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Education and Development

It is safe to say that the current living standard is the highest since the beginning of human history.We have achieved unprecedented levels of life expectancy, income per capita, and educational attainment over the past few decades. This unprecedented prosperity and achievement would probably not have been attained without the continuous technological progress of the peaceful era after World War II. Most people would acknowledge the role of education in the advancement of our socioeconomic development. The value of education is widely studied. For example, it has been found that better-educated farmers are more responsive to new technical possibilities and that better-educated women are more effective at allocating resources within the family, including those that enhance child survival (Cleland and Van Ginneken 1988; Lockheed et al. 1980; Mensch et al. 1985; Schultz 1979). This article examines the empirical relationship between education and development during recent decades. Included are a brief description of the history of world education and socioeconomic development since the early 1960s as well as discussions of theoretical background, data sources, research methodology, and findings.

Educational Development in Recent Decades

During the past few decades, a rapid expansion of educational provision at primary, secondary, and tertiary levels in much of the world has been documented (Shavit and Blossfeld 1993; World Bank 1998). Column 3 of Table 1 shows the primary school gross enrollment ratio from 1960 through 1990. The gross enrollment ratio is the ratio of total primary school enrollment, regardless of age, to the population of the age group that officially corresponds to the ‘‘usual’’ primary education years (World Bank 1998). The ratio for the world as a whole has increased from 86 per 100 population in primary school age group in 1960 to a virtually universal rate in 1990. Impressive gains have been observed for many areas of the world. In 1960, for example, the primary school enrollment ratio was only 39 per 100 for sub-Saharan Africa; by 1990, it had increased to 73 percent.

Similarly, the secondary school gross enrollment ratio for the world as a whole increased from 27 percent in 1960 to 54 percent in 1990. Progress was especially impressive in the Middle East and North Africa, where the enrollment ratio surged from 12 percent in 1960 to 57 percent in 1990. This gross enrollment ratio is lowest in sub-Saharan Africa, where only 4 percent and 22 percent of the population were enrolled in secondary school in 1960 and 1990, respectively.

One important reason for such educational expansion has been the adoption of a compulsory education policy by many countries. Egalitarian values regarding education have also emerged with increasing of modernization. According to Lenski (1966), the Western industrial nations began to subscribe to an egalitarian-democratic ideology, in which equality of educational opportunity is highly valued, after industrialization took place. Presumably this egalitarian-democratic ideology became part of the philosophy of the United Nations through the influence of Western countries. The United Nations General Assembly’s Universal Declaration of Human Rights, Article 26, which proclaimed education as a basic right and demanded that elementary education should be compulsory and free resulted from post-World War II expansion of the conception of education as a fundamental human right. In addition, the demand for more skilled workers in today’s economy has also played a role in the expansion of education.

Socioeconomic Development in Recent decades

As discussed earlier, the overall progress in socioeconomic development during the past few decades has pushed our living standard to the highest level ever. The World Bank defines development as follows:

Development is about people and their wellbeing— about people developing their capabilities to provide for their families, to act as stewards of the environment, to form civil societies that are just and orderly. (World Bank 1998, p. 35)

At the national level, development is generally divided into two dimensions: social and economic. Indicators of social development include life expectancy, infant mortality, and educational attainment. The most commonly used indicator for economic development is GNP per capita (the gross national product divided by midyear population).

Table 1: SOURCE: 1998 World Development Indicator, World Bank CD-ROM.

NOTE:

  • Primary enrollment ratio: The ratio of total primary school enrollment, regardless of age, to the population of the age group that officially corresponds to the ‘‘usual’’ primary education/years.

  • Secondary enrollment ratio: The ratio of total secondary school enrollment, regardless of age, to the population of the age group that officially corresponds to the ‘‘usual’’ secondary education/years.

  • Level of industrialization: The proportion of the total labor force recorded as not working in agriculture, hunting, forestry, or fishing.

  • The percentage of the total population living in urban areas.

  • GNP per capita (constant 1987 US$): Gross national product divided by midyear population.

  • #The average of U.S.A. and Canadian data.

  • *Canadian data only.

