Asian Economic Journal最新文献

This paper empirically investigates the impact of global value chain (GVC) participation on environmental pollution using data from China's manufacturing sector. A new Environmental Performance Index (EPI) is introduced as a proxy for assessing changes in environmental pollution. The key findings are as follows: Firstly, although total factor productivity (TFP) in China's manufacturing sector has not shown recent improvement, green total factor productivity (GTFP) has increased. This finding suggests an improvement in environmental quality. Secondly, an increase in the degree of GVC participation is associated with greater environmental pollution. Thirdly, an increase in the GVC position index across all industries in China contributes to a reduction in environmental pollution, suggesting that as production moves upstream, environmental quality tends to improve. Fourthly, however, in the case of energy-intensive industries, this reduction in environmental pollution was not evident. These findings highlight the importance of directing governmental policies toward promoting forward GVC participation rather than backward participation, particularly for reducing environmental pollution. However, it is crucial to note that for energy-intensive industries, shifts in GVC position toward the upstream may not necessarily result in environmental improvements.

This study examines the effect of class size on the academic achievement of ninth-grade students, using random variation in enrollment as an instrument for class size. I find a substantial improvement in reading test scores after a reduction in class size. These favorable effects are especially strong for students in coeducational schools and for boys. Distributional analysis shows a beneficial effect on reading across all percentiles and on mathematics and English in the lower and middle percentiles. I find that reducing class sizes increases counseling sessions and reduces incidents of school violence, resulting in beneficial effects on academic performance. These findings indicate that the beneficial effect can be attributed to the improved teacher–student relationship and the peer-to-peer relationship. These results suggest that the effect of class size reduction depends on the classroom environment.

The recent advances in robotics technologies and increased adoption of industrial robots have brought about tremendous changes to the production processes and labor market, thus raising the question of how women fared relative to men in this process. In this paper, we study the impacts of robot adoption on gender inequality. Using data on robot imports of Chinese industrial firms, we find that the use of robots significantly increases the relative share of female employees and thus reduces the gender employment gap. We then examine the heterogeneous impacts across industries and regions and find stronger positive effects of robots on women's employment in labor-intensive industries, low- and medium-tech sectors, male-intensive industries, and regions with lower female educational attainment. Further empirical analysis suggests that the use of robots significantly reduces the gender pay gap for low-skilled workers, but not for higher-skilled workers. Our findings are consistent with the fact that robots mainly substitute for brawn skills in which men have a comparative advantage. Overall, our study highlights the importance of robots and other automation technologies in boosting women's employment and reducing gender inequality in the labor market.

This study examines household income mobility in South Korea during two distinct periods (2011–2014 and 2014–2017), employing a second-order Markov chain model that incorporates novel analytical approaches, including Markovity tests, Class Mobility Delta (CMD), and phase-type distribution analyses. We find that income transitions depend significantly on income classes of the preceding 2 years rather than just 1 year. Our CMD analysis shows that income classes exhibited statistically significant divergence during 2014–2017, characterized by bipolarization with expansion at both the top (Q7) and contraction in the middle (Q4). Furthermore, phase-type analyses reveal statistically significant reductions in the expected absorbing time for lower-income groups transitioning to middle and upper classes, suggesting enhanced upward mobility during 2014–2017. These results underscore the importance of long-term policy approaches that address deeper structural dynamics influencing household income mobility.

This study examines the distinct economic effects of administrative and fiscal decentralization, explores their interrelationship, and investigates the underlying mechanisms. Using China's county-level decentralization reforms, the analysis shows that administrative decentralization promotes economic growth, particularly by advancing the secondary industry through reduced business costs and enhanced firm profitability. In contrast, fiscal decentralization, while driving local governments to raise firm debt and tax burdens, does not significantly boost economic growth on its own. Nevertheless, the two forms of decentralization are found to be complementary: when implemented jointly, they support industrial upgrading through more efficient resource allocation and help reduce regional growth disparities. Finally, in combination with a provincial analysis, this study suggests that an effective decentralization strategy involves simultaneously delegating both fiscal and administrative powers to the lowest levels of government.

Cheng, Q., Xiong, Y., & Liu, J. (2025). The impact of electric vehicle adoption on regional energy market integration in China. Asian Economic Journal, 39(2), 217-244. https://doi.org/10.1111/asej.12353

Affiliation 1 must be removed from the second author. The correct list of authors and their affiliations is as follows:

Qian Cheng^1,2, Yongqing Xiong², Jinghui Liu²

¹Party School of the Guangdong Provincial Committee of CPC, Guangzhou, Guangdong, China

²Business School, Central South University, Changsha, Hunan, China

We apologize for this error.

It is well documented that firms that participate in global value chains (GVCs) are larger and more productive, maintaining higher profitability compared to those without such connections. This paper asks the novel question of whether higher profits being connected to GVCs are shared with employees in the form of better pay. We investigated this rent sharing, using a matched employer-employee dataset of Vietnamese small firms surveyed between 2011 and 2015. There is no evidence for the presence of rent sharing in GVC-participating firms. We take this as evidence that GVC firms provide both higher wages and insurance against wage shocks.

Spatially granular poverty statistics can enhance the efficiency of targeting resources to improve the living conditions of the poor. Previous studies suggest that the use of high-resolution satellite imagery may be an alternative approach in generating granular poverty maps. This study outlines the methods in improving the spatial granularity of government-published poverty estimates using convolutional neural networks and ridge regression applied on publicly available satellite imagery, household surveys, and census data from the Philippines and Thailand. A convolutional neural network (CNN) was used to extract features of satellite images that are correlated with the intensity of nightlights. These features were then aggregated at the same level for which government-published estimates were available to estimate a prediction model for poverty rates. Results suggest that the adopted methodology performed satisfactorily in predicting lower levels of nightlight intensity for the specific years considered in this study. Additional preliminary numerical assessment also reveals that prediction accuracy may be enhanced by using random forest as an alternative to ridge regression. The use of proprietary satellite images with higher resolution may also improve prediction accuracy.

As non-financial resources, social networks have a pervasive influence on career prospects. However, among social networks, which relationships are most beneficial for self-employment? This study used survey data from rural–urban migrant workers in Beijing to examine the role of personal networks in rural migrants' self-employment decisions. Social networks were categorized based on the heterogeneity of occupational status. The analysis revealed that networks related to information exchange are more pivotal than those associated with the influence of migrants' self-employment decisions. Furthermore, social networks emanating from lower occupational status significantly decreased the likelihood of self-employment in individuals. Additionally, males and newcomer migrants received greater social support from information-related networks and were more likely to pursue self-employment. Our findings indicated that self-employed migrants earn higher incomes than wage earners, exhibit a greater propensity to settle in Beijing, and report higher satisfaction with their lives and economic status.

China progressively relaxed its one-child policy since 2013, allowing families to legally have a second child. Using data from the China Family Panel Studies and applying a difference-in-differences event-study approach, we find that the family size outcomes are nonlinear. We find the maternal labor force participation rate drops permanently after the second childbirth, but only temporarily after the first birth. The first child does not significantly worsen household finances by compressing non-essential expenses, whereas the second child does worsen them due to the lack of room for further frugality. This suggests that fertility incentives, especially based on material factors, may be more efficient when the childbearing structure of families is considered.