This is an analysis of impacts of the expansion of higher education on income inequality in China.
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Education is often an imperative predictor of a person’s future income (Lee 2006, 1). Basing on the Horace Mann tradition, Lee adds that education paces the society towards achieving a stable equality (1). Qian and Smyth note that the unraveling of the connection between education and income has attracted scholarly attention (3).
The need for the scholarly attention cannot be underestimated since an access to education is one of the basic human rights for everyone. From economic and social perspectives, quality education is one which facilitates an individual’s capability to increase income as well as general well-being.
In other words, education should cushion against widening income gap across the society. Qian and Smyth (2005) explain the empirical finding that irregular access to education across a populace impacts negatively income distribution and economic growth (2). Globally, China is the most populous nation. A World Bank assessment revealed that China contributes the largest portion of poverty to the world, especially those people living in the rural areas (Borooah et al. 2005, 2).
The pursuit to gain equality through education throughout the last century has had a fast diffusion of public education. In the contemporary society, education continues to be an undisputed tool for social mobility and expansion (Lee 2006 3; Wu 2007 3).
Nevertheless, the impact of education as a social bottom line can be likened to a double edged sword meaning that a scholar from a disadvantaged background can have a turnaround in regards to his/her future income. On the other hand, the turnaround depends on the investment made towards the attainment.
Arguably, this could be the underlying reason why the Chinese Government decided to adopt the Law on Nine-Year Compulsory Education in 1986 to make it possible for all children at school to have nine years of schooling (Lee 2006, 2). According to World Bank (2009) , the Education Gini coefficient based on gender and ethnicity, inequality pattern in China’s education had a positive trend from 0.57 in 1978 to 0.26 in 2004 (2).
Qian and Smyth (2005) state that in China the literacy levels among the adults rose from 60 percent within a period of 40 years to 85.5 percent in 2001 (3). In 1999, the student enrollment in primary schooling of 135 million and a teacher capacity staffing of 582 000 made China boast the largest primary school program.
China has diversified the secondary schooling to offer more than just general secondary education. Others include skilled labor, specialized, adult as well as vocational schooling (Qian and Smyth 2005, 3). At the tertiary level, the number of undergraduate enrollments and individual institutions in the year 2000 increased to 5.56 million and 1 770, respectively (Qian and Smyth 2005, 3).
By the turn of the millennia, China was experiencing an unprecedented and accelerated economic growth. However, this was paralleled by alarming disparities in income. Since the Mao era up to the early 1990s, income inequalities were on the decline, however, the 1990s decade experienced a reverse trend (Fleisher et al. 2008, 2).
Wu and Perloff pinpoint that economic growth in China grew by five times while the per capita income rose by four times, but disproportionately in the favor of the affluent and those in the urban areas (2004). Difficulties in demonstrating the income inequality have been aggravated by lack of consistent and reliable income dispersion data over time. The government has made limited attempts to provide Gini index.
In China, income inequality is fuelled by geographical factors, disparities in the access to education, the recurrent informal sector as well as barriers to employment and career progression for particular groups, especially rural migrants. Wu and Perloff (2004) argue that the income inequality is higher within the rural populace as well as between the rural and urban workers (4). Nevertheless, rural-urban migration has had a marginal impact on the status quo.
Wu and Perloff (2004) further explain that urban biased policies and institutions contribute markedly to such a situation and to the increase in urban-rural inequality (5). For instance, migrants to urban areas in search for income are discouraged from gaining urban residence status due to the strict residence registration system.
This discriminates them from welfare benefits as well as better pay commonly enjoyed by the urban residents. Wu and Perloff (2004) made an attempt to explain the scenario and generated inferences by the use of the Kuznets Curves and hypothesis (4). The scenario of growing inequality amid the migration restrictions becomes complicated with shifts in population trends.
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Income inequality problems in China are related to imperfect labor market. The labor market experience the oversupply of partially educated graduates who crowd the large eastern cities like Beijing. Ning (2010) observes that the expansion of higher education has dismally contributed to the harmonization of regional income distribution (10).
China’s cities are yet to coalesce into a single common job market base that will fairly address the differences in regards to education. This explains why graduates across the country tend to work in the eastern cities even if those are not their hometowns.
