Techniques for Testing the Constancy of Regression Relationships Over Time

Innovation and entrepreneurship of Chinese returning migrant workers in their home region

This study aims to investigate the influence of pre-entrepreneurial career mobility frequency and job changes among returning migrant workers (RMWs) on the innovation level of enterprises, with a particular focus on the mediating role of urban social capital accumulated by RMWs. Using data from the "current entrepreneurial status of RMWs", we applied an ordered probit model to validate our hypotheses. To address endogeneity, a recursive bivariate probit model was used, and stepwise regression combined with bootstrap methods was employed to ascertain the mediating influence of urban social capital. Our results demonstrate a significant positive correlation (P < 0.01) between pre-entrepreneurial career mobility frequency and the innovation level of enterprises among RMWs. However, there's a notable negative correlation (P < 0.01) between experiences as elementary workers and enterprise innovation level, while technical and marketing roles correlate positively (P < 0.01) with enterprise innovation level. Urban social capital mediates the relationship between career mobility and enterprise innovation level, suggesting that career mobility enhance urban social capital accumulation, influencing RMWs' enterprise innovation levels. This empirical evidence holds even after robustness tests. We further observed that RMWs with fewer than three career moves lean towards low level of enterprise innovation, while those with three or more gravitate towards high level of enterprise innovation. This study advances the theory of career mobility and enriches the understanding of enterprise innovation levels. Additionally, it provides critical theoretical insights for prospective RMWs entrepreneurs in strategizing their career mobility and job changes. Policy implications suggest that, in addition to providing entrepreneurial support, the government should facilitate pre-entrepreneurial career mobility channels for migrant workers and consider the transition from rural to urban employment as a socialized ritual for RMWs engaging in entrepreneurship.

Economic expansion and innovation: A comprehensive analysis of Pakistan's path to technological excellence

To encourage technological and industrial innovation, nations worldwide implement "re-industrialization" and "manufacturing return." This study investigates the relationship between GDP growth, expenditure on research and development, and medium- to high-tech as a percentage of manufactured exports on technological innovation in Pakistan. We evaluated long-run and short-run causal relationships using the ARDL, bound-F test, and ECM regression. The study found a positive relationship between GDP growth and technological innovation in the short and long run. In the short run, with a one-year lag, the analysis reveals a positive and statistically significant relationship between technological innovation, medium-high-tech exports, and GDP growth. In the long run, R&D is positive and significant, while economic growth and technological innovation are positive but not statistically significant. There is a 0.38 percent chance that exogenous shocks will eventually lead to equilibrium in the long run. Based on the findings of this study, it is recommended to allocate resources to research and development, promoting collaborative initiatives, ensuring intellectual property rights, and developing a skilled workforce.

Assessing the effect of energy consumption and food production from agriculture on environmental degradation in Pakistan: Does institutional quality matter?

The nexus between food production (FP), energy consumption (EC), institutional quality (IQ), and ecological degradation (ED) has important implications for environmental sustainability. Nevertheless, environmental degradation caused by FP is widely ignored, especially in Pakistan. To fill this void, we investigated the impact of energy use, FP, and IQ on Pakistan's environmental degradation between 1990 and 2021. We also explore the moderating influence of IQ on ED. To evaluate this influence, we use the autoregressive distributed lag (ARDL) method for cointegration and the fully modified ordinary least-squares method for robustness estimation. Our empirical results demonstrate that, whereas FP and EC contribute to pollution, IQ reduces the pace of environmental degradation. Furthermore, the presence of a strong IQ mitigates the harmful ecological effects of FP and EC. Moreover, the results revealed that unbiased domestic IQ is crucial to boosting energy and agricultural efficiency while reducing CO2 emissions. Our findings might be considered while public policies to reduce carbon emissions and increase FP in a healthy environment are being developed. Integr Environ Assess Manag 2024;20:518-532. © 2023 (SETAC).

An EKC-based modelling of CO2 emissions, economic growth, electricity consumption and trade openness in Serbia

Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO2 emissions, economic growth, electricity consumption, and trade openness in Serbia. Initially, an Autoregressive Distributed Lag (ARDL) model is used to characterize the Environmental Kuznets Curve (EKC) using data from the period from 1995 to 2019, followed by the construction of a bootstrap logistic regression model to predict environmental quality in Serbia. Long-term estimates of the model confirm an inverted U-shaped relationship, where all three variables exert a statistically significant influence on CO2 emissions. In the short run, however, a causal relationship is only observed between electricity consumption and CO2 emissions. The logistic regression results show that all three factors significantly influence environmental quality. The study proposes policy recommendations for Serbia, such as promoting sustainable economic growth, implementing long-term programs to reduce CO2 emissions, reviewing trade policies to prioritize sustainable practices, and investing in renewable energy sources to reduce emissions.

Methodology for examining the relationship between oil rent and crude oil production: Evidence from Cameroon

The relationship between oil rent and crude oil production remains unexplored in Cameroon. This study therefore aims to apply the Autoregressive Distributed Lag (ARDL) estimation technique and the Granger causality test using the Toda-Yamamoto procedure to capture the symmetric impact and causality links between oil rent and crude oil production in Cameroon. The study covers the period from 1977 to 2019, and includes crude oil prices, human development index (HDI) and corruption as other variables. The study indicates that there is a significant negative linear impact of crude oil production on oil rent and a bidirectional causality between oil rent and crude oil production. Finally, the price of crude oil, HDI and corruption are found to pass through production to influence oil rent. The results of this study will guide policy makers in managing and sustaining oil revenues for growth and prosperity.•The paper examines the linear impact of crude oil production on oil rent and the causal links between crude oil production and oil rent by incorporating crude oil prices, HDI and corruption.•Bidirectional causality between oil rent and crude oil production.•Convergence of crude oil price, HDI and corruption to crude oil production to influence oil rent.

Exploring sustainable energy consumption and social conflict risks in Turkey: Insights from a novel multiresolution ARDL approach

Nonrenewable energy sources have been shown to be a cause of conflict and terrorism, highlighting the global conflict aspect, but little is known about the causal relationship between the energy system and terrorism in Turkey. This study aims to fill this gap by examining the causal links among renewable energy consumption, fossil fuels, terrorist attacks, education, trade opening, and geopolitical risks in Turkey from 1980 to 2016. Using the autoregressive distributed lag (ARDL) approach and Granger causality tests, the study analyzes the short and long-term relationships between the variables. Additionally, robustness tests are conducted using a powerful multiresolution ARDL approach to ensure the stability of the statistical findings. The results reveal the existence of long-term relationships between all the variables, particularly among terrorism, renewable energy, and education. In the short term, a one-way relationship exists between terrorism and education to renewable energies and from trade openness to terrorism. The study demonstrates that nonrenewable energy increases terrorism in the long term, whereas renewable energy and trade openness reduce terrorism, highlighting the potential impact of global conflicts on Turkey's sustainable development. Therefore, renewable energy is a powerful tool to fight against terrorism, and Turkey has encouraged its use and deployment of diplomatic efforts to resolve political and military conflicts, particularly in the Middle East. This study provides insights into the complex relationship among sustainable energy consumption, terrorism, education, and trade opening, contributing to the understanding of the geopolitical risks and economics in Turkey. It has implications for policymakers in the region, highlighting the importance of renewable energy and trade openness as tools for conflict resolution and sustainable development in the face of global conflicts.

