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

I’ve had a few posts in the past few months (here and here) about the consequences of mechanization for the future of work. In short, what will we do when the robots take our jobs?

I wouldn’t call myself a techno-optimist. I don’t think the arrival of robots necessarily makes everything better. But I do not buy the strong techno-pessimism that comes up in many places. Richard Serlin has been a frequent commenter on this blog, and he generally has a gloomy take on where we are going to end up once the robots arrive. I’m not bringing up Richard to pick on him. He writes thoughtful comments on this subject (and lots of others), and it is those comments that pushed me to try and be more clear on why I’m “techno-neutral”.

The economy is more creative than we can imagine. The coming of robots to mechanize away our jobs is the latest in a long, long, long, history of technology replacing workers. And yet here we still are, working away. Timothy Taylor posted this great selection a few weeks ago. This is a quote from Time Magazine:

The rise in unemployment has raised some new alarms around an old scare word: automation. How much has the rapid spread of technological change contributed to the current high of 5,400,000 out of work? … While no one has yet sorted out the jobs lost because of the overall drop in business from those lost through automation and other technological changes, many a labor expert tends to put much of the blame on automation. … Dr. Russell Ackoff, a Case Institute expert on business problems, feels that automation is reaching into so many fields so fast that it has become “the nation’s second most important problem.” (First: peace.)
The number of jobs lost to more efficient machines is only part of the problem. What worries many job experts more is that automation may prevent the economy from creating enough new jobs. … Throughout industry, the trend has been to bigger production with a smaller work force. … Many of the losses in factory jobs have been countered by an increase in the service industries or in office jobs. But automation is beginning to move in and eliminate office jobs too. … In the past, new industries hired far more people than those they put out of business. But this is not true of many of today’s new industries. … Today’s new industries have comparatively few jobs for the unskilled or semiskilled, just the class of workers whose jobs are being eliminated by automation.

That quote is from 1961. This is almost word for word the argument you will get about robots and automation leading to mass unemployment in the future. 50 years ago we were just as worried about this kind of thing, and in those 50 years we do not have massive armies of unemployed workers wandering the streets. The employment/population ratio in 1961 was about 55%, and then it steadily rose until the late 90’s when it topped out at about 64%. Even after the Great Recession, the ratio is still 59% today, higher than it was in 1961.

This didn’t happen without disruption and dislocation. And the robots will cause similar dislocation and disruption. Luddites weren’t wrong about losing their jobs, they were just wrong about the economy losing jobs in aggregate. But I don’t see why next-generation robots are any different than industrial robots, mainframes, PC’s, tractors, mechanical looms, or any other of the ten million innovations made in history that replaced labor. We can handle this with some sympathy and try to smooth things out for those dislocated, or we can do what usually happens and let them hang out to dry. The robots aren’t the problem here, we are.

What exactly are those new jobs that will be created? If I knew, then I wouldn’t be writing this blog post, I’d be out starting a company. The fact that I cannot conceive of an innovation myself is not evidence that innovation has ceased. But I do believe in the law of large numbers, and somewhere among the 300-odd million Americans is someone who *is* thinking of a new kind of company with new kinds of jobs.

Robots change prices as well as wages. An argument for pessimism goes like this. People have subsistence requirements, meaning they have a wage floor below which they cannot survive. Robots will be able to replace humans in production and this will drive the wage below that subsistence requirement. Either no firm will hire workers at the subsistence wage or people who do work will not meet subsistence.

The problem with this argument is that it ignores the impact of robots on the price of that subsistence requirement. Subsistence requirements are in real terms (I need clothes and housing and food), not nominal terms (I need $2000 dollars). The “subsistence wage” is a a real wage, meaning it is the nominal wage divided by the price level of a subsistence basket of goods. Robots lowering marginal costs of production lowers the nominal human wage, but it also lowers the price of goods. It is not necessary or even obvious that real wages have to fall because of robots. History says that despite all of the labor-saving technological change that has gone on over the last few hundred years, real wages have risen as the lower costs outweigh the downward pressure on wages.

