Search Results (41)

This study analyzes the linkage between the higher education budget, college enrollment, and economic growth in Indonesia. Using a simultaneous equation model estimated with Three-Stage Least Squares (3SLS) over the 1974–2024 period, this study explores the sectoral dynamics of macroeconomic interdependencies. The results indicate an anomaly: increased higher education budgets are not significantly associated with higher college enrollment rates. However, higher education is significantly associated with improvements in labor productivity and has become one of the primary drivers of national output growth. Furthermore, a structural transformation pattern is observed, in which higher education is associated with labor mobility out of the primary sector into more productive sectors, a pattern that is consistent with, though not conclusive evidence of, the structural dynamics. This study recommends reorienting the budget toward reducing education costs and synchronizing investment policies to better accommodate skilled labor. Full article

Drawing on a panel of Chinese A-share listed firms covering 2007 to 2024, we construct a firm-level measure of climate risk exposure based on textual analysis of annual reports. Employing a three-way fixed effects model combined with endogeneity corrections and a battery of robustness checks, we empirically identify the causal effect of climate risk on the cost of debt, as well as its underlying transmission mechanisms and heterogeneous boundary conditions. Our analysis yields three core findings. First, climate risk exerts a statistically significant and economically meaningful positive effect on the cost of debt, indicating that greater climate risk exposure amplifies firms’ debt financing burdens. Second, the impact operates through two parallel transmission channels. On the one hand, climate risk erodes corporate financial fundamentals by disrupting production and operations and elevating default risk. On the other hand, it damages non-financial reputation by triggering downgrades in Environmental, Social, and Governance (ESG) ratings and weakening long-term financing credibility. Third, the relationship between climate risk and the cost of debt is significantly moderated by firm- and industry-level characteristics: high-quality information disclosure attenuates the adverse financing impact of climate risk, while affiliation with heavily polluting industries strengthens this positive association. These findings remain robust to alternative measures of climate risk and the cost of debt, alternative clustering specifications, high-dimensional interactive fixed effects, and subsample tests with restricted sample windows. To address endogeneity concerns stemming from reverse causality and omitted variable bias, we adopt two complementary identification strategies: using one-period lagged values of the core explanatory variable and conducting instrumental variable estimation via two-stage least squares (2SLS). Estimates from both approaches remain statistically and economically consistent with our baseline results. Further heterogeneity analyses show that the cost-increasing effect of climate risk is more pronounced for firms without ESG fund ownership, non-state-owned enterprises (non-SOEs), and firms located in non-eastern regions of China. Overall, this study provides novel firm-level evidence on the microeconomic consequences of climate risk in emerging economies, develops a dual transmission framework integrating financial fundamentals and non-financial reputation, and offers actionable implications for policymakers, financial institutions, and firms to improve climate risk governance and optimize the financing environment amid the low-carbon transition. Full article

This study examines how the composition of public education expenditure is associated with income inequality through educational quality and skill formation. While the existing literature largely focuses on aggregate education spending, this study argues that the allocation of resources across education levels plays a critical role in shaping educational outcomes and their distributional consequences. Using panel data for OECD countries over the period 2000–2022, we employ a simultaneous equation framework estimated using Three-Stage Least Squares (3SLS), complemented by a lag-structured empirical design and an instrumental-variable approach based on lagged expenditure to mitigate endogeneity concerns. The results reveal substantial heterogeneity across education levels. Tertiary education expenditure is positively associated with educational quality. Although its direct association with income inequality is not statistically significant, it exhibits a significant negative indirect association through the educational-quality channel. In contrast, spending at pre-primary, primary, and secondary levels exhibits weak or negative associations with measured learning outcomes and, in some cases, positive associations with income inequality. These patterns warrant cautious interpretation and may reflect diminishing marginal returns and endogenous policy responses in mature education systems. Further analysis suggests that educational quality serves as an important transmission mechanism linking education spending to income distribution, although no significant relationship is found with short-run economic growth, consistent with the long-term nature of human capital accumulation. Overall, the findings highlight the importance of improving the allocation and effectiveness of education spending rather than simply expanding aggregate budgets. Full article

