9.2 From Growth Theory to Growth Empirics
So far in this chapter we have introduced exogenous technological progress into the Solow model to explain sustained growth in standards of living. Let’s now discuss what happens when this theory is forced to confront the facts.
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Balanced Growth
According to the Solow model, technological progress causes the values of many variables to rise together in the steady state. This property, called balanced growth, does a good job of describing the long-run data for the U.S. economy.
Consider first output per worker Y/L and the capital stock per worker K/L. According to the Solow model, in the steady state both of these variables grow at g, the rate of technological progress. U.S. data for the past half-century show that output per worker and the capital stock per worker have in fact grown at approximately the same rate—about 2 percent per year. To put it another way, the capital–output ratio has remained approximately constant over time.
Technological progress also affects factor prices. Problem 4(d) at the end of this chapter asks you to show that, in the steady state, the real wage grows at the rate of technological progress. The real rental price of capital, however, is constant over time. Again, these predictions hold true for the United States. Over the past 50 years, the real wage has increased about 2 percent per year; it has increased at about the same rate as real GDP per worker. Yet the real rental price of capital (measured as real capital income divided by the capital stock) has remained about the same.
The Solow model’s prediction about factor prices—and the success of this prediction—is especially noteworthy when contrasted with Karl Marx’s theory of the development of capitalist economies. Marx predicted that the return to capital would decline over time and that this would lead to economic and political crisis. Economic history has not supported Marx’s prediction, which partly explains why we now study Solow’s theory of growth rather than Marx’s.
FYI
Economic Possibilities for Our Grandchildren
Imagine life a hundred years from now. Because of economic growth, average incomes will have risen substantially. If labor-augmenting technological change continues at a rate of, say, 2 percent per year, then over the course of a century the real amount earned per unit of labor will increase more than sevenfold. How do you think such a massive increase in living standards will affect the lives of most people?
That is precisely the question the renowned British economist John Maynard Keynes asked in a famous essay written in 1930 called Economic Possibilities for Our Grandchildren. Keynes noted that throughout much of human history, economic growth was meager or nonexistent. He wrote, “From the earliest times of which we have record—back, say, to two thousand years before Christ, down to the beginning of the eighteenth century—there was no very great change in the standard of life of the average man living in the civilised centres of the earth.” But then the Industrial Revolution occurred, and modern economic growth began. “In spite of an enormous growth in the population of the world, which it has been necessary to equip with houses and machines, the average standard of life in Europe and the United States has been raised, I think, about fourfold.” Keynes projected that this rapid growth would likely continue. He wrote, “the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is.”
Keynes then discussed the social impact of such a large increase in living standards. He concluded that with such abundance, satisfying most of our basic needs and material desires (what Keynes called “the economic problem”) would be easy. He wrote,
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I draw the conclusion that, assuming no important wars and no important increase in population, the economic problem may be solved, or be at least within sight of solution, within a hundred years. This means that the economic problem is not—if we look into the future—the permanent problem of the human race.
Why, you may ask, is this so startling? It is startling because—if, instead of looking into the future, we look into the past—we find that the economic problem, the struggle for subsistence, always has been hitherto the primary, most pressing problem of the human race—not only of the human race, but of the whole of the biological kingdom from the beginnings of life in its most primitive forms.
Thus we have been expressly evolved by nature, with all our impulses and deepest instincts, for the purpose of solving the economic problem. If the economic problem is solved, mankind will be deprived of its traditional purpose.
Keynes reasoned that with labor productivity so high, we wouldn’t need to work very long to produce all goods and services required for a good life. He suggested that a workweek of only 15 hours would do. The problem he foresaw: How would we use all the extra leisure time to give ourselves happy and satisfying lives? He wrote, “There is no country and no people, I think, who can look forward to the age of leisure and of abundance without a dread. For we have been trained too long to strive and not to enjoy. It is a fearful problem for the ordinary person, with no special talents, to occupy himself.”
