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One important example of this is the twentieth century U. Another would be those of certain East Asian economies since World War II, as documented in the growth accounting analysis by Young of the substantial contributions of their rising educational attainment to their rapid growth rates. Another sub-set of cases corresponding to more modest increases in schooling can be interpreted as applying either to countries experiencing schooling increases focussed at the elementary level, as in much of Western Europe over the nineteenth century. However, whether there were increases in output per capita corresponding to these more modest increases in educational attainment remains to be established.

The fourth situation is one in which economic growth has stagnated despite the presence of marked improvements in educational attainment. Possible examples of this situation would include the early rise of literacy in some Northern European areas, such as Scotland and Scandinavia, in the seventeenth and eighteenth centuries see Houston ; Sandberg and some regions of Africa and Asia in the later twentieth century see Pritchett One explanation of this situation is that it reflects instances in which any positive impact of educational attainment is small relative to other influences having an adverse impact.

But one can also interpret it as reflecting situations in which incentive structures direct educated people into destructive and transfer activities inimical to economic growth see North ; Baumol ; Murphy, Shleifer, and Vishny Cross-country studies of the relationship between changes in schooling and growth since have yielded conflicting results which in itself could be interpreted as supporting the presence of some mix of the four situations just surveyed. A number of studies have found at best a weak relationship between changes in schooling and growth Pritchett ; Bils and Klenow ; others have found a stronger relationship Topel Much seems to depend on issues of measurement and on how the relationship between schooling and output is specified Temple b; Woessmann , Whether education contributes to economic growth can be seen as depending on two factors, the extent to which educational levels improve over time and the impact of education on economic productivity.

The first factor is a topic for extended discussion in its own right and no attempt will be made to consider it in depth here. Factors commonly considered include rising income per capita, distribution of political power, and cultural influences Goldin , Lindert , Mariscal and Sokoloff , Easterlin ; Mitch The issue of endogeneity of determination has often been raised with respect to the determinants of schooling.

Thus, it is plausible that rising income contributes to rising levels of schooling and that the spread of mass education can influence the distribution of political power as well as the reverse. While these are important considerations, they are sufficiently complex to warrant extended attention in their own right. Insofar as schooling improves general human intellectual capacities, it could be seen as having a universal impact irrespective of context.

However, Rosenzweig ; has noted that the even the general influence of education on individual productivity or adaptability depend on the complexity of the situation. He notes that for agricultural tasks primarily involving physical exertion, no difference in productivity is evident between workers according to education levels; however, in more complex allocative decisions, education does enhance performance. This could account for findings that literacy rates were low among cotton spinners in the British industrial revolution despite findings of substantial premiums to experience Sanderson ; Boot However, other studies have found literacy to have a substantial positive impact on labor productivity in cotton textile manufacture in the U.

A more macro influence is the changing sectoral composition of the economy. It is common to suggest that the service and manufacturing sector have more functional uses for educated labor than the agricultural sector and hence that the shift from agriculture to industry in particular will lead to greater use of educated labor and in turn to require more educated labor forces.

However, there are no clear theoretical or empirical grounds for the claim that agriculture makes less use of educated labor than other sectors of the economy.

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In fact, farmers have often had relatively high literacy rates and there are more obvious functional uses for education in agriculture in keeping accounts and keeping up with technological developments than in manufacturing. Nilsson et al argue that the process of enclosure in nineteenth-century Sweden, with the increased demands for reading and writing land transfer documents that this entailed, increased the value of literacy in the Swedish agrarian economy. The findings noted above that those in cotton textile occupations associated with early industrialization in Britain had relatively low literacy rates is one indication of the lack of any clear cut ranking across broad economic sectors in the use of educated labor.

Changes in the organization of decision making within major sectors as well as changes in the composition of production within sectors are more likely to have had an impact on demands for educated labor. Thus, within agriculture the extent of centralization or decentralization of decision making, that is the extent to which farm work forces consisted of farmers and large numbers of hired workers or of large numbers of peasants each with scope for making allocative decisions, is likely to have affected the uses made of educated labor in agriculture.

Technological advance would have tended to boost the demand for more skilled and educated labor if technological advance and skills are complementary, as is often asserted. However, there is no theoretical reason why technology and skills need be complementary and indeed concepts of directed technological change or induced innovation would suggest that in the presence of relatively high skill premiums, technological advance would be skill saving rather than skill using.

Goldin and Katz have argued that the shift from the factory to continuous processing and batch production associated with the shift of power sources from steam to electricity in the early twentieth century lead to rising technology skill complementarity in U. It remains to be established how general this trend has been. It could be related to the distinction made between the dominance in the United States of extensive growth in the nineteenth century due to the growth of factors of production such as labor and capital and the increasing importance of intensive growth in the twentieth century.

