This study investigates the short- and long-run impact of infrastructure on export and trade deficit in selected South Asian countries during 1990–2017 by using Pooled Mean Group (PMG) estimator and cointegration techniques like Pedroni and Kao test. The empirical results of PMG approach confirmed the existence of significant long-run impact of aggregate and sub-indices of infrastructure (i.e., transport, telecommunication, energy and financial sector) on export and trade deficit. The findings suggested that infrastructure positively promotes exports while negatively affecting trade deficit. The relationship between infrastructure and export is worthy bulletin for South Asian economies to encourage the quantity of exports and catch-up on established economies. The control variables of exchange rate, human capital, per capita GDP and institutional quality enhance exports and retard trade deficit significantly in the long run. Furthermore, the Pedroni and Kao test indicates strong evidence of cointegration in selected variables. Fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) support robust and consistent results to the main model of this study. Furthermore, the study recommended that in long run aggregate and sub-indices of infrastructure promote exports and decrease trade deficit in selected South Asian economies.

BRICS countries’ contribution to the global economy has received wider attention. The critical factor behind their role is financial market reform that stimulates these economies’ productivity growth. This research contributes to constructing a comprehensive index of financial infrastructure and measuring its relationship with BRICS economies’ total factor productivity (TFP) within the purview of outward FDI, trade openness, human capital, innovation and institutional quality during 1990–2019 using the CS-ARDL technique. The findings divulge a significant and positive role of financial infrastructure in TFP both in the long and short runs, while outward FDI, trade openness, human capital, and innovation walk on the same footing in BRICS countries. Moreover, the CS-ARDL-based investigated findings remain the same across the two-way fixed effect with Driscoll and Kraay Standard Error technique. Therefore, BRICS countries’ more promotion of financial dynamics and other ancillary economic, demographic, and technological factors is critical to stepping towards the spectacular growth trajectory.

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 efficiency, 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, urbanization, and investment in agriculture cause ecological footprint. Finally, this study recommends that efficient utilization of energy resources as well as investment in agriculture are necessary for sustainable environment.

Purpose: China'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/approach: The 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).Findings: The results confirmed the significant and positive effect of Chinese OFDI on bilateral export sophistication in total sample, regions-wise and income groups sample.Originality/value: The study provides a helpful suggestion regarding policy towards achieving more sophistication in export and thus to achieve comparative advantage in trade.

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 (W_et), bursting energy index (K_e), dynamic failure time index (D_T), and compressive strength index (R_c), 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 W_et and K_e, having a determination factor of 0.99, while D_T shows a negative polynomial second order degree relationship with a determination factor of 0.94. The EDMI and R_c 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.