With the benefit of hindsight, how did Keynes’s prognostications do? We have not yet reached the year 2030, but it is already clear that Keynes’s optimistic projection about living standards was prescient and, if anything, conservative. Advanced nations like the United States and United Kingdom are on track to reach and perhaps even exceed the four- to eight-fold increase that Keynes forecast. But Keynes was wrong about the great rise in leisure. To be sure, people now have shorter workweeks and longer retirement than they did in Keynes’s day, but they work far more than Keynes thought they would. In the United States today, the average workweek for all employees is about 35 hours.
One development that Keynes might not have fully appreciated is that much economic growth takes the form of new goods and services that were not available in the past. We work today not only to provide ourselves food, clothing, and shelter but also to buy iPhones, flat-screen TVs, and the latest version of Grand Theft Auto. Economic growth might lead to satiation if it meant only producing more of the same goods and services, but satiation may be harder to reach if growth also means increased variety of goods and services.
Perhaps Keynes merely got the time period wrong when making his prediction about leisure. If labor productivity increases by 2 percent per year for two centuries, so that it rises to more than fiftyfold what it was in Keynes’s time, your grandchildren may well decide to cut back their work hours and enjoy the vast quantities of leisure that Keynes envisioned. If so, how will they use their time? Will they devote many hours to playing Grand Theft Auto: 2130 edition? Or will they find some more gratifying activity, maybe one that today we cannot even imagine?
Convergence
If you travel around the world, you will see tremendous variation in living standards. The world’s poor countries have average levels of income per person that are less than one-tenth the average levels in the world’s rich countries. These differences in income are reflected in almost every measure of the quality of life—from the prevalence of TVs, cell phones, and Internet access to clean water availability, infant mortality, and life expectancy.
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Much research has been devoted to the question of whether economies move toward each other over time. In particular, do economies that start off poor subsequently grow faster than economies that start off rich? If they do, then the world’s poor economies will tend to catch up with the world’s rich economies. This process of catch-up is called convergence. If convergence does not occur, then countries that start off behind are likely to remain poor.
The Solow model makes clear predictions about when convergence should occur. According to the model, whether two economies will converge depends on why they differ in the first place. On the one hand, suppose two economies happen by historical accident to start off with different capital stocks, but they have the same steady state, as determined by their saving rates, population growth rates, and efficiency of labor. In this case, we should expect the two economies to converge; the poorer economy with the smaller capital stock will naturally grow more quickly to reach the steady state. (In a Case Study in Chapter 8, we applied this logic to explain rapid growth in Germany and Japan after World War II.) On the other hand, if two economies have different steady states, perhaps because the economies have different rates of saving, then we should not expect convergence. Instead, each economy will approach its own steady state.
Experience is consistent with this analysis. In samples of economies with similar cultures and policies, studies find that economies converge to one another at a rate of about 2 percent per year. That is, the gap between rich and poor economies closes by about 2 percent each year. An example is the economies of individual American states. For historical reasons, such as the Civil War of the 1860s, income levels varied greatly among states at the end of the nineteenth century. Yet these differences have slowly disappeared over time. This convergence can be explained with the Solow model under the assumption that those state economies had different starting points but are approaching a common steady state.
In international data, a more complex picture emerges. When researchers examine only data on income per person, they find little evidence of convergence: countries that start off poor do not grow faster on average than countries that start off rich. This finding suggests that different countries have different steady states. If statistical techniques are used to control for some of the determinants of the steady state, such as saving rates, population growth rates, and accumulation of human capital (education), then once again the data show convergence at a rate of about 2 percent per year. In other words, the economies of the world exhibit conditional convergence: they appear to be converging to their own steady states, which in turn are determined by such variables as saving, population growth, and human capital.2
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Factor Accumulation Versus Production Efficiency
As a matter of accounting, international differences in income per person can be attributed to either differences in the factors of production, such as the quantities of physical and human capital, or differences in the efficiency with which economies use their factors of production. That is, a worker in a poor country may be poor because she lacks tools and skills or because the tools and skills she has are not being put to their best use. To describe this issue in terms of the Solow model, the question is whether the large gap between rich and poor is explained by (1) differences in capital accumulation (including human capital) or (2) differences in the production function.
