Asymmetrical ARDL correlation between fossil fuel energy, food security, and carbon emission: providing fresh information from Pakistan

Climate variability, population growth, and globalization impacting food security in Pakistan

Global hunger has increased recently, returning to levels observed a decade ago. Climate change is identified as a key factor contributing to these increases and is a significant cause of severe food crises. When combined with population growth and globalization, future climate variability is expected to significantly affect global food security. This study examined the influence of climate variability, globalization, and population growth on food security (FS) in Pakistan from 1995 to 2023. Food security data was sourced from the Food and Agricultural Organization, and globalization data was obtained from the KOF Globalization Index. Datasets on climate variability, population growth, unemployment, and inflation were collected from the World Development Indicators. A two-layer principal component analysis was utilized to develop the food security index. Multivariate Generalized Auto-Regressive Conditional Heteroscedasticity was used to assess the impact of globalization, population growth, and climate variability on food security. All indexed components explained more than 50% of the variance, resulting in a food security eigenvalue of 3.603 with a 0.901 proportion. The findings indicated that population growth and climate variability significantly negatively affect Pakistan's food security. Furthermore, the study found that globalization notably mitigates the adverse effects of climate variability and population growth on food security. This research may help alleviate the risk of future undernourishment, reverse current trends of escalating food insecurity, and support the sustainable development goal of eliminating global hunger by 2030.

Prolonged war reverses carbon emissions from an early decline to a late increase - Evidence from Syria

Given that war can have a serious impact on the climate, this article is aimed to discuss the impact of warfare on carbon emissions by examining changes in CO2 before and during the war in Syria based on the kaya constant equation and the LMDI decomposition method. In the decade before the war, population was the largest contributor, making up 32.64% of the total 51.02% increase in carbon emissions. The only factor that offsetting carbon emissions was energy intensity, making a 22.30% curbing effect. In the early stage of the war, carbon emissions decreased by 56.38%, in which per capita GDP contributed 37.55% of the total CO2 decline. Carbon intensive of energy was the only factor promoting the carbon increase with a 4.67% contribution. In the late war, carbon emissions start to resume slow increase with energy intensity and economy turning negative to positive. It can be speculated that the impact of the war on CO2 emissions: (i) in the first years of the war, CO2 would drop significantly at the cost of significant population decline and economic recession, the least desirable and the worst way to reduce carbon emissions. (ii) if evolves into a prolonged war, it would reverse carbon emissions from decline to increase, although the population and the economy are both falling. This research, therefore contends that once war is triggered, there is no other solution to prevent this worst-case scenario of Population Decline - Economic Recession - Increased Carbon Emissions from happening, unless the war is stopped immediately.

Dynamic association of stock market volatility, foreign portfolio investment and macroeconomic indicators by taking the impact of structural breaks

In an asymmetric information environment, investors diversify their investments to minimize risk and maximize their wealth. Such diversification ranges from one market to another market and from one country to another country. Investors prefer foreign portfolio investment over foreign direct investment because of the economy's turmoil, changes in macroeconomic indicators, and market liberation. This study analyzes the dynamic relationship among stock market volatility, foreign portfolio investment, and macroeconomic indicators (foreign exchange rate, interest rate, and Gross Domestic Product) using the dynamic long-run Auto-regressive Distributed Lag (ARDL) model concerning the Pakistan environment. This study also considers the impact of multiple structural breaks, representing variables' endogenous and exogenous shocks. The secondary data is used from Oct. 01, 2009, to Sept. 30, 2019, with monthly frequency. The results indicate a co-integration between SMV, FPI, FXR, IR, and GDP. In short-run analyses, the error correction term is statistically significant, while in the long run, the SMV, FPI, and FXR are not impacted. As no evidence of volatility has been found between SMV and FPI, unidirectional or bi-directional policies can be devised to further attract the new FPI for strengthening the foreign reserves, the balance of payments, and other macroeconomic variables. Additionally, investors should update their knowledge based on considering the endogenous and exogenous shocks on the SMV.

