Institute of Industrial Economics

Large capital investment, extended R&D cycle, and high uncertainties characterize green innovations. Consequently, financial risks easily emerge during firms’ green innovation process. This study utilizes data from Chinese A-share listed companies from 2011 to 2019 to examine the effects of digital finance on firms’ green innovation. The findings reveal that digital finance exerts significant and positive influence on green innovation. Digital finance institutions alleviate information asymmetry in the green innovation market through digital technologies such as big data analysis of firm behavior to directly promote firms’ innovation behavior. The internal mechanism analysis reveals that digital finance indirectly promotes green innovation by improving the quality of firms’ environmental information disclosure and reducing financial constraints. The heterogeneity analysis indicates that the promotional effect of digital finance on green innovation is more prominent in larger and state-owned enterprises.

Abstract This study investigates the influence of fintech on developments in China’s financial sector across 290 cities and 31 provinces between 2011 and 2018. Using a two-stage least squares instrumental variable regression approach and correcting for cross-sectional dependency, simultaneity, and endogeneity of regressors, the results establish a positive link between fintech and financial development. Our findings show that fintech supports financial sector development by enhancing access (loans), depth (deposits), and savings within China’s financial institutions. We also show that the emergence of fintech in the area of financial regulation (regulatory technology: regtech) can significantly improve financial development outcomes. Therefore, it is imperative for regulators to pursue policies that balance growth in the fintech sector while mitigating the associated risks. In addition, we use the difference-in-differences approach to show that policy measures such as interest rates liberalization also positively impacted financial development during the analysis period. In our conclusion, we suggest a policy framework for balanced fintech sector growth in developing countries.

The search for a green and low-carbon economy has been a guide to current energy and environmental research. Using current panel cointegration approaches, our study examines the interaction between trade and an environmental pollution proxy of carbon dioxide (CO2) emissions by integrating economic growth and energy usage as major potential determining factors in this relationship for 49 high-emission countries in Belt and Road regions over the period of 1991–2014. For a robust analysis, we further grouped these countries into income panels (high, middle, low) and various regions (East Asia, Southeast Asia, Central Asia, South Asia, the Middle East/Africa, and Europe). The results of the panel cointegration tests revealed that the four variables were stationary in the long run. Similarly, our panel results indicated that trade openness had both positive and negative impacts on environmental pollution, but the effect varied in these different groups of nations. The results of the vector error correction model (VECM) causality also showed a long-run causal effect between trade, economic growth, energy consumption, and environmental pollution in the Belt and Road, Europe, high-income, middle-income, and low-income panels. The environmental Kuznets curve (EKC) results further indicated the existence of an inverted U-form relationship between trade and carbon emissions. Finally, certain policy implications are discussed.

Abstract Many empirical environmental justice (EJ) studies lack a systematic framework in which to undertake research and interpret results. This paper characterizes the conventional EJ study and examines how results can be influenced by the choice of the spatial scale and scope of analysis. After thoroughly reviewing a sample of prominent EJ studies, a conventional EJ study was performed for (Superfund) National Priorities List sites at multiple scales and scopes. It was found that evidence of environmental injustice could be sensitive to scale and scope chosen, which partly explains the observed inconsistency in the empirical literature. Implications for interpreting existing EJ research and conducting future EJ research are discussed.

We employ Data Envelopment Analysis to compute the technical efficiency of Italian and English higher education institutions. Our results show that, in relation to the country-specific frontier, institutions in both countries are typically very efficient. However, institutions in England are more efficient than those in Italy when we compare jointly their performances. We also look at the evolution of technical efficiency scores over a four-year period, and find that, in line with an error-correction hypothesis, Italian universities are improving their technical efficiency while English universities are obtaining stable scores. Policy implications are addressed.

Recent years have witnessed the popularity of online peer-to-peer lending, which allows individuals to borrow from and lend to each other on an Internet-based platform. Using data from a large P2P platform in China, this article explores the factors that determine the default risk based on the demographic characteristics of borrowers. Moreover, we propose a credit risk evaluation model, which can quantify the default risk of each P2P loan. Empirical results reveal that gender, age, marital status, educational level, working years, company size, monthly payment, loan amount, debt to income ratio and delinquency history play a significant role in loan defaults. Finally, we analyse the relationship between default risk and these contributory variables, and the possible causes are also discussed in this study.

