain them, and how to interpret them? It is not at all obvious that information in trade with a durable good should matter. If you ship too much one day, then just store it and ship less in the next period, right? But note the reduced form evidence: it is not just that prices harmonize, but that total shipments increase. What is going on? Without the telegraph, the expected price tomorrow in Liverpool from the perspective of New York sellers is less variable (the conditional expectation conditions on less information about the underlying demand shock, since only the two-week-old autocorrelated demand shock data brought by steamship is available). When high demand in Liverpool is underestimated, then, exports are lower in the era before the telegraph. On the other hand, a low demand shock and a very low demand shock in Liverpool both lead to zero exports, since exporting is unprofitable. Hence, ignoring storage, better information increases the variance of perceived demand, with asymmetric effects from high and low demand shocks, leading to higher overall exports. Storage should moderate the volatility of exports, but not entirely, since a period of many consecutive high demand shocks will eventually exhaust the storage in Liverpool. That is, the lower bound on stored cotton at zero means that even optimal cotton storage does not fully harmonize prices in the presence of information frictions.

Steinwender confirms that intuition by solving for the equilibrium with storage numerically; this is actually a pretty gutsy move, since the numerical estimates are quantitatively quite different than what was observed in the data. Nonetheless, I think she is correct that we are fine interpreting these as qualitative comparative statics from an abstract model rather than trying to interpret their magnitude in any way. (Although I should note, it is not clear to me that we cannot sign the relevant comparative statics just because the model with storage cannot be solved analytically in its entirety…)

The welfare impact of information frictions with storage can be bounded below in a very simple way. If demand is overestimated in New York, then too much is exported, and though some of this cotton is stored, the lower bound at zero for storage means that the price in Liverpool is still too high. If demand in underestimated in New York, then too little is exported, and though some stored cotton might be sold, the lower bound on storage means that the price in Liverpool is still too low. A lower bound on the deadweight loss from those effects can be computed simply by knowing the price difference between the UK and the US and the slopes of the demand and supply curves; in the case of the telegraph, this deadweight loss is on the order of 8% of the value of US cotton exports to the UK, or equivalent to the DWL from a 6% tax on cotton. That is large. I am curious about the impact of this telegraph on US vis-a-vis Indian or Egyptian cotton imports, the main Civil War substitutes; information differences must distort the direction of trade in addition to its magnitude.

January 2014 working paper (No IDEAS version).

Tunzelmann and the Nature of Social Savings from Steam

Research Policy, the premier journal for innovation economists, recently produced a symposium on the work of Nick von Tunzelmann. Tunzelmann is best known for exploring the social value of the invention of steam power. Many historians had previously granted great importance to the steam engine as a driver of the Industrial Revolution. However, as with Fogel’s argument that the railroad was less important to the American economy than previously believed (though see Donaldson and Hornbeck’s amendment claiming that market access changes due to rail were very important), the role of steam in the Industrial Revolution may have been overstated.

This is surprising. To my mind, the four most important facts for economics to explain is why the world economy (in per capita terms) stagnated until the early 1800s, why cumulative per-capita growth began then in a corner of Northwest Europe, why growth at the frontier has continued to the present, and why growth at the frontier has been so consistent over this period. The consistency is really surprising, given that individual non-frontier country growth rates, and World GDP growth, has vacillated pretty wildly on a decade-by-decade basis.

Malthus’ explanation still explains the first puzzle best. But there remain many competing explanations for how exactly the Malthusian trap was broken. The idea that a thrifty culture or expropriation of colonies was critical sees little support from economic historians; as McCloskey writes, “Thrifty self-discipline and violent expropriation have been too common in human history to explain a revolution utterly unprecedented in scale and unique to Europe around 1800.” The problem, more generally, of explaining a large economic X on the basis of some invention/program/institution Y is that basically everything in the economic world is a complement. Human capital absent good institutions has little value, modern management techniques absent large markets is ineffective, etc. The problem is tougher when it comes to inventions. Most “inventions” that you know of have very little immediate commercial importance, and a fair ex-post reckoning of the critical parts of the eventual commercial product often leaves little role for the famous inventor.

