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This study assesses climate change impact on rice productivity in 28 top rice-producing districts in Pakistan. Driscoll and Kraay estimation is applied on panel data from 1981 to 2019. The cross-sectional dependency test results reveals that climatic factors such as rainfall, humidity, and temperature have correlation issue in different selected regions. The study observes that temperature, rice productivity, and rainfall have inverted U-shape relationship. Rice productivity response is quadratic instead of linear towards average rainfall and temperature during the particular cultivation time, comprising of harvesting, flowering, and planting. The coefficient of temperature during planting time is positive and significant, while the square of temperature during planting time is negative and significant. Temperature during flowering and harvesting time is significant and positive, while the square of temperature during flowering and harvesting time is negative and significant. Rain fall during planting and flowering time are positive and significant; besides that, fertilizer usage stimulates and humidity hinders rice productivity in selected districts of Pakistan. Our empirical results considered the issues of spatial dependency, serial correlation, and heterogeneity.

PurposeChina's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.Design/methodology/approachIn doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.FindingsThe investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.Originality/valueThe authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.

This research study examines the impact of sustainable development goals indexes like education, infrastructure, foreign direct investment (FDI), and green energy transitions on economic growth. We used three decades annual time series data for the above indexes from period 1990 to 2020. We use the principal components analysis and vector error correction model (VECM) econometric techniques to investigate the statistical significancy of above employed indexes to study the effect both in long and short term. More especially, to examine the short-term effect of SDGs we used the NARDL approach to study the real-time effect. Considering the long-term coefficients on the economy of the country, the results primarily reveal that the education, foreign direct investment, and infrastructure is playing a significant positive role in the economic growth of Pakistan. Similarly, in short-term the foreign direct investment, infrastructure, and green energy transition coefficients are significant positive related to sustainable development goals. However, the education found as unsubstantial as cotribitive as other variables. The granger causality test is employed to estimate the causal association between the selected parameters. The estimated outcomes find the unidirectional causality from education and green energy transition towards economic growth, and education is found with in relation to infrastructure. Additionally, bidirectional causal relationship is found between FDI and infrastructure towards economic growth which shows that the increase in foreign investment have the potential to boost the economic growth. Finally, all the examined indexes are considered as important sources towards the economic growth.JEL classifications: F43; Q01; C23; N35

PurposeChina's outward foreign direct investment (OFDI) has risen remarkably over the past two decades. Does such increase affect the sophistication of Chinese exports, is a significant issue that has surprisingly remained unaddressed? The purpose of this study is to investigate the impact of Chinese OFDI on bilateral export sophistication of China and its OFDI receiving partner countries during 2003–2017 by applying Poisson pseudo-maximum likelihood approach based on gravity model.Design/methodology/approachThe analysis has been performed for total sample, region-wise grouped sample (Europe and Central Asia, Middle East and North Africa, Latin America and Caribbean, East Asia and Pacific, South Asia, North America and sub-Saharan Africa) and income-wise grouped sample (high income, upper middle income, lower middle income and lower income group sample).FindingsThe results confirmed the significant and positive effect of Chinese OFDI on bilateral export sophistication in total sample, regions-wise and income groups sample.Originality/valueThe study provides a helpful suggestion regarding policy towards achieving more sophistication in export and thus to achieve comparative advantage in trade.

PurposeInfrastructure deficiency in Southeast Asian countries is ever growing and touched to a level where it harms the local economy as well as the international sector of the country. The gap between demand and supply for infrastructure is constantly on the upswing. The purpose of this study to investigate the effect of infrastructure on exports and foreign direct investment (FDI) inflow in selected Southeast Asian economies.Design/methodology/approachThis study employs the pooled mean group (PMG) technique to velaborate that how the infrastructure affects export and FDI in the short run and long run during 1990–2018. For cointegration, Pedroni and Kao tests are used. Dynamic ordinary least square (DOLS) and the fully modified least squares (FMOLSs) estimators are employed for robustness check.FindingsThe findings support that aggregate and sub-indices of infrastructure significantly promote the export and FDI inflow in the long run. Also infrastructure, export and FDI inflow are cointegrated in the long run. FMOLS and DOLS found the most robust results.Originality/valueInfrastructure development in determining trade and FDI has established a significant deal of attention in the modern era where a plethora of research studies encourage the opinion that better infrastructure attracts FDI and enhances export. However, this study uses a global infrastructure index, which comprises the sub-indices like transport, telecommunication, energy and financial sector, which gives us a clear picture regarding how Southeast Asia can catch up FDI and export benefits through infrastructure.

