World Yearbook of Education 1965: The Education Explosion

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A few more studies did of course find either weak or lack of relationship between education and economic growth. For example, Walters concluded that the economic growth rates between were least Influenced by primary and secondary enrollment ratios in , and by growth rates in primary and secondary enrollments during , even though she found high correlation between primary enrollment in and log 6NP per capita in and in An East African case study Rado and Jolly also found no consistent relationship between economic development and secondary and higher education.

Kanamori found that education accounts hardly one percent of the growth in Japan during Criticism was also levelled on the marginal productivity hypothesis taking wages as reflective of productivity e. But these theories lack strong empirical support. The screening role of education is found to be confined, if at all, to short periods, confining to the initial stages of employment.

Quantitative evidence on the whole is still overwhelmingly in support of the human capital theory, a basic tenet of which is that education contributes positively to economic growth. That education contributes to growth in output was clearly reaffirmed further by studies that considered not monetary benefits, but physical real output benefits, particularly in agriculture. Let us briefly look at this. Hayami and Ruttan , p. Surveying evidence from 31 countries.

Some of this evidence is stunmarized in Table 7. The other Important details on the empirical evidence on the contribution of education to agricultural productivity can be noted as follows: o Education significantly effects methods of production, use of modern inputs like fertilizers, seeds and machines, and selection of crops, o Wages among landless agricultural laborers are also positively influenced by differences in their levels of education.

For example in India, elementary education was the threshold level during the s, while It was secondary level during the s. If we divide the research into two catesories for a critical survey, viz. It is quit 3 possible that in the areas of farming under better technological environment, the impact of education could be much smaller than estimated in aggregate situations.

Simple numeracy may be adequate for traditional farming, numeracy and rudimentary literacy may be needed for farming with intermediate technology. Formal education of secondary and above that gives a basic knowledge of chemistry, biology, etc. It is clear that numeracy is the basic pre-requisite having most significant effect on farm efficiency.

Looking at the same problem in another way, there exists a gap between best practice of fanning and the current practice. Economic conditions, particularly the level of technology and agricultural prices significantly explain the best practice while the low levels of current practice could be attributed to, inter alia low levels of literacy and education.

The path from current to the best practice is not a smooth one, as both go on changing in a dynamic sense. Their relative importance, however, is determined by the gap between the best and the current practices. But in all cases, literacy and basic education form minimum conditions. In general, the role of research in agricultural development in any economy is quite significant.

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Advancement in research is a decisive factor in achieving increases in crop production throughout the world. In some countries the returns to investment in research are as high as 40 percent. Some other researchers estimated it to be 63 percent. The green revolution in India could be attributed largely to research and development activities besides, of course, to levels of literacy and education of the farmers, of course, basic education prepared people for change. Basically impact of education is not instantaneous; it is sequential. Production function approaches may not only assume that it has not only instantaneous effect, but also that it can be v xplained with the 39 28 help of static data analysis.

Perhaps the research In the area can be classified into two categories: one based on production function approaches and the other discrete approaches.

Fortunately, both yield not altogether Inconsistent results. The results on the whole reassert that education's effects on physical output are substantial, leading to Improvement In productivity and economic growth. Is proved to be not superficial. Education contrlbutPs towards enhancement of productivity and thereby In wages and economic growth.

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The contribution of education to the other facets of development like Improvements In health, fertility control, Improvement In mortality and life expectancy etc.. Is well documented. In fact It Is argued that these benefits exceed the direct economic benefits of education. However, we do not refer to these aspects here, and In the following section concentrate on the role of education In Income distribution. Even prior to Adam Smith, we find references In the literature to the equity role of education.

See also Behrman Nehenla Green and James Stewart of the Mercantilist period also advocated mass education so as to increase agricultural productivity in particular and society's progress in general. Lord Palmerston favored the spread of literacy. Horace Mann, a typical example of these reformers, viewed the school as an effective instrument to achieve justice and equality of opportunity and remove poverty.

