Contributing Writer: Eric Hsienchen Chu | May, 2022
In 2020, the Korean movie “Parasite” won Best Picture in the Oscars, making a name not only in the film industry but around the globe. This film became extremely renowned because it profoundly depicted the ingrained inequalities in South Korea’s society – the suffocating contrasts of the rich and the poor. But inequality is not confined to South Korea or nearby East Asia regions; inequality happens nearly everywhere. America, for example, also stands for a place in which diversified, promising opportunities are generated, but intensified inequalities are hiding beneath.
Iris Soojin Park, an undergraduate economics alum at the University of Wisconsin-Madison, examined opportunity inequality to infer income inequality in the U.S. and her home country of South Korea in her thesis “Inequality of Opportunity in the United States and South Korea.”[1] Normatively speaking, everyone may deserve an equal opportunity in an ideal society. Yet, in reality, we often see people attain different levels of education and engage in divergent jobs. Research even suggested that such variances could stem from your zip code and neighborhood from early childhood stages[2]. Economists try measuring these ‘variant outcomes’ by the Lorenz Curve, the derived Gini coefficient, or the other empirical methods, while the income(general) inequality naturally exists. Then the consequent question people might ask is: What is this income inequality attributable to? The composition of the income inequality can be mainly divided into two categories – the opportunity inequality and the effort inequality. The opportunity inequality and its factors “circumstance variables” capture the conditions that one can hardly decide on their own, such as sex, race, and family background. The effort inequality, on the other hand, implies the “effort variables” and situations in which one can utilize different degrees of effort to achieve distinguished individual outcomes. In this research, effort variables are simply defined as all the non-circumstance variables.
To further discuss her research models, Park explains that her research method was based on the previous study of Checchi and Peragine (2010), with two parts “ex-ante,” focusing on circumstances, and “ex-post,” focusing on effort, approach, which both measure income inequality[3]. The ex-post approach which Park implemented suggests that the opportunity equality among each person should appear once individuals’ degree of effort is controlled. To control the effort levels, XWS is denoted to the smooth income vector (XS) that captures the effect of circumstances on individuals’ income. Similarly, to control the circumstance levels, XBS is denoted to capture the effect of effort on individuals’ income. The Mean Log Deviation (MLD(X)) is then used to measure the Inequality Indexes, with I(XS) representing general income inequality, I(XWS) representing opportunity inequality, and I(XBS) representing effort inequality. The fraction I(XWS) / I(XS) means overall share of income inequality caused by opportunity inequality, and I(XBS) / I(XS) means overall share of income inequality caused by effort inequality. Thus, these two proportions and the MLD indexes could be used for further inference. While circumstance has been commonly discussed while identifying income variation and inequality, discussion of the effects of effort variables does not gain enough attention as it should. The value of Park’s research stands right on this foothold that she built an analysis of the U.S. and South Korea regarding the composition of income inequality with the circumstance/effort variables examination, since not so much precedent studies using this method have been conducted in the U.S.
It is worth noting that in this study Park defined circumstance variables and effort variables to be independent of each other, which might not always be the real case. An obvious counterexample is the education an individual can achieve. Education level is often the mixed result from both circumstance and effort, as one might work hard on coursework, engage in myriads of extracurriculars, and probably have supporting family backgrounds. This situation is simplified in Park’s research assumptions extending for empirical analysis. Speaking of the datasets, Park analyzes demographics in the US and South Korea. The former includes sex, race, income level, and the education level of parents with a sample size of 25,000 throughout 2007-2017, and the latter considers labor information, income, and parents’ education level and occupation with a sample size of 7,800 from 2003-2019, discarding ethnicity since South Korea is relatively racially homogeneous.
The statement that “Income inequality is significantly affected by opportunity inequality” might be already expected, and Park’s findings certify it with several more statistical findings. First of all, individual circumstances (i.e. opportunity inequality) still affect income inequality (i.e. general inequality) to a great degree, with a percentage of 18% in the U.S. and 22% in South Korea. These statistics also suggest that an individual’s sex and parental education, which are listed under circumstance variables of the opportunity inequality, play prominent roles in determining one’s income in South Korea than in the U.S. Furthermore, while South Korea reveals a relatively greater opportunity inequality than the U.S., the general income inequality is adversely larger in the U.S. than in South Korea. This result implies individual effort (effort inequality) impacts a higher proportion of income inequality in America than in South Korea.