This manuscript applies the GML model with unexpected output to measure agricultural green total factor productivity (GTFP) in 30 provinces in China from 2011 to 2019. We explore the effect and mechanism of digital inclusive finance (DIF) on agricultural green total factor productivity. Our empirical results show that during the sample period, China’s agricultural green total factor productivity has shown an increasing trend. Digital inclusive finance mainly promotes agricultural GTFP by improving green technology level. The coverage rate, the application rate and the digitalization rate of digital inclusive finance all generate positive effects on agricultural green total factor productivity, among which the coverage rate contributes the most. Besides, the positive effect of digital inclusive finance in the eastern coastal areas is more significant than in other areas. The analysis of the mechanism shows that digital inclusive finance can indirectly help improve agricultural green total factor productivity through motivating agricultural technology innovation and industrial structure optimization. The research results of this manuscript are extremely meaningful for better implement DIF-related policies, and promote the green development of agriculture.

Purpose As China embarks upon a new era of high-quality development, it is increasingly important and imperative for China’s economic development to live up to its real nature, which is to satisfy people’s growing needs for a better life. The paper aims to discuss this issue. Design/methodology/approach The paper attempts to discuss the implication of HQD and its related theoretical issues from the basic theory of economics, and literature review. It is necessary to return to Marx’s “dual character of commodity” to check the theoretical foundation of this issue, based on the duality methodology, namely, the duality of the value of use and the value of exchange. Findings Moving from HSG phase to HQD phase constitutes a major challenge and an arduous task that is extremely difficult both theoretically and practically. A series of new problems crop out as to the theoretical understanding and practical resolution. Fundamentally speaking, this new dynamic mechanism intrinsically requires a perfect integration of the instrumental rationality of market economy and the value-based rationality of economic development. Originality/value This new momentum requires a perfect match between the instrumental rationality of market economy and the value-based rationality of economic development.

The U.S. Environmental Protection Agency undertook a case study in the Detroit metropolitan area to test the viability of a new multipollutant risk-based (MP/RB) approach to air quality management, informed by spatially resolved air quality, population, and baseline health data. The case study demonstrated that the MP/RB approach approximately doubled the human health benefits achieved by the traditional approach while increasing cost less than 20%--moving closer to the objective of Executive Order 12866 to maximize net benefits. Less well understood is how the distribution of health benefits from the MP/RB and traditional strategies affect the existing inequalities in air-pollution-related risks in Detroit. In this article, we identify Detroit populations that may be both most susceptible to air pollution health impacts (based on local-scale baseline health data) and most vulnerable to air pollution (based on fine-scale PM(2.5) air quality modeling and socioeconomic characteristics). Using these susceptible/vulnerable subpopulation profiles, we assess the relative impacts of each control strategy on risk inequality, applying the Atkinson Index (AI) to quantify health risk inequality at baseline and with either risk management approach. We find that the MP/RB approach delivers greater air quality improvements among these subpopulations while also generating substantial benefits among lower-risk populations. Applying the AI, we confirm that the MP/RB strategy yields less PM(2.5) mortality and asthma hospitalization risk inequality than the traditional approach. We demonstrate the value of this approach to policymakers as they develop cost-effective air quality management plans that maximize risk reduction while minimizing health inequality.

Abstract The U.S. Southwest is projected to experience increasing aridity due to climate change. We quantify the resulting impacts on ambient dust levels and public health using methods consistent with the Environmental Protection Agency's Climate Change Impacts and Risk Analysis framework. We first demonstrate that U.S. Southwest fine (PM 2.5 ) and coarse (PM 2.5‐10 ) dust levels are strongly sensitive to variability in the 2‐month Standardized Precipitation‐Evapotranspiration Index across southwestern North America. We then estimate potential changes in dust levels through 2099 by applying the observed sensitivities to downscaled meteorological output projected by six climate models following an intermediate (Representative Concentration Pathway 4.5, RCP4.5) and a high (RCP8.5) greenhouse gas concentration scenario. By 2080–2099 under RCP8.5 relative to 1986–2005 in the U.S. Southwest: (1) Fine dust levels could increase by 57%, and fine dust‐attributable all‐cause mortality and hospitalizations could increase by 230% and 360%, respectively; (2) coarse dust levels could increase by 38%, and coarse dust‐attributable cardiovascular mortality and asthma emergency department visits could increase by 210% and 88%, respectively; (3) climate‐driven changes in dust concentrations can account for 34–47% of these health impacts, with the rest due to increases in population and baseline incidence rates; and (4) economic damages of the health impacts could total $47 billion per year additional to the 1986–2005 value of $13 billion per year. Compared to national‐scale climate impacts projected for other U.S. sectors using the Climate Change Impacts and Risk Analysis framework, dust‐related mortality ranks fourth behind extreme temperature‐related mortality, labor productivity decline, and coastal property loss.