Table 1 shows world education and socioeconomic development from 1960 through 1996. The selected indicators include level of industrialization, level of urbanization, percent of population with radio, GNP per capita, infant mortality, life expectancy, population growth rate, and total fertility rate. The results are summarized below.

Level of Industrialization

Level of industrialization is defined as the percent of the total labor force employed in areas other than agriculture, hunting, forestry, and fishing. In 1960, 39 percent of the world labor force was so employed; by 1990, this figure had risen to 51 percent. Similar gains were observed for all world regions. The Middle East and North Africa posted the largest change in the level of industrialization. For example, 41 percent of the labor force in the Middle East and North Africa was employed in areas other than agriculture, hunting, forestry, and fishing in 1960; by 1990, the figure had risen to 65 percent. On the other hand, the gain in North America was low: The level of industrialization increased from 90 percent to 97 percent during the same period. It should be noted that the level of industrialization in North America started at a very high level, This accounts for the low level of gains in North America.

Level of Urbanization

Urbanization is the process whereby the proportion of people in a population who live in urban places increases. As our world moves toward being a more industrial one, more people migrate from rural to urban areas to pursue better economic opportunities. The push–pull theory of migration is often cited to account for rural-to-urban migration (Ravenstein 1898; Lee 1886). The push factors are the unfavorable internal and external conditions in the places of origin that push individuals to leave their jobs/ residences. Unfavorable internal employment conditions include lack of economic opportunities, low pay, low prospect for upward mobility, poor interpersonal relations, lack of challenge in the job, poor working environments, and so forth. Individuals in such circumstances are more likely to be pushed out of their jobs. Adverse external conditions that push individuals away from their residences/jobs, include such unfavorable structural conditions as high crime rate, pollution, and traffic congestion.

On the other hand, pull factors are favorable conditions in the new place of employment that attract individuals to migrate there. Facing the pressures of population growth and deteriorating economic opportunities, rural residents are being pushed out of their villages and attracted to urban areas, where they find a variety of economic opportunities to raise their living standard. According to Table 1, only 33 percent of the world’s population lived in urban areas in 1960; by 1996, this number had increased to 46 percent. All the world regions have experienced similar gains, with the Middle East/North Africa and Latin America/ Caribbean countries posting the largest gain (about 25 percentage points). North America ranked first in level of urbanization in 1996, with 77 percent of the population living in urban areas.

Percent of Population with a Radio

Another indicator of development is the percent of population with a radio. This indicator is an indirect measure of exposure to modern values and ideas. In 1970, only 9 percent of the world’s population had a radio; this figure had risen to 36 percent in 1990. South Asia has the lowest level of radio possession; in 1990, only 8 percent of the population in South Asia had a radio. North America has the highest level of radio possession; specifically, there were more than 1,500 radios per 1,000 population in 1990.

GNP Per Capita

GNP per capita is defined as the gross national product divided by midyear population. Based on Table 1, the GNP per capita (inconstant 1987 US$) increased for most world regions from 1970 through 1996. For example, the GNP per capita in the world increased from $2,574 in 1970 to $3,502 in 1996; in North America, it increased from $12,084 in 1970 to $18,265 in 1996; in South Asia, it increased from $233 in 1970 to $419 in 1996.

Life Expectancy

Life expectancy at birth is the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life (World Bank 1998). According to Table 1, the life expectancy at birth for the world increased from 58.7 years in 1970 to 66.7 years in 1996. The gain is found for all world regions. The Middle East and North Africa posted the largest increase in life expectancy (from 52.8 in 1970 to 67 in 1996); the progress in South Asia has also been very impressive (from about 48.8 in 1970 to 62.1 in 1996). The observed increase in life expectancy from 1970 through 1996 is a strong indication of world socioeconomic development that enables newborns to live a longer life.