Evaluating the influence of green growth, institutional quality and financial inclusion on financial stability: evidence by sustainable finance theory

Financial stability is essential for economic growth because it fosters confidence and trust and promotes investment in green development. However, it is a dilemma for the world economies to create an equilibrium between financial stability and environmental sustainability. In the extent of these challenges, the present study aims at grabbing the link of financial inclusion to attain financial stability. Further, the present study investigates the association of institutional quality, renewable energy, green growth, environmental sustainability, and financial inclusion with financial stability. Two basic econometric models are applied that focused on the basic and interaction term outcomes. In addition, principal component analysis (PCA) is analyzed to design an index for five proxies of financial inclusion. Additionally, the research inspected the interaction term of institutional quality and financial inclusion (FIN*INSQ) and determined the multiplied impact on financial stability in a separate model. This research employed the linear autoregressive distributed lag approach from 1990 to 2020 for long- and short-term dynamics. Theoretically, the research supports the sustainable finance and financial development theory. Hence, results showed that financial inclusion and institutional quality are positively associated with financial stability, while green growth, environmental sustainability, and renewable energy mechanisms are achieved through financial stability. Following our findings, the government should establish consistency between financial development and economic policies to maintain financial instability and ensure financial soundness. Furthermore, countries require viable financial institutions prioritizing green growth and institutional quality to achieve financial stability and long-term development.

Nexuses between carbon emissions, trade openness, transport services, globalization index, and growth in China: targeting the sustainable development goals

Since the end of the twentieth century, the world has observed a considerable upsurge in carbon emissions as several countries have surfaced as industrial centers and production monsters worldwide. The present study contributes to the existing literature examining the effects of carbon-based emissions, industrial value added, trade openness, transport services, railway lines, and globalization index on per capita GDP growth in China. The study covers a period of 40 years, from 1982 to 2021, introducing the impact of railway transport on GDP growth in contemporary environmental empirics. A vector error correction model (VECM) was applied to achieve the study's envisaged objectives. The findings of this study reveal that carbon emissions are responsible for the reduction of per capita GDP growth in China. On the contrary, industrial value added, transport services, railway lines, and globalization index positively support the per capita GDP growth-dependent variable. The study proposes that pragmatic policies are needed to control pollution resulting from carbon emissions. The eventual effect of maintaining greenhouse gases is expected to assist in achieving sustainable growth of per capita GDP leading to the accomplishment of sustainable development goals in the economy.

Green investment, institutional quality, and environmental performance: evidence from G-7 countries using panel NARDL approach

The foremost purpose of the study is to establish a point that an economy of G-7 countries has an abundance of resources to tackle the environmental changes that occur in the world, but these countries are still behind the line because in this modern era, environmental performance changes their shape, dimension, and nature very frequently and create a huge impact on globalization of world economy. To fill this gap, we use green investment, institutional quality, and economic growth on environmental performance for this, we use four proxies for green investment and three proxies for greenhouse gas, and we also use six proxies of institutional quality to do this using period of 1997 to 2021. Moreover, we have used the panel nonlinear autoregressive distributed lag method to evaluate the long-run and short-run asymmetric effects of green investment, institutional quality, and economic growth on greenhouse gas emissions. The findings of the study affirm that the positive change of green investment has a positive and significant relationship with environmental performance, while the negative change of green investment has a significant and positive influence with environmental performance in the long run. Furthermore, the outcomes demonstrate that the positive shock of institutional quality has a positive and significant relationship with environmental performance, while the negative shock of intuitional quality has a significant and positive association with environmental performance in the long run, whereas positive change in economic growth has a positive and significant with the environmental performance, while the negative change of economic growth has a positive effect with environmental performance in the long run. This study finds future precautions that institutional quality has to perform exceptionally and shows results very rapidly, while green investment with economic growth has also made a deadly combination to control greenhouse gas emission, so the role of G-7 countries is pretty clear and straight. Furthermore, it is suggested that governments and policymakers take a proactive stance to promote resource acquisition and investment across all industries. To reduce gas emissions, public interest might also be complementary to private ones. So, economic policymakers, specifically in G-7 countries, should consider strategies that support sustainable economic growth.

The role of foreign direct investments, urbanization, productivity, and energy consumption in Finland's carbon emissions: an ARDL approach

This study investigates the effects of productivity, energy consumption, foreign direct investments, and urbanization on carbon dioxide emissions (CO2) in Finland during 2000-2020 using an autoregressive distributed lag (ARDL) model. The results show that (i) there is evidence of cointegration among variables; (ii) energy consumption has a positive effect on CO2 emissions in the long run; (iii) labor productivity and urbanization have a negative effect on CO2 emissions in the long run; (iv) foreign direct investments are not a significant explainer of CO2 emissions. The results are discussed with some policy implications and suggested future research.

Role of institutional quality in debt-growth relationship in Pakistan: An econometric inquiry

This study attempts to investigate the mediating role of institutional quality on the relationship between public debt and economic growth in Pakistan spanning 1996-2020. Time series data on all six World Bank World Governance indicators of institutional quality is used in the empirical analysis. Findings of the autoregressive distributed lag (ARDL) bounds testing technique and error correction method (ECM) confirmed the existence of cointegration among variables of interest. The short-run results indicate that public debt has a favorable association with economic growth, while the relationship is found to be detrimental in the long run. Furthermore, the combined effect of public debt and institutional quality indicators revealed the significant positive association with economic growth, suggesting that better institutional quality can contribute to mitigate the negative impact of public debt on economic growth in Pakistan.

The effect of sectoral natural gas consumption on economic growth: a study of Turkey

Turkey, which is among the developing countries, is highly dependent on foreign energy. This dependency creates a great burden on the country's economy. In recent years, Turkey has increased its hydrocarbon exploration in the seas in order to ensure energy supply security and to get rid of this burden on its economy. As a result of these exploration activities, Turkey announced that it discovered a natural gas reserve of 540 billion m3 in 2020. This study aimed to guide decision makers in the use of this discovered natural gas. To this end, this paper was examined the relationship between sectoral natural gas consumption and economic growth for Turkey in a multivariate model wherein capital and labour are included as additional variables. Using the annual data for the period 1988-2020, long- and short-run relationships were examined with the autoregressive distributed lag bound testing approach. According to the long-term findings, increases in natural gas consumption in all examined sectors encourage economic growth in Turkey. It has been determined that natural gas consumption in the industrial sector provides the greatest contribution to Turkey's economic growth. In the long run, a 1% increase in the natural gas consumption of the industrial sector increases the economic growth by 0.190%. On the other hand, it was noted that a 1% increase in natural gas consumption in the conversion sector increased growth by 0.134%, while a 1% increase in housing natural gas consumption increased by 0.072%. In line with the findings obtained, policymakers in the Turkish government are advised to substitute the natural gas used in the conversion sector with renewable energy sources and to use the discovered natural gas reserve for heating purposes in housings, in order to have long-run growth rates.