Who is going to buy what the robots produce? Call this the “Henry Ford” argument. If you are going to invest in opening up a factory staffed entirely by robots, then who precisely is supposed to buy that output? Ford raised wages at his highly mechanized (for the time) plants so that he had a ready-made market for his cars. The Henry Fords of robot factories are going to need a market for the stuff they build. Rich people are great, but diminishing marginal utility sets in pretty quick. That means robot owners either need to lower prices or raise wages for the people they do hire in order to generate a big enough market. Depending on the fixed costs involved in getting these proverbial robot factories up and running, robot owners may be a strong force for keeping wages high in the economy, just like Henry Ford was back in the day.

The wealthy are wealthy because they own productive assets. A tiny fraction of the value of those assets is due to the utility to the owner of the widgets they kick out. The majority of the value of those assets is due to the fact that you can *sell* that output for money and use that money to buy other widgets. Rockefeller wasn’t wealthy because he had a lot of oil. He was wealthy because he could sell it to other people. No other people, no wealth. Just barrel after barrel of useless black gunk.

The same holds for robot owners. Those robots and robot factories have value because you can sell them or the goods they make in the wider economy. And that means continuing to exchange with the non-wealthy. You cannot be wealthy in a vacuum. Bill Gates on an island with robots and a stack of 16 billion dollar bills is Gilligan with a lot of kindling.

Wealthy robot owners will do what wealthy (fill in capital stock here) owners have done for eons. They’ll trade access to the capital, or the goods it produces, to the non-wealthy in exchange for services, effort, flattery, and new ideas on what to do with that wealth.

Wealth concentration would be a problem with or without robots. The worry here is that because the wealthy will be the only ones able to build the robots and robot factories, they will control completely the production of goods and the demand for labor. That’s not a problem that arises with robots, that is a problem that arises with, well, settled agriculture 10,000 years ago. Wealth concentration makes owners both monopolists (market power selling goods) and monopsonists (market power buying labor), which is a bad combination. It gives them the ability to drive (real) wages down to minimum subsistence levels. This is bad, absolutely. But this was bad when (fill in example of a landed elite) did it in (fill in historical era here). This is bad in “company towns”. This is bad now, today. So if you want to argue against wealth concentration and the pernicious influence it has on wages, get started. Don’t wait for the robots, they’ve got nothing to do with it.

Again, be clear that in arguing against techno-pessimism I am not arguing that robots will generate a techno-utopia with ponies and rainbows. I just do not buy the dystopian view that somehow it’s all going to come crashing down around our ears because of the very particular innovations coming in the near future.

Market Failures in Developing Countries

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

I just came across a new World Bank paper by Brian Dillon and Chris Barrett about agricultural factor markets in Africa. Dillon and Barrett have written an “old school” development paper, meaning it reminds me of papers written in the 1980’s and 1990’s. They use observational data, and appeal to theory to motivate their empirical identification in an attempt to answer a classic development question. (This is going to be really distressing nomenclature to the development economists from that era, who were “new-school” when the field moved beyond the “old school” work by Lewis, Schultz, and others from the 1960’s and 1970’s. Sucks to grow up, I guess.)

They test for “household separation”, which means that the consumption decisions of a household (i.e. how much or what to eat) are completely divorced from the production decisions (i.e. how much or what to plant). If there are complete markets, then household separation is expected to hold. If you live in a modern Western country then you face effectively complete markets, and your decision about what to consume (a new TV!) is completely unaffected by what you do at work (accounts payable!). All that matters is that you make money producing, and then you spend that money on goods and services.

If markets are missing completely, or so unreliable as to effectively be missing, then household separation fails. The extreme case is easiest to think of. If a household is completely autarkic, and can trade with no one else, then it can only consume what it produces. The two decisions are inseparable. If they want a new TV, then they’d better have a source of rare earth elements in their back yard and a passion for soldering.

The importance of knowing if household separation holds or not is that it tells us something fundamentally important about why a developing area is poor. If separation fails because markets fail to exist, then this is like saying there is a lot of latent economic activity that is not being realized. Household A and household B would be better off if one specialized in raising goats and the other in rice, but because the markets for goats and rice don’t exist they each have to raise both. It’s a basic comparative advantage argument; households can be made better off (just like we argue countries can) by trading with each other. If you want to enact policies or take action to assist these households, then promoting functioning markets in outputs and inputs is the way to go. How do you do that? It could be by making institutional changes (making property rights clear so land can be easily exchanged), or providing insurance (so people can take the risk of producing for the market), or it might be as simple as paving a road (so that transport costs are low enough to trade with the next town over). It could be by promoting better information flows; one of my favorite development papers is by Robert Jensen about the positive effect of mobile phone introduction on the efficiency of the fish market in Kerala, India.