As early as in the role of education in reducing poverty was clearly recognized in Russia: "An increase o. This aspect his received the attention of the empirical researchers since the beginning of the s. Education is argued to be vital to increase economic growth and to improve economic equality Harbison Analyzing the problem in his numerous works, both from a positive point of view Tinbergen and a normative point of view Tinbergen and , concluded that human capital is one of the most Important determinants of income inequality.

The relationship between education and income distribution is, however, somewhat complex, as education's effect on Income inequality 41 30 depends upon not only the way education is planned, developed and financed, but also it is contingent upon the socio economic factors, employment probabilities, wage structure, the fiscal base etc. For instance, changes in the pay olfs to different levels of education also influence earnings distribution.

If returns to higher education fall, relative to returns to investment in primary education, earnings distribution is likely to improve; on the other hand, if the opposite occurs, the increasing returns to higher education relative to returns to lower levels of education reflect a trend towards greater inequality. As Knight and Sabot , p. Whether it raises or lowers inequality, ceteris pari bus , depends on the relative sizes of the different educational categories, their relative mean wages, and their relative wage dispersions.

This will produce "a shift from low paid, unskilled employment to high paid, skilled employment. This shift, produces higher labor incomes, a reduction in skill differentials, and an increase in the share of wages in total catput" Ahluwalia b, p. The increase in the number of more educated and skilled people 'ill increase the ratio of such people and decrease the ratio of less educated people in the total labor force.

Is the Demographic Dividend an Education Dividend? | SpringerLink

In the labor market over supply of highly educated people results, given no change in demand, in lowering their wages and increase in the wages of those with less education, thus on the whole contributes to dlmunition in inccm differences in the labor market. Thus expansion of education effects not only the wages ol those who receive better education, but also 31 of those who do not.

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  • In addition to that earnings distribution can be effected by education, as earnings and education are highly related, education may compensate for adverse socio economic background and open up better socio economic opportunities for the weaker sections of the society leading to faster mobility and higher wages.

    The financing pattern of education also influences income distribution. As education is largely state financed, the composition of relative shares of various income groups in state revenues, and the relative benefits received by various groups from education influences, if not exactly determines, income distribution. We examine some of these aspects in this and the following sections. We start with a few cross nation studies. Later we briefly refer to a few micro studies. Distribution of public subsidies to education forms the content of the next section.

    Accordingly they concluded that Improvement of human resources was the only acceptable strategy for the decades ahead Chiwsick suggested that inequality in earnings should be positively related to inequality in investment in human capital, mean level of investment in human capital, average level of rate of return to human capital and inequality in rate of return to human capital.

    Regressing 43 32 alternative earnings Inequality measures on Income per capita, rate of growth In Incomes and educational Inequality, Chlswlck based on data on a small sample of 9 countries found that schooling Inequality Is directly related to earnings Inequality, and hence Improvement In schooling Inequality could be an equalizer, Chlswlck used a different variable for schooling, viz, , Interaction of rate of return to education and variance of schooling.

    In examining Income Inequalities in the US and Canada around , and found this Interaction variable to be having a strong positive effect on Income Inequalities. Chenery and Syrquin based on a sample of 50 countries came to a similar conclusion when adjusted enrollments in schools primary and secondary levels were used to explain income distribution. Ahluwalia also found significant positive relationships between school enrollments and income equality. Using cross-country data on 66 countries, Ahluwalia fitted a regression equation.

    See also Fields c. ERIC 44 33 middle groups, and more importantly that primary school enrollment ratio is more significant in explaining the income share of the bottom 40 percent population, irtiile the secondary school enrollment rate is more significant in explaining that of the middle 40 percent. The secondary enrollment ratio and the income share of the top 20 percent are negatively related, suggesting that expansion of secondary education leads to redistribution of income away from top income quintile, Ahluwalia b; also a used literacy variable also in the regression equation and provided more details.

    An increase in the literacy rate from 10 percent to 60 percent is associated with a 2. Similarly, an increase in the secondary enrollment from 10 percent to 40 percent is associated with an increase of 4,6 percentage points in the income share of the middle 40 percent population.