Roy Kwon

Employment transitions and the cycle of income inequality in postindustrial societies

This article presents the claim that the current transition from service to knowledge employment impacts income inequality in a manner that is comparable to the previous transition from agriculture to industry. This contention is tested by an employment transition index that calculates the difference of employment between the higher- and lower-paid sectors of the economy. The calculation of this index is consistent with Kuznets’s view that income inequality increases during the early stages of industrialization due to the presence of a small and higher-wage modern sector that encroaches on the total numbers employed in the large and lower-wage traditional sector. However, income inequality eventually declines with continued industrialization as more workers enter the modern sector of the economy. Results confirm the central argument of this study for a panel of 25 Organisation for Economic Co-operation and Development countries from 1980 to 2008. According to the findings, classical Kuznetsian variables such as sector-dualism are not significant and/or signed in unanticipated directions in their prediction of income inequality. Instead, the employment transition index returns robust negative associations with income inequality and consistently outperforms sector-dualism. Furthermore, knowledge employment returns positive and significant connections with the dependent variable net of the employment transition index. These results confirm that both between- and within-sector employment patterns are key determinants of income inequality.

A New Kuznetsian Dynamic: The Knowledge Economy and Income Inequality in the United States, 1917–2008

The rise of the knowledge economy resulted in higher levels of income inequality in the United States and forced many to question the Kuznets Inverted-U hypothesis. However, this study argues that the establishment of a knowledge economy does not negate the importance of employment shifts for income inequality. Instead, the expansion of knowledge employment alters the major sectors that are responsible for the overall distribution of income. To this end, this article presents the key argument that the current service–knowledge transition impacts income inequality trends, of today, in a way that is similar to the agricultural–industrial transition, of the past. According to the autoregressive conditional heteroskedasticity regressions, the agricultural–industrial transition returns stronger associations with income inequality in the United States before 1950. The agricultural–industrial transitions impact diminishes thereafter as the service–knowledge transition shares a more robust association with income inequality after 1980.

Socioeconomic factors and mass shootings in the United States

Abstract This study explores whether population-level measures of income inequality and poverty rates are associated with mass shootings in the United States. We test these potential connections by examining the incidence rate of mass shootings using random effects negative binomial regressions for a panel data-set that included 3144 counties for the years 1990–2015. According to the adjusted models, income inequality is significantly associated with the three or more victim-related injuries (incidence rate ratio [IRR] = 1.39; 95% confidence interval [CI] = 1.11, 1.67; P < .001) and four or more victim-related deaths definition of mass shootings (IRR = 1.36; 95% CI = 1.08, 1.64; P < .01). However, poverty rates lack a reliable association with the three or more injuries (IRR = 1.07; 95% CI = .75, 1.39) and four or more deaths definition (IRR = .95; 95% CI = .71, 1.19). When considered in conjunction with the literature on inequality and crime, these results indicate that counties with high inequality may foster an environment of anger and resentment that ultimately leads to mass shootings.

What factors matter for trade at the global level? Testing five approaches to globalization, 1820–2007

This article uses a global-level dataset with information across nearly two centuries to explore the factors associated with the expansion of international trade. The results of the autoregressive conditional heteroskedasticity regressions show that trade since the early 1800s is strongly coupled with advancements in industrial technology and its ability to cut the cost of commodities transport. In addition, the spread of democracy and the geopolitical stability promoted by the hegemonic nation-state are additional factors that augment trade during the past two centuries. The findings also reveal that trade since the early 1900s is further enhanced by the growing membership base of the United Nations and the World Trade Organization, given their propensity to generate compatible national institutions and a uniform set of rules for cross-national commodities exchange. However, there is no support for the claim that advancements in communications technology or the expansion of international governmental organizations increases trade globalization.

Income Inequality, Household Income, and Mass Shooting in the United States

Mass shootings are becoming a more common occurrence in the United States. Data show that mass shootings increased steadily over the past nearly 50 years. Crucial is that the wide-ranging adverse effects of mass shootings generate negative mental health outcomes on millions of Americans, including fear, anxiety, and ailments related to such afflictions. This study extends previous research that finds a strong positive relationship between income inequality and mass shootings by examining the effect of household income as well as the interaction between inequality and income. To conduct our analyses, we compile a panel dataset with information across 3,144 counties during the years 1990 to 2015. Mass shootings was measured using a broad definition of three or more victim injuries. Income inequality was calculated using the post-tax version of the Gini coefficient. Our results suggest that while inequality and income alone are both predictors of mass shootings, their impacts on mass shootings are stronger when combined via interaction. Specifically, the results indicate areas with the highest number of mass shootings are those that combine both high levels of inequality and high levels of income. Additionally, robustness checks incorporating various measures of mass shootings and alternative regression techniques had analogous results. Our findings suggest that to address the mass shootings epidemic at its core, it is essential to understand how to stem rising income inequality and the unstable environments that we argue are created by such inequality.