Intensive growth is often associated with technological advance and a presumed enhanced value for education Abramovitz and David Some analysts have emphasized the importance of capital-skill complementarity. For example, Galor and Moav point to the level of the physical capital stock as a key influence on the return to human capital investment; they suggest that once physical capital stock accumulation surpassed a certain level, the positive impact of human capital accumulation on the return to physical capital became large enough that owners of physical capital came to support the rise of mass schooling.

They cite the case of schooling reform in early twentieth century Britain as an example. Even sharp declines in the premiums to schooling do not preclude a significant impact of education on economic growth. Economists have generalized the impact of schooling on labor force quality into the concept of human capital. Human capital refers to the investments that human beings make in themselves to enhance their economic productivity. These investments can take on many forms and include not only schooling but also apprenticeship, a healthy diet, and exercise, among other possibilities.

Some economists have even suggested that more amorphous societal factors such as trust, institutional tradition, technological know how and innovation can all be viewed as forms of human capital Temple a; Topel ; Mokyr Thus broadly defined, human capital would appear as a prime candidate for explaining much of the difference across nations and over time in output and economic growth. However, gaining much insight into the actual magnitudes and the channels of influence by which human capital might influence economic growth requires specification of both the nature and determinants of human capital and how human capital affects aggregate production of an economy.

Much of the literature on human capital and growth makes the implicit assumption that some sort of numerical scale exists for human capital, even if multidimensional and even if unobservable. This in turn implies that it is meaningful to relate levels and changes of human capital to levels of income per capita and rates of economic growth. Given the multiplicity of factors that influence human knowledge and skill and in turn how these influence labor productivity, difficulties would seem likely to arise with attempts to measure aggregate human capital similar to those that have arisen with attempts to specify and measure the nature of human intelligence.

Woessmann , provides useful surveys of some of the issues involved in attempting to specify human capital at the aggregate level appropriate for relating it to economic growth. One can distinguish between approaches to the measurement of human capital that focus on schooling, as in the discussion above, and those that take a broader view. Broad view approaches try to capture all investments that may have improved human productivity from whatever source, including not just schooling but other productivity enhancing investments, such as on-the-job training.

The basic premise of broad view approaches is that for an aggregate economy, the income going to labor over and above what that labor would earn if it were paid the income of an unskilled worker can be viewed as human capital. This measure can be constructed in various ways including as a ratio using unskilled labor earnings as the denominator as in Mulligan and Sala-I-Martin or using the share of labor income not going as compensation for unskilled labor as in Crafts and Mitch Mulligan and Sala-I-Martin point to some of the major index number problems that can arise in using this approach to aggregate heterogeneous workers.

Crafts and Mitch find that for Britain during its late eighteenth and early nineteenth century industrial revolution between one-sixth and one-fourth of income per capita can be attributed to human capital measured as the share of labor income not going as compensation for unskilled labor.

One approach that has been taken recently to estimate the role of human capital differences in explaining international differences in income per capita is to consider changes in immigrant earnings between origin and destination countries along with differences between immigrant and native workers in the destination country.

Olson suggested that the large increase in earnings of immigrants commonly observed in moving from a low income to a high income country points to a small role for human capital in explaining the wide variation in per capita income across countries. Hendricks has used differences between immigrant and native earnings in the U. One possible source of such skills is through the informal acquisition of human capital through on-the-job experience.

Insofar as work has been common from early adolescence onwards, the issue arises of why the aggregate stock of skills acquired through experience would vary over time and thus influence rates of economic growth. Some types of on-the-job experience which contribute to economic productivity, such as apprenticeship, may entail an opportunity cost and aggregate trends in skill accumulation will be influenced by societal willingness to incur such opportunity costs.

Insofar as schooling continues through adolescence, this can interfere with the accumulation of workforce experience. DeLong, Goldin and Katz note the tradeoff between rising average years of schooling completed and decreasing years of labor force experience in influencing labor force quality of the U.

Connolly has found that informal experience played a relatively greater role in Southern economic growth than for other regions of the United States. Hansen has also distinguished the academically-oriented secondary schooling the United States developed in the late nineteenth and early twentieth century from the vocationally-oriented schooling and apprenticeship system that Germany developed over the same time period. Goldin argues that in the United States the educational system developed general abilities suitable for the greater opportunities for geographical and occupational mobility that prevailed there, while specific vocational training was more suitable for the more restricted mobility opportunities in Germany.

Little evidence exists on whether long-term trends in informal opportunities for skill acquisition have influenced growth rates. Economists commonly claim that education yields benefits to society over and above the impact on labor market productivity perceived by the person receiving the education. These benefits can include impacts on economic productivity, such as impacts on technological advance.