What Tunzelmann and later writers in his tradition point out is that even though Watt’s improvement to the steam engine was patented in 1769, steam produces less horsepower than water in the UK as late as 1830, and in the US as late as the Civil War. Indeed, even today, hydropower based on the age-old idea of the turbine is still an enormous factor in the siting of electricity-hungry industries. It wasn’t until the invention of high-pressure steam engines like the Lancanshire boiler in the 1840s that textile mills really saw steam power as an economically viable source of energy. Most of the important inventions in the textile industry were designed originally for non-steam power sources.

The economic historian Nicholas Crafts supports Tunzelmann’s original argument against the importance of steam using a modern growth accounting framework. Although the cost of steam power fell rapidly following Watt, and especially after the Corliss engine in the mid 19th century, steam was still a relatively small part of economy until the mid-late 19th century. Therefore, even though productivity growth within steam was quick, only a tiny portion of overall TFP growth in the early Industrial Revolution can be explained by steam. Growth accounting exercises have a nice benefit over partial equilibrium social savings calculations because the problem that “everything is a complement” is taken care of so long as you believe the Cobb-Douglas formulation.

The December 2013 issue of Research Policy (all gated) is the symposium on Tunzelmann. For some reason, Tunzelmann’s “Steam Power and British Industrialization Until 1860″ is quite expensive used, but any decent library should have a copy.

“The ‘Industrial Revolution’ in the Home: Household Technology and Social Change in the 20th Century,” R. S. Cowan (1976)

The really fascinating thing about the “Second Industrial Revolution” (roughly 1870 until World War I) is how much of its effect is seen first for consumers and only later for production. Electricity is the famous example here; most energy-heavy industries were purposefully located near low-cost energy sources like fast-flowing water. Energy produced via transmitted electricity simply wasn’t that competitive until well into the 20th century in these industries.

Ruth Cowan, a historian, investigated how household production was affected by the introduction of electricity, which in the non-rural US roughly means between 1918 and the Great Depression; electrification rose from 25 percent to 80 percent during this period. Huge amounts of drudgery, once left to housewives and domestic workers, was reduced. Consider the task of ironing. Before electricity (barring gas irons, which were not widespread), ironing involved heating a heavy flatiron on a stove, carrying it to the ironing board and quickly knocking out wrinkles before the heat dissipated, bringing in back to stove, and so on. The replacement of the coal stove by central heating similarly limited tedious work, including constant cleaning of coal dust. Cowan traces diffusion of these technologies in part by examining advertisements in magazines like the Ladies’ Home Journal.

The interesting aspect of this consumer revolution, however, was that it did not in fact reduce the amount of work done by housewives. By the end of the 1920s, urban women, most affected by these technological changes, were still doing more housework per week than rural women. It appears the standard story of how Industrial Revolution technologies affected industry – more specialization, more importance of managerial talent, disappearing emotional content of work – was not true of household production. Instead, upper middle class women no longer employed specialized domestic help (and the implied importance of managerial talent on the part of the housewife), and advertisements for new consumer goods frequently emphasized the emotional content of, e.g., the improved cleanliness of modern appliances with respect to children’s health. Indeed, technological progress tended to significantly increase the number of tasks women were expected to perform within the house. There’s not much reason in economic theory for TFP improvements to lead to reductions or increases in worker skill or autonomy, so perhaps it’s no surprise that the household sector saw a different pattern from certain industrial sectors.

Final version in Technology & Culture Jan 1976. If you’re not familiar with the term “Second Industrial Revolution”, Joel Mokyr has a nice summary of this period of frequent important macro/GPT inventions. Essentially, the big inventions of the late 19th century were much more reliant on scientific knowledge, and much more connected to network effects and increasing returns to scale, than those of the late 18th and early 19th century.

“Technology and Learning by Factory Workers: The Stretch-Out at Lowell, 1842,” J. Bessen (2003)

This is a wonderful piece of theory-driven economic history. Everyone knows that machinery in the Industrial Revolution was “de-skilling”, replacing craft workers with rote machine work. Bessen suggests, using data from mid-19th century mills in New England, that this may not be the case; capital is expensive and sloppy work can cause it to be out of service, so you may want to train your workers even more heavily as you deepen capital. It turns out that it is true that literate Yankee girls were largely replaced by illiterate, generally Irish workers (my ancestors included!) at Lowell and Waltham, while simultaneously the amount of time spend training (off of piece-wages) increased as did the number of looms run by each worker. How can we account for this?

