* And lots of new stockings. Knitting anything but wool or silk was a pretty daunting task until 1758, when Jedediah Strutt—Richard Arkwright’s partner—patented the Derby Rib, which alternated two stitches, one the reverse of the other, and so made the production of ribbed cotton stockings as practical as that of silk.
CHAPTER ELEVEN
WEALTH OF NATIONS
concerning Malthusian traps and escapes; spillovers and residuals; the uneasy relationship between population growth and innovation; and the limitations of Chinese emperors, Dutch bankers, and French revolutionaries
IT TOOK ABOUT SIX hundred years for the publishing industry to get from Johann Gutenberg to the book you are now reading.* The most remarkable eight-week stretch in all of those six centuries fell between January and March 1776—a year overloaded with significant dates. On January 10, Thomas Paine published the pamphlet Common Sense (“Society is produced by our wants, government by our wickedness”). February 17 saw the first volume of Edward Gibbon’s History of the Decline and Fall of the Roman Empire roll off the presses (“In the second century of the Christian Era, the empire of Rome comprehended the fairest part of the earth …”). And on March 9, a former University of Glasgow colleague of Joseph Black published An Inquiry into the Nature and Causes of the Wealth of Nations.
Standing in London’s Science Museum, in front of Rocket and surrounded by models of Thomas Newcomen’s beam engine, Joseph Bramah’s challenge lock, and James Watt’s separate condenser, it takes very little imagination to see connections with iron foundries, coal mines, and even cotton fields. The road back to Adam Smith requires more thought, but is just as important, and as enlightening.
Smith’s book, like Darwin’s Origin of Species, was revolutionary in its impact, immediately and permanently, though both are far more frequently cited than read. In particular, Wealth of Nations demonstrates that Britain’s eighteenth-century transformation—the schoolboy’s “wave of gadgets”—was a revolution not merely in technology but in commerce. The founding text of economic science is staggering in its range, with disquisitions on the origin of money, the nature of commodities, interest rates, profitability, the mechanics of trade, bank interest, taxation, public debt, agriculture, and manufacturing. It devotes thousands of words to histories of Europe’s towns from the end of the Roman Empire to the present, and of colonial policy from the time of ancient Greece. It is telling, therefore, that Smith decided to open his magnum opus with a section entirely devoted to the “causes of improvement in the productive powers of labour [and] in the skill, dexterity, and judgment with which labour is applied in any nation.” This was a remarkable bit of insight, the application of Locke’s labor theory of value to national policy.
Smith argued that two conditions were necessary for labor to produce the maximum amount of wealth: perfect competition among sellers—everyone pursuing his or her selfish interest, the famous “invisible hand”—and the complete freedom of buyers to substitute one commodity for another. Under such ideal circumstances (Smith was not the first economist, but he was probably the first to “assume a can opener,” i.e. perfect conditions, in a model), specialization, or division of labor, was inevitable. Ten men could each bake their own bread, weave their own cloth, and build their own houses, but if one became a baker, another a weaver, and a third a builder, the result would be more food, clothing, bricks … and trade.
Smith’s theorems did a spectacular job of explaining the self-regulating character of a free market, in which prices and profits are forced by competition to the lowest possible level.* They inspired David Ricardo’s exposition, in 1817, of the principle of diminishing returns: his argument that the growth of the first decades of industrialization was certain to level off, as each successive improvement produced smaller results. Helped along by the inflation in food prices caused by the Napoleonic Wars, they even set the stage for Thomas Malthus’s Essay on the Principle of Population, with its famous argument that population always grows geometrically, food production arithmetically.
What they didn’t do was explain how wealth, profit, and competition can all grow over time. In short, it didn’t explain the two centuries of growth that were beginning just as Wealth of Nations was being published. It is in no way a criticism of the book to state that it covered everything except the reason the author’s own nation was about to get wealthier than any other nation in the history of mankind. The failure is pretty much explained by what is not in the book. Despite living in the middle of the biggest explosion of inventive activity ever recorded, and even though his illustration of the advantages of specialization was a factory for making pins, Smith’s book hardly mentions the role of the new machines then transforming his world. Next to nothing about waterpower, to say nothing of steam; nothing about the forging of iron,1 and his few paragraphs about the textile revolution are mostly an argument for restricting the export of spinning machines. His pin factory, it turns out, was only a metaphor; he never set foot inside one.
Nor did he show any understanding of Darby’s furnace, or Arkwright’s water frame, or Watt’s double-acting engine—none of the escape hatches out of humanity’s millennium-long Malthusian trap. The efficiencies of specialization are real, and the self-regulating “invisible hand” powerful, but it was the machines, and nothing else, that allowed Britain, and then the world, to finally produce food (or the wealth with which to buy food) faster than it produced mouths to consume it.
A lot more is known about how population increases than how wealth grows. Indeed, the Industrial Revolution was decades old before anyone realized that wealth was growing at all. The first edition of Malthus’s Essay on Population was published in 1798 and convinced nearly everyone that the hoofbeats of the horsemen of the Apocalypse could already be heard throughout England. In 1817, the English economist David Ricardo predicted2 that land rents would increase while wages would approach subsistence level, at precisely the moment when British farmland rents per acre started to plummet and the wages of laborers to explode. Partly this was evidence of the limits of accounting with very little data; Britain’s first census, inspired by Malthus, wasn’t conducted until 1800. But even more it was the lack of a model that carved up overall growth into its constituent parts.