If separation holds, and by implication markets are functioning relatively well, then the implications for development are different. Households are able to buy and sell, so they are probably taking advantage of nearly all the gains from trade available. They can likely benefit more from increased investments in factors of production than households without access to markets. Here’s what I mean. When markets are (reasonably close to) complete, then endowing a household with a tractor and the technical training to keep it running is a huge change in their productivity. They can use it on their own farm and they can rent it out to others. It may make sense for them to become a full-time tractor operator in their village because with complete markets they know they can buy what they need using the proceeds of the tractor business.

In a non-separating economy without markets, giving a family a tractor and technical training is kind of a waste. If they’re well off for a developing country they’ve got 2 hectares of land (about 5 acres or just under 4 football fields). Yes, the tractor can alleviate some of the workload, but it’s overkill. You’d spend more than half your time just turning the tractor around trying to plow that small of a space. Moreover, the tractor would sit idle for the vast majority of the year. Without markets, most investments and improvements in technology are not worth it.

Okay, back to Dillon and Barrett. They use data from the Living Standard Measurement Surveys from 5 Sub-Saharan African countries to test for household separation. The logic of the test comes from a classic paper by Benjamin (1992). If markets are functioning efficiently, then the characteristics of your household (age, gender, education, number of kids) should be unrelated to the input usage on your farm. The production decision (I need three workers to plant rice) is separated from your household characteristics (I have five workers in my household). Those extra workers in your household can go work on someone else’s farm if markets exist. (And if you don’t have enough household labor, you can hire in laborers).

What they find is that across all five countries (Ethiopia, Malawi, Niger, Tanzania, Uganda) separation fails, meaning that there are significant failures in factor and/or output markets. In every country, the size of the household is always significantly related to the amount of labor used on that household’s land. It doesn’t matter whether the household is led by a male or a female, or where the household is located within the country. The failure of separation appears to be a general failure. One thing to note is that this doesn’t mean households fail to participate in markets at all; Dillon and Barrett find that nearly all households do make some transactions in labor and land markets. It is likely that the actual transactions costs (fixed costs, time costs, etc..) of participating in the market are so high that people don’t undertake all the trades that they would otherwise make.

So what does this mean? It means that development assistance is likely to be most effective if it promotes making markets more efficient; perhaps through encouraging better information flows like in the Indian fish-market example. Pure investment strategies (let’s give everyone a bag of fertilizer!) are unlikely to be as effective without the markets in place that allow people to take advantage of that investment.

Research like this is particularly valuable to people like me who want to study growth and development from a macro perspective. It reminds us (beats us over the head with?) that “developing countries” and “developing economies” are not the same thing. Market failures mean that developing countries are really a collection of myriad small economies, and therefore we need to be careful in thinking about things at too aggregate a level. This is also an example of where I think the “institutions” literature could really add value. Can we provide better theories or models of what precisely it means for markets to “fail”? What particular institutional details are important for markets to work efficiently?

Unified Growth Theory is not the Enemy

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

In a recent post I compared and contrasted Joel Mokyr’s and Bob Allen’s viewpoints on the origins of the British Industrial Revolution (IR). One failure was to not link to a review paper by Nick Crafts. His is an in-depth review of their two positions, and you should read it.

One of the the themes running through Crafts review is that differences among economic historians in explaining the IR should be set aside (perhaps temporarily) in favor of defending themselves from the real enemy, unified growth theory (UGT). For the uninitiated, UGT is a set of work that develops dynamic models of growth that capture both a period of Malthusian stagnation in output per worker and the take-off to sustained growth. They are concerned with understanding what allows for that transition from stagnation to growth. Oded Galor is the capo di tutti capi of the UGT mafia, and early chapters of his book are an excellent introduction to this literature. I think Chad and I do a good job of giving a low-tech version of UGT in Chapter 8 of our book (you should buy lots and lots of copies).

Full disclosure here. Oded was my dissertation advisor, and I’ve co-authored a paper with him. I have papers of my own that hover around the edge of the true UGT world. So when I proceed to defend this literature below, I am not a neutral 3rd party.

