GMM Model Research Articles

Disentangling the Intelligentization–Carbon Emission Nexus within China’s Logistics Sector: An Econometric Approach

Amidst the global pursuit of environmental sustainability, the concurrent trends of decarbonization and intelligentization have emerged as critical strategic priorities. However, the interplay between these phenomena, particularly within the logistics sector, remains an underexplored area. This study investigates the complex dynamics between logistics intelligentization and decarbonization across 29 provinces in China from 2006 to 2019, providing a fresh perspective on a globally relevant issue. By employing Differential GMM, Systematic GMM, and instrumental variable-based GMM models, we evaluate the impact of logistics intelligence on carbon emissions while effectively addressing endogeneity issues inherent in the empirical analysis. Our findings reveal that the advancement of intelligent logistics correlates positively with increased carbon emissions, highlighting a significant incompatibility between decarbonization objectives and intelligentization efforts within the logistics sector. Additionally, we identify mediating pathways—specifically scale, structure, and technology effects—and moderating mechanisms that influence this relationship. These insights underscore the need for policymakers to establish environmental standards for intelligent technology adoption and to promote initiatives that reconcile intelligentization with sustainability goals. Ultimately, our study provides critical guidance for promoting sustainable and smart industrial growth in the logistics sector.

How do global value chains respond to climate change? A case study of Chinese manufacturing firms

This study investigates climate risk and its effects on global value chain (GVC) participation, with a focus on the impact of drought on the export value-added ratio (DVAR) of Chinese manufacturing firms. Using fixed effects (FE) and system GMM models, the main findings are: Drought significantly reduces manufacturing firms' DVAR, with the lagged dependent variable showing a strong persistence effect and an even greater impact in the second lag period. This impact varies based on the firm's location, the complexity of its value chain, and its ability to adapt to and mitigate climate change effects. Strategies such as improving operational efficiency, investing in sustainable technologies, and enhancing competitiveness in developed markets may help mitigate or reverse the adverse effects of climate change on these firms. Additionally, significant industry and regional differences are observed, with the Northeast, East, and South China regions being most severely affected by drought. Global innovation value chains and regional processing value chains are significantly negatively impacted, while labor-intensive value chains are affected only in the current period. These findings provide new insights into the economic impacts of climate change and offer a basis for policymakers to develop strategies that help firms adapt to and mitigate climate risks.

Velocimetry of coarse particles in pipeline flow based on GMM model and flow direction constraints

Coarse particle vertical pipeline hydraulic transport has been widely used in deep sea mining, petrochemical industry and shaft slag removal. The precise measurement of the velocity of coarse particles within a solid–liquid two-phase flow in a vertical pipe constitutes a pivotal and challenging aspect when investigating particle motion characteristics. We introduce a method for measuring coarse particle velocity that combines a GMM motion detection model with flow direction constraint matching. In this approach, a high-speed camera system captures the flow image of solid–liquid two-phase flow within a pipeline, and the GMM model analyzes the image to detect the motion particles. Subsequently, a rapid particle matching algorithm, incorporating flow direction constraints, is formulated to establish the particle matching relationships. Simulation and real experiments substantiate the efficacy of this method. Moreover, the method achieves high-precision matching with an accuracy of up to 99%. For videos captured at 30 frames per second (fps), the method enables real-time speed measurement, with an overall measurement error of less than 5%. In summary, this is an effective method for measuring coarse particle velocity field which is important to the study of the motion characteristics of solid–liquid two-phase flow.

Are natural resources a curse, a blessing, or a double-edged sword? Implications for environmental sustainability