Much research has attempted to estimate the relative importance of these two sources of income disparities. The exact answer varies from study to study, but both factor accumulation and production efficiency appear important. Moreover, a common finding is that they are positively correlated: nations with high levels of physical and human capital also tend to use those factors efficiently.3
There are several ways to interpret this positive correlation. One hypothesis is that an efficient economy may encourage capital accumulation. For example, a person in a well-functioning economy may have greater resources and incentive to stay in school and accumulate human capital. Another hypothesis is that capital accumulation may induce greater efficiency. If there are positive externalities to physical and human capital, then countries that save and invest more will appear to have better production functions (unless the research study accounts for these externalities, which is hard to do). Thus, greater production efficiency may cause greater factor accumulation, or the other way around.
A final hypothesis is that both factor accumulation and production efficiency are driven by a common third variable. Perhaps the common third variable is the quality of the nation’s institutions, including the government’s policymaking process. As one economist put it, when governments screw up, they screw up big time. Bad policies, such as high inflation, excessive budget deficits, widespread market interference, and rampant corruption, often go hand in hand. We should not be surprised that economies exhibiting these maladies both accumulate less capital and fail to use the capital they have as efficiently as they might.
CASE STUDY
Good Management as a Source of Productivity
Incomes vary around the world in part because some nations have higher production efficiency than others. A similar phenomenon is observed within nations: some firms exhibit greater production efficiency than others. Why might that be?
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One possible answer is management practices. Some firms are well run; others less so. A well-run firm uses state-of-the-art operations, monitors the performance of its workers, sets challenging but reasonable targets for performance, and provides incentives for workers to put forth their best efforts. Good management means that a firm is getting the most it can from the factors of production it uses.
An influential study by Nicholas Bloom and John Van Reenen documents the importance of good management, as well as some of the reasons that not all firms have it. Bloom and Van Reenen began by surveying 732 medium-sized manufacturing firms in four nations: the United States, the United Kingdom, France, and Germany. They asked various questions about how firms were managed and then graded each firm on how well it conformed to best practices. For example, a firm that said it promoted employees on the basis of performance was graded higher than one that said it promoted employees on the basis of how long they had been at the firm.
Perhaps not surprisingly, Bloom and Van Reenen report substantial heterogeneity in the quality of management. In each of the four countries, some firms are well run and some are badly run. More noteworthy is that the distribution of management quality differed substantially across the four nations. Firms in the United States have the highest average grade, followed by Germany, then France, and finally the United Kingdom. Much of the cross-country variation comes from the prevalence of especially badly run firms: firms with the lowest management grades are much more common in the United Kingdom and France than they are in the United States and Germany.
The study’s next finding is that these management grades are correlated with measures of firm performance. Holding other things equal (such as the size of the firm’s capital stock and work force), well-managed firms have more sales, greater profits, higher stock market values, and lower bankruptcy rates.
If good management leads to all these desirable outcomes, why don’t all firms adopt the best practices? Bloom and Van Reenen offer two explanations for the persistence of bad management.
The first is the absence of competition. When a firm with poor management practices is shielded from vigorous competition, its managers can take the easy life and muddle through. By contrast, when a firm operates in a highly competitive market, bad management tends to lead to losses, which eventually induce the firm to close its doors. As a result, in competitive markets, only firms with good management survive. One determinant of competition is openness to trade: when firms have to compete with similar firms around the world, it is hard to maintain bad management practices.
A second explanation for the persistence of bad management is primogeniture—the tradition of some family-owned firms to appoint as chief executive officer (CEO) the family’s eldest son. This practice means that the CEO position may not be going to the person who is most qualified for it. Moreover, if the eldest son knows he will get the job by virtue of birth order, rather than having to compete for it with professional managers or at least other family members, he may have less incentive to put in the effort necessary to become a good manager. Indeed, Bloom and Van Reenan report that firms with eldest sons as CEOs are more likely to earn poor management grades. They also find that primogeniture is far more common in the United Kingdom and France than it is in the United States and Germany, perhaps because of the long-lasting influence of the Norman tradition.
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The bottom line from this study is that differences in management practices can help explain why some nations have higher productivity and thus higher incomes than others. These differences in management, in turn, may be traced to differences in degrees of competition and historical traditions.4 