My guess as to why Crafts sets UGT up as the foil to economic history is that UGT takes on big questions while sweeping tremendous amounts of detail under the theoretical rug. The models in UGT are abstract, and while their assumptions may be based on stylized facts drawn from history, they ignore nearly all the nuance that an economic historian would find compelling.

But of course it does that, it’s theory. UGT is not meant to explain the specific instance of the British IR, or any other particular take-off. It is intended to illuminate general forces driving the take-off to sustained growth. Forces that are not obvious from studying James Watts’ personal correspondence or the minutiae of French textile plant accounts.

UGT separates the “Industrial Revolution” from the concept of the take-off to sustained growth. They are not necessarily the same thing, nor do they have to have occurred in any particular order. The take-off to sustained growth is a general economic phenomenon, and the British experience is just one example of it. The British experience happens to make the distinctions very clear. The IR is traditionally date to the late 1700’s but there is a robust literature arguing that sustained growth did not begin in Britain until well into the mid-1800’s (see Crafts and Harley, 1992 on output growth, see Allen for a more recent evaluation of the wage literature).

To wildly over-simplify, the IR is the onset of a specific package of technology that (depending on the author) includes some combination of the following: inorganic power sources, mechanization of tasks, large scale enterprises, institutions supporting innovation, urbanization, the expansion of finance, the expansion of trade, and [fill in whatever I missed]. Growth in wages or output per worker is one other feature of the IR to be studied alongside these. The British IR would have been a revolution even if sustained growth hadn’t occurred.

In contrast, the take-off to sustained growth is specifically and particularly about growth in output per worker. Under what conditions will population growth fail to keep up with output growth caused by technological change? What UGT demonstrates is that something needs to shift in the demographics for sustained growth to occur. Technology, however widely defined, is not enough. It is not until technology changes the trade-off between quantity and quality of children that sustained growth happens.

While UGT focuses on general conditions for the take-off, it is a mistake to think that UGT rules out path dependence or historical contingency. There is nothing in UGT that makes take-off inevitable. Under the right conditions on the demographic or technology functions, an economy will end up stagnating forever. UGT focuses on the take-off because that is what we see in the data, but it need not be the case.

One source of confusion is that UGT papers often use the British experience for examples of the forces at work (I cannot begin to count the number of papers I’ve read that try to calibrate their model to UK data). That, I think, has led to the impression that UGT is meant as a competing explanation for the British IR. It’s not, and the UGT crowd can and should do better in moving beyond the British IR in terms of stylized facts. That would go a long way towards making the distinctions clearer in the literature.

But UGT is not in any sense mutually exclusive with detailed economic history work. If someone wakes up tomorrow and shows that both Mokyr and Allen are wrong about the British IR, that doesn’t mean UGT “wins”. And if someone wakes up tomorrow and shows that some central result of UGT is theoretically incorrect, that doesn’t mean Mokyr or Allen are right. We should all be focused on the true enemy of increased understanding: grading papers.

Technology and “Good Jobs”

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

I got a number of comments and e-mails regarding a recent post on technological change, jobs that produce goods, and “good jobs”. This is a follow up meant to clarify some points and solidify others.