Infant Mortality Rate

Infant mortality rate (IMR) is defined as the number of deaths during the first year of life per 1,000 live births. The negative relationship between infant mortality and the level of economic development is often used as a barometer for economic development (United Nations 1982). Young (1993) found strong support for this relationship in developed countries. Krikshnan (1975) and Rodgers (1979) also reported a negative relationship between infant mortality and level of economic development for developing countries. Similarly, Berg (1973) and Gaise (1979) also maintain that as a country’s GNP increases, the standard of living improves, which leads to an improvement in nutrition and health services. Preston (1976), however, notes that one should not expect to find a direct relationship between mortality and per capita income, because per capita income is an average measure and does not take the distribution of income into account. The effects of income on mortality are likely to be greater at the lower end of the income distribution.

Table 1 shows that the world’s IMR decreased from 98 in 1970 to 54 in 1996. All world regions experience a decreased IMR during the same period; for example, the IMR decreased from 137 to 91 for sub-Saharan Africa. The progress in reducing IMR was especially prominent in the Middle East and North Africa, where the IMR decreased from 134 in 1970 to 50 in 1996. North America had the lowest IMR—7—in 1996.

Total Fertility Rate

Total fertility rate is an estimate of the average number of children that would be born to a woman if the current agespecific birthrates remained constant. The reproductive revolution or the transition from high to low fertility is one of the dimensions of socioeconomic development. According to demographic transition theory, socioeconomic development facilitates fertility decline through the following mechanisms:

1) reducing infant/child mortality rate,

2) raising the status of women (including an increased level of education for women and an increased proportion of women employed in the nonagricultural sectors),

3) raising the marriage age and celibacy rate,

4) increasing the costs of raising children, and

5) reducing the economic value of children.

Caldwell (1982) also argues that modernization creates reversed intergenerational wealth flows from parents to children. Such flow, unlike traditional wealth flow from children to parents, discourages couples to have high fertility. These changes coupled with accessible contraceptives, a higher value placed on smaller families, a latent demand for smaller families, and governmental family-planning policies are commonly cited factors that account for fertility decline. Moreover, diffusion/interaction theory (Bongaarts and Watkins 1886; Rosero-Boxby 1883; Casterline 1985) and ideational theory (Lesthaeghe 1883) also provide significant theoretical insights on fertility decline.

In 1970, the total fertility rate (TFR) for the world was 4.8 children per woman; it had dropped to 2.8 in 1996. Similar patterns of fertility decline are found for all world regions. The worldwide reduction in fertility is as predicted by the demographic transition theory. In most of the more developed countries and some East Asian countries (e.g., Taiwan, Singapore, South Korea, and Hongkong), the total fertility rate has reached the replacement level (when TFR=2.1) or even below replacement level. Hirschman and Young (1999) also found that the total fertility rate had dropped to below 2.0 for Thailand in 1990. (Impressively the reproductive revolution in Thailand occurred when its GNP per capita was only $1,470 in 1990 (World Bank 1994).)

In sum, the latest World Bank data show that we have made tremendous progresses in education and socioeconomic development over the past few decades. The central question, however, remains to be answered: What is the impact of education on socioeconomic development?

Theoretical Backround

The title ‘‘Education and Development’’ does not imply a straight, unidirectional causal effect of education on development. Actually, the relationship between education and development can well be covariational.

To identify the exact cause and effect between the two is a difficult task. For example, education can facilitate development by providing the bettereducated human resources that are essential for socioeconomic development. Education also reduces the fertility rate and thus population growth rate. It also transforms the labor-force structure and promotes rural-to-urban migration. On the other hand, the level of socioeconomic development in a country is likely to influence the level of education for that country. As development progresses, countries would have more resources to invest in education (thus development affects education). According to the functionist theorists, the rapidly changing technology of the twentieth century has generated a demand for a better-educated labor force. The expansion of schooling can be viewed as a direct response to these technological changes. Moreover, the need for a more skilled labor force would encourage government to invest more in education in order to keep the economy competitive in today’s world economy.

Thus, the relationship between education and development can be best viewed as covariational. Here I assume that education and development are related to each other in the initial stage of development. My goal is to investigate the net impact of education in an early stage on later stages of socioeconomic development after controlling for early-stage development and other important intervening variables. There are three main theories (modernization, human capital, and world-system) that address the impact of education on development.

