This study examines the dynamic and nonlinear effects of remittances on poverty, income inequality, human development, and financial development across 37 Asian countries from 1990 to 2022. Using System-GMM and panel quantile regression techniques, the study addresses endogeneity, heterogeneity, and distributional differences. The findings show that remittances significantly promote financial and human development by improving access to education, healthcare, and formal financial services. However, its effects on poverty and inequality are nonlinear and heterogeneous. Remittances initially reduce poverty and overall inequality, but their marginal developmental benefits weaken beyond a threshold, providing partial support for the Remittance Kuznets Hypothesis. While remittances increase inequality among lower-income groups, they reduce inequality at higher income levels. The results further reveal that stronger institutional quality enhances the developmental impact of remittances. Overall, the study underscores the importance of effective governance, financial inclusion, and migration policies in maximizing the developmental benefits of remittances in Asian economies.
Using annual data from 1960 to 2023, we estimate autoregressive distributed lag models to examine the effects of population aging and technological advances in high-cost areas of medical care, such as cancer treatment, on Japan’s public healthcare insurance finances in the long-run. Results show that while population aging and technological advances increase healthcare expenditure and public burden, their effects on insurance premiums and out-of-pocket payments differ. An increase in public burden will further deteriorate the Japanese government’s finances, which are already heavily indebted. Policy implications are presented to ensure the sustainability of the public healthcare insurance system in the future.
This study examines how the environmental experience of executive successors shapes corporate green investment in high-pollution industries. Drawing on attention-based theory, we argue that successors with prior exposure to environmental, social and governance (ESG) issues are more likely to direct managerial attention toward environmental protection, thereby increasing firms’ commitment to green investment. By using 268 firm–year observations of Chinese listed companies in heavy-polluting sectors between 2010 and 2019, we construct a multiple mediation model to assess the role of executive environmental attention and consider the mediating effect of successor origin. The results show that executive successors with environmental experience significantly enhance corporate green investment, and that this effect is mediated by their heightened attention to environmental issues. Robustness checks with year-fixed effects and alternative investment measures confirm the findings. These results highlight a distinct pathway from executive background to corporate sustainability outcomes, emphasizing the mediating role of attentional focus. For firms in highly regulated and environmentally sensitive industries, the study offers a concrete implication: succession planning should account for candidates’ ESG-related experience and attentional orientation, as these attributes materially influence green investment decisions. By incorporating environmental experience into leadership selection, firms can strengthen their environmental performance while maintaining competitiveness under increasing sustainability pressures.
Against the backdrop of the ongoing global green transition, how environmental governance reforms can steer newly created productive capacity toward low-carbon development has become a critical issue for achieving deep industrial decarbonization. This study exploits China’s reform of the vertical management system for environmental monitoring, supervision and law enforcement below the provincial level as a quasi-natural experiment. Using prefecture-level firm registration data from 2012 to 2023 and the staggered rollout of the reform across provinces, we employ a staggered difference-in-differences model to examine its effects on low-carbon firm entry and the underlying mechanisms. The results show that the environmental vertical management reform significantly promotes the entry of low-carbon firms, and this finding remains robust across a series of robustness checks. Mechanism analysis indicates that the reform facilitates low-carbon firm entry by reducing institutional barriers to entry and improving the efficiency of capital allocation. Heterogeneity analysis reveals that the effect is concentrated in knowledge-intensive industries, including scientific research and technical services, leasing and business services, and culture, sports and entertainment. The effect is also more pronounced in regions with greater dependence on tax revenues and in cities located away from provincial borders. Further analysis shows that the reform promotes industrial low-carbon transformation through multiple margins. At the aggregate margin, it facilitates the entry of firms in low-carbon industries and the exit of firms in high-carbon industries. Within high-carbon industries, it induces a green structural reallocation from more carbon-intensive firms toward less carbon-intensive firms. It also encourages surviving high-carbon firms to upgrade their production by increasing environmental investment and pursuing green technological innovation. By examining both firm entry and exit, this study uncovers the micro-level mechanisms through which environmental governance reform shapes industrial low-carbon transformation and provides empirical evidence and policy implications for improving vertical environmental governance and advancing coordinated industrial decarbonization.
