The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975–2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high–technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country’s economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.

Political challenges, unfairness, and dishonesty are the governing issues that need substantial reforms to improve the high regulatory quality standards. The study's objective is to examine the impact of corruption, violence, and the rule of law on Pakistan's regulatory control. The study used four forecasting techniques, i.e., Root Mean Square Error (RSER), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Theil inequality coefficient, on the available data series from 1996–2019. The study first obtained the forecast factors of the stated variables by using the Vector Autoregressive (VAR) technique and then used these variables in the least-squares regression technique to obtain the forecast parameter estimates. The simulation results show that corruption, violence, and the rule of law would likely negatively affect the country's regulatory control. The ex-ante analysis shows that the corruption level increases sharply reaches its highest point, and becomes constant. The rule of law initially decreases and then begins to rise steeply. Regulatory control initially decreases and is likely to increase at a decreasing rate. Finally, political stability is likely to decrease over the time horizon. Innovation accounting matrix estimates show that corruption would likely change the country's regulatory control, followed by the rule of law and violence in the next ten years. The study is the first to explore the dynamics of governance indicators in an inter-temporal setting. The study concludes that the country should devise broad-based governance reform policies to eliminate the high incidence of corruption, violence, and injustice and move forward towards implementing regulatory control for sustained growth.

Purpose: The study aims to analyze the role of coronavirus testing capacity to possibly reduce the case fatality ratio (CFR) in a large cross-section of countries. The study controlled health-care expenditures, logistics performance index (LPI), carbon damages, and corporate social responsibility (CSR) to understand the nature of causation between the CFR and stated factors. Design/methodology/approach: The study used a cross-sectional regression apparatus for coefficient estimates and variance decomposition analysis (VDA) for forecasting relationships between the variables over time. Findings: The results confirmed the W-shaped relationship between CFR and case-to-test ratio (CTR) in the presence of a LPI that exacerbates the CFR cases across countries. The VDA estimates suggest that carbon damages, logistics activities, and CSR are likely to influence CFR over time.

The service industry provides distributive services, producer services, personal services, and social services. These services largely breakdowns due to restrictions on border movements, confined travel and transportation services, a decline in international tourists’ visitation, nationwide lockdowns, and maintaining social distancing in the population. Although these measures are highly needed to contain coronavirus, it decreases economic and financial activities in a country, which requires smart solutions to globally subsidize the services sector. The study used different COVID-19 measures, and its resulting impact on the services industry by using world aggregated data from 1975 through 2020. The study benefited from the Keynesian theory of aggregate demand that remains provided a solution to minimize economic shocks through stringent or liberalizing economic policies. The COVID-19 pandemic is more severe than the financial shocks of 2018 that affected almost all sectors of the globalized world, particularly the services sector, which has been severally affected by COVID-19; it is a high time to revisit economic policies to control pandemic recession. The study used quantiles regression and innovation accounting matrix to obtain ex-ante and ex-post analysis. The quantile regression estimates show that causes of death by communicable diseases, including COVID-19, mainly decline the share of services value added to the global GDP at different quantiles distribution. In contrast, word-of-mouth helps to prevent it from the transmission channel of coronavirus plague through information sharing among the general masses. The control of food prices and managing physical distancing reduces suspected coronavirus cases; however, it negatively affects the services sector’s value share. The smart lockdown and sound economic activities do not decrease coronavirus cases, while they support increasing the percentage of the services sector to the global GDP. The innovation accounting matrix suggested that smart lockdown, managing physical distancing, effective price control, and sound financial activities will help to reduce coronavirus cases that will further translate into increased services value-added for the next ten years. The social distancing will exert a more considerable variance error shock to the services industry, which indicates the viability of these measures to contained novel coronavirus over a time horizon. The study used the number of proxies to the COVID-19 measures on the service sector that can be continued with real-time variables to obtain more inferences.

Background: Logistics operations are considered essential for transporting commodities from one location to another, helping to promote global economic activity. On the other hand, its negative impact eclipses its positive impact, namely the rise in healthcare expenditures due to its ecological footprint. Globally, rising out-of-pocket health expenses result from logistic-induced carbon emissions, posing a danger to the long-term viability of healthcare. Methods: Based on this critical fact, this study examined the impact of logistics operations on healthcare costs by controlling for carbon emissions, fuel imports, and economic development across a large cross-section of 131 nations by using the Robust Least Squares Regression. Results: The findings demonstrate a U-shaped association between logistical operations and healthcare expenditures, i.e., if there is a 1% increase in logistics operations, healthcare expenditures decrease by −2.421% initially, while at later stages, healthcare costs would increase by 0.139%. On the other hand, increased fuel imports and economic growth due to logistics activities are increasing healthcare expenditures with an elasticity estimate of 0.087% and 0.147%, respectively. According to the forecasting predictions, logistics-induced carbon emissions, fuel imports, and economic expansion will increase healthcare expenses. Conclusions: A sustainable logistics operation is critical for strengthening healthcare infrastructure and meeting the global carbon neutrality goal.