Two traditional stories – that history is driven by the great inventor, or that the mill-owners were driven by philanthropy – are quickly demolished. The shift to more looms per worker was not the result of some new technology. Indeed, adoption of the more rigorous process spread slowly to Britain and southern New England. As for philanthropy, an economic model of human capital acquisition shows that the firms appear to have shifted toward unskilled workers for profit-based reasons.

Here’s the basic idea. If I hire literate workers like the Yankee farm girls, I can better select high-quality workers, but these workers will generally return home to marry after a short tenure. If I hire illiterate workers, their initial productivity is lower but, having their family in the mill town, they are less likely to leave the town. Mill owners had a number of local methods to collude and earn rents, hence they have some margin to pay for training. Which type should I prefer? If there exist many trained illiterate workers in town already, I just hire them. If not, the higher the ratio of wage to cloth price, the more I am willing to invest in training; training takes time during which no cloth is made, but increases future productivity at any given wage.

Looking at the Massachusetts mill data, a structural regression suggests that almost all of the increase in labor productivity between 1834 and 1855 was the result of increasing effective worker experience, a measure of industry-specific human capital (and note that a result of this kind is impossible without some sort of structural model). Why didn’t firms move to illiterate workers with more training earlier? Initially, there was no workforce that was both skilled and stable. With cloth prices relatively high compared to wages, it was initially (as can be seen in Bessen’s pro forma calculation) much more profitable to use a labor system that tries to select high quality workers even though they leave quickly. Depressed demand in the late 1830s led cloth prices to fall, which narrowed the relative profitability of well-trained but stable illiterate workers as compared to the skilled but unstable farm girls. A few firms began hiring illiterate workers and training them (presumably selecting high quality illiterate workers based on modern-day unobservables). This slowly increased the supply of trained illiterate workers, making it more profitable to switch a given factory floor over to three or four looms per worker, rather than two. By the 1850s, there was a sufficiently large base of trained illiterate workers to make them more profitable than the farm girls. Some light counterfactual calculations suggest that pure profit incentive is enough to drive the entire shift.

What is interesting is that the shift to what was ex-post a far more productive system appears to hinge critically on social factors – changes in the nature of the local labor supply, changes in demand for downstream products, etc. – rather than on technological change embodied in new inventions or managerial techniques. An important lesson to keep in mind, as nothing in the above story had any Whiggish bias toward increasing productivity!

Final working paper (IDEAS version). Final paper published in the Journal of Economic History, 2003. I’m a big fan of Bessen’s work, so I’m sure I’ve mentioned before on this site the most fascinating part of his CV: he has no graduate degree of any kind, yet has a faculty position at a great law school and an incredible publication record in economics, notably his 2009 paper on socially inefficient patents with Eric Maskin. Pretty amazing!

“Inventors, Patents and Inventing Activities in the English Brewing Industry, 1634-1850,” A. Nuvolari & J. Sumner (2013)

Policymakers often assume that patents are necessary for inventions to be produced or, if the politician is sophisticated, for a market in knowledge to develop. Economists are skeptical of such claims, for theoretical and empirical reasons. For example, Petra Moser has shown how few important inventions are ever patented, and Bessen and Maskin have a paper showing how the existence of patents can slow down innovation in certain technical industries. The literature more generally often mentions how heterogeneous appropriation strategies are across industries: some rely entirely on trade secrets, other on open source sharing, and yet others on patent protection.

Nuvolari and Sumner look at the English brewing industry from the 17th to the 19th century. This industry was actually quite innovative, most famously through the (perhaps collective) invention of that delightful winter friend named English Porter. The two look in great detail through lists of patents prior to 1850, and note that, despite the importance of brewing and its technical complexity, beer-related patents make up less than one percent of all patents granted during that period. Further, they note that there are enormous differences in patenting behavior within the brewing industry. Nonetheless, even in the absence of patents, there still existed a market for ideas.

