Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?

We explore the impacts of economic and financial dislocations caused by COVID-19 pandemic shocks on food sales in the United States from January 2020 to January 2021. We use the US weekly economic index (WEI) to measure economic dislocations and the Chicago Board Options Exchange volatility index (VIX) to capture the broader stock market dislocations. We validate the NARDL model by testing a battery of models using the autoregressive distributed lags (ARDL) methodology (ARDL, NARDL, and QARDL specifications). Our study postulates that an increase in WEI has a significant negative long-term effect on food sales, whereas a decrease in WEI has no statistically significant (long-run) effect. Thus, policy responses that ignore asymmetric effects and hidden cointegration may fail to promote food security during pandemics.

Does the green finance initiatives transform the world into a green economy? A study of green bond issuing countries.

Green finance initiatives have received global support in modern times, relatively in response to safeguard the environment and preserve natural resources through channelizing the investments to create a green economy. This paper attempts to evaluate and compare the green finance growth in green bond issuing nations across the world. This study also assesses the effect of green finance growth on the dependence of non-renewable energy resources especially fossil fuels that have been creating several environmental issues for the past years. This study develops a pressure-state-response framework to evaluate the comprehensive system of green finance growth that depicts the interaction of sub-aspects. We employ the entropy technique to calculate the weights at each level within the evaluation system. We also constructed empirical models to assess the relationship between green finance growth and dependence on fossil fuel consumption and found that there exists a negative relationship between the two. The results convey that proliferation of green finance instruments can reduce the dependence on fossil fuels and smoothen the transition towards a carbon negative world.

Investigating the nexus between carbonization and industrialization under Kaya's identity: findings from novel multivariate quantile on quantile regression approach.

Developing nations aim to industrialize and grow sustainably often ignoring the environmental consequences. However, few empirical studies have looked at the influence of industrialization-driven economic transition on carbon footprint in developing nations using a non-parametric approach. In this milieu, on the ground of Kaya's identity and the novel multivariate quantile-on-quantile regression (QQR) (extension of Sim and Zhou's (2015) bivariate QQR model), the present research studies the impact of industrial value-added (IGVA), population, energy intensity, and carbon intensity on CO2 emissions in India. This study is one of the first in the literature to evaluate the industrialization-carbonization nexus in the context of Kaya's identity for the Indian economy utilizing an innovative multivariate QQR approach, which makes a methodological and empirical addition to the literature. The outcomes of the multivariate QQR technique demonstrate that economic and environmental development requires continual long-run strategies. The empirical findings revealed that there is no authentication that India's carbon emissions increased due to its industrialization, which exhibited that IGVA has a negative and significant connection with CO2 emissions. In some quantiles, population size positively impacts CO2 emissions. On the other hand, carbonization in the Indian economy is asymmetrically affected by GDP per capita and energy and carbon intensity. The quantile Granger causality study further supported the aforementioned results. The current analysis also offers policy suggestions for environmentally friendly sustainable economic growth and to achieve the sustainable development goals (SDGs) of India.

The asymmetric influence of environmental-related technological innovation on climate change mitigation: what role do FDI and renewable energy play?

This study aims to provide a new perspective on environmental studies by examining the influence of environmental-related technological innovation, foreign direct investment, renewable energy consumption, and economic growth on the climate change index (CCI), a novel proxy for environmental quality indicators. From the econometric standpoint, this study employs the "non-linear autoregressive distributed lag" model and spectral causality over the period of 1999-2018 for India. The results show that positive shocks to economic growth have detrimental long- and short-term effects on environmental quality, whereas negative shocks have no effect. While a positive shock has an insignificant impact, a negative shock to environmental technology innovation has a long-term negative impact on environmental quality. This study provides evidence for the pollution halo hypothesis in India. Besides, a long-term negative shock to the usage of renewable energy fosters environmental degradation. Furthermore, in short-, medium-, and long-term frequency, spectral causality demonstrates unidirectional causation from CCI to environmental-related technological innovation. Bidirectional causation is demonstrated between the CCI and renewable energy consumption in the short and medium term. In addition, environmental-related technological innovation and foreign direct investment are demonstrating a bidirectional relationship in the short term. This study has advocated the Sustainable Development Goals (SDGs)-centric policy paradigm, which can assist the Indian government in achieving SDG-13 (mitigating climate change) and SDG-7 (clean energy consumption).