This study investigates the impact of infrastructure on export in Belt & Road countries during 1990–2017 by applying System GMM approach. The results confirmed the significant and positive impact o...

This study attempts to empirically estimate the interdependence between COVID-19, tourism market, oil prices, and sustainable climate in United States. In doing so, we employ an advanced Morlet’s wavelet approach, namely, Wavelet coherence transform (WCT), Partial and Multiple Wavelet Coherence and found a strong co-movement between variables, which is varied across the time scales, indicating the initial, peak, and after peak effect of COVID-19 on tourism market, oil prices, and carbon emissions using daily data from 6 March 2020 to 6 August 2020. The visuals of WCT exhibit a cyclic (anti-cyclic) relationship between tourism and oil prices, suggesting a strong positive (negative) co-movement in the shorter and longer (medium) period. Tourism and carbon emissions possess a strong positive co-movement across all periods except in the medium run; however, the intensity of this movement is higher in the very short-run compared to medium and longer-run. The results reveal an anti-cyclic association between COVID-19 and tourism, and COVID-19 is leading tourism with strong negative co-movements. Finally, the results describe that carbon emissions and COVID-19 are anti-cyclical and display a positive causality in the shorter run. These results offer valuable guidelines for all stakeholders. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Purpose Over the past two decades, China’s outward foreign direct investment (OFDI) has risen remarkably. Whether such an increase affects the Chinese export diversification (ED) is a significant issue that has surprisingly remained unaddressed. This study aims to explain this issue that how OFDI plays a vital role in symmetric and asymmetric effects on its ED. Design/methodology/approach The authors introduce a robust nonlinear autoregressive distributed lag (NARDL) model. Ironically, the purpose of this study is to analyze the symmetric and asymmetric effect of OFDI on ED. Findings The authors propose that growing OFDI would be more advantageous to China, rather than the policies of contraction. Therefore, the study provides valuable policy insights to consider the long-run asymmetric momentum given to ED by China’s OFDI. Originality/value The results of this study may seem to be an important newsletter for further policy discussion on how China can catch up on the benefits of ED through OFDI.

This research, by using the autoregressive distributive lag method, examines the long- and short-term causal relationship between infrastructure and exports in Pakistan over the period 1990–2017. The empirical results revealed the existence of short- and long-term bi-directional causality concerning infrastructure and export in Pakistan. The results demonstrated that infrastructure strongly improves export in the short and long run. Conversely, export encourages the quality and availability of infrastructure in Pakistan in the long run. Furthermore, this study also uses sub-indices of infrastructure individually as dependent and independent variables. The study result demonstrated that the long- and short-term effects of infrastructure and its sub-indices (transport, electricity, communication, finance) on export is positive and significant. Also, when infrastructure sub-indices are used as dependent variables, the results indicate that the effect of export on sub-indices is positive and significant in the long run; however, in the short run, it is insignificant. The bi-directional linkage between infrastructure and export suggests that improving the quality and increasing the availability of infrastructure would enable Pakistan’s economy to catch up with the advanced economies, specifically in export. Furthermore, control variables of per-capita GDP, exchange rates, human capital, and domestic spending also expand the bi-directional causal relationship between Pakistan’s infrastructure and exports.

Objective: To identify the stage of Hepatocellular Carcinoma (HCC) at the time of presentation. Methods: This cross sectional observational prospective study was carried out at Gastro Department of Combined Military Hospital (CMH) Multan from August 2017 to December 2018. Patients were diagnosed on the basis of alpha fetoprotein, abdominal ultrasound, triphasic contrast enhanced computerized tomography (CECT). They were evaluated for etiology including Hepatitis B, C and non B & C. The patients were inquired about the previous treatment and when they came to know about the HCC. Staging of the tumor was done on the basis BCLC (Barcelona cancer liver clinic) and Melan’s criteria. Performance status (PS) of the patient was checked by Eastern Cooperative Oncology Group (ECOG) criteria. Severity of cirrhosis was assessed by CTP (Child Turcotte Pugh) and Model for end stage liver disease (MELD) score. The data was analyzed in IBM SPSS version 22. Results: Out of 135 patients 78% were males and 22% females. Age Mean SD was 58.81± 9.366. Frequency of hepatitis C, B, combined B, C and non-B non-C was 80%, 11%, 2.8% and 6.2% respectively. 96(73.8%) never got the treatment before for Hepatitis. 81(62.3%) came to know first time on this index admission. Maximum numbers of patients were in BCLC stage B i.e. 82(55.2%) with ECOG grade of one i.e.57 (39.3%), at the time of presentation. Mean MELD and CTP score were 12.24, 7.34 (class B) respectively. Conclusion: HCV was the most common in HCC, never treated before, presented for the first time in advance stage of the disease where very limited treatment options left behind.