How technological innovation and electricity consumption affect environmental quality? A road map towards achieving environmental sustainability

Still the world witnessed an upturn in environmental degradation in spite of commitment to climate change across the nations. However, this study attempts to examine linkages among environmental degradation, technological innovation, and electricity consumption in India from 1981 to 2018 using time series data. To examine the long-run equilibrium relationship among the studied variables, we used robust econometric methods such as the autoregressive distributed lag (ARDL), fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS) methods. Furthermore, Granger causality also investigates through the vector error correction model (VECM) model, to assess inter-connotation among the underlying variables. From our empirical findings, urbanization, financial development, and technological innovation have a negative impact on carbon emissions, indicating long-term improvements in environmental quality. While economic development and electricity consumption are deteriorating environmental quality in India. The study's findings suggest that policymakers should prioritize renewable energy, which decreases environmental damage without impeding economic growth.

Relationship between carbon emissions, economic growth, renewable energy consumption, foreign direct investment, and urban population in Vietnam

At the 26th UN Climate Change Conference in late 2021, Vietnam set a target of achieving net-zero carbon (CO₂) emissions by 2050. However, the country's rapid economic growth, urbanization, and industrialization have historically relied on coal-based energy, a source of significant greenhouse gas (GHG) emissions. Although contributing only 0.8% of the world's emissions over the last two decades, Vietnam currently has one of the fastest increasing GHG emissions rates per capita. Over the 2000-2015 period, Vietnam's per capita gross domestic product increased from $390 to $2,000, and CO₂ emissions nearly quadrupled. Hence, this research explores the causal relationships among CO₂ emissions, economic growth, foreign direct investment, renewable energy usage, and urban population in Vietnam over the period from 1990 to 2018 using the Environment Kuznets Curve. An autoregressive distributed lag bounds testing technique for measuring integration is utilized to investigate the long-run relationship. Results indicate that economic growth increases with CO₂ emissions until a certain threshold level and then CO₂ emissions decrease, thereby supporting the environmental Kuznets curve theory for Vietnam. Furthermore, this study examines the causal relationship among variables using a Granger causality model and determines that FDI, urban population, and renewable energy consumption play an important role and have substantial impact on carbon emission in Vietnam.

Determinants of the CO2 emissions, economic growth, and ecological footprint in Pakistan: asymmetric and symmetric role of agricultural and financial inclusion

In this study, the effects of financial inclusion (FI), agricultural innovation (AI), trade (TR), and forest rent (FR) on carbon dioxide emissions (CO₂), economic growth (Y), and ecological footprint (EFP) for Pakistan from 1970 to 2017 are examined using symmetric and asymmetric cointegration approaches. These links are investigated using linear and non-linear autoregressive distributive lag (NARDL) techniques. In contrast to the asymmetry results, the symmetric results revealed no cointegration among the variables over the long run. Moreover, asymmetry results from the Y-model indicated that a positive shock in AI significantly affects Y over the long run while raising it over the short term. Furthermore, CO₂ rises in the wake of positive shocks like AI, Y, and FR but falls in the wake of adverse shocks. A negative shock to FI raises CO₂ temporarily, whereas a negative shock to FR causes CO₂ emissions to fall over time. According to the EFP-model, long-term EFP is decreased by both positive shocks to AI and adverse shocks to FR with one-period lags. On the other hand, positive shocks to FI and FR cause the short-term EFP to rise. In addition to a bidirectional causal relationship between Y, EFP, and FI, we found a one-way causative relationship between Y, FR, AI, CO₂, and EFP. The FMOLS estimator also supports NARDL estimations. The key recommendations to help Pakistan keep its environment and economy are to enhance green mechanization in agriculture, allocate adequate research and development funds, and initiate integrated environmental and economic growth policies by relevant institutions.

Investigation of the relationship between renewable energy, natural gas, and coal consumption with economic growth in Turkey: evidence from augmented ARDL approach

Energy is an indispensable requirement for the sustainable development of countries. Turkey has been trying to increase the use of renewable sources in electricity energy production with the policies it has implemented recently. This study investigates the effect of disaggregate energy consumption on economic growth in Turkey via the Augmented ARDL. Robust results are obtained by Augmented ARDL in econometric analysis. In this context, it is to examine the impact of renewable energy, natural gas, and coal consumption. Considering the 2001 crisis in Turkey, we add a dummy variable to the cointegration equation. The paper employs the recently developed augmented ARDL approach in the presence of one structural break to investigate annual time series data during the period 1988-2018. The results obtained in this study showed that all variables were statistically significant eventually. Long-term estimation results suggest that among the energy sources examined in the study, on economic growth has a positive effect coal consumption, natural gas consumption, and renewable energy. Moreover, empirical results indicated that economic growth and energy consumption also contribute to environmental damage. On the contrary, natural gas both increases economic growth and is effective in increasing environmental quality. The fact that the positive effect of renewable energy sources on economic growth eventually is greater than natural gas is the most striking finding of the study. In line with these results, it can be said that Turkey can reduce its energy dependence by increasing the use of domestic and renewable energy sources and providing sustainable economic growth.

The effects of renewable energy sources on Turkiye's economic growth: ARDL estimation

Hydroelectric power plants have been in use for more than a century in countries with rich river resources owing to their cheaper installation costs. Hydroelectric power plants, which have particular importance for the economic growth of developing countries, have been generating electricity in Turkiye over many decades, since the early 1900s. The ultimate objective of the study is to observe the relationship between Turkiye's hydroelectric power generation and its economic growth, which is rarely addressed in the literature, by using recent data. Aimed in the empirical analysis are to test the impact of renewable energy use on economic growth in Turkiye between the years 1965 and 2019 and, in particular, to determine the role and importance of hydroelectric energy, which has an important historical background in respect of Turkish economy, in this relationship. In the analysis part of the study, firstly, unit root analyses were performed, and the ARDL estimator was made, which is the most appropriate estimator among the series with different orders of stationarity. In addition to the diagnostic tests showing whether the ARDL estimator was an appropriate estimator, findings with respect to causality between the variables were revealed with the Toda-Yamamoto causality test, which allows for different orders of stationarity of the series. According to the results of the ARDL estimator, which allows to examine the short and long-term results of the independent variables, it was concluded that renewable energy had no significant effect on economic growth in the long and short run, while hydroelectric energy has increased economic growth in the long run in the analyzed period. In Turkiye, which is highly dependent on foreign for energy production, the contribution of energy consumption to economic growth in the long run was found to be negative.