Natural resources have a significant impact on economic and political landscapes of developing countries which determines environmental sustainability. This study explores the convoluted connection between governance and natural resources, examining how resource abundance might influence governance quality. The main components of this dynamic that the theoretical framework considers are the Rentier effects, the repression effects, and the obstruction of modernization. This study creates a governance index applying principal component analysis (PCA) on several governance characteristics, such as political stability, rule of law, government efficacy, regulation and control of corruption, to measure governance comprehensively. Natural resource exports, rents, and the differentiation between renewable and non-renewable natural resources are the three proxies used to quantify natural resources, providing a more nuanced view. To calculate the effect of renewable and non-renewable natural resources on governance in developing nations, the econometric methodology uses a dynamic panel model and system GMM. This analysis reveals that the ability of renewable resources to promote inclusive development has a favourable impact on governance. On the other hand, non-renewable resources show a negative correlation, mainly because of their vulnerability to swings in the world price and their propensity to consolidate power and promote corruption. The significance of differentiating between natural resource types is highlighted in this study, along with the possible advantages of renewable resources for governance and the disadvantages of an over-reliance on non-renewable resources. Policymakers, researchers, and practitioners interested in the development and governance difficulties encountered by resource-rich developing nations can benefit greatly from this research's larger and more complex understanding of the link between natural resources and governance.

How does ESG performance determine the level of specific financing in capital structure? New insights from China

Sustainable finance has gained attention as investors emphasize environmental, social, and governance (ESG) factors in investment decisions. Understanding ESG's impact on corporate financing is crucial for stakeholders. However, evidence on ESG and capital structure, especially in Chinese enterprises, is limited. This study investigates the link between ESG performance and capital structure in Chinese firms, focusing on debt and equity financing. Using panel data from 2010 to 2022 and the system GMM model, the study controls for firm-specific factors. Results show environmental and governance scores negatively relate to debt financing and positively to equity financing. Social scores show no significant impact on debt but a positive one on equity financing. All ESG indicators positively relate to the debt-to-equity ratio, highlighting sustainability's role in capital structure decisions. These findings guide policymakers in incentivizing sustainable practices and help corporate leaders align financing strategies with sustainability goals, supporting long-term growth and stakeholder value.

China’s foreign direct investment: driving green growth or seeking pollution havens? Based on the perspective of green total factor productivity

China has significantly increased its foreign direct investment (FDI). Although these investments help to boost global development, their impacts on the environment are still controversial and deserve careful investigation. This paper uses the super-efficiency SBM model to measure the green total factor productivity (GTFP) of 123 host countries of China’s FDI. On this basis, we adopt the two-step system GMM and dynamic panel threshold effect model to analyze the impact of China’s FDI on the GTFP of host countries. The research results show that: 1) The impact of China’s FDI on the GTFP of host countries is mainly through green technology efficiency. Its impact is inhibitory, followed by a promotional one, with the latter being significantly larger than the former. 2) There is no evidence of the “pollution haven effect” associated with China’s FDI. In fact, for countries with lower environmental regulations, China’s FDI promotes the growth of GTFP more effectively. 3) The innovation level of host countries moderates the relationship between China’s FDI and GTFP growth. For host countries with stronger innovation level, their GTFP growth can be enhanced to a greater extent by China’s FDI.

Nonlinear and threshold effect of corporate social responsibility on bank performance

ABSTRACT This study examines the non-linear and threshold effects of corporate social responsibility (CSR) on bank performance. For empirical analysis, this study has used data from 30 Bangladeshi and 26 Indian banks from 2015 to 2021. The non-linear dynamic GMM and panel VAR model results suggest a U-shaped relationship. The threshold regression suggests that there is tipping point for earning to earnings assets, Tobin’s-Q, and return on equity for Bangladeshi and Indian banks. Additionally, this study shows the negative (positive) relationship exists between CSR expenditure and bank performance before (after) the tipping point. Findings reveal that lower CSR does not have any marginal benefit but rather increase cost, and optimal CSR increase the bank's performance. Therefore, policymakers and bank management should invest considering the threshold level to get a positive outcome from CSR.