Inconsistencies within the education sector are traced back to a failed rationale in the examination system as well as weaknesses in the quality screening. Quality differences within same study courses result in skill imbalances in the labor market. In order to better chances as a highly skilled individual, there is a need to invest more in education. Costs associated with skill screening discourage firms from investing.
Government Spending on Education
Compared to nations of relatively the same level of per capita income and economic robustness, China has historically scored dismally with regard to investment in human capital development particularly at post secondary level. In 2004, the national budgetary spending on education was 2.79 percent of the GDP, which had always remained below 3 percent since 1992.
This is lower relative to the average of 5.1 percent achieved by other countries in the developed world (Fleisher et al. 2008 2). There was a rise in the proportion of college graduates within the population in 1992 (at 1.7 percent) compared to 1982 (0.4 percent); nevertheless, this was marginal.
As from 1999, sharp rise in government spending on education resulted in a remarked steep increase in enrollment from 7.4 percent to 21.3 percent in 1997/98 and 1998/99, respectively. However, this did not translate to a sharp increase in the proportion of college graduate vis-a-vis the population, which was as low as 5.2 percent in 2003 (Fleisher et al. 2008 3).
Investing in Higher Education in China
Towards the start of the 1990s some universities in China passed some institutional policies that required students to pay a portion of tuition levy. This trend was popular until 1997 when fees were institutionalized as part of the higher education package that students had to meet.
Thereafter, higher education in China has had to be paid for by the student (Dong and Wan 2012, 2). Students have to pay for tuition even if it’s a subsidized charge. Over the time, the government made deliberate efforts to improve policies that support the paying of tuition levies. This has seen an annual rise in fees. Within the 1990s the annual per-student recurrent expenditure in public institutions of higher education rose by two-thirds to RMB 10 230 million (Levin and Xu 2005, 38).
The rise in expenditure was due to the tuition and research. Analysts forecast that making the costs of higher education lower will result in market efficacy and improved student learning. Dong and Wan (2012) observe that such measures may raise the inequality levels, however (2).
The development witnessed in higher education financing was motivated by the government’s desire to expand the sphere of education as well as domesticate the cost-sharing theory into education system (Dong and Wan 2012, 3). If the government insists on not interfering in the sphere of education as part of the expansion, then education will cease to be public; it will only be accessed by those from the upper class. This will not only result in educational inequality but also income inequality.
Decomposing the Impacts of Expansion of Higher Education on Income Inequality in China
The higher education expansion program was intended to enhance internal efficiency (Levin and Xu 2005, 52). Although China is expanding its education across the country, the ability to optimize the opportunity widely varies in different financial limits and regional areas.
Actually, the trend is exacerbated by a possible vicious cycle that exists between income inequality and education inequality (Ning 2010, 5). Trends in the access to higher education since the expansion of education reforms in 1989 signal a rise in inequality. The regional differences between the east and west better explain this. In the year 2007, college graduates in Qinghai province located in the Country’s west were 15 483, which is relatively lower than 242 617 in Beijing in the east (Ning 2010, 5).
Based on these figures, more employment opportunities will be allocated to those in the east than the west. Considering that labor migrations are in favor of flowing to the east than to the west, the west remains economically stagnated due to lower level of education attained by people, thus offering lower remunerated jobs.
Actually, this is highly evident and likely when subjected to the Kuznets Curve and hypothesis, where the peculiarities of various inequalities are better explained. Ning (2010) cites that China’s public education has hardly become efficient to foster economic growth as well as bridge wage gap (6).
Labor Choice Effect
Students from disadvantaged background particularly those discriminated through social stratification hardly benefit from expansion of higher education. Ning (2010) highlights that the poor were not beneficiaries of educational expansion even with the market approach rolled out in the 1990s (6).
This justifies the fact that the education choice is not an obvious cause. It is a necessity that students from poor background have to go to school in order to reverse their fate, but this is derailed by economic hurdles that deny any opportunity to maximize on that potential. Eventually, education inequality through social stratification further widens the economic and income inequalities.
Even though graduates from poor background have attained higher education, they may not succeed in getting jobs that are well remunerated because of the reduced social capital network. In order to avert this hurdle, these students opt for a higher degree of education to imply their professional competence.
In other words, they resort to over-education. Over-educated people are likely to originate from humble backgrounds, thus switching labor markets.
