Creating a Learning Society
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Creating a Learning Society

A New Approach to Growth, Development, and Social Progress

Joseph E. Stiglitz, Bruce Greenwald, Philippe Aghion, Kenneth Arrow, Robert Solow, Michael Woodford

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eBook - ePub

Creating a Learning Society

A New Approach to Growth, Development, and Social Progress

Joseph E. Stiglitz, Bruce Greenwald, Philippe Aghion, Kenneth Arrow, Robert Solow, Michael Woodford

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It has long been recognized that an improved standard of living results from advances in technology, not from the accumulation of capital. It has also become clear that what truly separates developed from less-developed countries is not just a gap in resources or output but a gap in knowledge. In fact, the pace at which developing countries grow is largely a function of the pace at which they close that gap.

Thus, to understand how countries grow and develop, it is essential to know how they learn and become more productive and what government can do to promote learning. In Creating a Learning Society, Joseph E. Stiglitz and Bruce C. Greenwald cast light on the significance of this insight for economic theory and policy. Taking as a starting point Kenneth J. Arrow's 1962 paper "Learning by Doing," they explain why the production of knowledge differs from that of other goods and why market economies alone typically do not produce and transmit knowledge efficiently. Closing knowledge gaps and helping laggards learn are central to growth and development. But creating a learning society is equally crucial if we are to sustain improved living standards in advanced countries.

Combining accessible prose with technical economic analysis, Stiglitz and Greenwald provide new models of "endogenous growth," up-ending thowhe thinking about both domestic and global policy and trade regimes. They show well-designed government trade and industrial policies can help create a learning society, and how poorly designed intellectual property regimes can retard learning. They also explain how virtually every government policy has effects, both positive and negative, on learning, a fact that policymakers must recognize. They demonstrate why many standard policy prescriptions, especially those associated with "neoliberal" doctrines focusing on static resource allocations, have impeded learning. Among the provocative implications are that free trade may lead to stagnation whereas broad-based industrial protection and exchange rate interventions may bring benefits—not just to the industrial sector, but to the entire economy.

The volume concludes with brief commentaries from Philippe Aghion and Michael Woodford, as well as from Nobel Laureates Kenneth J. Arrow and Robert M. Solow.