This paper examines the relationships between natural resource dependence, public education investment, and human capital accumulation. It addresses why the "blessing" of abundant natural resources often turns into a "curse" in many countries and regions, focusing on the crowding-out effect of natural resources on human capital. According to our empirical analysis of provincial panel data from China, natural resource dependence is significantly and negatively correlated with human capital accumulation. The crowding-out effect of natural resources on human capital exists only in the central and western regions of China. Our introduction of an interaction term for natural resource dependence and public education investment underscores the possibility of investing in public education to reduce the crowding-out effect of natural resource dependence on human capital. The government should utilize the income of the natural resource sector to increase investment in education to enhance local human capital.

The rapid development of trade along the Belt and Road Initiative (BRI) directly affect economic growth and influence carbon emission. This study used fifty-two BRI countries out of the sixty-five countries that signed onto the BRI in 2013 for the empirical study. The panel data extracted is from the period 1993 to 2018. The study utilized the Common Correlated Effects Mean Group (CCEMG) and the Augmented Mean Group (AMG) estimation techniques for the empirical analysis. The findings revealed a positive link between imports and carbon emissions. Contrarily, exports revealed an inverse relationship with carbon emission, while foreign direct investment inflow revealed a positive but insignificant relationship with consumption-based carbon emission. Therefore, it is recommended that to control the environment and maintain ecological balance, there is the need to establish environmental protection clauses in many international treaties and domestic legislation while promoting international trade.

To achieve the goals of sustainable economic and environmental protection, more and more firms intend to implement green supply chain (GSC) initiatives in their products. The adoption of GSC initiatives in turn influences the firms’ operations performance. Thus, the firms have to evaluate their performances carefully when implementing GSC initiatives. The performance evaluation of GSC initiatives is a laborious task, which needs to take into account many factors including the inventory level and assurance of supply purchasing-wise and the technical capability and the innovation capability manufacturing-wise, etc. This paper develops a new probabilistic linguistic VIKOR approach to support such an assessment. To do so, a new comparison method of probabilistic linguistic term sets (PLTSs) is first presented to effectively determine the probabilistic linguistic positive ideal solution and the probabilistic linguistic negative ideal solution. Next, a new defuzzification function of PLTSs is proposed to take into account the main-criteria weights and the sub-criteria weights which are represented by PLTSs. Furthermore, several probabilistic linguistic measures are introduced, such as the probabilistic linguistic group utility measure, the probabilistic linguistic individual regret measure and the probabilistic linguistic compromise measure. Finally, the compromise solution is obtained based on these three measures. The desirable advantages of the developed method are summarized as (1) it allows the evaluators to employ PLTSs to express the imprecise performances of the GSC initiatives with respect to various criteria, which greatly improves the elicitation of linguistic information; (2) it presents a probabilistic linguistic compromise solution, which is a maximum probabilistic linguistic group utility for the majority and a minimum probabilistic linguistic individual regret for the opponent. This proposed technique provides a simple and efficient decision making approach to assist the firms to make an appropriate decision in GSC management.

We present an estimated dynamic stochastic general equilibrium model of stock market bubbles and business cycles using Bayesian methods. Bubbles emerge through a positive feedback loop mechanism supported by self-fulfilling beliefs. We identify a sentiment shock that drives the movements of bubbles and is transmitted to the real economy through endogenous credit constraints. This shock explains most of the stock market fluctuations and sizable fractions of the variations in real quantities. It generates the comovement between stock prices and the real economy, and is the dominant force behind the internet bubbles and the Great Recession.

The purpose of this study was to examine the nexus amid economic growth, energy consumption and carbon emissions in G20 countries for the period 1992 to 2014. In order to obtain valid and reliable outcomes, more robust econometric techniques were employed. From the results, the studied panel was heterogeneous and cross-sectionally dependent. Also, the series of observed variables were first-differenced stationary and co-integrated. The key findings from the CCEMG and the AMG regression estimators adopted showed that economic growth and energy consumption promoted the emission of carbon in the countries. In addition, urbanization and foreign direct investments as control variables escalated the rate of the countries' CO2 emissions. From the discoveries of the Dumitrescu and Hurlin panel causality test, a feedback causality between economic growth and CO2 emissions; energy consumption and CO2 emissions; and between urbanization and CO2 emissions were correspondingly unveiled. Howerver, a one-way caual link was evidenced from foreign direct investments to CO2 emissions. This exploration is vital because it will propel the countries to formulate policies that could help them to minimize their dependence on environmentally unfriendly energy sources, while promoting the usage of clean energies like solar, wind, biogas, biomass and hydropower among others. The study is also pertinent because it will aid the countries to plan, organize and implement environmental policies in compliance to their macroeconomic objectives. When this is accomplished, energy conservation policies implemented to minimize the emanation of CO2 will improve the countries' economic growth.