Port State Control (PSC) inspections play a critical role in enforcing international maritime safety and environmental standards, yet little is known about how compliance behaviour interacts with economic cycles. This study examines the relationship between vessel detentions and freight market conditions using monthly data from the Paris and Tokyo Memoranda of Understanding (MoUs) over the period 2010–2021. A system of simultaneous equations is estimated using the Generalized Method of Moments (GMM) and Three-Stage Least Squares (3SLS) to address the bidirectional relationship between detention activity and freight market conditions, proxied by the Baltic Dry Index (BDI) and, for tanker specifications, the Baltic Dirty Tanker Index (BDTI). The results are consistent with a positive and statistically significant bidirectional relationship: vessel detentions increase during periods of strong freight market conditions, while past detentions are positively associated with freight rates, a pattern consistent with a signalling and sentiment channel. Institutional factors, including flag state quality, classification society affiliation, and ISM-related deficiencies, are also found to significantly influence detention risk, though their direction and magnitude vary across MoUs and vessel segments. These findings are consistent with the presence of opportunistic incentives during economic upswings, challenging the conventional expectation that stronger market conditions promote higher compliance. The study contributes to the literature by linking regulatory compliance with economic cycles and highlighting the importance of adaptive, risk-based enforcement strategies. It is important to note, however, that the aggregate nature of the data does not permit direct identification of firm-level behavioural mechanisms, and the findings should be interpreted as associational evidence consistent with these theoretical mechanisms. Full article

Green Total Factor Productivity (GTFP) serves as a pivotal indicator for balancing high-quality economic growth with increasingly stringent environmental regulations. However, empirical evidence regarding whether and how firm-level GTFP is associated with enhanced Environmental, Social, and Governance (ESG) performance in emerging markets remains limited. This study addresses this gap by examining the GTFP–ESG nexus within the macro-context of China’s “Dual-Carbon” goals (aiming for peak carbon emissions by 2030 and carbon neutrality by 2060). Utilizing an unbalanced panel dataset of Chinese A-share listed companies strictly covering the period from 2011 to 2022 (with 2010 data exclusively used for one-period lagged variables), we construct firm-level GTFP metrics using a non-radial SBM-DDF global Malmquist–Luenberger index—incorporating both desirable economic outputs and undesirable environmental emissions—and link them with Huazheng ESG ratings. To ensure robust empirical identification, we employ two-way fixed-effects models with lagged variables, propensity score matching (PSM), and an instrumental variable two-stage least squares (IV-2SLS) approach utilizing the leave-one-out provincial average GTFP as an instrument. The results indicate a significant positive association between GTFP and overall ESG performance, as well as its three sub-pillars. Specifically, a one-standard-deviation increase in GTFP corresponds to a 0.15-standard-deviation increase in the ESG score, a marginal effect of profound economic significance, providing robust associational insights via the IV estimates. Mechanism analyses reframe traditional mediation as descriptive associational pathways, revealing that digital transformation, green innovation, and information transparency serve as significant channels, theoretically demonstrating how resource efficiency translates into social legitimacy. Heterogeneity tests show that this association is more pronounced for non-state-owned enterprises, firms in eastern China, and those with lower financing constraints. These findings unpack the “black box” between technical efficiency and sustainability, providing empirical support for policymakers to align corporate productivity with international disclosure standards (such as the EU’s CSRD). Full article

The deep integration of the digital and real economies is a critical force reshaping the global economic landscape. At the same time, new high-quality productive forces that are distinguished by their high level of efficiency, quality, and technology mark a new phase in productivity evolution. Understanding the spatial interplay between these two phenomena is crucial for coordinated development. This study empirically investigates their bidirectional relationship and spatial spillover effects. With panel data from 30 provinces in China (2011–2022), we use the Generalized Spatial Three-Stage Least Squares (GS3SLS) approach to estimate a spatial simultaneous equations model. The results reveal a significant bidirectional positive correlation, with the promotional effect of digital–real integration on new quality productive forces being slightly stronger. However, we also identify significantly negative spatial spillover effects between them. These findings underscore the necessity of strengthening their interactive development, fostering interregional cooperation, and optimizing source allocation to alleviate adverse spillovers. This study systematically examines their spatial dynamics and proposes policy recommendations to foster the coordinated advancement of both digital–real integration and New Quality Productive Forces. Full article