Modernization Theory

Modernization is a transformation of social and economic structures. The International Encyclopedia of the Social Sciences (1868) defines modernization as ‘‘the process of social change in which development is the economic component’’ (p. 387). From a comparative perspective, modernization can be viewed as the process of social change whereby less developed countries acquire characteristics common to more developed countries. Lasswell (1965) argued that modernization not only shapes economic factors but also reshapes all social values such as power, respect, rectitude, affection, well-being, skill, and enlightenment. Common characteristics of modernity include:

(1) a degree of self-sustaining growth in the economy;

(2) a measure of public participation in the polity;

(3) a diffusion of secular- rational norms in the culture;

(4) an increment of mobility in the society; and

(5) a corresponding transformation in the modal personality that equips individuals to function effectively in a social order that operates according to the foregoing characteristics.

Proponents of modernization theory argue that the transformations of socioeconomic structures— such as the mechanization of agriculture, urbanization, a mass communication network, demographic transition, the expansion and integration of a national market, and an increase in political participation—are necessary preconditions for sustained economic growth (Apter 1965; Rostow 1960). Obviously, changes in these social forces create new opportunities, incentives, and normative influences that can affect

(1) an individual’s view on the world and

(2) his or her behavior. Another thread of the modernization theory stresses that exposure to modern values leads to socioeconomic development.

Inkeles and Smith (1975) maintain that modern people, as opposed to traditional people, are prepared to act on their world rather than fatalistically accept it; have a cosmopolitan rather than a local orientation; see the sense of deferring gratification; welcome rather than distrust change; are not constrained by irrational religious or cultural forms; and recognize the value of education. According to modernization theory, education plays a crucial role in making the route to modernization possible.

Macroeconomic studies have shown that education is positively correlated with overall economic growth, with one year of additional schooling of the labor force possibly leading to as much as a 9 percent increase in gross domestic product (GDP) for the first three years of schooling and a yearly 4 percent increase for the next three years (Summers 1994). Increased education has also been found to result in greater agricultural productivity, even in developing countries (Jamison and Lau 1982; Lockheed et al. 1980). The National Research Council (1986) also reported that ‘‘urbanization plays a beneficial role in the development process, providing an increasing share of population with access to relatively high-wage employment, education, health care, and other modern public services’’ (p. 76).

However, in a case study of Egypt, Faksh (1977) found that ‘‘educational expansion in modern Egypt thus far has not been conductive to development in the general configuration of the Egyptian polity’’ (p. 238).

Human Capital Theory

Human capital theory argues that education leads to development by increasing the efficiency and productivity of workers. Investment in human capital is a key element in achieving long-term sustainable economic growth. According to this perspective, ‘‘the main contribution of education to economic growth was to increase the level of cognitive skills possessed by the work force and consequently to improve their marginal productivity’’ (Benavot 1989, p. 15). According to the theory, the provision of education is not a form of consumption but a productive investment in society’s ‘‘stock’’ of human capital. Investment in human capital is at least as profitable as investment in physical capital. At the national level, increasing the overall level of education will raise the stock of the human capital, which will have a positive impact on national productivity and economic growth. At the individual level, education level provides some indication of the ability of a person to perform certain duties and adapt to other work situations.

World-System/Dependency Theory

Worldsystem and dependency theories suggest that the specialization of some countries in the export of raw materials and lightly processed goods is an important cause of their underdevelopment. Moreover, the world-system/dependency theories argue that the needs and interests of Western capitalism determine the pattern of education in developing countries. Education is seen as part of the process whereby peripheral countries are kept underdeveloped. The prevalence of foreign investment capital, the presence of multinational corporations, the concentration on exporting primary products, and the dependence on imported technologies and manufactured goods constrain longterm economic development (Bornschier and Chase-Dunn 1985; Delacroix and Ragin 1978). According to the theory, ‘‘education, far from a key component in development, modernization, self-sufficiency, and so on, is in fact yet another instrument of enslavement, a way of tightening, rather than loosening, the dependency bond.’’ (Dale 1982, p. 412).

Each of the above theory examines the relationship between education and development from different angles. Each theory delineates part of the dynamics of the relationship. Due to the limitation of data, this article will examine only the validity of modernization theory.