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Année
2014
ISBN
9780231525541
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FROM ROMAN times, when the first data on per-capita output are available, until 1800, average human standards of living increased only imperceptibly if at all (see, e.g., Maddison 2001). Consumption for the great majority of human beings consisted predominantly of food, and food was largely limited to staples—rice, wheat, and other grains. Housing entailed barnlike living conditions with no privacy, and climate control consisted only of necessary heat in winter. Clothing was utilitarian and rarely involved more than single outfits with the seasonal addition of overclothes. Medical care was almost nonexistent. Travel was rare, largely local, difficult, and uncomfortable. Recreation was self-generated and primitive. Only a small aristocratic minority enjoyed what we would consider today an appropriate human standard of living—varieties of fresh food, including meat; private, well-warmed accommodations; multiple sets of clothing for varied occasions; rudimentary personal and medical care; and opportunities for travel and sophisticated entertainment.
Beginning in 1800 and accelerating markedly after the mid-to-late nineteenth century, that privileged standard of living began to diffuse throughout Europe, North America, and Australia. The impact of this change is apparent even in critical contemporary commentaries. The Communist Manifesto is in many ways a paean to the potential of the newly apparent economic progress—the benefits of which had not yet been widely shared.
In the twentieth century, elite standards of living became pervasive in Europe, North America, Australia, and many parts of Asia; a trend which continues in much of Asia today.
The significance of these transformations can be seen in another way: until the beginning of the nineteenth century, most individuals spent most of their time meeting the basic necessities of life—food, shelter, clothing. Today, for most of those in the advanced industrial countries—and for an increasing number in the emerging markets—satisfying these basic necessities of life takes but a few hours of work a week. Individuals can choose how to spend the “extra” time available: to work, to earn enough to consume more (whether higher quality “necessities” or luxuries) or to enjoy more leisure.1,2
What was the source of these societal transformations? Was it capital accumulation or technological progress? Although economists, such as Schumpeter (1943), had identified the major source of these transformative developments as technological progress, it was not until Robert Solow (1957) that there was a way of quantifying the relative importance of capital accumulation versus technical progress. Changes in capital intensity could account for at most a third of changes in output per worker. The remainder was attributable largely to various forms of technical progress.3
Subsequent literature suggested that the quantification was perhaps less robust than seemed initially the case, partly because the measurement of key inputs (capital, human capital) was more difficult and problematic than had at first been realized, partly because the underlying model, entailing a constant returns to scale aggregate production function and full competition, seemed more questionable.4 Some of the difficulties of parsing out the sources of growth was that they were intertwined—new machines (investment) were required to implement new technologies.5 Still, there is no doubt that there have been enormous increases in productivity and that advances in technology as well as “learning to do things better” have played a critical role in these increases in productivity. For our purposes, that is all that matters.6
Not only is the pace of learning (innovation) the most important determinant of increases in standards of living, the pace itself is almost surely partially, if not largely, endogenous. The speed of progress has differed markedly both over time and across countries, and while we may not be able to explain all of this variation, it is clear that government policies have played a role. Learning is affected by the economic and social environment and the structure of the economy, as well as public and private investments in research and education. The fact that there are high correlations in productivity increases across industries, firms, and functions within firms suggests that there may be common factors (environmental factors, public investments) that have systemic effects or that there may be important spillovers from one learner/innovator to others. But the fact that there are large, persistent differences across countries and firms—at the microeconomic level, large discrepancies between best, average, and worst practices—implies that knowledge does not necessarily move smoothly either across borders or over firm boundaries.
All of this highlights that one of the objectives of economic policy should be to create economic policies and structures that enhance both learning and learning spillovers; creating a learning society is more likely to increase standards of living than is making small, one time improvements in economic efficiency or sacrificing consumption today to deepen capital.7
And this is even more so for developing countries. Much of the difference in per capita income between these countries and the more advanced is attributable to differences in knowledge. Policies that transformed their economies and societies into “learning societies” would enable them to close the gap in knowledge, with marked increases in incomes.8 Development entails learning how to learn (Stiglitz 1987c).
Solow, in his seminal paper on the economics of growth (1956), had, for simplicity, modeled the rate of technological progress as fixed and exogenous, unaffected by the decisions of firms. This left unexplained the most important source of increases in living standards—and thus provided little guidance on how economic policy might increase that pace. Thus, Solow’s 1957 paper showed that what his 1956 paper focused on, capital accumulation, was relatively unimportant; what was important was what his 1956 paper took as simply given. Not surprisingly, soon after Solow’s pioneering work, there developed a large literature in growth theory attempting to “endogenize” technological change—starting at least as early as the 1960s,9 with further progress being made during the 1980s.10
The best work tried, of course, to base the analysis of aggregate (macro) behavior on micro-foundations. There is, by now, a large literature on the microeconomics of technological progress,11 but many of the insights of that literature have not been incorporated into the macroeconomic growth models, which often take a simplistic view, ignoring, for instance, sectoral differences in the pace of innovation, the multitude of ways in which progress occurs, and the interrelationships among them and alternative policies. To deal with the complexities posed by endogenous growth, and the challenge of deriving long-run steady-state growth, much of the literature has focused on parameterizations that turn out to be very, very special. While some of the literature has recognized that when innovation is endogenous, markets are not likely to be fully competitive, the interplay between market structure and innovation is typically not at the center of discussion. Is even the kind of competition that Schumpeter envisaged really viable? Some of the literature makes assumptions that virtually prejudge the conclusions: If trade is assumed to enhance learning (and more effectively than a corresponding amount of domestic production), then trade barriers have an adverse effect on economic growth. As we show, alternative (and we would argue more plausible) assumptions about the innovative process suggest that some trade restrictions may be desirable.
If our contention that the success of modern economies is due to innovation and learning is correct, then understanding the processes of learning and innovation, and how policy can affect its pace, should be at the center of economic analysis.12 We can...

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