Correlation and causality between carbon and energy markets: a complexity perspective

Global warming obliges humans to focus on the relationships between carbon and energy markets. This study considers the relationship between carbon and energy markets from a complexity perspective. Chinese carbon prices and four energy indexes are selected as empirical variables. First, the complexities of carbon and energy markets are measured by multi-scale fuzzy entropy. The critical time delay of the series is then obtained by maximizing the Pearson coefficients between these markets. Further, analysis of the detrended cross-correlation coefficient confirms the existence of time delay. Finally, transfer entropy is applied to investigate the causality pertaining to dynamic complexity. Results of fuzzy entropy analysis reveal that the carbon market has lower complexity than energy markets. Meanwhile, multi-scale results indicate greater complexity on the small time scales in all markets than on the large time scales. The critical time delay is found to be about 50, which maximizes the correlation coefficient. Finally, causality between carbon and energy markets varies. Expectations in the carbon market impact oil gas and coal markets; electricity and new energy affect the carbon market; and cross-causality exists in the relationship between coal and carbon markets. The participants should focus on the information transmission between carbon and energy markets.

Bibliometrics of the nexus between food security and carbon emissions: hotspots and trends

With the growth of global food demand, agricultural carbon emissions caused by agricultural production have become a major challenge in controlling global warming. However, a systematic and visual literature review of food security and carbon emissions (FSCE) is still lacking, and there is a lack of exploration on the balanced path between ensuring food security and realizing carbon emission reduction. Based on 872 articles related to FSCE in the Web of Science (WOS) core database, this paper used CiteSpace and VOSviewer bibliometric software to analyze the relevant research focus and trends. This study found that developed countries dominated the research in this field, and the quantity, quality, and intensity of their authors, institutions, and cooperation among countries are higher than those of developing countries. Although the intensity of interdisciplinary cooperation has increased, it remains at a low level. Since 2007, the number of papers published in this field has increased significantly, and the research perspectives have diversified. Moreover, the research theme continues to expand with the core of "food security," involving the impact of climate change, crop production and food security, soil carbon sequestration, and farmers' livelihood sustainability. In addition, food production, food transportation, and food loss reduction are key paths that need to be balanced to ensure global food security and realize carbon emission reduction, and how to promote "economic growth" under the constraints of FSCE will be a future research hotspot.

Energy mix with technological innovation to abate carbon emission: fresh evidence from Mexico applying wavelet tools and spectral causality

The global warming issue arises from climate change, which draws scientists' attention toward cleaner energy sources. Among clean sources, renewables and nuclear energy are getting immense attention among policymakers. However, the significance of nuclear energy in reducing CO₂ emissions has remained ambiguous, necessitating further research. Therefore, the present study draws impetuous attention to the United Nations Sustainable Development Goals-7 (affordable clean energy) & 13 (climate change mitigation) by looking at the relationship between energy mix (fossil fuels, renewables, and nuclear), economic growth, technological innovation, and CO₂ emissions in Mexico from 1980 to 2019 using the autoregressive distributed lag (ARDL) model. In addition, to assess the direction of causality, this study applied wavelet techniques and spectral causality. The findings affirm that renewable and nuclear energy use and technological innovation tend to curb CO₂ emissions, whereas fossil fuel consumption and economic expansion trigger CO₂ emissions. The study lends support to the environmental Kuznets curve (EKC) phenomenon in Mexico. The FMOLS and DOLS tests show that our long-run estimates are reliable. In different time scales, the wavelet coherence result is also consistent. Finally, the results of the spectral causality approach demonstrate a significant causal association between the variables tested at various frequencies. As a result, in order to achieve SDGs 7 and 13 and support an environmentally friendly ecosystem, Mexico's energy mix must be changed to renewables and nuclear.

The influence of FDI on GHG emissions in BRI countries using spatial econometric analysis strategy: the significance of biomass energy consumption