Evaluating the symmetric and asymmetric effects of fossil fuel energy consumption and international capital flows on environmental sustainability: a case of South Asia

South Asia is primarily affected by environmental degradation. As a result, it is worthwhile to explore the impact of international capital flows on the ecological sustainability of the South Asian region. There are many studies in the literature on the CO₂-remittances nexus, CO₂-FDI nexus, and CO₂-economic growth; however, no study has yet taken remittances and FDI into account in the symmetric and asymmetric model for the South Asian region. To address the research gap, this study investigates the effect of international capital flows, fossil fuel energy consumption, and economic growth on South Asian carbon emissions. This study examines the effect of fossil fuel energy consumption, remittances, foreign direct investment, and economic growth on the environmental sustainability of the South Asian region from 1975 to 2020. Autoregressive distributive lag (ARDL) and non-linear ARDL (NARDL) models are used to estimate the symmetrical and asymmetrical relationships among the variables. The findings of the ARDL models reveal that fossil fuel energy consumption and economic growth increase while remittances and FDI decrease carbon dioxide (CO₂) in the long run. According to the NARDL empirical findings, positive remittances and negative FDI shock reduce CO₂. Besides, the positive and negative fossil fuel energy consumption shock increases CO₂. Moreover, the positive (negative) economic growth shock increases (decreases) CO₂. The cumulative dynamic multipliers revealed the adjustment pattern to new long-run equilibria. The study recommends that policymakers regard remittances and FDI as policy instruments, particularly when developing long-term strategies and policies connected to environmental quality.

Evaluation of renewable energy policies in Turkey with sectoral electricity demand forecasting

Energy is an essential requirement for sustainable development, society, and the world. Turkey has been trying to increase the use of renewable sources in electricity energy production with the incentive policies it has implemented in recent years. Accordingly, in the 2019-2023 Strategic Plan of the Ministry of Energy and Natural Resources, targets to increase the installed capacity of renewable energy sources have been determined. In this context, this article examines fort the first time, the effect of installed capacity of renewable energy sources on sectoral electricity demand. Thus, the study aims to evaluate the renewable energy policies implemented in Turkey. For this purpose, firstly, sectoral electricity demands were estimated for the period 1988-2017 using the autoregressive distributed lag bound testing approach. Then, forecasts were made for the period 2019-2023 with the econometric simulation method. The findings show that the Installed Capacity variable significantly and negatively affects electricity demand in all sectors in the long run. According to the forecast results made in the second stage of the study, it was observed that the higher the increase rate in the installed capacity of renewable energy sources, the faster the electricity demand would decrease. According to these results, Turkey needs to increase the share of renewable energy sources in electricity production in terms of economic and environmental sustainability.

Structural change in feedlot cattle death loss rates

Introduction

Industry reports and anecdotal evidence indicate that the death loss rate in cattle feedlots has increased over time. Such increases in death loss rates impact feedlot cost and thus profitability.

Objectives

The primary objective of this study is to examine whether feedlot death loss rates in cattle have changed over time, to analyze the nature of any identified structural change, and to identify possible catalysts for that change.

Methods

Data from the Kansas Feedlot Performance and Feed Cost Summary from 1992 through 2017 is used to model feedlot death loss rate as a function of feeder cattle placement weight, days on feed, time, and seasonality in the form of monthly dummy variables. Commonly used tests of structural change, including the CUSUM, CUSUMSQ, and Bai and Perron methods, are implemented to examine the existence and nature of any structural changes in the proposed model. All tests indicate the presence of structural breaks in the model, including both systematic change and abrupt change. Following a synthesis of structural test results, the final model is modified to include a structural shift parameter for the period from December 2000 to September 2010.

Results

Models indicate that days on feed has a significant positive influence on death loss rate. Trend variables indicate that death loss rates have increased systematically over the period studied. However, the structural shift parameter in the modified model is positive and significant for December 2000 to September 2010, indicating that death loss is higher on average during this period. Variance of death loss percentage is also higher during this period. Parallels between evidence of structural change and possible industry and environmental catalysts are also discussed.

Conclusions

Statistical evidence does indicate changes in the structure of death loss rates. Ongoing factors such as changes in feeding rations prompted by market forces and feeding technologies may have contributed to systematic change. Other events, such as weather events and beta agonist use could result in abrupt changes. No clear evidence directly connects these factors to death loss rates and disaggregated data would be required to facilitate such a study.

The impact of climate variables on marine fish production: an empirical evidence from Bangladesh based on autoregressive distributed lag (ARDL) approach

Several studies have highlighted the significant impact of climate change on agriculture. However, there have been little empirical enquiries into the impact of climate change on marine fish production, particularly in Bangladesh. Hence, this study aims to investigate the impact of climate change on marine fish production in Bangladesh using data from 1961 to 2019. Data were obtained from the Food and Agriculture Organization, Bangladesh Meteorological Department, the World Development Indicators, and the National Oceanic and Atmospheric Administration. The autoregressive distributed lag (ARDL) model was used to describe the dynamic link between CO₂ emissions, average temperature, Sea Surface Temperature (SST), rainfall, sunshine, wind and marine fish production. The ARDL approach to cointegration revealed that SST (β = 0.258), rainfall (β =0.297), and sunshine (β =0.663) significantly influence marine fish production at 1% and 10% levels in the short run and at 1% level in the long run. The results also found that average temperature has a significant negative impact on fish production in both short and long runs. On the other hand, CO₂ emissions have a negative impact on marine fish production in the short run. Specifically, for every 1% rise in CO₂ emissions, marine fish production will decline by 0.11%. The findings of this study suggest that policymakers formulate better policy frameworks for climate change adaptation and sustainable management of marine fisheries at the national level. Research and development in Bangladesh's fisheries sector should also focus on marine fish species that can resist high sea surface temperatures, CO₂ emissions, and average temperatures.

Exploring the nature of EKC hypothesis in Asia's top emitters: role of human capital, renewable and non-renewable energy consumption

The present study uses both carbon dioxide emission and ecological footprints as proxies for environmental degradation to examine the environmental Kuznets curve hypothesis for the top three emitters from Asia, i.e., China, India, and Japan. To this end, the autoregressive distributed lag model for time series and panel estimation is used for a period spanning over 1980-2016. For carbon dioxide emission, China presents an inverted-U shape of the environmental Kuznets curve, while a U-shape relationship is found for India and Japan. Similarly, when the hypothesis is tested with the ecological footprint, Japan offers an inverted U-shape and U-shaped association is detected for China and India. The panel analysis indicates the existence of the environmental Kuznets curve with both proxies of environmental degradation. Besides, human capital and renewable energy promote environmental sustainability, while non-renewable energy use hinders environmental quality. The findings of this study suggest that in order to meet the combined goals of economic growth and environmental protection, the three economies, i.e., China, India, and Japan, should employ renewable energy-enabled technology.

Hierarchical medical system and local medical performance: A quasi-natural experiment evaluation in Shanghai, China

Background

In order to maintain high standards of healthcare, it is necessary for medical departments to provide high-quality and affordable medical services to local residents. This has been widely accepted in developed countries, while the medical treatment systems in developing countries remain to be improved. This research is based on a pilot of a hierarchical medical system in Shanghai, China, to evaluate the effects on policy of medical reform in developing countries.

