Diverse impact of greenhouse gasses (GHGs) over the landscape of environment is generally believed in literature. As CO2 emission acutely leads to GHGs is a major contributor for global warming, it creates a serious pressure on natural resources and ecological settings. Similarly, low-carbon (CO2) economy, plenty of energy resources, and sustainable growth are a big ask for worldwide economies in this era of mechanization. This paper analyzes the Environmental Kuznets Curve (EKC) hypothesis, for Belt and Road Initiative (BRI) economies, to contend the role of mega projects in BRI as an attribute for ecological detriments. The on-hand study engages fresh data information ranging from 1981 to 2016 holding with heterogeneity and cross-sectional dependence as a special deliberation. The calculated outcomes expose that, mean group estimator provides strong evidence and favor the existence of EKC approximately in every region. The long-run influence is measured by pooled mean group estimators, which shows significant outcomes in every region; additionally, the EKC hypothesis affirmed in the long run especially for developed economies. Mega projects, i.e., BRI requisite immense energy sources to accomplishing the enclosed projects efficiently and effectively. The positive association between carbon emission and energy consumption troubled the governments to make policies for restraining the magnitude of carbon emission and controls energy usage for enduring environment to its original position. Next, the valuations depicted the dense recommendations for state administrations in capacity of rigorous level supremacy, trash managing campaigns, renewable energy reliance, and advance for desirable judgments to sterilize the atmosphere.

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Innovation and globalization fosters a tendency towards multiparty collaboration and strategic contacts among nations. A similar path was followed by the Chinese administration in 2013, with its “Belt and Road Initiative” (BRI). The most important objective of the present fact-finding study was to demonstrate the links between economic growth, energy consumption, urbanization, gross fixed capital formation, trade openness, financial development and carbon emissions (ecological degradation) from a panel of 47 BRI economies, over a time span of 1980 to 2016. Dynamic panel estimations (dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS)) were engaged to examine the long-run links between the subjected variables. Synchronized outcomes for the full panel show that energy consumption, gross fixed capital formation, economic growth, financial development, and urbanization unfavorably led to environmental degradation (CO2 emissions). However, trade openness is negatively correlated with emissions. Furthermore, pairwise panel Granger causative estimations justified bi-directional links from all regressors towards CO2 emissions, except for trade openness, which had unidirectional ties with environmental quality. In cross-country, long-run assessments, different results were found, with CO2 emissions being greatly increased by economic growth in all countries and energy consumption in 30 countries; other predictors testified to some mixed interactions with CO2 emissions in the country-level examination. The reported investigation provides some noteworthy guiding principles and policy inferences aimed at governments and ecological supervisory administrations, suggesting assertive moves towards truncated used of carbon fossil fuels and dependency on renewable energy, establishing waste and water treatment plants, familiarizing themselves with the concept of a green economy, and making the general public aware of eco-friendly investments in BRI economies.

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This study attempts to investigate the short-run and long-run impact of formal credit (CR) and climate change (CC, via CO2 emissions) on agricultural production (AP) in Pakistan. In addition, other imperative control variables included in this study comprise technology factors (tractors (TRs) and tube wells (TWs), energy consumption (EC), and labor force (LF). This study used annual data covering the period 1983–2016. The autoregressive distributed lag (ARDL) approach is applied to explore the cointegration between the underlying variables and used the granger causality test under the vector error correction model (VECM) context to determine the direction of causality among the variables. The findings of the ARDL bounds-testing approach suggest that there is a long-term relationship among formal credit, climate change (CO2 emissions), technology factors (tractors and tube wells), energy consumption, labor force, and agricultural production. The empirical results reveal that formal credit, technology use (tractors), and labor force have a positive and significant impact on agricultural production in both the short-run and long-run. CO2 emissions have a positive impact on agricultural production but are not significant in either case. Finally, a unidirectional relationship is established from formal credit to agricultural production; labor force to agricultural production; and electricity consumption and technology factors (tractors and tube wells) to CO2 emissions. The recent study claims that formal institutions should guarantee the redeployment of their services/amenities to those who call for them acutely, with the purpose of boosting their approach to monetary credit facilities and empower farmers to further the resilience that will capitalize on post-fruitage enrichments. Finally, considering that climatic change is a widespread fact with regional community trajectories, perhaps the global community may provide reassurance for loaning to smallholder agriculturalists through central and commercial banks by protecting the moneys that banks lend to the agriculturalists towards supporting climatic change espousal strategies.

The study aims to explain the economic impact of Internet implication in tourism sector by taking sample of mega project listed countries (which provide big pitch to boost tourism business). Our work find the volatility cause of tourism revenue at country i, by examining the inbound tourist expenditures as a factor of technological infrastructure. We deploy data ranging from 1990 to 2017 and uses error correction model as representative of Autoregressive-Distributed Lag (ARDL) model after addressing diagnostic tests (for data reliability concern). We found long- and short-run association between tourism expenditure and information and communication technology (ICT) proxies in case of developed economies, while only short-run association in underdeveloped countries. The startling scenario about underdeveloped economies are also confirmed by one-way causation in our analysis. After sensitive analysis at each slot, the study concludes that tourism revenue is streaming low across those boundaries where tourists are suffered by paying more due to technological inaccessibility and its underdeveloped infrastructure. The suffered economies are recommended to upgrade their ICT sector to facilitate inbound tourist.