Does ESG disclosure enhance firm performance during COVID-19? Evidence from Nifty 500 firms

Market turmoil caused by COVID-19 has weakened firms’ financial performance, highlighting the prominence of sustainable business practices by incorporating Environmental, Social, and Governance performance and their disclosure. Though past studies investigated COVID-19’s impact on firm performance, there is consensus on the role of firms’ Environmental, Social, and Governance disclosures between firm performance and the pandemic. With this view, the study aims to examine the impact of COVID-19 on firms’ financial performance with the moderating role of Environmental, Social, and Governance performance disclosure. To do so, the study retrieved data of Nifty 500 index companies from the Bloomberg database for a sample period ranging from 2016 to 2022. To this end, the study performed the fixed-effect regression and GMM model. The findings reveal a significant negative impact of the pandemic on Return on Assets (β =-4.812), Return on Equity (β =–.675), and Earnings Per Share (β = –2.875), highlighting the unfavorable effect of the pandemic on firm performance. Further results showed that firms’ Environmental, Social, and Governance performance disclosure positively moderates the connection between COVID-19 and Return on Assets (β = 3.231), Return on Equity (β = 0.032), and Earnings Per Share (β = 1.523), respectively. This indicates that companies actively involved in Environmental, Social, and Governance disclosure are less likely to suffer during the pandemic in terms of financial performance due to their ESG disclosures.

The Role of Comparative Advantage in Enhancing Trade in Value-Added Using a Dynamic GMM Model

The Role of Comparative Advantage in Enhancing Trade in Value-Added Using a Dynamic GMM Model

Determinants of Bank’s Financial Stability in Pakistan

The purpose of this study is to investigate the role of both internal and external factors in achieving better stability in context of Pakistani banking industry. The internal determinants that this research study have used are bank size, funding risk, liquidity risk, credit risk and return on assets while external variables utilized includes money supply and unemployment rate. The study contains 10 years secondary data over the period 2013-2022 of 24 commercial banks of Pakistan. This study conducted correlation analysis and GMM model estimation for analysis. The findings show that liquidity risk, bank profitability, funding risk and bank size have positive and significant impact on bank stability. On the other hand, credit risk effects negatively bank stability. The result showed that money supply positively affects the stability of banks in Pakistan. On the contrary, unemployment is negatively affecting banks stability. The findings of this study have important implications for policymakers, regulators, banks, investors, and other stakeholders in the Pakistani banking sector. By enhancing the understanding of the factors influencing bank stability, the research contributes to identifying the importance of development of evidence-based policies, risk management strategies, and regulatory reforms aimed at development of a stable and resilient banking system in Pakistan.

Technological innovation and profit

This study examines the effect of technological innovation on economic performance. Solow’s growth accounting measures the contribution of productivity to economic growth, but the active role of technological change in attaining economic growth is ignored. Kaldor emphasizes capital accumulation in technological process, but does not cover the dynamic process of technological innovation. Schumpeter explains the dynamic process by focusing on capital accumulation and efficiency. Following Schumpeter’s view of innovation, we empirically analyze the dynamics of technological innovation measured in terms of capital turnover and return on sales. Capital turnover represents process and organizational innovation, and return on sales reflects product innovation. For the empirical analysis, a large panel data set of 445 Korean firms during the period 2000–2015 is used. The empirical study performs panel regression analysis by using fixed effects model, FGLS model, dynamic GMM model, and a split sample method. The empirical results support the positive relationship between technological innovation and profitability.

The decline of bank ownership and firm’s capital structure: evidence from Japanese business groups

ABSTRACT This paper examine how firms adjust their capital structure when their relationship with banks weaken. To this end, we use the data from Japan, a country that has experienced a sharp decline in the traditional bank-oriented business group system after its banking crisis in the late 1990s. We document the decline of financial leverage of Japanese firms after the crisis. The dynamic GMM model reveals that the decline is pronounced as the bank’s influence weakens firm’s financial leverage decreases. Finally, we show that as the bank relationship weakens, the speed of adjustment for target leverage fastens. These results indicate that the shift of bank-oriented to market-oriented economic system change the firm’s financial decision making.

Input costs’ pass-through to output prices: a cross-country empirical analysis

ABSTRACT This article decodes the pass-through behaviour from input prices to output prices, which is a key component in assessing second-order effects of cost-push pressures. Using panel GMM model, this paper has tried to empirically test the degree of pass-through of Purchasing Managers Index (PMI) input prices to output prices in a cross-country framework for 28 countries for the period 2011–2023. Empirical results support modest pass through with the sensitivity of output prices to input prices being lower for advanced nations and inflation targeting countries and higher for manufacturing sector with signs of non-linearity.