Enhancing green water resource utilization efficiency (GWRUE) is a critical imperative for developing nations pursuing a comprehensive green transition. This study theoretically and empirically investigates the impact of urban digitalization on GWRUE and its underlying mechanisms. Using panel data from 282 Chinese cities from 2013 to 2022, we leverage the establishment of China's National Big Data Comprehensive Pilot Zones as a quasi-natural experiment. We first employ a Super-Efficiency Slacks-Based Measure (SE-SBM) model to calculate GWRUE, then utilize a multi-period Difference-in-Differences (DID) framework to assess the policy's causal effect. The empirical results demonstrate that urban digitalization significantly improves GWRUE, a conclusion robust to a series of validation tests.The heterogeneity analysis reveals that the positive effect is statistically significant across most regions excluding the West, while the Central region exhibits the greatest magnitude. Additionally, the impact is notably more pronounced in resource-based cities than in their non-resource-based counterparts. Further mechanism analysis indicates that urban digitalization drives GWRUE improvements by enhancing sewage treatment, fostering green technological innovation, and optimizing industrial structure. Moreover, a moderation analysis shows that environmental regulation positively amplifies the impact of urban digitalization on GWRUE. These findings offer robust evidence for the role of digitalization in promoting sustainable water management and provide valuable policy insights for developing countries aiming to leverage digital transformation for green development.
This study examines whether platform characteristics affect NPLs in peer-to-peer lending. This research helps regulators understand P2P lending platform expansion regulations and investor decision-making. The dataset came from 61 Indonesian platforms registered before and during COVID-19. It uses Generalized Least Squares panel regression and subsample analysis. This study shows consumptive loans increase NPLs. NPLs and CEO age in P2P lending platforms are also linked by the research. License from regulator is only significantly related to NPL for short-duration platforms. This work pioneered P2P lending research distinguishing productive from consumptive loans.
Gender wage inequality persists in Taiwan despite substantial improvements in women’s labor force participation and educational attainment over the past four decades. Using nationally representative data spanning the period from 1982 to 2022, gender wage differentials across the wage distribution are examined through the Recentered Influence Function decomposition framework. This approach allows the total wage gap to be separated into composition effects arising from differences in observable characteristics and wage structure effects reflecting differential returns to those characteristics. Across all quantiles, real wages increased for both men and women, while men consistently earned higher wages throughout the sample period. The gender wage gap is primarily driven by the wage structure effect, indicating that differences in returns to characteristics dominate the contribution of observable endowments. These differential returns reflect not only potential social discrimination but also structural mechanisms such as occupational sorting, heterogeneity in labor market valuation and differences in employment arrangements. The relative importance of these mechanisms varies across the wage distribution, with age contributing more strongly at lower and middle quantiles and employment type playing a larger role at the upper end. The composition effect contributes modestly to the gender wage gap and, at lower wage levels, is associated with an increase in women’s relative wages. This pattern suggests that improvements in women’s observable characteristics partially mitigate wage inequality at the bottom of the distribution but are insufficient to offset structural disparities in wage determination. Marital status systematically amplifies the wage structure effect in favor of men, while family-related characteristics widen the wage gap through compositional differences, particularly among low-wage workers. The evidence indicates that gender wage inequality in Taiwan is shaped predominantly by structural differences in wage-setting processes rather than by disparities in observable characteristics. Policies focusing exclusively on human capital accumulation or labor force participation are therefore unlikely to eliminate gender wage gaps. More effective interventions are likely to involve reforms that address wage-setting institutions, career progression mechanisms, and the unequal allocation of family responsibilities in the labor market.
Whether cloud adoption improves corporate carbon efficiency remains underexplored, since prior work has concentrated on aggregate environmental outcomes and left the firm-level routes largely unexamined. Drawing on Chinese A-share listed companies from 2013 to 2023, this study applies a staggered difference-in-differences design to estimate the effect of cloud adoption on carbon emission intensity, with the Sun-Abraham and Callaway-Sant'Anna estimators employed to address heterogeneous adoption timing. Results show that cloud adoption significantly reduces carbon emission intensity, a finding that survives parallel trends testing, placebo testing, and propensity score matching. Cloud adoption raises operational efficiency by enabling more precise asset scheduling and resource allocation, and fosters technological innovation by lowering the cost of data-intensive experimentation. The effect is more pronounced in high energy-consuming industries and among large firms, reflecting stronger compliance incentives and deeper technical integration capacity, respectively. These findings extend the understanding of cloud computing's environmental effects from infrastructure-level energy savings to firm-wide carbon efficiency, offering practical guidance for enterprises embedding cloud adoption into decarbonization strategies and for policymakers directing green technology support, with potential reference value for other Asia-Pacific economies navigating comparable digital and environmental transitions.