  1. The entire point of my post was to say that the exact tasks people do is unrelated to whether they have a “good job”. Working in manufacturing does not make a job “good”, and working in services does not make a job “bad”. Yes, “good” and “bad” are fuzzy terms.
  2. I’m not denying that technology is replacing manufacturing jobs. It is. It will. We may well end up with robots making everything. If so, then you want to make sure that the jobs that people do have are “good jobs”.
  3. Service jobs are not, even to a first approximation, poor people doing things for rich people. So no, we won’t run out of jobs because rich people can only get so many massages or restaurant meals. The vast majority of workers in the US for the last 60 years have been non-rich people doing service-like things for other non-rich people. [Teachers, cops, firemen, nurses, waiters, store clerks, everyone in HR, everyone in accounts payable, secretaries, receptionists, every computer programmer, truck drivers, warehouse workers, chefs, everyone who works on any TV show, record, or movie, claims adjusters, insurance agents, financial analysts, everyone at your local bank, your IT guys, everyone working in state or federal government, priests, librarians, florists, pizza delivery guys, photographers, personal trainers, dietitians, optometrists, dentists, physical therapists, veterinarians, security guards, dishwashers, hostesses, exterminators, HVAC workers, plumbers, electricians, roofers, rodeo clowns, pit bosses, morticians, barbers, day-care attendants, real estate brokers, airline pilots, car mechanics, flight attendants, taxi drivers, and yes, even used car salesmen. Just to give a few examples.] We are very good at finding things to do for each other. We’ll continue to be good at that
  4. No, you cannot “work any day you want to”. Ask the day laborers that hang out at the Home Depot near my house how they are doing. Some days you pick the wrong parking lot. Some days it’s raining. Some days there just isn’t anyone with a job. The frictions and costs of working day-to-day are huge.
  5. Personally, I think that the following characteristics are associated with “good jobs”. (A) Security/steadiness. As per #2, knowing that your job will be there next week/month/year is incredibly valuable. It allows you to undertake long-run commitments, like marriage, home-ownership, and schooling. (B) Family flexibility. You can deal with your life (i.e. all the crap you need to get your kids to) without the fear of being fired for it. (C) Pay/Benefits. Enough money to afford decent health insurance, or decent health insurance provided by the employer. In short, I think people want stability more than anything. The attraction of those mid-20th century union jobs for workers was that they had lock-it-down certainty about the future.
  6. Yes, it is possible to make any kind of job a “good job”. I used the Costco/Wal-mart distinction as an example. Justin Wolfers and Jan Zilinsky just posted a piece containing further examples. In short, worker productivity is not a fixed value, and paying higher wages is associated with getting higher productivity from the same workers. Costco has a wage/benefit structure that encourages their workers to be productive. In return, Costco saves money from lower turnover. What Wolfers and Zilinsky show is that this works in a variety of settings.
  7. The original post made it sound as if unions were the only way to generate the conditions of “good jobs”. That is not true, and not what I intended to say. Unions were one way to elicit those good conditions from employers, and manufacturing workers were particularly well placed to unionize and negotiate those conditions. But unions aren’t necessary for this. Costco isn’t unionized. [CORRECTION: About 15,000 Costco workers are part of the Teamsters. Roughly 174,000 total Costco workers. DV 1/20/15] We need companies to recognize the value of becoming a “good job” employer, but there are lots of ways to do that.

Research on Persistent Roots of Development

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

A few papers of interest regarding the persistent effect of historical conditions (geographic or not) on subsequent development:

  1. Marcella Aslan’s paper on the TseTse fly and African development is now out in the American Economic Review. I believe I’ve mentioned this paper before, so go read it finally. Develops an index of suitability for TseTse flies by geography, then shows that within Africa higher TseTse suitability is historically associated with less intensive agriculture, fewer domesticated animals, lower population density, less plow usage, and more slavery (If you are queasy about using Murdock’s ethnographic atlas, then avoid this paper). Marcella shows that TseTse suitability is currently related to lower light intensity (everyone’s favorite small-scale measure of development), *but* this effect disappears if you control for historical state centralization. The idea is that the TseTse prevented the required density from forming to create proto-states, and that these places remain underdeveloped. Great placebo test in this paper – she can map the TseTse suitability index of the whole world, and show that it has no relationship to outcomes. The TseTse is a uniquely African effect, and she is not picking up general geographic features.
  2. James Ang has a working paper out on the agricultural transition and adoption of technology. Simple idea is to test whether the length of time from when a country hit the agricultural transition is related to their level of technology adoption in 1000 BCE, 1 CE, or 1500 CE (think “did they use iron?” or “did they use plows?”). Short answer is that yes, it is related. Places that experienced ag. transition sooner had more technology at each year. Empirically, he uses instruments for agricultural transition that include distance to the “core” areas of transition (China, Mesopotamia, etc..) and indexes of biological endowments of domesticable species (a la Jared Diamond, and operationalized by Olsson and Hibbs). The real question for this kind of research is the measure of technology adoption. We (meaning Comin, Easterly, and Gong) retrospectively code places as having access to technologies in different years. A worry is that because some places are currently poor (for non-agricultural reasons) the world never bothered to adopt their particular technologies, but that doesn’t necessarily mean they were technologically unsophisticated for their time.
  3. Dincecco, Fenske, and Onorato have a paper out on historical conflict and state development. The really interesting aspect here is how Africa differs from other areas of the world. Across the world and over history (meaning from 1400 to 1799) wars are associated with greater state capacity today. That is, places that were involved in conflicts in the past are now stronger states (measured as their ability to tax) than those without conflict. The basic theory is that wars allow states to concentrate their power. However, historical conflict is unrelated to current civil conflicts…except in Africa. In Africa, historical wars are correlated with current civil conflicts, and this is associated with poor economic outcomes today, so things are bad on multiple fronts. Here’s my immediate, ill-informed, off-the-cuff analysis: In non-African places, wars generated strong states who were able to use their power to completely and utterly eliminate ethnic groups or cultural groups that were alternative power centers. They don’t have armed civil conflicts today because the cultural groups that might have agitated conflict were wiped out or so completely assimilated that they don’t exist any more. In Africa, central states were just not as successful in eliminating competing cultural groups, so they remain viable sources of conflict. Africa’s problem, perhaps, was a lack of conclusive wars in the past.