Repercussions of Hydroelectricity use on Carbon Emissions in Bangladesh: Evidence using Novel Fourier-Bootstrapped ARDL and Fourier-Gradual Shift Causality analyses.

Bangladesh has recently pledged at the 26th Conference of Parties (COP26) to reduce its carbon dioxide emission figures by 22% at the end of 2030. However, since this South Asian country has always turned to fossil fuels for electricity generation purposes, achieving this emission reduction goal is a challenging task for the Bangladesh government. Nevertheless, considering the negative environmental implications associated with the generation and consumption of unclean energy, particularly electricity, it is critically important for Bangladesh to expedite the process of clean transformation of its traditional pollution-intensive power system. Hence, the objective of this study is to dissect the repercussions of hydroelectricity use on Bangladesh's fossil fuel consumption-related carbon dioxide As opposed to the traditional method of quantifying environmental quality using total carbon dioxide emissions, this study considers Bangladesh's annual carbon dioxide emissions generated from the combustion of gas, oil, and coal. Besides, novel Fourier-based econometric methods that effectively handle structural break problems in data are utilized in this study. Based on the results, it is found that up-scaling hydroelectricity consumption levels exert emission-inhibiting effects while greater economic globalization activities are witnessed to boost the emissions. More importantly, hydroelectricity consumption and economic globalization are observed to jointly curb fossil fuel consumption-based emissions of carbon dioxide. Additionally, the results verify the environmental Kuznets curve hypothesis for Bangladesh. Furthermore, financial sector development is found to be effective in reducing the natural gas consumption-related carbon dioxide emissions while urbanization is held responsible for amplifying emissions generated from all three types of fossil fuels. Therefore, considering these findings, the Bangladesh government needs to particularly emphasize scaling up production and consumption of hydroelectricity to decarbonize its economy.

Re-examining the environmental Kuznets curve (EKC) for India via the multiple threshold NARDL procedure.

Irrespective of the vast array of empirical evaluations pertaining to the environmental Kuznets curve (EKC) hypothesis, both for India and other countries, previous studies, amid divergent submissions, inadvertently failed to highlight the relevant threshold that ensures significant reductions in environmental decay. Additionally, the implications of environmental-control technology on environmental quality are also lacking mostly in the context of Indian economy. Thus, this study enlists environmental-control technology and other relevant factors over the period 1980-2018 and employs the novel multiple threshold nonlinear ARDL technique, a model rarely applied in previous studies for updated empirical narratives. Accordingly, the empirical evidence rectifies that the variables converged to long-run equilibrium. Furthermore, from the tercile partial deviations, it is established that at the middle threshold (GDP2W2), pollution shrinks more significantly amid rising income, thereby validating the EKC hypothesis for India. Likewise, environmental-control technologies provided only a short-term insignificant carbon neutrality pathway, whereas they provided long-term insignificant emission increasing effects. This implies that the depth of such technology in India is inadequate to invoke cleaner environments at all times. Likewise, energy consumption and urbanization processes are significant environmental polluters, while trade openness provides insignificant long- and short-term carbon emission effects. Against this background, economic growth within the middle threshold promises a more sustainable environment amid rising national income at all times. Moreover, given its short-term outcomes, strengthening the depth of environmental-control technology is imperative to ensure a long-lasting clean environment in India.

Impacts of renewable energy on output elasticities and implications for factor shares in European countries: fresh evidence from panel threshold models.

The objective of this paper is to examine, for a panel of seven countries from the European Union, spanning the period 1986-2015, whether the use of renewable energy impacts their output elasticities of capital and labor and, thereby, influences the factor shares. By applying a set of models from threshold analysis, the analysis detects-for the first time-the presence of thresholds in the use of renewable energy with nontrivial consequences; notably, once the thresholds are crossed, the output elasticity of capital declines, while the output elasticity of labor rises. These changes in the elasticities indicate substantial changes in factor shares triggered by the identified threshold level of renewable energy consumption. This paper also finds changes in output elasticities of factors of production for other threshold variables including energy production from oil and gas or coal. These findings portray a complex and non-linear relationship between energy sources (e.g., renewables and non-renewables) vis-à-vis the economic growth level (e.g., GDP), with far-reaching consequences for factor shares from using renewables vis-à-vis non-renewables. Accordingly, it can be assumed that the changes in factor shares can, in turn, shape the incentives for the adoption of renewables within the selected European nations. Hence, future economic policies should emphasize the augmentation of renewable energy in the national energy system in order to sustain the rate of economic growth.