How does green credit affect industrial green transformation? Mechanism discussion and empirical test

Sustainable development has become a strategic consensus in response to the global environmental problems. Green credit is a major policy innovation that promotes the transformation of economic development mode and industrial green transformation (IGT). Using provincial panel data from 2005 to 2020, we investigate the effect of green credit on IGT using a systematic GMM model, a dynamic threshold model, as well as the possible nonlinear relationship. Benchmark regression results show that green credit can encourage industrial green transformation. In addition, there is a single green credit threshold with a value of 0.2612. The trend is “negative to positive”. According to the moderating effect results, environmental regulation moderates in a negative manner. As environmental regulations become more stringent, the contribution of green credit to IGT will diminish. The intermediary mechanism test demonstrates that green technology innovation and marketization level play a partial intermediary role. Heterogeneity testing confirms that the function of green credit in promoting industrial green transformation is more significant in regions with a higher level of green finance development and a lower degree of government intervention. Therefore, the government should encourage financial institutions to provide green credit products and services to meet the financing needs of different green projects, thereby facilitating the industrial green transformation.

Does international trade improve carbon productivity? Evidence from countries along the Belt and Road.

The Belt and Road Initiative proposed by China has significantly increased trade in countries along the Belt and Road (B&R). Since most of these countries are developing and emerging economies, the pressure to reduce carbon emissions poses a leading challenge for them. Carbon productivity has become a key indicator for assessing the degree of low-carbon development, as it can link economic development with CO2 emission reduction. However, few studies have investigated how international trade affects carbon productivity. Based on panel data from 43 countries along the B&R during 2001-2019, this paper uses a system GMM model to explore the impact of international trade on carbon productivity. Then, we divide the 43 countries in the sample into two groups according to their income levels to compare the different effects of international trade on carbon productivity. The results show that, first, the carbon productivity of the examined B&R countries has an overall increasing trend, and there is a significant heterogeneity of carbon productivity among countries with different income levels. Second, the effects of international trade, export, and import on carbon productivity are all significantly positive, and export's effect is higher than import. In the high-income group, carbon productivity is more likely to be improved by trade than in the middle (low)-income group. Third, economic development level, urbanization, and energy productivity are positively associated with carbon productivity, while CO2 per capita and government size inhibit carbon productivity improvement. Insight into the impact of international trade on carbon productivity provides theoretical support for B&R countries to better leverage foreign trade activities to achieve a green economy.

Improved methods for identifying the operational determinants of a bank’s capital ratio

ABSTRACT Published research using econometric models to identify the determinants of bank capital ratios has produced inconsistent results. This is partly due to the failure of model formulations to distinguish between operational and managerial effects. This paper explains how the use of bank leverage can separate these effects, how to prevent financial ratios from undermining model interpretability, and how to identify and avoid ratio-related biases. The application of these improvements is tested on a panel of East Asian retail bank data from 2004 to 2014, covering China, Hong Kong, Indonesia, India, Japan, Singapore, Malaysia, the Philippines, and Thailand. Conclusions are drawn from quasi-experimental designs comparing two-way GMM models before and after implementation of the improvements. The results show that the improved models identify the operational determinants of capital ratios and avoid simultaneity and omitted variable bias and ratio-induced opacity in the results. The use of complementary data segments helps to interpret the results and identify paradigmatic cases for a better understanding of the relationship between regulatory capital and risk.

Income‐linked pathways towards sustainable development goals: Analyzing the interplay of green energy, financial inclusion, and militarization in shaping aggregated economic sustainability

AbstractThis research examines the dynamic impact of green energy (GE), financial inclusion (FI), and militarization (MS) on attaining global economic sustainability (EGS, SDG‐8) in 121 nations from 2003 to 2022. Further, explore and compare 44 high‐income, 33 upper‐middle‐income, and 44 low‐ and lower‐middle‐income countries for a better understanding of empirical and policy contributions. This study utilized second‐generation econometric methods. Consequently, it employed a two‐step system GMM model, which was validated using the D‐K regression approach. The findings revealed that green energy and financial inclusion benefit EGS across all income levels having a significant and positive impact on economic sustainability. In contrast, militarization has a negative relationship with EGS, which proves it is detrimental to EGS in the overall sample and high‐income countries. However, it positively influences economic sustainability in low‐ and lower‐middle‐income countries. Moreover, other factors, such as institutional quality and armed conflicts, have mixed effects on ESG at different income levels. This study also provides persuasive policy measures and implications for achieving global economic sustainability.