Indeed, the Belt and Road Initiative (BRI) plays an increasingly important role in global economic and climate change mitigation. However, scientists have insufficient attention to the issues related to the elements that contribute to justifying these impacts and bolstering its response in BRI nations. Accordingly, the existent study executed an in-depth examination of the spatial direct and spillover effects of foreign direct investment inflows (FDI) and biomass energy consumption (BEC) on greenhouse gas emissions (GHG) for 57 BRI countries (1992-2012). We applied the spatial lag model (SLM), the spatial error model (SEM), and the spatial Durbin model (SDM) with five different weights matrices to verify the existence of the pollution haven hypothesis (PHH), the pollution halo hypothesis (P-HH), and the N-shaped environmental Kuznets curve (EKC). We linked the study results with the implementation level of the sustainable Development Goals (SDGs). The findings of local Moran's I (LMI) and Lagrange Multiplier (LM) tests confirm the existence of spatial autocorrelation (SAR). The empirical results revealed that FDI has a positive direct and spillover influence on GHG emissions, which supports the presence of PHH. Also, the nexus between economic growth and GHG emission is an N-shaped curve. The results revered that BEC has a negative sign for direct and spillover effects. In contrast to BEC, Fossil Fuel Energy Consumption (FFEC) and population positively sign for direct and indirect impact. Some policy proposals and future research directions are discussed for BRI countries.

Agriculture, globalization, and ecological footprint: the role of agriculture beyond the tipping point in the Philippines

This study is hinged on analyzing factors such as agriculture and globalization (de jure trade and financial) that threaten a sustainable environment using two proxies of ecological footprint: carbon and noncarbon ecological footprint in the Philippines while controlling for the influence of fossil to GDP, economic growth, urban population, and financial development using the autoregressive distributed lag (ARDL) framework. The result provides evidence of long-run stable state among the variables. The result validates inverted U-shaped pattern of EKC involving relationship between agricultural development and ecological footprint for the Philippines indicating that initially, ecological footprint increases as the agriculture develops and then declines as the agriculture matures to generate efficiency and low carbon. In addition, this study explores elasticities of the variables using ARDL, FMOLS, DOLS, and CCR procedure and found that de jure financial globalization exerts positive influence on ecological footprint in the long run. De jure trade globalization is found to be negative and significant in the long run. It is also found that agricultural level operates below the threshold level required to maximize the growth benefits of agricultural system towards mitigating environmental sustainability. Further empirical result shows a positive relationship between economic growth, fossil fuel, urban-population growth, and ecological footprint, and negative insignificant relationship between credit to private sector and ecological footprint. The government should optimize the use of agricultural land through well-articulated economic integration strategy fashioned to pave way for cleaner and low-carbon technologies sources like solar, geothermal, biomass, biogas, tidal power, photovoltaic, and wind energy in the agricultural production to avoid further deterioration of the environment.

Environmental pollution and agricultural productivity in Pakistan: new insights from ARDL and wavelet coherence approaches

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO₂) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018. The autoregressive distributive lag (ARDL) and wavelet transform coherence (WTC) approaches are applied to estimate the long-run and short-run elasticity estimates. The empirical findings discover that CO₂ emissions, agricultural land, labor, feed, and fertilizers exert high pressure on agricultural productivity which is backed up by the WTC findings. Furthermore, the gradual shift causality test results reveal the presence of a unidirectional causality relationship between all regressors and agriculture productivity, demonstrating that all the factors significantly influence agriculture productivity. Moreover, these findings are robust to different robustness tests that we perform to test the reliability/accuracy of our core results. From policy perspectives, regulations must be developed to explore a practicable expansion strategy that includes the use of efficient fertilizers and feed at optimal levels, as well as environmental protection through public-private investment in the agricultural sector.

Financial development and environmental sustainability in West Africa: evidence from heterogeneous and cross-sectionally correlated models

Although West African nations are flourishing economically of late, they still have environmental issues due to the high rate of emissions in the bloc. Despite the worsening environmental condition, there have been limited studies on the causal agents of this situation in the region. Therefore, drawing strength from the United Nations' Sustainable Development Goals (SDGs) and their targeted impacts of 2030, this study explored the nexus between financial development and environmental sustainability in West Africa (WA) for the period 1990 to 2016. The cross-sectional autoregressive distributed lag (CS-ARDL) estimator alongside the cross-sectionally augmented distributed lag (CS-DL) and the cross-sectional augmented error correction (CAEC) estimators were engaged to examine the elastic effects of the explanatory variables on the explained variable and from the results, financial development was harmful to environmental sustainability in WA through high carbon emissions. Also, control variables foreign direct investments, energy consumption, industrialization, and population growth were detrimental to the sustainability of the environment. On the causal connections amid the series, a unidirectional causality from financial development and population growth to carbon emissions was uncovered. Also, feedback causalities between foreign direct investments and carbon emissions, between energy consumption and the effluents of carbon, and between industrialization and environmental pollution were unraveled. Based on the findings, the study recommended among others that the countries should integrate environmental welfare objectives into their financial development policies. Also, the nations should ensure that their citizens have access to energy that is affordable, reliable, sustainable, and modern (SDG 7). Finally, improvement in energy efficiency, sustainable infrastructure, and good use of resources (SDG 12) should be promoted by the nations. The above recommendations if seriously taken into consideration will help the region to combat climate change and its impacts, which is the focus of SDG 13. The main flaw of this exploration was the lack of data for some specific time periods. Therefore, in future when such data become available, similar investigations could be carried out to confirm the robustness of the study's results.

