Towards sustainable management of agricultural resources: A framework to assess the relationship between water, soil, economic factors, and grain production.

As the requirements for environmental protection and high-efficiency economies increase, grain production (GP) across the globe faces more stringent ecological constraints and economic pressure. Understanding the relationships between natural resources and economic and agricultural factors in grain-producing regions is paramount for ensuring global food security. This paper proposes a methodological framework to explore the relationships between water and soil resources (WSRs), economic input factors (EIFs), and GP. We employed the northeast region of China as a case study to advance our understanding of the factors driving the development of grain-producing capacity. We first constructed and calculated the region's water and soil comprehensive index (WSCI) to describe water-soil properties. We then used hotspot analysis to explore the spatial agglomeration characteristics of WSRs, EIFs, and GP. Finally, we used threshold regression analysis to understand the effects of EIFs and GP with the WSCI as the threshold variable. With the improvement of the WSCI, the positive impact of fertilizer and irrigation on GP shows a U-shaped curve in elasticity coefficients. The positive effect of agricultural machinery on GP decreases significantly, and the impact of labor input on GP is insignificant. These results provide new insights into the relationship between WSRs, EIFs, and GP and a reference for improving GP efficiency globally. This work thus contributes to advancing our capabilities to enable food security while considering aspects of sustainable agriculture in important grain-producing regions across the globe.

Understanding the nexus between environmental, social, and governance (ESG) and financial performance: evidence from Chinese-listed companies.

Before discussing how to balance and decide on environmental, social, and corporate governance (ESG) and traditional revenue enhancement projects, it is crucial to clarify the relationship between corporate financial performance (CFP) and ESG. However, little attention has been paid to the nexus of ESG and CFP. This paper attempts firstly to investigate the bidirectional causality of ESG and CFP, followed by the micro-foundations, and finally, the moderating effect of intrinsic factors. A GMM-PVAR method was used to examine the research hypotheses, which can effectively deal with endogenous problems that have been ignored by traditional literature. The findings of this research demonstrate that CFP promoted ESG growth, but ESG did not boost CFP. This asymmetric causality was because CFP had a supportive effect on the environment and society pillars, while the social pillar cannot promote CFP, and the environment pillar negatively affects CFP. The relationship between ESG and CFP was moderated by total quality management, environmental sensitivity, and the pay gap. Furtherly, a panel threshold model was constructed to access the threshold effects of ESG on CFP, showing an inverted U-shape. Based on these findings, the theoretical implications, managerial prescriptions, and limitations are also discussed.

Impact of digital infrastructure inputs on industrial carbon emission intensity: evidence from China's manufacturing panel data.

Digital infrastructure inputs (DIIs) are vital in strengthening the framework for developing the digital economy and encouraging economic growth. Nonetheless, the risks of environmental contamination are pervasively caused by the rapid expansion and utilization of digital infrastructure. Assessing the carbon emission intensity (CEI) and level of the DIIs of 18 manufacturing in China as the research subject, this study discusses the heterogeneous behavior of various input sources and industries. Furthermore, a two-way fixed effects model, threshold effects model, mediating effects model and moderated mediation effects model have been adopted to examine the nexus between DIIs and CEI of manufacturing. The results show that (1) DIIs raise China's manufacturing CEI and exert a non-linear threshold effect. (2) From the perspective of national attributes, the foreign DIIs will put more pressure on reducing the CEI in China. From the perspective of industry characteristics, DIIs are the most unfavorable for low-carbon development in capital-intensive industries. (3) Due to the mediating effect of total factor productivity (TFP), the positive influence of DIIs on CEI has dramatically diminished. (4) Participation in the global value chain (PAR) and foreign direct investment (FDI) exert moderating effects in the process of the direct effect and mediating effects. In light of the aforementioned conclusions, specific recommendations for developing digital infrastructure and reducing carbon emissions are proposed.

Threshold effects of green technology application on sustainable grain production: Evidence from China.

Sustainable production is considered as an important approach to solve the dilemma of food insecurity. Green technologies have made contributions to improving food production and reducing environmental pollution. Studying the effects of green technologies on sustainable food production has great significance. The paper started with the influence mechanism of green technology application on the green total factor productivity of grain (GTFPG). With the GTFPG, green technology efficiency change of grain (GECG) and green technical progress change of grain (GTCG) measured, threshold models were constructed to explore the nonlinear impacts of various green technologies on GTFPG and the influence paths. Results indicated that the differences of GTFPG among provinces in China were decreased mainly due to the changes of GTCG, while the regional differences of GECG remained small. The impacts of green technologies had threshold effects that depended on the ecological effects of green technologies in different application stages, and were significantly different in the major and non-major grain producing areas. Meanwhile, significant differences existed in the influence paths of green technologies. In the major grain producing areas, green technologies were more likely to improve GTFPG through the GTCG path; while in the non-major grain producing areas, the GECG path and the GTCG path were both important to improve GTFPG. The differences of green technologies' threshold effects and influence paths in the major and non-major grain producing areas were caused by regional technology preference, resource endowment and technology compatibility. This study emphasizes that the development of green technologies should fully consider the resource endowment and economic development of different regions, as well as the applicability and adoption rate of green technologies.