Although many countries have reduced the use of agricultural price intervention policies, such measures continue to be applied intermittently by the Thai government. In the current work, which examines the cassava price intervention policy from 1981 to 2024 in Thailand through a supply and demand framework, the authors estimate a dynamic simultaneous equation model (DSEM) via the lag-augmented three-stage least squares (LA-3SLS) approach in order to measure the welfare effects of these interventions. The results indicate that the policy mainly redistributes welfare among market participants rather than improving allocative efficiency. Producers experience temporary income gains during intervention periods, but these gains dissipate once the policy is withdrawn, leaving long-run total surplus largely unchanged. When fiscal costs are incorporated, the intervention generates a net welfare loss, suggesting limited contribution to long-term economic sustainability. The findings suggest that policy approaches emphasizing income stabilization and productivity enhancement are more consistent with long-term welfare and fiscal sustainability than reliance on direct price controls, with direct relevance to SDG 1 (No poverty) and SDG 8 (Decent work and economic growth), highlighting trade-offs between income support, market efficiency, and fiscal sustainability in agricultural policy design. This study contributes by integrating a welfare-based dynamic econometric framework with sustainability assessment, which enables long-term welfare metrics for evaluating the economic sustainability of agricultural price policies. Full article

Digital–intelligent integration (DII) has emerged as a pivotal driver for high-quality urban development, offering a pathway to overcome pressing resource and environmental constraints. By harnessing data as a core production factor and integrating advanced intelligent technologies, DII can substantially elevate urban green economic efficiency (GEE). This study constructs a quasi-natural experiment using the staggered rollout of national big data comprehensive pilot zones (initiated in 2012) and smart-city pilot programs (from 2016 onward). Employing a rigorous staggered difference-in-differences (DID) estimator on panel data from 279 Chinese prefecture-level cities over 2010–2021, we find that DII causally increases GEE by 5.03 percentage points (p < 0.01). This benchmark result remains robust across a comprehensive set of checks, including parallel-trend validation, placebo tests, double/debiased machine learning, two-stage least squares with historical IT-sector instruments, and controls for overlapping policies (e.g., ETS, low-carbon pilots, green finance zones). Mechanism analysis, conducted via a sequential 2SLS control-function approach with lagged mediators and Sobel–Goodman mediation tests, reveals three theoretically grounded channels: (i) enhanced urban ecological resilience (mediates 62%, z = 4.68), (ii) accelerated green technological innovation (55%, z = 4.12, measured by IPC/Y02 patent share), and (iii) heightened entrepreneurial vitality (58%, z = 4.39, new firms per 10,000 residents). Heterogeneity tests show pronounced effects in growing and mature resource-based cities (+1.21% and +11.21%), high-fintech cities (+11.35%), and high-river-density areas (+10.29%) but insignificant impacts in declining resource-exhausted cities (joint F p = 0.08). This study makes four key contributions: (1) it innovatively constructs a continuous DII policy variable by exploiting the synergistic timing of dual pilots, thereby overcoming the limitation of analyzing policies in isolation; (2) it opens the “theoretical black box” by integrating institutional theory and information economics into a unified conceptual framework that explicitly links DII to GEE through reduced transaction costs and alleviated information asymmetry; (3) it enriches the mediation identification strategy in staggered settings using 2SLS control functions and sequential G-estimation, addressing endogeneity in intermediary variables more rigorously than traditional three-step approaches; and (4) it delivers nuanced evidence on the contextual conditions (when and where) under which DII yields the strongest green dividends, providing actionable guidance for China’s “dual-carbon” goals and the global green transition. Full article