In fact, over educated students tend to migrate to affluent regions of China which suppresses in turn the growth of local human resource capital in such areas. Lee (2006) applies the classical human capital theory to explain the net impact of high education levels, the migration trends and the ultimate outcome (16).
Majors at universities, such as finance, for example, enroll more students not because of the ability to provide the students with innovative ideas, high rates, etc., but due to perceived skewed income distribution across the labor market. Based on this, there is no motivational fee for skilled workers within the technical or any other training, thus the standards of education in this type of higher education are average, if not substandard. In addition, the labor market experiences a shortfall of technical experts.
Besides, the job market is flooded with graduates in humanity studies and social sciences. In other words, the number of students that enter such departments to meet the demand of labour workers in corresponding fields leads to an across-the-board income differences. Levin and Xu (2005) note that at the turn of the millennia the national market supply for graduates with a degree in Philosophy was the highest (50).
Others that followed respectively were law, history, science, engineering and medicine. Employment opportunities for students of agriculture, education, economics and literature were hard to come by. In 2001, unemployment rates stood at 3.6 percent up from 2.3 percent in 1992 (Levin and Xu 2005, 50).
Although the literacy and higher education training requirements have been met for some labor segments even beyond market demand, this has come at an expense of not only other professions, but of the market as a whole. Ning (2010) implies that this state of affairs results in semi-skilled graduates being supplied to the market, who at the end may not be able to upgrade the technology (6). In other words, the skill competitiveness has been compromised.
In such a scenario, the productivity of the labor market becomes questionable and meeting the revenue generation target is impossible. This leads to inequality whereby those in the monopolized industries are better remunerated due to high monopoly rents.
Inasmuch as such industries do not obviously require highly trained or qualified employees, employers tend to set high academic requirements for recruits. In the end, the talent may not be rewarded since the employer focuses on the academic qualification as the yardstick, which may lock out those not privileged with better schooling opportunities especially from disadvantaged backgrounds.
Price (Return Rate) Effect
Ning (2010) explains the relationship between income inequalities and the level of higher education is attained via the convex return context (7). In such a context, the educational attainment is directly proportional to the return outcome. Previous empirical studies in Mexico show that changes in inequalities are driven by adjustment in earning across educational groups.
In the 1980s, the increase in inequality was as a result of convex return context. During this decade, income inequalities favored those with relatively higher education attainment across the population. With the expansion of higher education, China is experiencing an almost similar scenario.
This is exemplified in the return rates for schooling independently as well as along the different educational groups. Those with higher education attainment are being favored.
This skews the income distribution more when the higher education attainment is not readily translated into productivity resulting to possible exploitation of people with lower education levels. At the end, the return rates become pegged to academic rewards other than skills and productivity. Lower education attainment is rewarded through the absolute income increase.
It is likely that if poor students fail to achieve an adequate return on investment on schooling, then the income gaps will continue to increase. Often in developing countries, the occupation level will be dictated by education.
In a relational society where social network is necessary to penetrate government jobs, there is no guarantee that poor students with high education level will make it into the government sector. Ning (2010) states that the education level of parents influences the wage earnings of the children on the basis of human capital accumulation as well as possibilities to find a job (8).
Differences of one’s abilities, luck as well as adjustments during schooling may influence how individuals with the same education attainment experience income inequality. Increase in income pegged on education level favors candidates with unobservable characteristics that rank them well above within the conditional wage distribution, Ceteris paribus.
Ning (2010) cites that this revolves around the non-cognitive skill (9). This has close ties with the observation that students from disadvantaged background attain education, but their job prospects are not immediately promising.
Income inequality occurs when overeducated people have to contend with incommensurate wage. Ning (2010) observes that in the recent years graduates have not been unable to get jobs in China (9). Graduates had to switch to jobs below their educational background. To a greater extent, these inflicted their return on education. This disapproves that over-education is an end to the persisting income inequality.
Expansion of higher education makes income distribution susceptible to inequality outcomes when the quality of education translates to compromised returns to education. When college enrollment is not proportionate to schooling resources (education resource per capita), it is predictable that quality of education will decline. Ning (2010) observes that skill quality in the decade before education expansion scored better than thereafter (10).
The employer suffers expertise deficits translating to income losses due to unqualified graduates. Levin and Xu (2005) suggest some improvements that ought to accompany the expansion of higher education to sustain quality (37). There should be a national effort to devote and diversify resources and funding for higher education.