Methods and results

By means of the difference-in-differences (DID) method, the causal relationship between medical care services' improvement and hierarchical medical systems' implementation could be identified. This project also explores the differential effects of policy intervention and confirms that the pilot showed a significant improvement in medical performance in central districts while the result remains uncertain in terms of suburban districts. Furthermore, the dynamic effect of a hierarchical medical system has also been identified with the event study method, while the policy pilot only had short-term effects on local medical resources' improvement. In order to ascertain the function mechanisms of hierarchical medical systems and explain why the policy pilot only had short-term effects, this project also conducts influencing mechanism analysis with the triple-differences method (also known as difference-in-difference-in-differences or DDD method). According to the empirical results, there is no direct evidence indicating the hierarchical medical system could bring obvious benefits from the perspectives of patients and medical institutions.

Conclusions

For better implementation of hierarchical medical systems in the future, long-term supervision mechanisms should be given more attention in the enforcement process of hierarchical medical systems. At the same time, more safeguarding measures should be implemented, such as supervising the payment systems of the medical institution and conducting performance evaluation.

A Note on the Structural Change Test in Highly Parameterized Psychometric Models

Equal parameter estimates across subgroups is a substantial requirement of statistical tests. Ignoring subgroup differences poses a threat to study replicability, model specification, and theory development. Structural change tests are a powerful statistical technique to assess parameter invariance. A core element of those tests is the empirical fluctuation process. In the case of parameter invariance, the fluctuation process asymptotically follows a Brownian bridge. This asymptotic assumption further provides the basis for inference. However, the empirical fluctuation process does not follow a Brownian bridge in small samples, and this situation is amplified in large psychometric models. Therefore, common methods of obtaining the sampling distribution are invalid and the structural change test becomes conservative. We discuss an alternative solution to obtaining the sampling distribution-permutation approaches. Permutation approaches estimate the sampling distribution through resampling of the dataset, avoiding distributional assumptions. Hereby, the tests power are improved. We conclude that the permutation alternative is superior to standard asymptotic approximations of the sampling distribution.

An empirical analysis of the impact of higher education on economic growth: The case of China

China's domestic labor market has limited demand for tertiary graduates due to an unbalanced industrial structure, with a weak contribution to economic performance over the past decade. This study estimates the asymmetric effects of higher education progress (highly educated employed workforce), higher education utilization (highly educated unemployed workforce), and the separate effects of higher education utilization interactions with high-tech industries on economic growth in China from 1980 to 2020. Using a Nonlinear Autoregressive Distributed Lag (NARDL) model, this study finds that the expansion of higher education progress (the employed workforce with higher education) promotes economic growth, while contraction of higher education progress (employed workforce with higher education) reduces economic growth. Likewise, an increase in higher education utilization (the unemployed labor force with higher education) suppresses economic growth, while a decline in the higher education utilization (the unemployed labor force with higher education) promotes economic growth. The study also found that the expansion of high-tech industries and government spending on education significantly stimulate economic growth. The moderating role of higher education utilization (unemployed labor force with higher education) in the impact of high-tech industries on economic growth is significantly positive. This study strategically proposes that China's higher-educated unemployed labor force can be adjusted to high-tech industries, which need to be developed equally in all regions. Moreover, the country is required to invest more in higher education and the development of high technological industries across all regions, thus may lead to higher economic growth.

Examining the macro-determinants of tourist arrivals in India

The present study analyzes the asymmetric association of exchange rate and world income with inbound tourism demand in India using a recently developed nonlinear autoregressive distributed lag model. For this purpose, the study uses monthly data from January 2003 to December 2020 for inbound tourism demand, real effective exchange rate, and world income as the variables of the model. The study used an asymmetric causality test on the lines of Hatemi-J. The findings confirm the existence of a nonlinear association between exchange rate and tourism demand in the long run. Furthermore, the increases in the world income have a positive and significant effect on tourist arrivals in India. In addition, the findings indicate that exchange rate shocks play a vital role in the long run. The cointegration test is supplemented with nonlinear causality analysis. The causal result depicted positive shocks in the exchange rate and world income sharing a unidirectional causal relationship with tourist arrivals. The result of this research can significantly facilitate the policymakers for devising short-run as well as long-run policies to consolidate the macroeconomic fundamentals such that tourism demand can be enhanced in India.

The Impact Effect of Coal Price Fluctuations on China’s Agricultural Product Price

Few studies have used China’s latest economic data to verify the interaction between coal price fluctuation and vegetable price fluctuation. Therefore, the sharing of existing knowledge in the academic community is mainly reflected in this paper, which explores the influence between coal prices and agricultural product prices for the first time. Further, it supplements the verification of the effective parameters of vegetable price fluctuation in academia. The current study investigates the relationship between coal prices (thermal coal price) and agricultural product prices (vegetable prices) in China from 2016 to 2021. It uses separate time-series models to verify the effect of China’s coal price fluctuation on the price of agricultural products and explores the effect of the coal price on the vegetables’ price trend. The results confirm that the thermal coal price significantly impacts and positively affects vegetable prices. There is also a linkage between the price of coal and the security of agricultural products. It might mainly be due to coal usage in various stages of the growing, storage, transportation, and distribution of agricultural products. Higher coal prices may lead to higher agricultural prices, threatening China’s coal-dominant energy structure. These higher coal prices will endanger domestic energy security and agricultural security. Finally, this study also suggests ways to manage the effect of increased coal prices on agricultural product prices and then puts forward policy suggestions.

A comparative study of stage characteristics and factorial decomposition of CO2 emissions between China and the USA

CO₂ contributes a lot to the greenhouse effect. The total CO₂ emissions of the two countries, China and the USA, as the world's top two economies, have exceeded 40% of the total global carbon emissions. In this context, the exploration of the evolution of carbon emissions from energy consumption in China and the USA and the comparison of the characteristics of carbon emission drivers in different periods play a significant role in the policy formulation and climate change cooperation between China and the USA. In this study, the BP structural breakpoint test was used to divide the carbon emission stages of China and the USA from 1970 to 2019. The generalized Divisia index model (GDIM) was developed to decompose the growth of carbon emissions in China and the USA into eight items, GDP, carbon intensity of GDP, energy use, carbon intensity of energy, population, carbon emissions per capita, GDP per capita, and energy intensity, and to analyze the characteristics and cumulative contribution of carbon emission drivers at each stage. Based on the stage and cumulative characteristics of carbon emissions between China and the USA, the USA should take the initiative to assume the legal responsibility of carbon emissions and further deepen the cooperation with other countries in the field of climate change. China should transform the economic growth mode, optimize the energy structure, and improve the efficiency of resource utilization to help achieve the peaking carbon emissions and the carbon neutrality smoothly.