Whether open government data improve how efficiently firms convert R&D resources into innovation outcomes remains underexplored, as existing studies focus on the scale of innovation activity rather than the quality of output per unit of input. Drawing on A-share listed firms in China from 2007 to 2024, this paper exploits the staggered rollout of public data platforms across 283 prefecture-level cities as a quasi-natural experiment. Platform launch raises the intensity of invention patent output per unit of R&D investment, and this effect proves robust to alternative specifications including patent quality measures, stochastic frontier efficiency scores and constructions that accommodate the multi-year examination cycle of invention patents, as well as to corrections for endogeneity. Platform launch is followed by a systematic narrowing of corporate bond issuance spreads within cities, a result that holds after controlling for local government financing vehicle issuance volumes, suggesting that government disclosure of administrative records lowers the cost for external capital providers to verify firm credit conditions and compresses financing risk premiums. Firm-level financing constraint indices and commercial credit utilization patterns yield concordant evidence on the channel. The positive effect is more pronounced among private enterprises, R&D-intensive industries and cities with stronger digital infrastructure, indicating that gains from open data depend on firms’ information needs aligning with the absorptive capacity of their local digital environment. These findings carry implications for open data governance reform across developing economies in the Asia-Pacific region.
This study examines changes in China’s fiscal policy before and after the US–China trade war during President Trump’s first term using the Granger causality test with monthly data from January 2015 to July 2021. The findings are as follows: Before the trade war, taxation played a key role in supporting exports, controlling imports and promoting consumption, while government expenditure had a limited impact on exports and domestic consumption. After the trade war, exchange rate volatility increasingly influenced government expenditure and tax revenues. Government spending significantly impacted exports, imports, taxes and consumption, while taxes continued to affect exports and imports. The trade war created uncertainty in the global trade environment, challenging China’s fiscal policy. However, the government’s policy adjustments before and after the trade war showcased its flexibility and resilience, highlighting the fiscal policy’s role in adapting to new economic conditions, stabilizing the economy and sustaining international trade. This study provides insights into the potential effects of US–China trade tensions during Trump’s second term and offers a basis for understanding future fiscal policy adaptations. It is recommended to enhance export competitiveness, maintain stable tax policies, adopt proactive fiscal measures, manage exchange rates and boost domestic consumption.
Amid growing global uncertainties, agricultural supply chain resilience (ASCR) is vital to national economic stability. Although supply chain resilience has been widely studied, the role of digital financial inclusion (DFI), particularly as moderated by the digital access divide, remains underexplored. To address this gap, this study leverages Chinese provincial data to investigate how DFI strengthens ASCR and the moderating role of the digital access divide. We find that DFI significantly enhances ASCR by improving supply chain integration and increasing credit accessibility. It also boosts all three resilience dimensions–emergency response, recovery, and transformation–with the strongest impact on transformation. However, while DFI shows strong positive effects in the eastern region, its impact is limited in central-western regions. Critically, the digital access divide significantly diminishes benefits of DFI. These findings highlight the urgency of bridging this divide to unlock full potential of DFI. This study advances the theoretical understanding of DFI and supply chain resilience and offers practical insights for optimizing rural financial services, formulating differentiated regional policies, and enhancing ASCR.
In the context of globalization, variations in carbon emission intensity and economic growth rates exhibit not only direct, reciprocal effects within individual countries but also indirect transmission mechanisms across regions and nations. Employing the Global Vector Autoregressive (GVAR) model and utilizing quarterly data from 33 countries—including 8 Eurozone members—spanning from the first quarter of 1990 to the fourth quarter of 2019, this paper demonstrates that major global economies continue to exhibit salient features of low-carbon economic development. Specifically, reductions in carbon emission intensity in developed countries frequently exert adverse spillover effects on the economic growth rates of other nations. In response to negative economic shocks, numerous countries increase their carbon emission intensity as a countercyclical measure, while others reduce emissions—potentially reflecting that they have surpassed the turning point posited by the Environmental Kuznets Curve (EKC). These findings highlight that advancing low-carbon economic development requires sustained improvements in production technologies and energy efficiency, alongside strengthened international cooperation in carbon emissions management, in order to alleviate the additional costs arising from the asynchronous progression of global carbon reduction efforts.