China's rapid economic development has caused some environmental damage in recent years. The popularity of the Internet has enriched the ways for investors to obtain information, which would exert an impact on corporate environmental behavior. Focusing on micro-enterprise green innovation from the perspective of informal regulation, this paper investigates the impact of investor attention on corporate green innovation. This study takes Chinese A-share listed companies from 2011 to 2018 as samples, constructs panel fixed-effects models and adopts multiple linear, Logistic and Tobit regressions. This article finds that investor attention, measured by the web search index, can significantly improve corporate green innovation. The conclusion is still valid after a series of robust tests. Besides, mechanism tests reveal that investor attention can promote corporate green innovation by improving the implementation efficiency of punitive environmental regulation, the use efficiency of environmental subsidies, and by increasing the reputation cost of enterprises. In additional tests, this paper further clarifies that investors' attention to negative public opinion can play a better role in environmental governance, and reveals the reason why investors are motivated to improve corporate green innovation. This research puts forward a unique perspective, which extends the understanding of informal environmental regulation and enriches research on green innovation at the micro-enterprise level, promoting the cross research of finance and environmental protection. © 2022 The Author(s)

The successful ability to conduct underwater transportation using multiple autonomous underwater vehicles (AUVs) is important for the commercial sector to undertake precise underwater installations on large modules, whilst for the military sector it has the added advantage of improved secrecy for clandestine operations. The technical requirements are the stability of the payload and internal collision avoidance while keeping track of the desired trajectory considering the underwater effects. Here, a leader-follower formation control strategy was developed and implemented on the transportation system of AUVs. PID controllers were used for the vehicles and a linear feedback controller for maintaining the formation. A Kalman Filter (KF) was designed to estimate the full state of the leader under disturbance, noise and limited sensor readings. The results demonstrate that though the technical requirements are met, the thrust oscillations under disturbance and noise produce the undesired heading angles.

Countries of the Middle East and Central Asia depend heavily on natural resources for their exports, income, and employment. This study is a preliminary investigation that explores the effect of natural resources on domestic investment in a sample of 12 highly resource-dependent countries in the Middle East and Central Asia from 2000 to 2019. The recently advanced cross-sectional dependent auto-regressive distributed lag (CS-ARDL) model and panel quantile regression are employed. The results validate the accelerator theory that an increase of the non-oil GDP growth rate has a robust positive impact on domestic investment, while natural resources crowd-out domestic investment. The long-run estimate of ICT reveals a significant positive impact, while corruption shows a significant negative effect. These findings urge sample resource-dependent countries to focus on developing ICT-based enterprises and control prevailing corruption levels. Moreover, adopting liberal trade policies can also enhance domestic investment opportunities.

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the "pollution damage function" was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the "pollution halo" and "green energy" hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth's temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies. Source: Authors' self-extract.

The massive rise in the world's average temperature has created major economic and environmental issues that must be addressed by strict environmental legislation. Carbon pricing is seen as a sustainable instrument capable of assisting in the reduction of negative environmental externalities associated with global carbon emissions. The race-to-the-bottom (RTB) hypothesis describes a competitive environment in which economies sacrifice environmental quality standards to undercut competitors, thus undermining the ecological sustainability objective. The study contributed to the evaluation of the RTB hypothesis by examining the role of emissions cap trading instruments in conjunction with inbound foreign direct investment, economic growth, renewable energy demand, and trade openness in reducing carbon emissions, using aggregated data from high-income countries from 1975 to 2019. The linear and non-linear ARDL estimator is used for empirical analysis. The results show that emissions cap trading lowers carbon emissions in the long run while increasing in the short run. Inbound FDI confirmed the "pollution halo hypothesis" in the long run while verifying the "pollution haven hypothesis" in the short run. The per capita income and its associated positive shocks substantially decrease carbon emissions in the short and long runs. Renewable energy demand and trade openness increases carbon emissions in the short and long runs, respectively. On the other hand, trade openness decreases carbon emissions in the short run. The results confirmed the RTB hypothesis in the short run. At the same time, it substantiates the "race-to-the top" (RTT) in the long run, by imposing stringent environmental policies to the way forward towards green and clean development. The study concludes that emissions cap trading and investment in cleaner technologies played a decisive role in reducing environmental pollution. As a result, it is desired to make environmental regulations more environmentally friendly by adopting carbon pricing and technology transfer that will lower the average world temperature.