The impact of the digital economy development on haze pollution: evidence from the perspective of factor marketization.

How to eliminate haze pollution is a major concern for all countries around the world. Based on panel data from 286 cities in China from 2011 to 2019, the article examines the impact of the digital economy development (DIGS) on haze pollution and the impact of transmission mechanisms in different dimensions using various methods such as the fixed effects model, mediated effects model, and threshold effects model. The study found that firstly, DIGS helps reduce pollution, and further research found that DIGS contributes to the reduction of haze pollution in the western region by improving the market allocation of factors. Secondly, the study concludes that the DIGS shows heterogeneity by dividing the full sample according to region, level of factor marketization, and city size. Finally, the threshold test model finds that the relationship between the DIGS and haze pollution is non-linear depending on the economic development level. The research in this paper provides new research literature on the development of the digital economy and the reduction of haze pollution, contributing to the development of a green economy in China.

Does Clean Energy Use Have Threshold Effects on Economic Development? A Case of Theoretical and Empirical Analyses from China.

Increasingly serious energy security and environmental problems have become the main constraints to China's economic development. Therefore, it is critical to explore the threshold effect of clean energy use on China's economic growth. Based on the panel data of 30 Chinese provinces from 2000 to 2019 and using energy intensity (EI) as the threshold variable, this study adopts a panel threshold model to explore the threshold effect of clean energy development on the economy. Empirical results indicate that clean energy has a significant threshold effect on economic development, with the threshold value of EI being 0.7655. When EI is less than 0.7655, clean energy development has a more positive effect on economic growth. When the EI exceeds 0.7655, the impact is significantly positive but with a smaller coefficient. EI weakens the role of clean energy development in promoting economic growth. After 2015, the EI of most provinces in the sample was below the threshold value, which indicates that in recent years, with the economic cost of developing clean energy decreasing, the role of clean energy development in promoting the economy has become more significant. Therefore, we propose policy implications to better promote the effect of clean energy development in promoting economic growth.

A counterfactual economic analysis of Covid-19 using a threshold augmented multi-country model.

This paper develops a threshold-augmented dynamic multi-country model (TGVAR) to quantify the macroeconomic effects of the Covid-19 pandemic. We show that there exist threshold effects in the relationship between output growth and excess global volatility at individual country levels in a significant majority of advanced economies and several emerging markets. We then estimate a more general multi-country model augmented with these threshold effects as well as long term interest rates, oil prices, exchange rates and equity returns to perform counterfactual analyses. We distinguish common global factors from trade-related spillovers, and identify the Covid-19 shock using GDP growth projection revisions of the IMF in 2020Q1. We account for sample uncertainty by bootstrapping the multi-country model estimated over four decades of quarterly observations. Our results show that, without policy support, the Covid-19 pandemic would cause a significant and long-lasting fall in world output, with outcomes that are quite heterogenous across countries and regions. While the impact on China and other emerging Asian economies are estimated to be less severe, the United Kingdom, and several other advanced economies may experience deeper and longer-lasting effects. Non-Asian emerging markets stand out for their vulnerability. We show that no country is immune to the economic fallout of the pandemic because of global interconnections as evidenced by the case of Sweden. We also find that long-term interest rates could temporarily fall below their pre-Covid-19 lows in core advanced economies, but this does not seem to be the case in emerging markets.

How Does Income Inequality Influence Environmental Regulation in the Context of Corruption? A Panel Threshold Analysis Based on Chinese Provincial Data.

The question of how the income inequality of residents affects the level of environmental regulation in the context of official corruption was the core research issue of this study. We analyzed this problem using the panel threshold regression model from 26 provinces in China from 1995 to 2017. We found that when there is no official corruption, the widening of the residents' income inequality promotes stricter environmental regulations; when the corruption problem is serious, the expansion of the residents' income inequality leads to the decline in environmental standards; that is, the impact of residents' income inequality on environmental regulation has a threshold effect due to corruption. In addition, the threshold effect due to corruption of all residents' income inequality on environmental regulation is mainly generated by the urban residents' income inequality and the urban-rural income inequality. This paper contributes to the literature that concentrates on the relationship between income inequality and environmental regulation, and shows that corruption is a key factor that can deeply influence that relationship. The research conclusion shows that increasing anti-corruption efforts can not only maintain national political stability, social fairness, and justice, but also be a powerful measure for environmental pollution governance.