Analytical Model of Education and Development

Figure 1: Analytical Model of Education and Development

Data Source, Analytical Model, Measurement, Intervening Variables, and Research Methods

Data Source

The World Bank compiles national data on education, demographics, and socioeconomic development from various years and sources. The data used for this research is from the World Bank’s 1998 World Development Indicator CD-ROM.

Analytical Model

In this article, education and economic development are assumed to be related to each other in the initial stage of analysis (e.g., measures for both variables obtained in 1970). Both education and development are the independent variables. From there, I analyze how both 1970 factors affected the intervening variables (1980 level of industrialization, urbanization, and population growth rate). Finally, I estimate the net effect of 1970 education on 1990 development, after controlling for 1970 development and other 1980 intervening variables. The effect of education on development is also estimated for the 1980–1996 period. This model is shown in Figure 1.

Measurement

Education is defined as the formal schooling, although education can also be defined as an alternative to family education, an instrument of state social policy, a site of civic reform, or a form of humanistic progress. Socioeconomic development is broadly defined as the progress in the areas of GNP per capita, infant mortality, and life expectancy.

There are three sets of variables—the independent, the intervening, and the dependent variables. The independent variables include the level of education and economic development observed at a earlier time period. The intervening variables, including urbanization, industrialization, and population growth rate, are controlled to mediate the effects of the independent variables on the dependent variable. Finally, the dependent variable is the level of socioeconomic development observed at a later period of time. Three indicators are used: GNP per capita, life expectancy, and infant mortality.

Level of education is defined as the secondary school gross enrollment ratio, defined in the previous section on ‘‘Educational Development in Recent Decades.’’ I use this as the main independent variable rather than the primary school enrollment ratio because for many countries compulsory education is limited to the primary level. Lack of variation in primary school enrollment ratio could pose a threat to the validity of the study.

Socioeconomic development include three indicators: life expectancy, GNP per capita, and infant mortality rate. Lift expectancy at birth measures the overall quality of life. It is defined as ‘‘the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throught its life’’ (World Bank 1998: 19). The GNP per capita measures the economic aspect of progress. Infant death is the final biological expression of a process that is determined basically by the economic and social structure of a country of region. These conditions influence the occurrence and spread of disease as well as quality and availability of health care facilities, all of which are crucial to survival probabilities. The structural determinants are mediated at the family level, because the child’s growth and development are heavily dependent on the living conditions of the family.

Table 2

Intervening Variables

The intervening variables include urbanization of population in urban areas, industrialization of labor force in nonagricultural activities, and annual population growth rate. Time-lag path analysis is used to investigate the direct and indirect effects of education at an earlier time (e.g., 1970) on socioeconomic development at the later time (e.g., 1990), after controlling for urbanization, population growth rate, and industrialization. Specifically, two models will be examined. The first model uses 1970 data for the independent variables, 1980 data for the intervening variables, and 1990 data for the dependent variables. The second model examines the periods between 1980 and 1996. That is, I use 1980 data for the independent variables, 1990 data for the intervening variables, and the 1996 data for the dependent variables. For both analyses, the unit of analysis is country.

Research Method

Path analysis will be used to study the proposed model. The path coefficient represents the standardized regression coefficient. The standardized regression coefficient (ß) represents the change in the standard deviation of the dependent variable associated with one standard deviation of change in the independent variable, when all other variables are controlled for.

The coefficient of alienation (defined as the square root of 1−R2) is also provided to show how well each development indicator is predicted by all the independent variables. A larger coefficient of alienation indicates that the development model has a smaller R2 or coefficient of determination. On the other hand, if a development model has a smaller coefficient of alienation, then the independent variables in that model explain more variation in that development indicator.

Findings and Discussion

Descriptive Statistics

Table 2 presents means, standard deviations, the minimum values, and the maximum values for all variables used in the analysis. The upper panel shows the data for 1970–1990 period and the lower panel for 1980–1996 period. There are two independent variables, percent of secondary school enrollment and logged GNP per capita. GNP per capita has an extremely skewed distribution. In regression analysis, normal distributions for all variables are expected. To correct this problem, I take the natural log of GNP per capita. The mean logged GNP per capita in 1970 was 7.2. The 1990 logged GNP per capita was 7.4. The intervening variables include industrialization, urbanization, and population growth rate. Finally, the dependent variables include economicdevelopment (logged GNP per capita at a later year), life expectancy, and infant mortality.

Table 3

Corelation Matrix

Table 3 shows the correlation matrix for all variables used in the two-panel analyses. All the correlation coefficients are significant at .01 level. Furthermore, the strengths of all correlations are substantially strong. Moreover, the direction of relationship is as expected by modernization theory. For example, there is a high correlation between 1970 education and 1990 socioeconomic development. Specifically, .81, .79, and −.76 are the correlations between 1970 education and 1990 logged GNP per capita, 1990 life expectancy, and 1990 infant mortality rate, respectively.

Similarly, there is also a high correlation between 1980 education and 1996 socioeconomic development. Specifically, the correlations between 1980 education and 1996 logged GNP per capita, 1996 life expectancy, and 1996 infant mortality rate are .69, .75, and −.75, respectively. Since the bivariate correlation between the independent variable and the dependent variables does not control for other causal mechanisms, I will be controlling for intervening variables in path analyses. The results of path analyses are reported below.

Path Models

Figure 2 shows the relationship between education and economic development during the 1970–1990 period. The path model shows that the level of education, as measured by secondary school enrollment rate in 1970, has no direct effect on economic development, as measured by GNP per capita in 1990, after the 1980 urbanization, 1980 industrialization, 1980 population growth rate, and 1970 economic development are held constant. Similarly, urbanization has no effect on economic development after other variables are controlled for, although crossnational studies suggest that urbanization is related to the level of economic development as measured by per capita income or GNP (Chenery and Syrquin 1975).

Education and Economic Development, 1970–1990

Figure 2: Education and Economic Development, 1970–1990

Nevertheless, education has indirect effects on economic development. The first indirect effect of .09 (.45×.02=.09) from education to economic development is through its effect on industrialization (the path coefficient is .45). High enrollment rate in secondary school is found to have a moderate and positive effect on level of industrialization. Industrialization is found to have a positive direct effect on economic development (the path coefficient is .20). The second indirect path from education to economic development is through population growth rate. High secondary school enrollment rate lowers a country’s population growth rate (path coefficient is −.90). A country’s population growth rate is found to have a weak and negative effect on its economic development (the path coefficient is −.11). The second indirect effect of education on economic development is .10 (−.99×−.11=.10). The total indirect effect of education on economic development is .19 (.09+.10=.19).

Education and Life Expectancy, 1970–1990

Figure 3: Education and Life Expectancy, 1970–1990

Figure 3 shows the relationship between education and life expectancy during the 1970–1990 period. The path model shows that the level of education in 1970, as measured by secondary school enrollment rate, has a positive and moderate direct effect on 1990 life expectancy (the path coefficient is .32), after 1980 urbanization, 1980 industrialization, 1980 population growth, and 1970 GNP per capita are controlled for. Countries that invest their resources in education can directly increase their population’s life expectancy. Urbanization and population growth rate are found to have no effect on life expectancy. In addition to its direct effect on life expectancy, education also has an indirect effect on life expectancy. The indirect effect of .32 (.45×.71=.32) from education to life expectancy is through its effect on industrialization (the path coefficient is .45). High level of industrialization is found to have a very strong positive effect on life expectancy (path coefficient is .71). High proportion of population engaged in nonagricultural occupations increases a country’s life expectancy. The total effect of education on life expectancy is .64 (the sum of direct effect, .32, + indirect effect, .32).

Education and Infant Mortality, 1970–1990

Figure 4: Education and Infant Mortality, 1970–1990

The last model for the relationship between education and development between 1970 and 1990, as measured by infant mortality, is shown in Figure 4. According to Figure 4, level of education in 1970 reduces the infant mortality rate in 1990. This finding is consistent with other studies based on individual-level analysis. Moreover, 1980 industrialization also has a direct and negative effect on infant mortality. Countries with a low proportion of the labor force in nonagricultural activities are more likely to have higher infant mortality rate. The indirect effect of education on infant mortality through industrialization is −.32. (.45 × −.70 = −.32). The total effect on education on infant mortality is −.63 (−.32 + −.31 = −.63).