China’s “Dual Carbon” strategy faces severe challenges from rapid land urbanization, and the resulting erosion effect on terrestrial vegetation carbon sequestration requires precise quantification. Based on panel data from 288 Chinese cities, this study empirically tests the distributional dependence of land urbanization’s impact on terrestrial vegetation carbon sequestration using the Quantile-on-Quantile Regression (QQR). The results show that: (1) The effect of land urbanization on terrestrial vegetation carbon sequestration exhibits an inverted U-shaped relationship, with the average inflection point occurring at a land urbanization level of 14.3%. (2) This relationship demonstrates significant distributional heterogeneity: the more favorable the ecological baseline conditions, the later the negative inflection point of land urbanization’s impact on vegetation carbon sequestration appears, indicating that a stronger ecological baseline enhances resilience to land urbanization pressures. However, once the inflection point is exceeded, the decline in vegetation carbon sequestration accelerates more rapidly in regions with superior ecological conditions. (3) Compared to traditional linear regression and quantile regression, the QQR provides results with higher precision and captures the nonlinear influences under varying levels of land urbanization and carbon sequestration conditions. (4) Based on these findings, land management and ecological conservation policies should establish a differentiated governance system tailored to urban development stages and ecological endowment characteristics. Specifically, three typical models can be identified: eco-optimization, resource-dependent and high-density expansion, to enhance the targeting and effectiveness of policy implementation.
This study examines whether the technological innovation performance of Chinese firms is driven by government foreign direct investment (FDI) policies - specifically the Catalogue for the Guidance of Foreign Investment Industries - or by endogenous spillovers among domestic firms. Utilizing a difference-in-differences framework, we investigate the impact of China's FDI policy and inter-firm knowledge spillovers on firm-level innovation outcomes. Our identification strategy compares a treatment group of firms in industries prioritized by the Catalogue against a control group of non-beneficiary firms. The findings reveal that the policy's impact is highly significant during the high-growth period (2002-2011) but dissipates during the "New Normal" era (2012-2019). Conversely, inter-firm spillovers consistently and significantly bolster innovation across both periods. Furthermore, regional analysis indicates that policy effects are most pronounced in the economically developed eastern provinces. These results suggest that as the Chinese economy matures, endogenous knowledge diffusion increasingly surpasses direct policy intervention as the major driving force of technological progress.
The monetary value of a loss is conceptually best measured by the minimum sum people require to accept it, willingness to accept (WTA), yet analysts routinely substitute the maximum amount people are willing to pay (WTP) to avoid it. This substitution has long been justified by the assumption that WTA and WTP are approximately equivalent. Decades of empirical evidence now decisively refute that assumption: WTA systematically and substantially exceeds WTP, a divergence rooted in the asymmetric structure of reference-dependent preferences. Continued reliance on WTP therefore leads to a serious understatement of the value of losses, biasing policy responses toward inadequate protection. We illustrate these consequences using the prominent valuation of the 2010 BP Deepwater Horizon oil spill.
This paper examines the relevance and frequency of econometric methods in 3,125 empirical papers published in 27 top economics journals during 2014-2018. There are three major findings. First, 93% of these empirical papers use microdata, while only 7% and 4% of them employ macrodata and time series data, respectively. Second, two-stage least squares and difference-in-differences are the two leading identification strategies, accounting for nearly half and a quarter, respectively, in empirical studies using microdata. Third, there is a clear divide in empirical studies using microdata and macrodata in terms of data collection, identification strategies and econometric methods.
This study investigates the impact of a natural experiment - the establishment of China's free trade zones (FTZs) - on employment in manufacturing enterprises. Using data from the China National Tax Survey (2010-2020) and employing a difference-in-differences method, we find that FTZs significantly promote employment growth, especially for non-state-owned, younger trading enterprises. Mechanism analysis reveals that FTZs substantially reduce corporate tax burdens and improve access to financing, thereby alleviating cash constraints. These improvements in financial conditions facilitate increases in fixed-asset investment. In addition, related institutional innovations within FTZs contribute to reducing operating costs and improving production efficiency. The institutional innovations embodied in China's FTZs offer valuable policy implications for other developing economies seeking to stabilize labor markets and promote economic growth.
This paper develops a Diamond-Mortensen-Pissarides search-and-matching model to study how blockchain-related primitives affect labor-market outcomes. Adoption raises the effective matching parameter A(eta) subject to private R&D cost eta, reflecting reductions in search, verification, and coordination frictions. Comparative statics reveal a cost threshold: modest eta lowers unemployment, while high costs offset these gains. We show that the welfare effects of firm-side taxation are non-monotonic: lower taxes increase employment but also raise recruiting costs, generating a trade-off that yields an interior optimal tax rate when the social cost of unemployment is sufficiently high.