The Industrial Revolution and Modern Development

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Trust, Familes, and Growth

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

Warning: this post is too long and wildly speculative.

Culture has (re)-emerged as one of the proposed “deep determinants” of economic development. A good place to get a feel for this literature is a piece in J. of Economic Perspectives by Guiso, Sapienza, and Zingales (GSZ). They define culture as “those customary beliefs and values that ethnic, religious, and social groups transmit fairly unchanged from generation to generation.” Keep in mind, this is what GSZ a narrow definition of culture. Culture is like institutions; we seem to know it when we see it, but can’t define it.

Regardless, one of the stronger results that pops up in the culture literature that GSZ review (and often authored in the first place) is the relationship of “trust” and economic success. Population groups that tend to trust others also tend to be economically successful.

This one figure from GSZ is particularly striking. Using data from the U.S. and self-reported ethnic backgrounds, they plot “trust” for each group relative to people who report as being descended from British ancestors. Trust is measured by asking individuals if “most people can be trusted (yes/no)”. The way to interpret the figure is that the percentage of Japanese-descended answering “yes” is 24.7 percentage points higher than whatever the British-descended answered.

Guiso etal 2006 fig 2

What do we see? The Japanese and Scandanavians are must more trusting than the British, while other Western Europeans are just about as trusting as the British. Southern Europeans are less trusting, and as we get to African and Indian-descended Americans, trust falls off a cliff. Patterns like this show up if you alternatively look at the World Values Survey at individual countries. In general Western Europeans (and their descendants in places like the US and Australia) report a higher degree of trust than other regions of the world. They also tend to have much more economic success wherever they live – see my recent post on population groups and development.

Now, there is no way for me to tell you that this is causal. It could well be that a lack of economic success leaves you less likely to trust others. But pending a definitive study on this, let me leap ahead on the assumption that there is a strong relationship of trust to economic success.

Why? The basic model here would be that economic exchange is a repeated game you play with strangers. In each round, you can either cooperate or cheat (you can pay your bar tab or you can slink out the back). Everyone is better off if you and all the strangers you interact with continually play “cooperate”. But at any given moment, you could take a stranger for a sucker by playing “cheat”. Once someone plays “cheat”, though, everyone plays “cheat” and we are all worse off. A culture of trust – and in particular trust in non-kin strangers – means that people take “cooperate” as their default option. We grab all the win-win exchanges possible.

Trust in non-kin strangers is such a powerful force for economic success because it scales so well. There are a nearly limitless number of strangers to make win-win trades with. If you restrict yourself to only your kin-group, the number of trades is severely limited. How do you build up complex networks of exchange and division of labor with, at best, a few hundred people you trust? Trust opens up economic possibilities.

So where did Western Europeans get this culture of trust, and in particular trusting non-kin? (If you already thought this post was highly speculative, then buckle up). Let me propose that the origins of this may be located in the re-organization of northwestern European society that occurred around 800-1100 AD. There was a fundamental shift away from kin-groups as the organizing principle for families towards households in this period. The alternative that arose was a “household” that centered around a smaller core of kin (the nuclear family) but also included non-kin members. This meant that NW European households were constantly exposed to, and interacting with, non-kin “strangers”. The NW European “culture of trust” was built on that foundation.

There are two books that I’ll suggest you read on this if you want to get some real depth on this idea. Whatever I say after this is culled in large part from these works.