A Dynamic Analysis of the Asymmetric Effects of the Vocational Education and Training on Economic Growth, Evidence From China

Since 2010, China's economic growth has stagnated due to an unbalanced regional industrial structure and lack of sufficient qualified technical personnel. A nonlinear autoregressive distributed lag (NARDL) model has been used in this study to examine the asymmetric effects of secondary vocational education and training (SVET) and higher vocational education and training (HVET) and their interaction with high-tech industries on economic growth over the period 1980-2020. The findings show that an increase in secondary vocational education and training (SVET) significantly boosts long-term economic growth, while a decrease in secondary vocational education and training (SVET) insignificantly reduces long-term China economic growth. Likewise, the upward change in higher vocational education and training (HVET) promotes and the downward fluctuation in higher vocational education and training (HVET) significantly reduces China's long-term economic growth. The moderating role of secondary vocational education in the impact of high-tech industries on China's economic growth is positive, but not significant. However, higher vocational education plays a significant positive moderating role in high technology industries impact on economic growth. Strategically, the study analysis suggests that economic transition prosperity can be achieved by encouraging higher vocational education and the equal development of high-tech industries in all regions. In addition, this study also proposes to cultivate high-quality talents related to high-tech development and modern industrial innovation and upgrading through higher vocational education, improve productivity, and promote the country's intensive development.

Assessment of Economic Sustainability in the Construction Sector: Evidence from Three Developed Countries (the USA, China, and the UK)

The construction sector plays a significant role in contributing to uplifts in economic stability by generating employment and providing standardized social development. Economic sustainability in the construction sector has been less addressed despite its wide applicability in the economy. This study aimed to perform a comparative analysis to determine the application of a circular economy in the construction sector toward economic sustainability, along with its long-term forecasting. A time series analysis was used on the construction sector of the United States of America (USA), China, and the United Kingdom (UK) from 1970 to 2020, by taking into account individual effects to propose a framework with global validity. Statistical analysis was performed to analyze the dependence of the construction sector and determine its short- and long-term contributions. The results revealed that the construction sectors in these countries tend to bounce back to equilibrium in the case of short-term effects; however, the construction sector behaves differently with respect to each sector after experiencing long-term effects. The results show that the explanatory power of the forecasting model (R2) was found to be 0.997, 0.992, and 0.996 for the USA, China, and the UK. Based on the concept of the circular economy, it was concluded that the USA will become a leader in attaining sustainability in construction owing to its ability to recover quickly from shocks, and that the USA will become the largest construction sector in terms of GDP, with a USD 0.3 trillion higher GDP than that of the Chinese sector. Meanwhile, there will be no significant change in the construction GDP of the UK up to the end of 2050. Moreover, the speeds of the construction sector toward equilibrium in the long run in the USA, China, and the UK, and regaining of their original positions, is 0.267%, 1.04%, and 0.41% of their original positions, respectively. This study has a significance in acting as a guideline for introducing economic and environmental sustainability in construction policies, because of the potential of the construction sectors to recover from possible recessions in their respective countries.

The Granger Causal Effects of Canady Helios Cold Plasma on the Inhibition of Breast Cancer Cell Proliferation

Cold atmospheric plasma (CAP) has become a promising tool for modern medicine. With its recent applications in oncology, regenerative medicine, and immunotherapy, CAP can be used for a myriad of different clinical treatments. When using CAP specifically for the treatment of tumors, it is known to elicit an oxidative response within malignant cancer cells, inducing cell cycle arrest and apoptosis. In this study, data of intracellular reactive oxygen species (ROS), caspase activity, Ki-67 expression, and cell cycle activity in the G1 phase were acquired to determine the causal relationships these intermediates have with cell proliferation and death after Canady Helios Cold Plasma (CHCP) treatment. The data were derived from four different subtypes of breast cancer cell lines: BT-474, MCF-7, MDA-MB-231, and SK-BR-3. Data transformation techniques were conducted on the time-series data for the input into the causal model code. The models were created on the basis of Granger causality principles. Our results demonstrated that there was a Granger causal relationship among all potentially causal variables (ROS, caspase, Ki-67, and G1 activity) and cell proliferation after 5 min CHCP treatment; however, not all variables were causal for the 3 min models. This same pattern did not exist for cell death models, which tested all potentially causal variables (ROS, Ki-67, and G1 activity) vs. caspase activity. All models were validated through a variety of statistical tests and forecasting accuracy metrics. A pseudo data set with defined causal links was also created to test R’s ability in picking up known causal relationships. These models, while nonexhaustive, elucidated the effects cold plasma has on cell activity regulators. Research in causal modeling is needed to help verify the exact mechanism of cold plasma for the ultimate optimization of its application in the treatment of cancers.

Nepal's domestic material consumption-projection and causal impact of external financial inflows, services value-added, population, and economic growth

Literature on material flow accounting has increasingly emphasized the need for an equitable resource allocation for least developed countries (LDCs) considering their future growth and the social outcomes (e.g., poverty alleviation) they intend to deliver. This paper aims to project Nepal's domestic material consumption (DMC)-scale and structure for different economic growth scenarios. We also investigate the causal impact of exogenous factors: (1) external financial inflows, such as the remittance and official development assistance (ODA); (2) services value-added; (3) population; and (4) economic growth on DMC by material types (e.g. biomass, fossil fuels, non-metallic minerals, and metal ores). We use the R tools, ridge regression and its machine learning algorithms, the autoregressive-distributed lag approach, and the abovementioned variables' time-series data between 1993 and 2017 as methodological and data tools. While Nepal's absolute DMC will increase even in the low-growth scenario, we found that the biomass-based DMC prevalent in many LDCs, including Nepal, will be non-metallic minerals-based-a material consumption trait of existing middle-income and emerging economies. Despite this, the United Nations' LDC graduation growth pathway, often assumed to deliver sustainable development objectives by policymakers in LDCs, including Nepal, is material intensive. The increase in the gross domestic product per capita, remittance, and ODA cause a rise in DMC because of their strong correlation and causal relationship. In these circumstances, we suggest policy measures that can leverage present consumption-oriented remittances as a source of investment in up-scaling small-scale modern renewable energy technologies across the residential sector, particularly in rural areas. We suggest this policy measure considering the future rise in non-metallic minerals and the challenges to reduce it because of the rising urbanization.

An Ideology of Sustainability under Technological Revolution: Striving towards Sustainable Development

The recent decades have witnessed an unprecedented surge in global warming occasioned by human anthropogenic activities. The ensuing effects have brought devastating threats to human existence and the ecosystem, with the sustainability of the future generations highly uncertain. Resolving this pervasive issue requires evidence-based policy implications. To this end, this study contributes to the ongoing sustainable development advocacy by investigating the impacts of renewable energy and transport services on economic growth in Germany. The additional roles of digital technology, FDI, and carbon emissions are equally evaluated using data periods covering 1990 to 2020 within the autoregressive distributed lag (ARDL) framework. The results show the existence of cointegration among the variables. Additionally, renewable energy and transport services positively drive economic growth. Furthermore, economic growth is equally stimulated by other explanatory variables, such as digital technology and carbon emissions. These outcomes are robust for both the long-run and short-run periods. More so, departures in the long run are noted to heed to corrections at an average of 60% speed of adjustment. The estimated models are confirmed to be valid based on the outcomes of the postestimation tests. Policy implications that support the path to sustainability are highlighted based on the findings.