Is the Dutch disease well and alive? A cross-country assessment of mining spillovers on employment in the 2002–2014 period

Following the Dutch disease model of Corden and Neary (1982), the expansion of a booming extractive sector crowds out employment in key sectors, i.e., manufacturing. To this day, these potential negative labor spillovers remain a cause of concern for policymakers. Empirical literature has explored this question by focusing on regional dynamics of employment, but country-wide effects remain understudied. This paper explores the mining sector's employment spillovers at the national level over the 2002–2014 period. Using data from WIOD, we employ Moretti's (2010) specification, as extended in Fleming and Measham (2014), and adopt a GMM model to address potential endogeneity issues. Following the decomposition in Foster-McGregor (2019), we differentiate mining employment expansion based on a) changes in domestic demand and b) changes due to exports. Along with regional studies, our results indicate that there is no evidence of negative spillovers on manufacturing jobs, regardless of the source of mining jobs expansion (domestic or exports). Such results hold even in countries with relatively low levels of manufacturing output. We do find some evidence of negative effects in agriculture, and positive effects on construction and services; this, however, seems to hold only in countries with relatively low manufacturing output. Findings also suggest that positive elasticities at the national level, when observed, are quite moderate: e.g., a 10% increment in mining employment leads to a 1.1%–1.4% increment in construction employment.

Unveiling the Catalytic Role of Digital Trade in China’s Carbon Emission Reduction under the Dual Carbon Policy

Digital trade (DT), a key component of today’s digital economy, is pivotal in attaining “carbon neutrality and carbon peaking”, essential for low-carbon and high-quality growth. This study delves into the intermediary role of carbon emissions (CE) reduction in DT, analyzing both production and consumption angles, and examines the moderating influences of CE in DT through industrial agglomeration and low-carbon pilot policy. The research employs spatial panel and system GMM models for an empirical investigation. On the production side, the scale and technological effects on CE outweigh the structural impact on emissions. In terms of consumption, the mediating role of urban residents’ consumption upgrading is to enhance the effect of DT on reducing CE by promoting consumption upgrading, whereas the mediating role of rural residents’ consumption upgrading is to promote consumption upgrading but weaken the effect of DT on reducing CE. Regarding regulatory influences, the factor of industrial agglomeration tends to diminish the impact of DT on reducing CE; thus, industrial agglomeration does not amplify the reduction effect of DT on CE. Low-carbon pilot policy(pol)s can enhance the CE reduction effect of DT, showing stronger CE reduction effects in provinces participating in low-carbon pilot programs.

Unraveling the Nexus Between Financial Openness and Environmental Quality: Green Finance as the Catalyst in CEE Countries

The use of fossil fuels, which is still seen as the cheapest energy source today, has increased carbon emissions and contributed to the formation of greenhouse gases, and this gas has reached levels that threaten world health. While studies on this problem often question the relationship between production volume, energy use, and carbon emissions, few studies question the effects of the financial assets, which are the providers of investments made for production purposes, on environmental degradation. This study used the fixed effect model and system GMM technique to analyse the moderating effect of green finance in connection to financial openness and environmental quality from 2015 to 2020 in the CEE countries. Findings show, among other things that (1) CO2 in CEE countries is still growing; (2) financial openness is a positive and significant indicator of CO2 emission; and (3) that green finance usage reduces the positive impact of financial openness on CO2 emissions. The study suggests that financial openness, renewable energy (RE) investment, and green technology innovation (GTI)– consistently drive CO2 emissions in CEE countries. The study suggests that policies promoting green finance, particularly RE investment and GTI, can help mitigate environmental degradation and reduce CO2 emissions.