  1. The First European Revolution: c. 970-1215 (The Making of Europe) by R.I Moore. This tends to be more about the changes taking place at the top levels of the aristocracy and church.
  2. Why Europe?: The Medieval Origins of Its Special Path by Michael Mitterauer. This gets more finely into the changes in economic organization occurring at the “low” levels that led to changes in family structure for the peasants. Chapters 1-3, in particular.

Mitterauer lays out the basic concept (p. 96):

The fundamental form of the European family is not the lineage group but the household. Its members do not necessarily have to be related through descent or marriage. This makes the system very flexible and adaptable to other situations.

He also makes the case that this was a particularly important social change (p. 93):

The loosening of lineage ties created some leeway for striking up new social relationships beyond the family circle. Ties to people other than one’s kin played an important part in European social history and made a major contribution to Europe’s social dynamics.

Moore finds this same process going on in the upper reaches of society (p. 70):

Upon his accession the eldest son became head of what was now conceived as a dynastic family, capable of being depicted by the diagram or `tree’ in which the European aristocracy has invested its identity ever since. The dynastic family…gradually superseded the more loosely articulated kinship group in much of northwestern Europe for the purpose of controlling and transmitting landed property.

We’ve got a process going on by which the wider kin-group is being put aside in favor of nuclear families, and these nuclear families are incorporating non-kin strangers into their households.

Why was this happening? Let’s start with the peasants. The non-kin strangers tended to be young adults. They were farm hands (both male and female), apprentices, or servants in the manor house, and they left these positions once they married. “Working as a life-cycle servant…seems to have been the defining experience of European youth” (Mitterauer, p. 94). This was not just a case of young adults working as servants for a lord. Farm hands were prevalent on most of the smaller hides (farms) that made up a lords estate.

The origin of this structure for households is located by Mitterauer in the particular agricultural system that developed as NW Europe went from being a frontier to being settled. This “cerealization” of NW European agriculture was most productive in the hide system. Simply put, there is an efficient scale to operate at if you are growing rye and oats (“Rye and Oats” is the title of Mitterauer’s first chapter). That scale is fit best by a nuclear family accentuated by some farm hands. Most importantly, you want to keep the scale of the hide constant, so you cannot have families splitting them up across children. But you need something for all those children to do, so the lords shuffled them around as farm hands and apprentices and servants between households. This is an atrocious over-simplification of Mitterauer’s argument, but I think it gets the main points right. The non-kin-based families of NW Europe arose because of a peculiar agrarian system in that area. The lingering effect of these families was to build up trust in non-kin strangers.

At the top end, a similar change was taking place. Moore does not place as much weight on the nuances of agricultural production as he does on the closing up of the frontier. He paraphrases George Duby (p. 63, no cite given, but I think he means this book):

..described the social history of this period as one of disorder in transition between two ages of order, that of the Carolingian world where a large but loosely defined and structured nobility supported itself with a haphazard combination of plunder and booty….and that of the precisely articulated society of orders, sustained by legal and social domination…which..remained familiar in western Europe until the age of revolution.

Once you could not keep you wider kin-group happy by plundering some new corner of France, you had to get serious about dividing up what you did have.

As Moore notes (p. 66), the crisis arising from having multiple kin-group claims to inheritance was not unique to NW Europe. It happens everywhere. It was not this problem that made Europe unique, it was the solution. Europe honed in on strict dynastic succession, eliminating disputes over inheritance by telling everyone in the extended kin-group (uncles and male cousins in particular) to go f*** off. Moore does a nice job of explaining how this was accomplished with the collusion of the Church. This post is already too long, so I’ll push you off to his book for the details.

The end result was that at the top level of society, the households of kings, dukes, and such were no longer kin-based. Sure, they were gigantic. But they were filled with non-kin “strangers”. Pages and servants and advisors and priests who were not related by blood or marriage, but owed their allegiance to the lord nonetheless.

So at both top and bottom levels of society in NW Europe in the years between 800-1100 we have all of these people learning to trust non-kin strangers. Perhaps unwillingly at first, but the mere exposure to non-kin strangers in economic relationships would have to build up some trust over time. Once that trust is built into these households, it gets passed on. It becomes “culture” as GSZ would describe it. But that culture of trust allowed the populations of NW Europe to take advantage of more win-win exchanges between strangers, and contributed to their on-going economic advantage.