Delving deeper, the authors show that many patentees were seen more as charlatans than as serious inventors. The most important inventors tended to either keep their inventions secret within their firm or guild, keep the inventions partially secret, publicize completely in order to enhance the status of their brewery as “scientific”, or publicize completely in order to garner consulting or engineering contracts. The partial secrecy and status-enhancing publicity reasons are particularly interesting. Humphrey Jackson, an aspiring chemist, sold a book with many technical details left as blank spots; by paying to attend his lecture, the details of his processes could be filled in, though the existence of the lecture was predicated on sufficiently large numbers buying the book! James Bavestock, a brewer in Hampshire, brought his hydrometer to the attention of a prominent London brewer Henry Thrale; in exchange, Thrale could organize entry into the London market, or a job in Thrale’s brewery should the small Hampshire concern go under.

2012 Working Paper (IDEAS version). This article appeared in the new issue of Business History Review, which was particularly good; it also featured, among others, a review on markets for knowledge in 19th century America which will probably be the final publication of the late Kenneth Sokoloff, and a paper by the always interesting Zorina Khan on international technology markets in the 19th century. Many current issues, such as open source, patent trolls, etc. are completely rehashing similar questions during that period, so the articles are well worth a look even for the non-historian.

“Without Consent or Contract,” R. W. Fogel (1989)

Word comes that Bob Fogel, an absolute giant in economic history and a Nobel Prize winner, passed away today. I first encountered Fogel in a class a decade or so ago taught by Robert Margo, another legendary scholar of the economics of American history.

Fogel’s most famous contribution is summarized in the foreword to the very readable Without Consent or Contract. “Although the slave system was horribly retrogressive in its social, political, and ideological aspects, it was quite advanced by the standards of the time in its technology and economic organization. The paradox is only apparent…because the paradox rests on the widely held assumption that technological efficiency is inherently good. It is this beguiling assumption that is false and, when applied to slavery, insidious.”

Roughly, it was political change alone, not economic change, which could have led to the end of slavery in America. The plantation system was, in fact, a fairly efficient system in the economic sense, and was not in danger of petering out on its own accord. Evidence on this point was laid out in technical detail in Fogel and Engerman’s “Time on the Cross”. In that text, evidence from an enormous number of sources is brought to bear on the value of a slave over time; McCloskey has called Fogel “a carpenter of history…measure, measure again, measure again.” The idea that the economic effects of history can be (and are) wildly different from the moral or political effects remains misunderstood; Melissa Dell’s wonderful paper on the Peruvian mita is a great example of a terrible social policy which nonetheless had positive long-run economic effects. As historians disdain “Whig history”, the idea that things improve as time marches on, economists ought disdain “Whig economics”, the idea that growth-inducing policies are somehow linked to moral ones.

There is much beyond the slavery research, of course. In one of the most famous papers in economic history, Fogel studied the contribution of the railroad to American economic growth (Google has this at only 86 citations; how is such a low number possible?). He notes that, as economists, we should care about the marginal benefit, not the absolute benefit, of the railroad. In the absence of rail, steamboats and canals were still possible (and would likely have been built in the midwest). He famously claims that the US would have reached its income in January 1890 by the end of March 1890 had there been no rail at all, a statement very much contrary to traditional historical thinking.

Fogel’s later life was largely devoted to his project on the importance of improved nutrition and its interaction with economic growth, particularly since the 1700s. If you’ve not seen these statistics, it is amazing just how short and skinny the average human was before the modern era. There has been an enormous debate over the relative role of nutrition, vis-a-vis technologies, knowledge like germ theory, or embodied or diffused knowledge, in the increased stature of man: Angus Deaton summarizes the literature nicely. In particular, my read is that the thesis whereby better nutrition causes a great rise in human incomes is on fairly shaky ground, though the debate is by no means settled.

Amazon has Without Consent or Contract for sale for under 15 bucks, well worth it. Some quick notes: Fogel was by no means a lone voice in cliometrics; for example, Conrad and Meyer in a 1958 JPE make very much the same point as Fogel concerning the economic success of slavery, using tools from capital theory in the argument. Concerning the railroad, modern work suggests Fogel may have understated its importance. Donaldson and Hornbeck, two of the best young economic historians in the world, use some developments in modern trade theory to argue that increased market access due to rail, measured as market access is capitalized into farmland, was far more important to GDP growth than Fogel suggested.

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