Dynamic impacts of energy use, agricultural land expansion, and deforestation on CO2 emissions in Malaysia

This study empirically investigates the nexus among energy use, agricultural land expansion, deforestation, and carbon dioxide (CO₂) emissions in Malaysia. Time series data from 1990 to 2019 were utilized using the bounds testing (ARDL) approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the energy usage coefficient is positive and significant with CO₂ emissions, indicating a 1% increase in energy consumption is related to a 0.91% rise in CO₂ emissions. In addition, the coefficient of agricultural land is positive, which indicates that agricultural land expansion by 1% is associated with an increase in CO₂ emissions by 0.84% in the long run. Furthermore, the forested area coefficient is negative, which means that decreasing 1% of the wooded area (i.e., deforestation) has a long-term effect of 5.41% increased CO₂ emissions. Moreover, the pairwise Granger causality test results show bidirectional causality between deforestation and energy use; and unidirectional causality from energy use to CO₂ emissions, agricultural land expansion to CO₂ emissions, deforestation to CO₂ emissions, agricultural land expansion to energy use, and deforestation to agricultural land expansion in Malaysia. The empirical findings reveal that increased energy use, agricultural land expansion, and deforestation have a negative impact on environmental quality in Malaysia. Thus, the effective implementation of policy measures to promote renewable energy, climate-smart agriculture, and sustainable management of forest ecosystems could be useful for reducing environmental degradation in Malaysia.

Food Production Security in Times of a Long-Term Energy Shortage Crisis: The Example of Poland

In countries with industrialized agriculture, the contribution of fossil energy equals or exceeds the energy provided to society in food. Poland is one of the countries which, in the absence of its own sufficient oil and gas resources, is forced to import these fossil fuels in order to benefit from modern solutions in the field of food production and distribution. This situation poses a serious threat to food security if there is a prolonged shortage of energy from such sources. Using the example of Poland, the following were identified: the causes and level of agricultural dependence on fossil fuels, energy threats to agriculture and energy source alternative to fossil fuels. The results of these considerations indicate that Poland is not a country that has irretrievably lost its ability to restore its food self-sufficiency in the event of loss of access to external sources of fossil fuels.

The combined effect of climatic factors and technical advancement on yield of sugarcane by using ARDL approach: evidence from Pakistan

Sugarcane is one of the most important crops in the world and has a major influence on environmental concerns. This study aims to examine the association between sugarcane crop yield, climate change factors, and technical advancement using time series data for the period of 1989 to 2015 in Pakistan. An autoregressive distributed lag (ARDL) model and descriptive statistics analysis were employed in this study. The outcomes of the bound F-test for co-integration confirmed that there is a long-run and short-run equilibrium among sugarcane crop yield, temperature, rainfall, fertilizer use, and agricultural machinery. The results of long-run estimate that the coefficient of area, rainfall, and fertilizer use have significantly positive impacts on sugarcane crop yield. The coefficient of temperature had positive and non-significant while agricultural machinery had negative and statistically significant relationship with sugarcane crop yield. In the short-run estimates, the coefficient of area, rainfall, and fertilizer use have statistically positive impact, temperature had non-significant impact, and agricultural machinery had significantly negative impact on the yield of sugarcane crop. In addition, both CUSUM and CUSUMsq test results confirmed the goodness of fit of this model. The outcomes of our study suggest that climate change has negative impact on the yield of sugarcane. Based on the study findings, the Government requires to take effective measures for constructive policy-making and identification of environmental threats in Pakistan. Large-scale mechanical activities and rapid growing may be useful initiatives for raising the yield of sugarcane. Furthermore, technical advancement needs to be improved because it plays a vital role in increasing the yield of sugarcane and other major crops.