A geographically and temporally weighted regression (GTWR) model is an effective tool for dealing with spatial heterogeneity and temporal non-stationarity simultaneously. As an important characteristic of spatiotemporal data, spatiotemporal autocorrelation should be considered when constructing spatiotemporally varying coefficient models. The proposed local autoregressive geographically and temporally weighted regression (GTWRLAR) model can simultaneously handle spatiotemporal autocorrelations among response variables and the spatiotemporal heterogeneity of regression relationships. The two-stage weighted least squares (2SLS) estimation can effectively reduce computational complexity. However, the weighted least squares estimation is essentially a Nadaraya–Watson kernel-smoothing approach for nonparametric regression models, and it suffers from a boundary effect. For spatiotemporally varying coefficient models, the three-dimensional spatiotemporal coefficients (longitude, latitude, and time) inherently exhibit larger boundaries than one-dimensional intervals. Therefore, the boundary effect of the 2SLS estimation of GTWRLAR will be more serious. A local–linear geographically and temporally weighted 2SLS (GTWRLAR-L) estimation is proposed to correct the boundary effect in both the spatial and temporal dimensions of GTWRLAR and simultaneously improve parameter estimation accuracy. The simulation experiment shows that the GTWRLAR-L method reduces the root mean square error (RMSE) of parameter estimates compared to the standard GTWRLAR approach. Empirical analyses of carbon emissions in China’s Yellow River Basin (2017–2021) show that GTWRLAR-L enhances the adjusted $R^2$ from 0.888 to 0.893. Full article

In the era of new urbanization and shared prosperity, addressing the entrenched contradiction between unequal urban–rural public services and consumption disparities is central to achieving sustainable urban–rural development. As the world’s largest developing country, China faces a pronounced urban–rural consumption gap, underscoring the urgency of narrowing this divide through improved urban–rural public services. This study constructs a theoretical framework to analyze how urban–rural public service gaps influence consumption disparities, developing an evaluation index system for public service gaps across three dimensions: basic education, healthcare, and social security. Using panel data from 26 Chinese provinces (2011–2023), we employed fixed effects (FE) estimation, two-stage least squares (2SLS), and two-step system GMM models to examine the impact of public service gaps on consumption disparities and explore heterogeneous effects across inter-period dynamics and economic catching-up levels. Findings show that the coefficients of the three public service gaps (education, healthcare, social security) on the consumption gap are positive and statistically significant. This indicates that further widening of urban–rural public service gaps will exacerbate consumption disparities. The urban–rural consumption gap exhibits a reinforcing effect: gaps in the previous period strengthen current-period disparities, forming a vicious cycle that hinders sustainable development. Heterogeneity analysis across time reveals that the impacts of healthcare and social security gaps on consumption disparities tend to weaken, while the effect of compulsory education gaps increases significantly. From the perspective of economic catching-up heterogeneity, regions with higher catching-up levels exhibit a stronger impact of public service gaps on consumption disparities compared to lower catching-up regions. Full article

Farm household pluriactivity has become increasingly prevalent in China; however, its influence on crop structure remains insufficiently explored. This study examines the impact of farm household pluriactivity on crop structure in China, focusing on factor input mechanisms. Based on survey data from 473 farm households in Sichuan Province, this study employs ordinary least squares (OLS), two-stage least squares (2SLS), and mediation analyses to systematically assess the impact of pluriactivity on crop structure through factor input mechanisms. The analysis reveals three key findings. First, rather than reducing the grain planting area, an increase in part-time farming is associated with a significant rise in the proportion of grain cultivation. Second, factor inputs partially mediate this relationship: while pluriactivity tends to reduce staple crop cultivation through mechanisms such as cultivated land transfer-out, land abandonment, and increased non-agricultural labor input, it simultaneously promotes staple crop expansion via enhanced agricultural technical services. Third, heterogeneity tests indicate that the positive effect of pluriactivity on staple crop cultivation is especially pronounced among households in hilly areas and those that have adopted agricultural insurance. These findings provide valuable policy insights for fostering sustainable agricultural transitions and enhancing food security in developing regions. Full article

Microfinance aims to promote financial inclusion among underprivileged individuals, particularly through progressive microcredit, which enables borrowers to access increasing loan amounts over time. This study examines the conditions under which progressive microcredit positively impacts both small business performance and household well-being, considering borrower characteristics and business activity conditions. Using a dataset of 278 households across 110 administrative sectors in Tunisia from 2012 to 2020, this study employs two-stage least squares (2SLS) and three-stage least squares (3SLS) econometric techniques to estimate simultaneous equation models. The findings reveal that the cumulative amount of progressive microcredit received is mainly determined by project capital, suggesting that businesses with higher capital requirements tend to secure larger loans over successive cycles. Household well-being is significantly influenced by progressive microcredit, household income, net business benefit, rate of development index, and homeownership. Meanwhile, business profitability is driven by project capital and total fixed assets, highlighting the long-term impact of microcredit. The results highlight the critical role of microfinance in enabling small-scale entrepreneurs to expand their businesses while simultaneously improving household financial security. By promoting sustainable income generation, progressive microcredit serves as a key instrument in poverty alleviation and economic stability. This study underscores the necessity for microfinance institutions (MFIs) to tailor their lending strategies, ensuring optimal loan progression that balances business expansion with financial sustainability. Additionally, policymakers should refine microcredit frameworks to enhance accessibility and long-term economic benefits for low-income borrowers. Overall, these insights contribute to the broader discourse on financial inclusion and sustainable development, emphasizing that progressive microcredit not only facilitates entrepreneurship, but also serves as a driver of socioeconomic mobility. Full article