In 1890, another economist, the mathematically trained Cambridge scholar Alfred Marshall, suggested that the century of growth in both income and wealth that began just as Ricardo predicted its opposite was largely due to ideas whose benefits spilled over into the economy soon after they had enriched their creator. An idea—a separate condenser, for example, or a spinning jenny—might be costly for one inventor to develop, but it wasn’t long (not even the fourteen years of a patent) before it became de facto public property, and inspired others to improve upon it.
Marshall’s “spillovers” were intriguing but remained anecdotal until the 1950s, when the Nobel Prize–winning economist Robert Solow incorporated something very like it into an equation known as the fundamental equation of growth. Working from a contemporary economic model that had shown that capital, labor, and land could be substituted for one another—as one component grew more expensive, producers could substitute one for the other—Solow was able to calculate the rate at which average workers increase their output. He found three components of output increase, each one reflecting the key inputs to the national wealth calculus. The first two, land per worker and capital per worker, are, if not easy, at least possible to measure. Except during times of dramatic depopulation, such as the Black Death of the fourteenth century, or extremely large additions to the stock of arable land, as with Europe’s discovery of the New World, growth in land per worker has been negligible for centuries, so small that its effect on growth can be eliminated in the simplest calculations. The second component, growth in capital3 per worker—that is, all the buildings, machinery, tools, and so on—explains only about 24 percent of total growth. However, since the growth in the amount of land and capital per worker together doesn’t
equal the overall growth rate, a fudge factor must be used, called the residual: what’s left over.
This also means that the residual, despite the ass-backward way it is calculated, amounts to at least three-quarters of the total increase in economic growth since 1800. That’s a big chunk of activity defined by subtracting everything else, a little like a ten-drawer file cabinet with seven drawers marked “Miscellaneous.” Solow first assumed4 that the residual represented increasing efficiency over time, and he incorporated an arbitrary constant to represent the rate of the growth in useful knowledge.
Useful knowledge, in this formulation, is not all knowledge. The growth in capital includes not just cash, buildings, and machines, but also patents—for the duration of the grant. That’s how a corporation reports it on a balance sheet, and that’s therefore how it is accounted for in estimating national growth as well.
But all the patented knowledge that was originally counted as growth in capital becomes part of the residual once the patent expires, and what it loses in the value it had to its original inventor is gained by the inventor’s nation. Just as public domain books, such as the Bible and the works of William Shakespeare, are both more numerous and more valuable than the universe of copyrighted ones, the universe of useful knowledge is a lot bigger than the universe of patented ideas.
How much bigger? Solow attempted to put a number on the rate of growth in formerly (and also never) patented knowledge—which included everything from calculus to the laws of motion—and assumed, for the sake of simplification, that the rate of increase was not only regular, but independent of changes in custom, law, or historical contingency; that is, knowledge, like Topsy, just “grow’d.” Such simplifications are essential for theory building, but this particular one just pushed the big question back another step: Since knowledge, whether patented or not, is rarely lost, and the sum available has been increasing at least since the invention of written language more than five thousand years ago, what caused it, for the first time in history, to increase faster than the rate of population growth?
Population and prosperity are correlated, albeit imperfectly. Adam Smith was the first to recognize the hugely important but completely obvious correlation (this is a pretty good definition of genius) when he pointed out that the value of specialization utterly depends on the size of the community in which one lives. A family living alone grows its own wheat and bakes its own bread; it takes a village to support a baker, and a town to support a flour mill. Some critical mass of people was needed to provide enough customers to make it worthwhile to invest in ovens, or looms, or forges, and until population levels reached that critical level, overall growth was severely limited.
That level, however, was reached long before it had any impact on per capita growth in productivity. From 1700 to 1820, China grew in population from 138 million to 328 million, which increased its production of goods and services from $83 billion to $229 billion—but both population and production increased at almost exactly the same rate, about 0.75 percent annually. Population growth alone is clearly not sufficient to explain, for example, how the population of Britain, during the same period, could increase at the same rate as China’s, but its gross domestic product nearly one-third faster. Something more than specialization through population growth was at work.
This was the conclusion of E. J. Hobsbawm, who argued that the fuel for the Industrial Revolution was not coal but demography: population—or, more precisely, the growing size of markets both domestic and foreign. While recognizing, generally, the importance of a cadre of mechanics to build and repair steam engines, forges, lathes, and spinning machines, he minimized the importance of the inventions on which they practiced their trade. The presence of a thousand brilliant inventors was far less important, in Hobsbawm’s words, than “the mass of persons with intermediate skills,5 technical and administrative competence … without which any modern economy risks grinding into inefficiency.”
Another currently fashionable explanation for the Industrial Revolution is also a demographic one, though subtle: not the nation’s overall birth rate, but the birth rate in a particular subset. This is essentially the theory proposed in Gregory Clark’s examination of the relationship between differential reproduction in different classes.