Validation of environmental Philips curve in Pakistan: a fresh insight through ARDL technique

The tremendous increase of greenhouse gases puts adverse effects on environmental degradation, unemployment, and economic growth. Against this backdrop, and implementing the more recent estimation approach, the present study investigates the validity of the novel environmental Phillips curve (i.e., inverse relationship between unemployment and environmental degradation) carried by Kashem and Rahman (2020). The unique contribution of this research is to examine the three environmental indicators (CO₂, CH₄, and ecological footprint) as a dependent variable with the same independent variables, i.e., unemployment rate, energy consumption, economic growth, foreign direct investment, and globalization, from 1975 to 2014 in Pakistan. The results validate a negative relationship of unemployment rate with CO₂, CH₄, and ecological footprint in the long run that proves the existence of environment Philips curve for Pakistan. However, a positive association is observed for energy consumption and CO₂, CH₄, and ecological footprint. The positive connection of energy consumption and environmental indicators determined that not only CO₂ emissions rather CH₄ and ecological footprint play an equal role in environmental degradation. Furthermore, in the long run foreign direct investment improves environmental sustainability for CO₂, and ecological footprint thus proved the pollution halo hypothesis for Pakistan. Probing the effects of globalization that badly pollutes environmental sustainability. Therefore, the policymakers should focus on innovations and technological improvements to contemplate both environmental degradation and unemployment. There is a need for sudden actions for energy consumption plans in Pakistan for the nation's health, economic growth, and environmental sustainability.

Developing long- and short-run nexus between industrial growth, economic growth, and trade balance of China

The study examined the short- and long-run nexus between industrial growth, economic growth, oil production, inflation, and trade deficit of China, using quarterly data from 1995Q1 to 2020Q4. We used autoregressive distributed lag model (ARDL), after affirmation of long-run relationship and uni-directional causality. To examine short-run dynamics, an error correction model (ECM) was specified, and Granger causality test was conducted to find the direction of causality between variables. Empirical findings confirmed cointegration between trade deficit and industrial growth, economic growth, inflation, and oil production. Further, uni-directional causality between trade deficit and all independent variables was found, running from independent variables towards trade deficit. Results revealed that growth of industrial production index play a substantial role in determining trade balance of China. The study further confirms the effectiveness of economic growth and inflation for trade deficit, in both short run and long run. The findings are consistent with extant literature. On the policy front, a couple of suggestions including trade policies with special focus on industrial reforms, and loose monetary policies are made on the basis of derived conclusions.

The role of electricity consumption, capital, labor force, carbon emissions on economic growth: implication for environmental sustainability targets in Nigeria

Despite consistent investments, grants, and other concessions in the power sector, nationwide power outages still remain an issue, even in 2020, disrupting business operations, contributing to huge recurrent expenses on generators and alternative sources of electricity in homes, businesses, and institutions. In this paper, we examine the role of electricity consumption on economic growth, while controlling for labor, capital, and carbon emissions, using the autoregressive distributed lag (ARDL) and the novel dynamic ARDL (DYNARDL) simulation analysis over the periods 1981-2019. Empirical results show that electricity consumption, capital, and labor exert positive inelastic impacts, while carbon emissions exert negative inelastic significant impact on economic growth within the period under investigation. From policy standpoint, we are of the opinion that stable supply and consumption of electricity can possibly boost economic growth and engender social stability in Nigeria. Thus, there is a need to strengthen the effectiveness of power sector and its energy generating agencies by ensuring periodic replacement of worn-out equipment in terms of adequately financed and efficient labor in order to enhance the contribution of the sector on economic growth, while in terms of environmental degradation, policy makers should work towards promotion of green economy for a sustainable economic growth and environment in Nigeria.

A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan

The modern logistics industry in relation to economic growth and carbon emission has opened new strategic perspectives. Recent research work have analyzed such complex interference from a broad perspective. However, analyzing this overlap needs comprehensive insight into the logistics industry while simultaneously estimating its short-run and long-run effects from regional aspects due to continue-evolving factors and their impact on it. This paper competently analyzes logistics industry components in connection with economic prosperity, energy consumption, trade development, and carbon emission from a more specific regional perspective of a developing country. Methodologically, an autoregressive distributive lag model (ARDL) is employed using correlative evaluation of the dynamic factors and their interactive impact in short and long run on this relation, based on time-series data of Pakistan from 1990 to 2019. The study results endorse the previous studies’ outcomes by recognizing that an increase in carbon emission depends on trade development, energy usage, economic development, and the logistics industry’s various components except for air logistics. However, study results show a unidirectional long-run causality directing from economic development, logistics industry, energy utilization, and trade development to carbon emission. Moreover, these results reveal that this emission is the leading factor to introduce stringent emission standards that further overlap with regional demographics trends, i.e., carbon emission implications. These findings imply that economic development applies a substantial demand-pull impact on national logistics, i.e., regional economic development directs to the growth of the logistics industry in the corresponding region. Consequently, high-income geographical regions have higher long-run risk concerning contemporary developmental activities of the logistics industry when adhering to carbon emission standards. Particularly, the influence of upcoming emission standards must be prioritized when planning the future returns of contemporary research and development activities of the logistics industry in a given geographic area, such as CPEC. Given Pakistan’s perspective, the proposed empirical analysis can be exampled to other developing countries. This analysis may facilitate the design and development of strategies for upcoming financial funding in the modern logistics industry to seek its sustainable development-goals in developing economies.

The Asymmetric Impact of Oil Price Shocks on Sectoral Returns in Pakistan: Evidence from the Non-Linear ARDL Approach

This study explores the asymmetric impact of oil supply and demand shocks on the sectoral stock market returns of Pakistan. For this purpose, the study uses the non-linear autoregressive distributed lag (ARDL) approach based on monthly time series data for four sectors in the Pakistan Stock Exchange over the period 2005–2018. First, the findings of the unit root tests identified that all data series are stationary at first difference. Second, the F-bound test explored that oil supply and demand shocks have a cointegration relationship with sectoral stock market returns. Third, the study explored the asymmetric impact of oil supply shocks (OSS) and oil-specific demand shocks (OSDS) on sectoral returns of commercial banking and the symmetric impact of oil demand shocks (ODS) on sectoral returns of commercial banking. In addition, the asymmetric impact of oil supply shocks (OSS) and oil demand shocks (ODS) on sectoral returns of the power generation, chemical and fertilizer sectors was found. Moreover, the symmetric impact of oil-specific demand shocks (OSDS) on sectoral returns of the power generation, chemical and fertilizer sectors was explored. The study suggests important policy implications for policymakers and investors.

Short and Long-Run Causal Effects of CO2 Emissions, Energy Use, GDP and Population Growth: Evidence from India Using the ARDL and VECM Approaches

This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the “vector error correction” model (VECM) and “auto regressive distributed lag” (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications.