Over the past 70 years since the founding of the People’s Republic of China, urban development has achieved remarkable progress but also encountered severe atmospheric pollution, which has become a significant obstacle to high-quality urban development. Understanding the interaction mechanisms between urban development and atmospheric pollution is thus crucial for promoting sustainable urban construction. This paper explores these mechanisms by analyzing the interplay between urban population, industry, space, social development, and pollution through a theoretical framework. Using a simultaneous equations model and the Three-Stage Least Squares (3SLS) method, it examines these relationships and further investigates threshold effects. The findings reveal a nonlinear relationship with significant thresholds: (1) High levels of PM_2.5, population size, and industrial agglomeration can shift from exacerbating pollution to enabling governance, though excessive thresholds reverse this trend. (2) PM_2.5 mediates the impact of spatial sprawl, environmental regulation, and population dynamics, oscillating between governance and pollution effects. (3) Industrial agglomeration and spatial sprawl show variable impacts on pollution mitigation depending on pollution intensity and urban thresholds. These findings provide critical insights into the intricate dynamics between urban development and atmospheric pollution, emphasizing the importance of adopting differentiated strategies based on specific urban thresholds. Ultimately, this research contributes to the broader goal of harmonizing economic growth, social development, and environmental sustainability in urban areas, serving as a valuable reference for cities worldwide facing similar challenges. Full article

This study investigates the relationship between corporate shared institutional equity (SIE) holders and eco-transparency reporting (ETR). Specifically, it examines three distinct types of SIE: (1) common institutional shareholders with industry peers, (2) the average count of unique institutional owners holding shares in both the focal company and its peers, and (3) the total percentage of SIE within the focal company. The findings indicate that firms with higher levels of SIE are more likely to disclose ETR, signaling a commitment to enhancing public trust and aligning with governmental expectations. Furthermore, the study explores the impact of SIE across different stages of the firm’s life cycle, revealing that the influence of SIE on ETR is more pronounced during the growth and mature stages. The results remain robust even when alternative thresholds for SIE are applied, such as adjusting from a 5% to a 3% threshold. To account for potential misspecification and omitted variables, propensity score matching (PSM), System generalized method of moments (Sys GMM) and two-stage least squares (2SLS) methods were employed. This research contributes to the literature by highlighting the role of shared institutional ownership in promoting environmental transparency, offering novel insights into how institutional investors can drive corporate sustainability practices across different firm life cycles. Full article

This study investigates the impact of Central Bank interventions on the pricing dynamics of select stock markets. The research utilizes the instrumental variables three-stage least square (3SLS) model approach. It analyses the effects of variations in the Federal Reserve’s balance sheet size across three distinct intervention scenarios: the 2008–2013 Great Recession, the 2020–2021 COVID-19 pandemic periods, and an overarching analysis spanning these timelines. Our methodology includes estimations of the Seemingly Unrelated Regression Equations (SURE), and the results are robust under the two-step Generalized Method of Moments (GMM). Our findings indicate that changes in the size of the Fed’s balance sheet correlate significantly with the pricing of principal U.S. equity market indices. This correlation reflects a time-dependent effect emanating from the Fed’s balance sheet expansion, marking a growing divergence between the adaptability of pricing mechanisms in equity and debt markets. Notably, the Federal Reserve’s interventions during the COVID-19 crisis are associated with an increase of approximately 0.0403 basis points per billion in treasury yields. This research makes a significant contribution to the understanding of financial asset pricing, particularly by elucidating the extent to which interventions in government debt securities engender price distortions in certain equity markets. Full article