Clark’s discovery, arrived at by combing through centuries’ worth of parish records, was that the wealthiest families in England were far likelier to have more sons than similarly wealthy families in China, and therefore had less real property to pass along to the average member of the next generation. Throughout the period 1540–1640, preindustrial Britain exhibited a fair bit6 of both upward and downward mobility, largely due to primogeniture, which obliged a prosperous landowner to leave his land to only one of his sons—and the typical landowner had up to eight. Since all but one of those sons would have to find his own niche in the economy, “craftsman’s sons became laborers,7 merchant’s sons petty laborers, large landowner’s sons smallholders” carrying with them the habits of hard work, deferred gratification, literacy, and a disposition to settle disputes peacefully, all of which showed a decided increase during the eighteenth century. As upper-class habits trickled throughout society, so did economic growth.
This theory explains fairly well why the son of a country squire might find himself learning the craft of a carpenter, and it may explain some critical aspects of historical growth in national wealth, particularly in Britain. A literate population bound by the rule of law and exhibiting middle-class behaviors such as deferral of gratification and low levels of corruption is as valuable to a nation as it is to a business firm. A recent World Bank analysis8 found that a significant amount of wealth worldwide is derived from such behaviors, and that human capital and the rule of law might account for up to 30 percent of the residual.
But the middle-class work habits that proved so vital for a new generation of factory laborers were valuable only because there were factories for them to work in. And Boulton and Arkwright weren’t motivated to build the factories because good workers suddenly became available, but because they had machines that needed housing. Similarly, whatever percentage of Solow’s residual is attributed to a reliable labor force operating in a relatively uncorrupt economy ruled by law, something still needs to explain why growth in prosperity, three-quarters of it derived from the creation of useful knowledge, stagnated for five millennia and then exploded in Britain in the eighteenth century.
This is where Solow’s simplifying assumption—the idea that the growth in useful knowledge occurs at a constant rate, directly proportional to population—however analytically valuable, runs out of gas. It can’t explain the steam engines and reciprocating chisels of the Portsmouth Block Mills, or the boring machines of Bersham Furnace, or the water frames in the Derwent Valley, because it implies that the decisions made to investigate the properties of steam, or iron, or silk were just as probable in eighteenth-century India as in eighteenth-century Europe; more likely, really, since India was home, in 1700,9 to more than thirty million more potential inventors than all of Europe, including Russia. The only thing that can be said in favor of making the growth of knowledge what economists call an exogenous variable (i.e. one without deliberate purpose, a kind of magical growth in knowledge from which everyone could benefit) was that its constant rate of increase made the equations simpler. By the 1980s, however, a number of economists examining the eighteenth century’s wealth explosion thought that Solow’s equations might be too simple.
The best known of them, Paul Romer of Stanford, made his reputation by demonstrating that useful knowledge—the largest component in Solow’s residual, and therefore the most important component of any increase in national wealth—doesn’t accumulate by itself, independent of the larger economy, but rather is almost entirely dependent on decisions made by individuals seeking some sort of economic advantage. Romer showed that such growth depended on real people acting, in their perceived self-interest, to create knowledge. His model was both s
table and reflective of the real experience of economic growth since 1800. It also resolved, in a mathematically rigorous manner, the conundrum in Solow’s fundamental growth equation,10 which was precisely how the initial stage of knowledge creation benefits the investor/inventor and therefore is counted in the “capital growth” segment, while the larger sum spills over into the economy at large and forms the residual.
More important, Romer demonstrated that the growth in useful knowledge occurred at anything but a constant rate; that it was, instead, highly sensitive to the economy in which it occurred. Romer recognized that the creation of the idea behind a new invention, or product, was just another fixed cost, like constructing a building, or buying a machine; it was just as expensive in skull sweat for James Watt to design the first Watt linkage as to manufacture a thousand. Because knowledge is the sort of property that can be sold to multiple consumers without lowering the value to any of them—Romer termed it nonrivalrous, as distinct from tangible, or rivalrous, property, which can be sold only once—the payoff for anyone producing it can be very large indeed.
At least, in a large enough population.
IN 1993, A DEVELOPMENT economist named Michael Kremer published a paper in the Quarterly Journal of Economics that examined population growth over time and tracked it against the expansion of what Romer called nonrivalrous, useful knowledge, and concluded that the creation of knowledge is directly proportional to the size of the population. Kremer’s model made two assumptions:11 first, that inventive talent and motivation are randomly distributed throughout any population; and, second, that the larger the population, the larger the total output of inventions. The idea—that since each person has the same likelihood as any other of inventing the wheel, or the steam engine, or the iPod, more people means more inventors—may seem counterintuitive; it took only one genius, after all, to put stirrups on a saddle. But it works. A nation needs only twelve players to field a team to compete for the Olympic gold medal in basketball, and even tiny nations would find such a number easy enough to assemble. But only a few nations are actually competitive, because the twelve players represent the top of a pyramid of competition in which the larger the base, the greater the height.*
The Most Powerful Idea in the World Page 29