Lastly, in terms of regional analysis, while the difference of opportunity inequality in South Korea is not significant, the U.S. displays huge divergence among different areas. Generally, the Northeast has a more significant opportunity inequality than the South and the West, and a potential cause may be the relative abundance of high-skilled laborers in the Northeast. While people in the Northwest put in great effort to acquire higher degrees of education, it is possibly not enough for them to get jobs from such a competitive environment, which means parents’ privileged ability derived from educational background (circumstance) is still a critical factor in these young students’ ability to ‘realize’ their academic credentials into high salaries. This alerts the issue of intergenerational mobility[4][5].
Our general expectation of income inequality and opportunity inequality is validated in Park’s study, but there remains some room for justification. As a first limitation discussed previously, this study assumed effort is independent of circumstances, saying that it fits empirical cases. But sometimes there are occasions that we can not easily define which category a situation belongs to. For example, Park listed education acquired, labor market participation, and birth choice as counterexamples of her core assumption, and these violations are simplified in the research assumptions so that they could fit empirical cases. However, a question might arise is that when a determinant commingles with both the circumstance and effort categories and is simply omitted, the interpretation of the percentage of income inequality caused by opportunity inequality apparently would also be affected/distorted. Park did not justify this issue clearly, which might mitigate the credit of the research result.
Secondly, Park’s study would be more inclusive and well-rounded if it had run “state-by-state” analysis in the U.S. and had explained why the rural area of South Korea has a higher total inequality and opportunity inequality than Seoul Metropolitan. The former is mainly restricted by the fact that not enough sufficient and varied datasets were acquired amongst the states. The latter, though not stated in her study, is quite intriguing while inspecting the statistical results and leaves room for eliciting further arguments and study. Meanwhile, the composition of the general inequality figure shown in this study is partitioned with respect to sex, and the treatment of these partitions of the “South Korea vs the U.S.” analysis caused a bit of confusion. Understandably, a circumstance variable is chosen to illustrate the opportunity inequality share, but we would also be interested in seeing the result if examined by race or the other circumstance variables, given that race might provide a different angle of interpreting the percentage of opportunity inequality in varied areas. It would be better if we see such comparisons in this study. Also, the location partitions of the U.S. are divided into four areas – Northeast, North Central, South, and West – while South Korea is simply defined as Seoul vs Rural area. Even though it is stated that regional differences in South Korea are not significant, the yardstick of this comparison identifying “significant” remains unanswered in this study.
Overall, despite the several limitations discussed above, this research still confirmed our intuition of how opportunity/effort inequality affects income/general inequality. Park suggests a compelling answer to “Why does individual effort yield higher outcomes in America than in South Korea”- it is due to the differences in education systems and the scarcity of workers possessing post-secondary degrees in these two countries. Accordingly, the data reports that 70% of the young population in South Korea earns a college degree[6], dominating that of 47% in America[7]. Since the scarcity of higher degrees of education for a laborer is relatively low in South Korea, it will be more challenging for a South Korean student to compete for a job and thus the outcomes for a South Korean student’s effort would typically be lower than for an American. This inference is aligned with her finding that the Northeast has a larger opportunity inequality than the South and the West. Following a similar argument, we could restate that ample opportunities for higher-level education are provided in South Korea and the Northeast area, compared domestically, the marginal benefit of acquiring higher degrees diminishes and thus it is not enough for young adults in these areas to realize their education into high returns.
REFERENCE
- Park, I., (2021). Inequality of Opportunity in the United States and South Korea. Department of Economics, the University of Wisconsin-Madison.
- Chetty, R., & Hendren, N. (2018). The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects. Quarterly Journal of Economics, 133(3), 1107–1162. https://doi-org.ezproxy.library.wisc.edu/https://academic.oup.com/qje/issue
- Checchi, D., & Peragine, V. (2010). Inequality of opportunity in Italy. The Journal of Economic Inequality, (8), 429–450. https://doi.org/10.1007/s10888-009-9118-3
- Aiyar, S., & Ebeke, C. (2019). Inequality of Opportunity, Inequality of Income and Economic Growth. IMF Working Paper.
- Chetty, R., & Hendren, N. (2018). The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates. Quarterly Journal of Economics, 133(3), 1163–1228. https://doi-org.ezproxy.library.wisc.edu/https://academic.oup.com/qje/issue
- Kim, V. (2019). In a tough market, young South Koreans vie for the security of government jobs. Los Angeles Times. https://www.latimes.com/world/asia/la-fg-south-korea-jobs-20190206-story.html
- Frezza, R., Ayres, C., Aghanoury, P., Coffman, T., & Johnson, J. (2018). South Korea Has the Most Educated Young People in the Entire World. College Media Network. https://www.collegemedianetwork.com/south-korea-has-the-most-educated-young-people-in-the-entire-world/