Unveiling the asymmetric impact of energy consumption on environmental mitigation in the manufacturing sector of Pakistan

The manufacturing sector is the backbone for the development of an economy. Numerous studies investigated the impact of aggregative energy consumption on environmental degradation by using typical econometric techniques. To correct this gap, our study uses energy consumption and environmental degradation only in the manufacturing sector of Pakistan for the period 1985 to 2018. Our study also demonstrates the symmetric and asymmetric behaviour of energy consumption with carbon emissions by using a recently developed methodology by Shin et al. (2014). The findings of linear autoregressive distributive lag model shows that energy consumption and financial development intensify environmental degradation, while foreign direct investment and globalization mitigate environmental degradation that leads to validate pollution halo hypotheses in Pakistan. However, non-linear autoregressive distributive lag results confirm the asymmetric behaviour of energy consumption with co₂ emission. This study recommends the policies for policymakers in Pakistan to consider asymmetric behaviour of energy consumption as well as the installation of renewable energy sources and technological improvements in the industrial sector needed to enhance environmental sustainability. Further, there is a need to enhance globalization and foreign direct investment for Pakistan to achieve its environmental targets.

The Impact of Industrialization, Trade Openness, Financial Development, and Energy Consumption on Economic Growth in Indonesia

This study aimed to scrutinize the impact of financial development, energy consumption, industrialization, and trade openness on economic growth in Indonesia over the period 1984–2018. To do so, the study employed the autoregressive distributed lag (ARDL) model to estimate the long-run and short-run nexus among the variables. Furthermore, fully modified ordinary least squares (FMOLS), dynamic least squares (DOLS), and canonical cointegrating regression (CCR) were used for a more robust examination of the empirical findings. The result of cointegration confirms the presence of cointegration among the variables. Findings from the ARDL indicate that industrialization, energy consumption, and financial development (measured by domestic credit) positively influence economic growth in the long run. However, financial development (measured by money supply) and trade openness demonstrate a negative effect on economic growth. The positive nexus among industrialization, financial development, energy consumption, and economic growth explains that these variables were stimulating growth in Indonesia. The error correction term indicates a 68% annual adjustment from any deviation in the previous period’s long-run equilibrium economic growth. These findings provide a strong testimony that industrialization and financial development are key to sustained long-run economic growth in Indonesia.

Do China's coal-to-gas policies improve regional environmental quality? A case of Beijing

Clean energy transition has been considered as an indispensable way to attain sustainable development for China, where the coal-to-gas initiative plays a vital role towards the goal. This paper takes Beijing, China's political and economic center as well as a national pioneer in the energy transition, as a case to systematically analyze the co-mitigation of air pollution (PM_2.5) and carbon emissions (CO₂) achieved by the policy-driven natural gas-coal consumption substitution. Firstly, a qualitative analysis of the relationship of Beijing's coal-to-gas policies and its air quality has been conducted. Then, VAR and ARDL models are employed to quantitatively analyze the impacts of coal-to-gas policies on PM_2.5 and CO₂, respectively. Results show that (i) an innovation of natural gas/coal consumption ratio will reduce PM_2.5 concentrations, and the effect decreases over time; and (ii) an increase of 1% in natural gas/coal consumption ratio in Beijing will cause a decrease of 0.0784% in CO₂ emissions in the long run. Therefore, the coal-to-gas policies do increase the usage of natural gas and improve Beijing's air quality. The assessment methods and conclusions can be regarded as a reference for not only China's policymakers, but also other countries, especially nowadays when air quality is becoming more valued and GHGs are being tightly controlled.

Are Tourism and Energy Consumption Linked? Evidence from Australia

Tourism contributes to the growth of an economy via earning foreign currencies and employment opportunities. However, tourism also contributes to greater energy consumption because of various tourist activities such as hotel accommodations and transportation. This study investigates the long-term cointegrating relationship between international tourist arrivals and primary energy consumption in Australia. In addition, the roles of gross domestic product, gross fixed capital formation, financial development, and total population on energy consumption are also examined. The study covered the last four decades (1976–2018) using data from the Australian Bureau of Statistics, BP Statistical Review, and the World Development Indicators. Augmented Dickey-Fuller, Phillips-Perron, Autoregressive distributed lag (ARDL) bound tests, Johansen and Juselius, Bayer-Hanck cointegration test, and several key diagnostic tests have been conducted to assess the relationship. The estimated results indicate that tourist arrivals, gross domestic product, and financial development have a significant long-run cointegrating relationship with energy consumption. Policy measures are suggested based on the findings of this study.

Exploring the Relationship between Residential CO2 Emissions, Urbanization, Economic Growth, and Residential Energy Consumption: Evidence from the North Africa Region

Rapid urbanization, coupled with income growth, will inevitably cause the residential energy consumption in the North Africa region to continue to increase, with adverse effects on the climate, human health, and the economy. In these regards, this paper explores the relationship between residential carbon dioxide emissions (RCO2), urbanization, economic growth, and residential energy use in four North African countries (Morocco, Tunisia, Algeria, and Egypt) over the period 1990–2016. To do this, we used the bounds cointegration and the Toda–Yamamoto Granger causality test. The existence of cointegration relationships was confirmed for the four countries. In the long run, the environment Kuznets curve relationship between increased income per capita and RCO2 emissions was verified for only Morocco and Tunisia. The causality analysis also reveals a combination of neutral, unidirectional, and bidirectional relationships for all countries. The RCO2 emissions have not proved to be a limiting factor in any country’s economic growth. The findings of this study certainly contribute to advancing the existing literature by emphasizing the income–pollution nexus in African countries. Policy makers and government regulators should implement the necessary policies that accelerate the development of renewable technologies to drive sustainable cooling and heating as well as water management.

An Officious Impact of Financial Innovations and ICT on Economic Evolution in China: Revealing the Substantial Role of BRI

The Belt and Road Initiative removes regional barriers and brings communities closer together. In addition, ICT and financial innovation have helped transform the world into a big village and promoted economic growth. The study assessed the dynamic impact of ICT, economic globalization, and financial innovation on China’s economic growth. The study used quarterly data from 2000 to 2019 and used the ARDL model to determine long-term and short-term consequences. The results of the study show that ICT has a positive affiliation with economic growth in China. In addition, financial innovation has also shown a direct impact on economic growth. The study shows that China’s One Belt One Road project (economic globalization) has a great positive impact on its GDP. The consequences of the causality test discovered the significant unidirectional causality running from ICT and economic globalization (ECGI) to GDP. The study recommends mandatory policies related to ICT, financial innovation, and economic globalization to achieve long-term and sustainable development in China.

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.

Inward Foreign Direct Investment-Induced Technological Innovation in Sri Lanka? Empirical Evidence Using ARDL Approach

Fostering innovation is considered one of the key policy priorities in most governments’ agendas in developing countries. Foreign direct investment (FDI) is a principal resource for financing sustainable development, corresponding to 17 sustainable development goals (SDGs). This study analyzes how inward FDI affects innovation in Sri Lanka using secondary data from 1990 to 2019. We used the Autoregressive Distributed Lag (ARDL) cointegration procedure to examine the long-run relationships between variables. As per the study results, the coefficient of inward FDI is a negative sign while the coefficients of education expenditure (EDU) and research and development expenditure (RDE) show positive signs of 0.26 and 5.7, respectively, and are statistically significant in the long run. It is demonstrated that research and development expenditure is vital in explaining technological innovation, and inward FDI inflows do not contribute to widening technological innovation in Sri Lanka. More FDI inflows will not bring higher innovation. Shaping the future of FDI in Sri Lanka is essential to foster innovation capability.