An asymmetric analysis of the impacts of energy use on carbon dioxide emissions in the G7 countries

The foremost theme of the paper is to explore the asymmetric/symmetric impact of energy consumption on the carbon dioxide emission of G7 countries (Germany, Canada, USA, Italy, France, Italy, UK, and Japan). The nonlinear autoregressive distributed lag is used to measure asymmetric/symmetric cointegration by using annual data of G7 countries from 1965 to 2019. The augmented Dickey-Fuller and structural break unit root test is employed to measure the stationarity in variables while the Brock, Dechert, and Scheinkman test is used for measuring nonlinearity and the Wald test is used to figure out short- and long-run asymmetries/symmetries, respectively. The estimated findings of the nonlinear autoregressive distribution lag model show a significant effect of energy use on the ecological footprint. The asymmetric causality test provides evidence of unidirectional, bidirectional, and asymmetrical/symmetrical causality among the variables of G7 nations. The finding of the study suggested policy for the government of Canada and France to use coal instead of oil and gas while the USA, Germany, Italy, UK, and Japan are required to consume gas as compared to oil and coal. Similarly, the study also suggests using modern technology, renewable energy, and preventive measurement for ensuring environmental betterment.

A causal link between renewable energy, energy efficiency, property rights, and CO2 emissions in developed countries: A road map for environmental sustainability

CO2 emissions are the leading causes of deterioration in air quality and global warming. Likewise, it has been shown that clean energy reduces air pollution, so this would be a way out of environmental pollution. Some previous studies have focused on knowing the determinants of environmental pollution; however, they have omitted the State's role. Thus, this study explores the long-term nexus between CO2 emissions and renewable energy, energy efficiency, fossil fuels, GDP, property rights from 1995 to 2019 in nine developed countries. The results reveal a long-term equilibrium relationship in developed European countries, but not in developed non-European countries. The main results show that renewable energy and energy efficiency are negatively correlated with CO2 emissions. In developed European countries, a 1% increase in renewable energy consumption represents a 0.03% decrease in CO2 emissions. Finally, some policy measures are suggested to achieve environmental sustainability.

Multielement synergetic effect of NiFe2O4 and h-BN for improving the dehydrogenation properties of LiAlH4

NiFe₂O₄@h-BN composites significantly improved the dehydrogenation and rehydrogenation properties of LiAlH₄. The Al₄Ni₃ and LiFeO₂ found in doped LiAlH₄, and Al_1.1Ni_0.9 in the process of heating, improved the dehydrogenation properties of LiAlH₄.

Analysis on the nexus of CO2 emissions, energy use, net domestic credit, and GDP in Pakistan: an ARDL bound testing analysis

Greenhouse gas effect is known as the main cause of worldwide warming and environmental change. The present study was planned to examine the causal relationship between carbon dioxide (CO₂) emissions, CO₂ emissions from solid fuel consumption (CO₂S), energy use (EU), fossil fuel energy consumption (FOF), gross domestic product (GDP), and net domestic credit (NDC). This research work is based on Pakistan's annual data from 1971 to 2014. Autoregressive distributed lag (ARDL) bound testing design was used to measure both long-run and the short-run relationships among all study variables. To inspect the stationarity of the study variables, augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests were also carried out. The outcome of the long-run estimates indicated that CO₂S, EU, and GDP all have a significant relationship with CO₂ emissions while both FOF and NDC did not exhibit any significant effect. The value of error correction term (ECT) was - 0.977 which signifies that the deviation of CO₂ emissions from short-run to long-run equilibrium was fitted by 97.7% per year. Johansen co-integration test results display a long-run association between the study variables. Based on the study findings, the government requires to take effective measures for constructive policy-making and identification of environmental threats in Pakistan. Additionally, emission decreasing actions should be settled the fundamental agenda in energy and environmental strategies of Pakistan for the reduction in damages connected with carbon dioxide emissions.