There is a need to put in place progressive regulations for higher education against which institutions can be evaluated as well as be held accountable. It should be demonstrated that quality of learning in higher education is dignified even with expansion in quantity. Levin and Xu (2005) observe that there is a perception that a fully fledged university in China offers almost every professional specialties (54). In other countries of equal magnitude to China like the USA, this is not usually so.
Levin and Xu (2005) regard Yale and Princeton as top universities that currently don’t offer some appealing majors, yet their reputation remains stable and intact attracting and training qualified graduates (54).
With reference to China, Ning (2010) analyzed the impact of education on the employees’ future income. It was revealed that when wage was a dependent variable, the rate of return to education was 7.9 percent (14). When the annual earning was the dependent variable, the return rate was higher at 11.3 percent (Ning 2010, 14).
Lastly, according to Lee (2006), implications of earning inequalities related to return rate effect as well as labor choice effect loom wider than population (23).
Initially, scholars argued that expansion of education would increase attendance rates of schooling in due course; consequently, this would result in a decline in disparities in educational opportunities since the attendance rates of children from disadvantaged backgrounds will grow considerably in regards to the upper class. However, this early belief has been disputed a lot by the modern day scholars. The planned expansion of education has been considered as a switch from the elitist to mass education.
It is evident that the level and distribution of education are key subsets of income distribution. Gregorio and Lee (2002) conclude that a rise in the average level of education among the population in China has a balancing effect on earning distribution (406). This has a Kuznets-inverted U relationship especially when the government economizes on the social expenditure.
Ning (2010) also states that the inverted U relationship between income and expansion of education in China has been demonstrated using macro-data (4). Lee (2006) explains that the Kuznets Curve scenario where the level of higher education rises with an expanding economy resulting in rise in education inequalities that stabilize in reaching the threshold (14).
Gregorio and Lee (2002) during their cross-country analysis of the relationship between education and income inequality note that policymakers perceive education spending as a powerful tool for addressing the income inequality, however, it is not that obvious (395).
Nevertheless, there remains a positive connection sand link between education inequality and income inequality, especially when education inequality is measured on the basis of schooling variance. Trends in the return rate on education will eventually dictate whether the impact of higher education attainment of income inequality is either positive or negative.
Considering the stratified nature of China’s society, the expansion of education may not necessarily have the same impact on populace equality as the distribution of educational opportunities will have. Wu (2007) observes that during the expansion of education in China, the Gini Coefficient (that assesses inequality across a populace) rose to 0.449 in 2005 from 0.317 in 1978 (5).
The approach of distribution of educational opportunities takes care of the distribution of scarce resources that are imperative for the education system, which allows for the equalizing of the other fundamentals of the social structure across the populace.
In the case of China, expansion of education impacted the distribution of educational opportunities by introducing the market approach into the education, thus widening the gap of inequality on the basis of access and distribution of economic resources.
Lee (2006) notes that the net impact of the expansion of education on income inequality follows the Classical Economic Theory (14). Furthermore, the expansion lacked a clarified equalizing impact through unevenly and unequally distributed opportunities. He further faults the market approach fronted through policy reforms as intended to widen the inter-provincial educational inequality in higher education.
In re-dressing the inequality issues, Lee (2006) suggests developing stratified collection and redistribution of educational resources strategy, as well as breaking down structural social barriers that would allow more mobility (15). He applies the Nee’s theory of transition economy to explain the inter-provincial inequalities that arise when the market is used for education expansion in China.
He further explains that the introduction of market approach into the expansion of education by the Chinese government was intended to bring on-board the efficiency of market mechanisms, as well as liberalize the redistribution of resources to individual level after the attempts of the central government to execute re-distribution modalities failed to a greater extent. This raises the worry on whether the government of China has abandoned the quest for ameliorating the inequality difference.
Levin and Xu (2005) observe that there has been no clear pattern from studies on the linkages that exist among China’s wage rates, expansion of higher education, current level of development as well as graduate employment (49).
In conclusion, Lee (2006) states that unless the impact of the expansion of education is clearly understood, it is difficult to forecast future trends of income inequality, thus formulate appropriate policy that will curb the negative growth (1). The consequences are huge, considering that policy implication is favoring the rise in tuition costs and fees for higher education, yet students anticipate having an ultimate return on investment from their education.
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