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They can also include non-labor market benefits. Thus McMahon , 11 in his assessment of the social benefits of education includes not only direct effects on economic productivity but also impacts on a population growth rates and health b democratization, political stability, and human rights, c the environment, d reduction of poverty and inequality, e crime and drug use, and f labor force participation. While these effects may appear to involve primarily non-market activity and thus would not be reflected in national output measures and growth rates, factors such as political stability, democratization, population growth, and health have obvious consequences for prospects for long-term growth.

However, allowance should be made for the simultaneous influence of the distribution of political power and life expectancy on societal investments in schooling. For the period since , numerous studies have employed cross country variation in various estimates of human capital and income per capita to directly estimate the impact of human capital on levels of income per capita and growth.

A central goal of many such estimates is to see if there are externalities to education on output over and above the private returns estimated from micro data. The results have been conflicting and this has been attributed not only to problems of measurement error but also to differences in specification of human capital and its impact on growth. There does not appear to be strong evidence of large positive externalities to human capital Temple a.

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Furthermore, McMahon reports some empirical specifications which yield substantial indirect long-run effects. For the period before , limits on the availability of data on schooling and income have limited the use of this empirical regression approach. Thus, any discussion of the impact of externalities of education on production is considerably more conjectural. The central role of government, religious, and philanthropic agencies in the provision of schooling suggests the presence of externalities. Politicians and educators more frequently justified government and philanthropic provision of schooling by its impacts on religious and moral behavior than by any market failure resulting in sub-optimal provision of schooling from the standpoint of maximizing labor productivity.

Thus, Adam Smith in his discussion of mass schooling in The Wealth of Nations, places more emphasis on its value to the state in enhancing orderliness and decency while reducing the propensity to popular superstition than on its immediate value in enhancing the economic productivity of the individual worker. The approaches considered thus far relate changes in educational attainment of the labor force to changes in output per worker.

The argument for doing so is that a high but unchanging level of educational attainment should contribute to growth by facilitating creativity, innovation and adaptation to change as well as facilitating the ongoing maintenance and improvement of skill in the workforce.

Topel has argued that there may not be any fundamental difference between the two types of approach insofar as ongoing sources of productivity advance and adaptation to change could be viewed as reflecting ongoing improvements in human capital. The paucity of data on schooling attainment has limited the empirical examination of the relationship between levels of human capital and economic growth for periods before the late twentieth century. However, Sandberg has argued, based on a descriptive comparison of economies in various categories, that those with high levels of schooling in subsequently experienced faster rates of economic growth.

Bowman and Anderson , a much earlier study based on international evidence for the mid-twentieth century, can be interpreted in the spirit of relating levels of education to subsequent levels of income growth. Their reading of the cross-country relationship between literacy rates and per capita income at mid-twentieth-century was that a threshold of 40 percent adult literacy was required for a country to have a per capita income above dollars. Some have ahistorically projected back this literacy threshold to earlier centuries although the Bowman and Anderson proposal was intended to apply to mid-twentieth century development patterns.

The mechanisms by which the level of schooling would influence the rate of economic growth are problematic to establish.

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One can distinguish two general possibilities. One would be that higher levels of educational attainment facilitate adaptation and responsiveness to change throughout the workforce. This would be especially important where a large percentage of workers are in decision making positions such as an economy composed largely of small farmers and other small enterprises.

The finding of Foster and Rosenzweig for late twentieth century India that the rate of return to schooling is higher during periods of more rapid technological advance in agriculture would be consistent with this. Likewise, Nilsson et al find that literacy was important for nineteenth-century Swedish farmers in dealing with enclosure, an institutional change.

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The other possibility is that higher levels of educational attainment increase the potential pool from which an elite group responsible for innovation can be recruited. Recently, Labuske and Baten have found that international rates of patenting are related to secondary enrollment rates.

Two issues have arisen in the recent theoretical literature regarding specifying relationships between the level of human capital and rates of economic growth. This specification of the impact of the initial level of human capital allows for ongoing and unbounded growth of human capital and through this its ongoing contribution to economic growth.

Such ongoing growth of human capital could occur through improvements in the quality of schooling or through enhanced improvements in learning from parents and other informal settings. While it might be plausible to suppose that improved education of teachers will enhance their effectiveness with learners, it seems less plausible to suppose that this enhanced effectiveness will increase unbounded in proportion to initial levels of education Lord , A second issue is that insofar as higher levels of human capital contribute to economic growth through increases in research and development activity and innovative activity more generally, one would expect the presence of scale effects.

Economies with larger populations holding constant their level of human capital per person should benefit from more overall innovative activity simply because they have more people engaged in innovative activity. Jones has pointed out that such scale effects seem implausible if one looks at the time series relationship between rates of economic growth and those engaged in innovative activity.