The Effects of Chinese Educational Development in Post Cultural Revolution, Article Review Example

The article discussed on about the Chinese students who had attained their university degrees after the Cultural Revolution army war and their impact on educational development prior to the Cultural Revolution. Due to the Cultural Revolution in 1966 to 1977, duringat that time, there were several life-altering circumstances or factors that had influenced Chinese’ decision to acquire the university degrees because of the severity of theenvironmental situations that placed an impact upon Chinese students such aswork labor, or natural disasters, or political upheavals, or war that mitigates the choices to return to school at older age after they missed some schooling.In the 1980s,China reformed their education system in focus on the university entry examinations for students who missed junior high or senior high school and formed the Cultural Revolution cohort to which extent the standards under Chinese education system. The Cultural Revolution cohort is implying the Chinauniversity degrees, in terms of, its tertiary education levels: high school students in a university are conditioned; and, they completed their education at university level in less than three years therefore they were acquiring a semidegree. While, some students were acquiring a formal degree within four years of educationand some other students did obtained their correspondence degrees (via television or night school) as they earned their semidegrees. In that following education acquisition sequence, authors were researching the lacunae of Chinese students’ educational development by examining their university entry ages they were interrupted by either or all of their primary, junior, senior high schools; and, their experience of missing school as their educational attainments were interrupted in three differentinterval (1988,1990, 1995) gaps as shown on Table A1.The authors then dissembles the dummyvariables for measuring the size of “missing school” effect and its relationships—based on the 1988 Urban Income Distribution Survey (UIDS) data —The students who missed junior high schooling were examined at the university entry age between the ages of 19 and 22 year olds; and, the students who missed junior and high school were examined at the university entry age were from 23 to 27 year olds; and, the last group who missed senior high school were examined at the university entry age were from between the ages of 28 and 30 year olds. Under the “missing school” variables, authors also examined the leverage ofpresent value of marginal costs and against future marginal benefits of formal degree and semidegree to find out whether the effect of the model of education can maximize the individual’s intertemporal utility.They used the multinomial logit model to estimate education attainment because they were able to find the probability of individuals being affected by the decision to obtaining a degree either formal, semidegree or no degree by usingthe 1988 Urban Income Distribution Survey (UIDS) data from the Institute of Economics of the Chinese Academy of Social Sciences. The 1988 UIDS survey data only can provide information on the age of students missing junior and senior high school. Whereas, the 1995 Shanghai Residents and Floating Population Survey (RFPS) dataof the Institute of Popular Studies at the Shanghai Academy of Social Sciences has provided information pertaining to earnings for further investigation on whether there are students who had missed three or four years of high school had successfully completed 4 year education at the university. This marginal effect also adds on to the feasible economy returns based on the students’ investment in re-learning their academic subjects, innate abilities, and budget responsibilities as their intertemporal utility in their educational development process starting at the age of 31 years old.  As evidenced in authors’ empirical work, they used both types of data to explore the students’ age and level of education before and after Cultural Revolution. In part, they found a group based on the 1995 data that did not miss any schooling and did obtained a formal degree only, non-Cultural Revolution cohort, even though not everyone in the non-Cultural Revolution cohort group were in the region of Shanghai when surveyed as some of the people were from other region of Jiansi. The “university entry exam” questions were not asked in the 1988 data even though they were not allowed to be included in the sample under which these variables were removed from the findings for future earnings. However, they were statistically significantly positive with labor-markets, the 1981 returns were 29% and 22% for a formal degree and a semidegree; after 6 years, incrementally, the rate has increased slightly to 31%; that is, the labor market has beeninfluenced by the social change in employment and wages then the changes in educational economy—that is, the preparation on the university admission examinations for the students—andof its costs and benefits. It was determined that the investment costs would be coming from the students whose education were interrupted and missed the school the mosthad to pay more for their knowledge acquisition for university admission examination as predicated. In addition, the students’ level of school interruption and the number of years are the effects of students’ ability to acquire new knowledge at the university, hence, the time spent was affected; and, those students who missed the school the most were affected by the quality of a university education which has reduced the benefit of future earnings. Hence, moreover, there are three types of effects that the authors were attempting to investigate the conditions on thestudents’ interrupted education and missed schooling between the university entry age to which these are: (1) the time lapsed effect; (2) the missing school effect; (3) and, the delay effect. Because, the authors could not find any studies of the economics relating to the metric measures regarding to the rate of return of interrupted schooling patterns in developing countries. Thisis a special significance on education development and research across education literature. For this discussion, a delay effect posed a concern as to the result that is not statistically significant and is negatively to the effect of students’ missing school and the number of years of delay before university entry for each age group in the Cultural Revolution cohort. Because, the authors used the regression statistics to estimate the students’ age and the time of interrupted education on all levels of education, and to analyze the exogenous variables for a significance between the Cultural Revolution cohort and the non-Cultural Revolution cohort for comparison on education development. For the dummy variables, authors used the multinomial logit statistics to analyze the parent background, family responsibilities, and the success rate of possessed university degrees. In which their findings stated that the variables cannot correlated to a stronger significance of difference between the university entry age of both students’ ages and parents’ ages at the time for the university entry examination. Instead, authors suggested a probability analysis as a different insight of analysis for all of the variables that has or has not over lapped on one another on time between the variables of the students’ interrupted education, missed schooling, and parents’ background based on the given data. For instance, the marginal effect based on the 1995 data indicated that students’ who missed schooling each year loses the probability by about 1 percentage point. Under the missing schooling levels: primary, junior, senior, high school and delayed university loses the probability by about to that 3, 4, 5 percentage points. Whereas, missing both junior and senior high schools loses the probability by about 7 percentage points. Meanwhile, the 1988 data indicated that missing school at every level reduced the probability of obtaining a formal degree. However, the effects on gender difference of family responsibilities while each have had experienced missing schools has indicated that they have the least chance to obtain a university degree. Similarly, for the marital status of being married before entering the university has indicated that there is a strong negative impact on a women’s probability in obtaining university degree. As there are many variables and sub variables to explore in depth on individuals missing school education background because each data year differ in separating the variables that were not included in other data year (i.e., 1988, 1990, 1995) which makes it difficult because there is no valid empirical evidence of research elsewhere beside this paper. Therefore this paper is irrelevant to support the claim of missing schools, unless university entry admission and examination has submitted the validity of such claim.

Reference

Meng, X. & Gregory, R. (2013) The Impact of Interrupted Education on Subsequent Educational Attainment: A Cost of the Chinese Cultural Revolution. Economic Development and Cultural Change, Vol. 50 (4) p. 935-959. Chicago, Illinois; The University of Chicago Press.