Additional energy demand is needed to accomplish the mega-projects of the Belt & Road Initiative (BRI). As energy consumption is one of the prime determinants of environmental degradation, the present study investigates the impact of energy inequalities on environmental degradation along with financial development. The entropy approach is applied to quantify the three energy consumption inequalities; average, between, and total energy consumption inequality respectively. The energy consumption inequality of BRI economies follows an uprising temporal trend. The estimates reveal that East Asia and South Asia have the highest and lowest energy consumption inequality among the BRI regions. Within regions, it is found that Central Asia has the lowest, and East Asia has the highest energy inequality among the BRI regions, respectively. Based on bootstrapping, the generalized least square (GLS) is applied to quantify the impact of energy consumption inequalities on environmental degradation along financial development. The energy inequalities have a statistically positive impact on environmental degradation in BRI regions, East Asia, Central Asia, the Middle East and North African region (MENA), and Southeast Asia respectively. In contrast, South Asian economies are sustaining environmental quality despite the energy consumption inequalities. Financial development also has a significantly major impact on environmental degradation in BRI, and its regions except for Central Asia, and MENA.

The aim of this study was to identify the influences of psychological capital (PC) on students' entrepreneurial intention (EI) in China's universities. The mediating effects of Entrepreneurial Capitals were also examined. Based on the analysis of the traditional capital and PC, the paper proposes that traditional capital is the direct factor to drive the behavior of entrepreneurship, while psychological factors do not directly affect EI, but improve EI by influencing traditional capital. A total of 1914 responses from universities in southeast China were analyzed using the structural equation modeling (SEM) approach to test study hypotheses. Results show that PC has a significant indirect impact on students' EI only through traditional financial, human, and social capital (SC). These results support the mediating role of the traditional entrepreneurial capitals in explaining the relationship between PC and EI. Additionally, the impact of SC on EI is higher than that of financial and human capital (HC). Finally, research limitations and implications are discussed and future research directions are suggested.

Purpose This study aims to investigate the effects of social capital (defined as networks) on the performance of Chinese private enterprises. Design/methodology/approach The paper employ an econometric model to test relationships between social capital and firm performance, using a sample of private enterprises in a survey in China in 2000. Findings The analysis suggests two findings. First, memberships in various organizations do not appear to be significant in affecting the performance of Chinese private enterprises. Second, short‐time investment in, and the flow of, social capital are significant determinants of enterprise performance. Research limitations/implications The study examines only the effects of the short‐time investment in social capital. Further research is suggested to examine the effects of long‐term investments in social capital, the relationship between short‐time investment and long‐time investment in social capital, and the network as a whole, including informal networks. Originality/value The paper uses the survey data in China to test Krishna's hypothesis which suggests that short‐term investments can play a positive role in the financial performance of firms.

Regulations designed to increase homeland security often require balancing large costs against highly uncertain benefits. An important component of these benefits is the reduced risk of fatalities from terrorist attacks. While the risk to an individual appears small, the benefits may be large when aggregated over the population. U.S. regulatory agencies have well-established approaches for valuing mortality risks, but address risks that differ in significant respects from those associated with terrorism. The best available estimates of the value of small risk reductions, expressed as the value per statistical life (VSL), average about $6.5 million. However, terrorism-related risks may be perceived as more dreaded and ambiguous, and less controllable and voluntary, than the workplace risks underlying many VSL estimates. These factors may increase the VSL appropriate for terrorism risks, possibly doubling the value.

China's digital economy has made amazing achievements, which brings deep impacts on enterprise innovation. Based on unbalance panel dataset covering more than two thousand manufacturing listed companies in A-stock market of China during the 2011 to 2018 period, this paper employs two-way fixed effects (TWFE) model to examine the effects of attention to digital economy on enterprise innovation. The primary explanatory variable in this research is attention degree that enterprises pay to the digital economy measured by Python technology and text analysis. Additionally, the intermediate effect model is adopted to check the underlying mechanisms of cost control in enterprises, which is also impacted by the digital economy. Several novel findings emerge. First, the number of patent applications increase as enterprises pay more attention to the digital economy. Digital economy has positive impacts on different innovation processes, not only promotes invention, but also promotes appearance design. Second, digital technology and business model as two aspects of digital economy have different effects on innovation. The attention to digital technology has positive impacts on invention patents and design patents, while business model only has a positive impact on design patents. Third, enterprises that pay attention to the digital economy are more likely to increase their R&D expenditure and decrease their sales and finance expenses, which encourages the innovation output. This paper explains these findings in the context of China and makes some specific suggestions for enterprises to promote digital transformation and innovation.