The study examines the impact of climate variables on wheat production in 10 major wheat-producing districts of Pakistan. In doing so, we apply the Driscoll–Kraay approach to estimate the panel data from 1981 to 2019. Our empirical analysis reveals that climate variables, including temperature, rainfall and humidity, follow a common correlation across districts. We find that wheat productivity and temperature, as well as rainfall, follow an inverted U-shaped relation. The response of the wheat productivity is quadratic rather than linear towards average temperature and rainfall during the specific time of cultivation, including planting, flowering and harvesting. Besides, fertilizer use promotes and humidity impedes wheat productivity. Our findings are robust considering heterogeneity, serial correlation and spatial dependency.

Developing countries, including Pakistan, need a considerable effort to withstand economic growth; however, these countries have to cope with greenhouse gases emission and other environmental concerns. Financial advancement gives rise to modern, sometimes even innovative and energy-efficient technologies and, thus, contributes to a decline in energy usage among market entities: organizations and households. The current study explores the nonlinear asymmetric relationship between economic growth (Y) and the selected exogenous variables in Pakistan by incorporating time series data spanning from 1971 to 2016. Economic growth was considered as a target variable, while energy consumption (EC), electric power consumption (EPC), financial development (FD), and energy imports (EM) were considered independent variables. To investigate cointegration among the given variables, a nonlinear ARDL bound testing approach was employed. BDS independence test was used to check the nonlinearity, and a structural break unit root test was used for testing data stationarity. The findings confirm the presence of co-integration in the selected variables. A symmetric unidirectional significant causality exists running from EPC to Y, while a bidirectional symmetric causality was found between FD and Y. In contrast, any negative shocks in EPC, FD, and EM were found to have a positive asymmetric effect on Y. Meanwhile, a neutral effect was found between EC and Y. The outcomes of this study can provide guidelines for future re-searchers and policymakers. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

The sustainable environment has been a desired situation around the world for the last few decades. Environmental contaminations can be a consequence of various economic activities. Different socio-economic factors influence the environment positively or negatively. Many previous studies have resulted in the efficient allocation of inputs as an environment-friendly component. This paper investigates the effects of energy efficiency on ecological footprint in the ASEAN region using balanced panel data from 2001 to 2019. First, this paper technically derives the energy effi-ciency, using the stochastic frontier analysis (SFA) of the translog production type of single output and multiple inputs. Findings of the SFA show that the Philippines and Singapore have the highest energy efficiency (94%) and Laos has the lowest energy efficiency (85%) in the ASEAN region. The estimated average efficiency score of the ASEAN region was around 90%, ranging from 85% to 96%, indicating that there is still 10% room for improvement in energy efficiency. Second, this study employed the panel autoregressive distributed lag (ARDL) model to explore the short run and long run impact of technically derived energy efficiency on ecological footprint in the ASEAN region. Results of the panel ARDL model show that energy efficiency is a reducing factor of ecological footprint in the long run. Moreover, energy efficiency plays a significant role to control the environmental contaminations. In addition, results of this study also explored that urbanization is an increasing factor of ecological footprint, and investment in agriculture is also beneficial for the environment. Moreover, to obtain the directional nature of the associations between the ecological footprint and its independent variables, this paper has employed the paired-panel Granger causality test. The results of the paired wise panel Granger causality test also confirm that the energy efficiency, ur-banization, and investment in agriculture cause ecological footprint. Finally, this study recom-mends that efficient utilization of energy resources as well as investment in agriculture are neces-sary for sustainable environment. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Funding: Project no. 132805 has been implemented with support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the K_19 funding scheme and supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (BO/00095/18 and BO/8/20).

This study investigates the bidirectional causal relationship between institutional quality and aggregated and disaggregated (primary, secondary and services sector) FDI inflow in India by employing new simulated autoregressive distributed lag (SARDL) dynamic techniques, which is an extended version of NARDL and ARDL. The empirical results supports that institutional quality strongly attract aggregated and disaggregated FDI and reversely FDI enhance the quality of institutions. The nexus between FDI inflow and institutional quality is good news for India to enhance the institutional quality and catch-up on advanced economies. The empirical findings detect cointegration and bidirectional causal-relationship between aggregated FDI and institutional quality.

