This paper examines the inequality of overall labor market rewards in South Korea for 2023 by combining monetary and non-monetary rewards. Using data from the Korean Labor and Income Panel Study (KLIPS), we estimate non-monetary rewards via OLS regressions, measuring the correlation between occupations and life satisfaction, and then scale the results into wage-equivalent units. Although descriptive in nature, our findings suggest that the non-monetary rewards of occupations increase overall inequality, as indicated by the standard deviation, the 90？50 gap, and the 50？10 gap. Whereas wage inequality is more pronounced in the top half of the distribution, inequality of non- monetary rewards is more pronounced in the bottom half. Including non-monetary rewards also narrows gender gaps but widens education gaps. When comparing the monetary and non-monetary rewards associated with atypical work schedules and public sector employment, we find evidence consistent with the theory of compensating wage differentials. The results highlight the importance of considering both monetary and non- monetary rewards when assessing labor market inequality, with implications for researchers seeking to better measure inequality and for policymakers designing interventions to reduce disparities.

JEL Classification: J28, J32, J81

In the context of rising geopolitical tensions and complex regulatory environments, Chinese pharmaceutical export enterprises face growing institutional barriers that hinder their participation in Global Value Chains (GVCs). Drawing on dynamic capability theory and contingency theory, this study examines how enterprise resilience— comprising anticipatory and adaptive capabilities—facilitates international collaboration under institutional pressure. Using survey data from 319 managerial respondents of Chinese pharmaceutical export enterprises and hierarchical regression analysis, the results show that both anticipatory and adaptive capabilities are positively associated with GVC participation and restructuring. Additionally, the empirical evidence partially supports the proposed moderating effects of institutional barriers—namely institutional distance, institutional uncertainty, and institutional stringency. While these barriers do not significantly affect the relationship between resilience and GVC participation, they selectively weaken its positive relationship with GVC restructuring. These findings suggest the conditional role of enterprise resilience in navigating complex institutional environments and offer preliminary insights for policymakers to improve institutional conditions and mitigate the constraining effects of institutional barriers.

JEL Classification: F14, Q34, Q56

This study finds that the one-period lagged income of China’s rice farmers, as measured by net profit, has a significant linear negative impact (inhibitory effect) on rice green total factor productivity (RGTFP), a relationship characterized by two separate single-threshold effects. Against the backdrop of escalating global climate shocks and prominent agricultural ecological issues, the ambiguity of this driving mechanism has constrained in-depth research on the green transition of rice farming. Based on panel data from 22 major rice-producing provinces in China from 2005 to 2022, our analysis using dynamic panel models (to account for time-lag effects) and threshold models (to identify non-linear shifts) reveals that for each unit increase in net profit, RGTFP decreases by an average of 0.14%. A one-period lagged farmer income threshold is identified at 857.4 CNY/ha; the negative impact is strongest in the low-income regime (below the threshold), but becomes an insignificant positive effect after crossing the threshold. Furthermore, a mechanization level threshold exists at 6.14 kW/ha; no significant impact is observed in the low-mechanization regime, whereas the impact of lagged farmer income on RGTFP turns significantly positive after surpassing this threshold. This research provides empirical support for policy adjustments aimed at fostering a green agricultural transition

JEL Classification: O13, Q56, C24

Amidst the pervasive expansion of global uncertainty, trade and the associated division of labor between Korea and China are undergoing significant structural transformations. To accurately estimate the Korea-China Free Trade Agreement's effect, this study controlled for these various confounding factors to isolate the specific impact of the agreement on bilateral trade. We employed a multifaceted methodological approach, incorporating techniques such as Two-Way Fixed Effects (TWFE), the Staggered Difference-in-Differences (Staggered DiD) framework, and event study analysis. Furthermore, the scope of the investigation was delineated by analyzing both aggregate trade flows and trade disaggregated by end-use. The findings confirm that even when juxtaposed against underlying structural changes in both economies and the prevailing uncertainty in the global trade landscape, the Korea-China Free Trade Agreement successfully acted as a stimulant for bilateral trade

JEL Classification: F13, F14, F15, C23

This study examines how digitalization influences income inequality in OECD countries, emphasizing that its effects depend on the stage of ICT development. Using panel data and a fixed-effects framework, we analyze four indicators of digitalization—fixed telephone subscriptions, mobile cellular subscriptions, individuals using the internet, and fixed broadband subscriptions—and interact them with a dummy capturing the transition to an advanced ICT era. The results show a clear stage-dependent pattern. In the early ICT-development period, digitalization reduces inequality by increasing income shares of the bottom four quintiles and reducing that of the top quintile. However, in the advanced ICT period, these equalizing effects weaken or reverse: digitalization becomes inequality-increasing, particularly for internet use and broadband subscriptions. The findings indicate that digitalization is not uniformly inclusive and underscore the need for policies that strengthen digital skills, broadband quality, and equitable participation in advanced digital ecosystems

JEL Classification: O33, O15, D31