Education and Economic Development, 1980–1996

Figure 5: Education and Economic Development, 1980–1996

Figures 5, 6, and 7 examine the relationship between education and economic development, life expectancy, and infant mortality rate during 1980–1996. The intervening variables—urbanization, industrialization, and population growth rate—are based on 1990 data. Surprisingly, the results from Figure 5 shows that there was no direct or indirect effect of education on economic development during 1980–1996. Only 1980 GNP per capita had a direct impact on the 1996 GNP per capita.

Education and Life Expectancy, 1980–1996

Figure 6: Education and Life Expectancy, 1980–1996

Figure 6 shows that the level of education in 1980 had no direct effect on the 1996 life expectancy. However, it had an indirect effect on life expectancy through its effect on industrialization. The indirect effect of education on life expectancy is .31 (.40 − .77 = .31).

Education and Infant Mortality, 1980–1996

Figure 7: Education and Infant Mortality, 1980–1996

Similar to what was reported in Figure 6, Figure 7 shows that the level of education in 1980 had no direct effect on 1996 infant mortality. However, it had an indirect effect on infant mortality through its effect on industrialization. The 1980 industrialization has a substantially strong negative and direct effect on 1996 infant mortality rate (path coefficient= −.67). The indirect effect of education on infant mortality is −.27 (.40 × −.67 = −.27) for the 1980–1996 period. The level of economic development in 1960 is also found to have an indirect and negative impact on 1996 infant mortality rate. The indirect effect of economic development on infant mortality is −.37 (.55 × −.67 = −.37), which is stronger than the impact of education during this period.

There were some weaknesses in the study. The variables used in the study are period data. Period data are collected in a given year when their values are very much influenced by macro socioeconomic conditions. The time intervals between the independent and the dependent variables of 20 years (or 16 years for second model) may seem long. Finally, secondary school enrollment was used as the independent variable. Further studies may consider tertiary education as an indicator of education.

Summary and Conclusion

Modernization theory maintains that education promotes development. For many developing countries, education is a prominent means of attempting to narrow the knowledge gap between the highly industrialized countries and the developing countries.

This chapter reported the world’s impressive education and socioeconomic developments over the past few decades. It also examined a diverse set of mechanisms through which education affects socioeconomic development for two periods: 1970– 1990 and 1980–1996. The overall findings suggest that education has a positive effect on life expectancy for both time periods examined. Moreover, education was found to have had negative relationship to infant mortality for the 1970–1990 and 1980–1996 periods. However, the effect of education on economic development is more complicated. Education is found to have had a positive effect on economic development for only the 1970–1990 period, not for 1980–1996 period. Another interesting finding is that the effect of education on development was lower during 1980–1996 than the 1970–1990 period.

The study shows that education, industrialization, and development are inextricably interrelated. To achieve a higher level of socioeconomic development, policy makers would need to consider the complex relationship between education and development. Several countries have taken steps to improve their educational systems in order to bolster their economies and improve conditions in their nations. In recent history, for example, China and Taiwan have made attempts to modernize and strengthen their economies by encouraging people to further their education, especially in science and technology. It is clear from this study that to improve the welfare of the billions of people in the developing world, governments in developing countries need to continue and expand their investments in education for their population.

The sociology of education and the sociology of development have become very important areas in sociological research. As more advanced data become available, we will be able to do better research in this area by conducting more sophisticated and comprehensive studies. Examining modernization and other theories in the area of education and development will enable sociologists to provide solid knowledge about the mechanisms whereby education affects development, which can be important information for policy makers when they implement policies related to education and development.

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This Aricle was Written by
YIH-JIN YOUNG

This Article was Published in
ENCYCLOPEDIA OF SOCIOLOGY
Second Edition
A Book by

EDGAR F BORGATTA
Editor-in-Chief
University of Washington, Seattle

AND

RHONDA J. V. MONTGOMERY
Managing Editor
University of Kansas, Lawrence

 

 
 
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