Whether better infrastructure influences Chinese export sophistication (ES) and diversification (ED) is an important question, which surprisingly remains unaddressed. The current study contributes to the ES and ED literature by capturing the symmetric and asymmetric effect of infrastructure on ES and ED. We employ a robust dynamically simulated autoregressive distributed lag (DYS-ARDL) dynamic method, which is an extended version of NARDL and ARDL. The major aim of this new DYS-ARDL dynamic approach was to abolish the issue in orthodox ARDL model approach while examining the long-run and short-run. The new dynamic DYS-ARDL model is accomplished in estimating, stimulating, and robotically plotting predictions of counterfactual alterations in one explanatory variable and its impact on the dependent variable while holding the remaining regressors constant. Furthermore, this new method of DYS-ARDL model can estimate, stimulate, and plot to forecast graphs of positive and negative variations in the variables robotically as well as their short and long-run associations. Interestingly, the results of this study witness the presence of long-run relationship between infrastructure and ES and ED in China. The present study shows that better infrastructure will be more beneficial for Chinese ED and ES. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

This article investigates the bidirectional causal relationship between outbound foreign direct investment (ODI) and export sophistication in China by using autoregressive distributed lag (ARDL) te...

Transportation using multiple autonomous vehicles with detection avoidance capability is useful for military applications. It is important for such systems to avoid collisions with underwater obstacles in an effective way, while keeping track of the target location. In this paper, sensor-based and path-planning methods of external collision avoidance were investigated for an underwater transportation system. In particular, sensor-based wall-following and hard-switching collision avoidance strategies and an offline RRT* path-planning method was implemented on the simulation model of the transportation system of four Hovering Autonomous Underwater Vehicles (HAUVs). Time-domain motion simulations were performed with each method and their ability to avoid obstacles was compared. The hard-switching method resulted in high yaw moments which caused the vehicle to travel towards the goal by a longer distance. Conversely, in the wall-following method, the yaw moment was kept to zero. Moreover, the wall-following method was found to be better than the hard-switching method in terms of time and power efficiency. The comparison between the offline RRT* path-planning and wall-following methods showed that the fuel efficiency of the former is higher whilst its time efficiency is poorer. The major drawback of RRT* is that it can only avoid the previously known obstacles. In future, offline RRT* and wall following can be blended for a better solution. The outcome of this paper provides guidance for the selection of the most appropriate method for collision avoidance for an underwater transportation system.

Financial Inclusion is a key factor in achieving the sustainable development goals of the United Nations. The research in the area of financial inclusion is becoming more critical for scholars and policymakers. In previous studies, effects of formal institutions on financial inclusion have been explored. However, influence of informal institutions (culture) on financial inclusion remained untapped. To fill this gap, we investigate how national culture affects the financial inclusion of 81 Belt and Road economies using 17 years of data from 2004 to 2020. The empirical findings of the two-stage least square (2SLS) show that Hofstede’s cultural dimensions are significantly associated with financial inclusion with different signs and levels of magnitude. We find that financial inclusion is lower in countries where uncertainty avoidance and power distance is high and that the opposite is true for individualism and masculinity. The overall results are reliable to a series of robustness checks and provide a useful basis for policymakers, regulatory agencies, and other stakeholders in achieving the sustainable development goal of financial inclusion in Belt and Road countries. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. Huazhong University of Science and Technology, HUST We are grateful for the profound ethical and technical support given by Muhammad Asif Khan, University of Kotli, Azad Jammu, and Kashmir, Muhammad Atif Khan, University of Kotli, Azad Jammu, and Kashmir, and Mirza Muhammad Naseer School of Economics, Huazhong University of Science and Technology and Atta Ullah School of Management, Huazhong University of Science and Technology.

The risk of a coal burst rises with the excavation depth and other mining-related activities. These devastating coal burst activities are a major concern during deep coal mining. During such activities, the loading rate is a major cause of damage. Different indexes, including the elastic strain modulus index (Wet), bursting energy index (Ke), dynamic failure time index (DT), and compressive strength index (Rc), are used for coal bursting intensity; however, the loading rate and damage factors are not included in these indexes. In this study, a new coal bursting liability index called the elastic modulus damage index (EMDI) was developed using rock damage variables and the elastic strain modulus index, and is based on energy evolution characteristics under different loading rates. The results of this new index were compared with the existing indexes, and their range was proposed to evaluate coal bursting liability. The EDMI shows a positive polynomial second order degree relationship with Wet and Ke, having a determination factor of 0.99, while DT shows a negative polynomial second order degree relationship with a determination factor of 0.94. The EDMI and Rc show a positive power relationship having a determination factor of 0.99. The relationships with other indexes revealed that the EDMI can be effectively used in evaluating the coal bursting liabilities in different stress environments. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. Funding: The authors would like to thank the YUTP under grant numbers 015LC0-150 and 015LC0-326 for providing financial assistance.