Does technology advancement reduce aggregate carbon dioxide emissions? Evidence from 66 countries with panel threshold regression model.

The influence of technology advancement on carbon dioxide (CO2) emissions is complex and controversial, yet existing literature ignores the level of economic development in regard to its influential effect. With the panel threshold regression model, this research investigates the marginal and non-linear impacts of technology advancement on CO2 emissions along with the changes of economic development and presents the heterogeneity between different countries. The results are as follows: First, technology advancement and CO2 emissions have a non-linear inverted U-shaped relationship, which is significantly affected by different levels of economic development. When economic development exceeds a certain threshold, the impact turns from positive to negative. Second, the impact varies remarkably among different countries. We provide evidence for inverted U-shaped and N-shaped correlations in the Organization for Economic Co-operation and Development (OECD) countries and high-income countries (non-OECD), respectively. Although technology advancement always promotes CO2 emissions in middle- and low-income countries, its marginal effect is decreasing. This study not only indicates the dynamic impacts of technology advancement on CO2 emissions in different countries, but also contributes to policymakers' understanding of the "common but differentiated responsibilities" involved in mitigating CO2 emissions.

Impact of technological innovation and industrial-structure upgrades on ecological efficiency in China in terms of spatial spillover and the threshold effect.

In the past 40 years, China's rapid industrialization has resulted in remarkable social progress and regional economic prosperity but also has caused problems, such as excessive resource consumption and environmental pollution. Ecological efficiency is an important indicator of whether economic efficiency and environmental efficiency are balanced. Exploring ecological efficiency is vital for achieving sustainable development, as technological innovation, industrial structure upgrading, and ecological efficiency are probably related. However, there has been little research on the relationships among them. In this study, we used the super-efficiency slacks-based model (SBM) involving undesirable output to calculate the ecological efficiency of 30 provinces in China from 2008 to 2017. We found that China's ecological efficiency has risen, fallen, then fluctuated, and that there were significant spatial differences. Then, we used 3 spatial econometric models for comparative analysis, which revealed that the independent effects of technological innovation on ecological efficiency was significant and negative; however, technological innovation demonstrated a strong positive effect in tandem with industrial structure upgrading, and industrial structure always had a positive effect on ecological efficiency. On this basis, we added the cross-item of technological innovation, and industrial-structure upgrades had a significant and positive impact on ecological efficiency, which was significantly greater than the independent effect of technological innovation and industrial-structure upgrades. To explore the mechanism of industrial-structure upgrading and technological innovation on regional ecological efficiency, we set the first 2 as threshold variables. We found that there is in fact a threshold effect of technological innovation and industrial-structure upgrading on ecological efficiency due to the mismatch of periods. These results provide a theoretical rationale for China to formulate strategies to improve ecological efficiency. Integr Environ Assess Manag 2021;17:852-865. © 2020 SETAC.

Threshold effects of economic growth on water stress in the Eurozone.

This paper empirically examines the environmental Kuznets curve (EKC) hypothesis using a country's water stress as an indicator of the pressure on renewable water resources. The sample consists of 9 European countries by covering the period 1995-2013. The paper adopts a panel threshold regression model which can predict the threshold level endogenously to analyze whether income per person has an impact on water stress. The empirical findings strongly demonstrate the existence of a threshold beyond which environmental pressures of GDP (real) per capita growth on renewable water resources tend to increase. The growth below the threshold levels has no statistically significant effect on water stress, while the growth rate above the threshold increases stress on water resources. The available empirical findings obtained, albeit limited, tend not to support the EKC hypothesis, which postulates an inverted-U-shaped relationship.

Foreign direct investment, environmental regulation, and environmental pollution: an empirical study based on threshold effects for different Chinese regions.

On the basis of previous studies on the relations among foreign direct investment (FDI), environmental regulation, and environmental pollution, this work uses provincial panel data from 2000 to 2014 to study the effects of FDI and environmental regulation on environmental pollution by applying the panel-corrected standard error (PCSE) method. This paper then utilizes environmental regulation as the threshold variable to estimate the threshold effects of environmental regulation on FDI's influence on environmental pollution in a threshold regression model for the eastern, central, and western regions of China. The results show that stricter environmental regulation can substantially reduce the pollution in each region. FDI can decrease environmental pollution in the eastern and central regions, but it can increase pollution in the western region. There are double-threshold effects of environmental regulation on the effects of FDI on environmental pollution in each region. When the environmental regulation level is between the first threshold and the second threshold, FDI can decrease environmental pollution much more in the eastern and central regions and increase environmental pollution much less in the western region.

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological review of health technology assessments.

BACKGROUND: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. METHODS: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. RESULTS: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. CONCLUSIONS: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests.