Chinese stock market integration with developed world: A portfolio diversification analysis

This study investigates integration dynamics between the Chinese stock market and major developed counterparts-Australia, Germany, Japan, the UK, and the US-focusing on portfolio diversification. Using a comprehensive analytical approach from 2012 to 2022, encompassing events like the Belt and Road Initiative, the Shanghai market crash, US-China trade tensions, and the COVID-19 pandemic, the research employs descriptive statistics, unit root tests, cointegration analysis, and VECM-based Granger Causality Tests. Findings indicate modest integration, endorsing diversified portfolios for developed country investors due to higher returns in China with acceptable risk. Unit root analysis confirms cointegration with developed indices, indicating relatively low integration. Granger Causality Tests reveal bidirectional causality, emphasizing mutual influence. Notably, no causal link exists between the US and China, possibly due to regulatory disparities and the trade war. The study enhances understanding of Chinese stock market dynamics, supporting global economic intertwining and urging further openness of China's domestic shares for economic growth.

Effects of some weather variables on the signal strength of Maloney FM radio, Nasarawa State, Nigeria

This study aims to assess the effects of atmospheric temperature, relative humidity, and atmospheric pressure on the signal strength of Maloney FM Radio, 95.9 MHz, Keffi, Nasarawa State. It is essential to measure the signal strength of the new radio station in relation with some parameters of weather to provide effective service delivery to the critical sectors and the entire populace. The research was conducted using the data of atmospheric temperature, atmospheric pressure, relative humidity, and the strength of the Maloney radio signal acquired from 6.00 a.m. to 6.00 p.m. daily at a 30 min interval, from January 2023 to June 2023, in Karshi, Abuja, a neighbouring town to Nasarawa state where the radio station is located. The data analysis involving cointegration and descriptive statistics of the effects of atmospheric variables on the radio signal strength was implemented using Eviews and Microsoft Excel Software. The results showed daily and monthly variations of the radio signal strength as well as the atmospheric temperature, atmospheric pressure and relative humidity. The variation is such that the lowest monthly signal strength was in June, probably due to higher rainfall in the area in June being the last month in this work (Jan.-Jun.) compared to other months which are dry season (January-March) or when the rain was just starting (April-May), in the study area. It was observed that atmospheric temperature and pressure negatively correlate with signal strength while relative humidity positively correlates with received signal strength in all the six months under study. The cointegration analysis also showed a long-term relationship between the radio signal strength and the atmospheric components, as the probability on the first row on the tables of both Trace Test and Maximum Eigenvalue methods were 0.0016 and 0.0008, which are less than the 5% (0.05) set critical value. In the same way, the critical value results on the same first row in both methods are smaller than the Trace statistics values. This implies that there is a long-term relationship between the atmospheric variables and the Maloney FM radio signal strength. These results will help mitigate the attenuation effect, and attendant signal loss of the radio station's signal strength. By proxy, the results will support the operations and regulations of spectrum management in the design of satellite communications and satellite microwave band specifications in Nigeria. In addition, the pre-determination of the radio station location will depend on this study's result analyses, considering that the effects of atmospheric temperature, pressure, and humidity conditions are inevitable. Governments, policymakers, stakeholders, and other relevant authorities should ensure the domestication of the study by providing the necessary research materials and facilities for wider studies. As regards the Maloney FM radio station, Keffi, studied in this work, there is no similar or related work done on it before now, hence, providing the detailed relationship between the signal strength of the radio station and some weather variables will go a long way in the improvement of the quality of signal transmission from Maloney radio station. The results when provided to the station, will enable the management to also evaluate if their set target of the station such as the radio horizon, radio signal coverage, and the link budget have been met.

Unraveling the South Asian enigma: concurrent manifestations of child anthropometric failures and their determinants in selected South Asian countries

Malnutrition among children is pervasive in South Asia and there are also reports of overnutrition. To better understand this phenomenon, we need a composite measure. However, the existing measures such as CIAF (Composite Index of Anthropometric Failure) and its revised version have ignored the overnutrition aspect of the phenomenon. This study proposes an extended version of CIAF which also considers overnutrition. This new measure was compared with the existing measures by using data from 1990 to 2018 for three selected South Asian countries including Pakistan, India and Bangladesh. We also examined the effects of socioeconomic and environmental variables on the outcome variable. The results reveal that the new measure (ECIAF) is better at measuring the phenomena. The burden of overall malnutrition has been decreased in the region. However, an increase in the concomitant prevalence of wasting and underweight is observed in both Pakistan and India and stunting and overweight is observed only in India. Besides, political stability, prevalence of undernourishment, anemia in children, mother's education, household size, dependency ratio, air pollution and unimproved sanitation are significantly correlated with childhood malnutrition. The findings also testified to long-run cointegrating relationship among the variables.

Is fiscal deficit 'curse' or 'haven' for environmental quality in India? Empirical investigation employing battery of distinct ARDL approaches

Undoubtedly, throughout the past half-century, environmental quality has emerged as a significant obstacle to both economic and social endeavors. Recent local and international policy debates have focused on environmental deterioration and global warming, but how governments balance economic growth and environmental sustainability is still enigmatic. For this reason, we have examined the determinants of environmental quality in India from 1972 to 2021. More specifically, we have investigated whether the fiscal deficit is 'curse' or 'haven' for environmental quality (CO2) in India. Moreover, this study deliberated four other predictors, comprising technological development (TIN), fossil fuel consumption (FFC), urbanization (Ub), and human capital index (HCI). In order to attain this objective, a range of econometric estimation techniques are employed to ensure the validity and reliability of the outcomes. For instance, we have employed a battery of ARDL approaches, such as standard ARDL, nonlinear ARDL, and multiple threshold NARDL approaches. In light of our research findings, we will be focusing directly on the examination of the NARDL and MTNARDL outcomes. This is due to the empirical evidence indicating the existence of asymmetric effects resulting from FD on CO2 emissions in India. The NARDL approach reveals that the consequence of fiscal deterioration is more pronounced, and the influence of fiscal progress is mild in terms of CO2 emission growth. Further, the outcomes of the MTNARDL approach revealed that the size of the extremely low changes in FD is much higher than the extremely high changes in FD in both models. This implies that as the FD rises, CO2 ascends more significantly, and when the FD lowers, CO2 declines progressively. In a nutshell, FD has a long-run positive and asymmetric impact on CO2 in India; thus, we may conclude that FD is considered the 'curse' for CO2 in India. Furthermore, TIN, HCI, and Ub have detrimental effects on CO2, whereas FFC stimulates CO2 in India. This research work provides some important policy implications for environmentalists, economists and macroeconomic policymakers to promote a green and healthy environment.

Reconsidering the relationship between health and income in the UK

The present paper revisits and extends the examination of the long-run relationship between UK life expectancy and income provided by Tapia Granados (2012). Adopting a more detailed form of analysis, a clear break corresponding to the 1918-1919 Influenza Pandemic is identified in the long span of data examined. This finding of structural change, along with detected uncertainty regarding the orders of integration of the series examined, results in the application of split-sample analysis employing autoregressive distributed lag (ARDL) modelling. The results obtained reverse the 'no long-run relationship' conclusion of Tapia Granados (2012) with overwhelming evidence presented in support of a negative relationship between life expectancy and income. Our findings add to both health-income research and a burgeoning literature on the reproduction and replication of previously published empirical research.

How does economic complexity improve energy efficiency? Mechanism discussion and empirical test

Energy efficiency represents one of the best productive strategies to lessen the effects of global warming and climate change. Similarly, the manufacturing and export of a wide variety of high-tech, knowledge-based items like chemicals and machinery have significant effects on both economic growth and the environment. The main goal of this study is to examine the long-run effects of economic complexity on energy efficiency in 93 countries over the period from 1995 to 2015. The empirical outcomes reveal that economic complexity improves energy efficiency. Specifically, countries that produce and export a wide range of sophisticated products tend to enjoy higher levels of energy efficiency compared to their counterparts who export a limited range of simple products. Moreover, empirical findings suggest that economic growth and population density increase energy efficiency, while trade impedes it. Further empirical investigations from a mediation analysis revealed that about 63% and 38% of the effects of economic complexity on energy efficiency mediate through income inequality reduction and human capital accumulation, respectively. Based on these results, political leaders and governments are provided with solid reasons to pay more attention to improving their productive structures in order to promote energy efficiency and a green future.

Identifying the nexus among environmental performance, digital finance, and green innovation: New evidence from prefecture-level cities in China

Globally, nations are increasingly focusing on green innovation in their environmental protection efforts as part of sustainable development, and digital finance is playing a vital role in enhancing green innovation. Employing annual data from 220 prefecture-level cities between 2011 and 2019, we empirically analyze the connections among environmental performance, digital finance, and green innovation via the Karavias panel unit root test with structural breaks, the Gregory-Hansen structural break cointegration test and pooled mean group (PMG) estimation. The following four points are the key conclusions: (1) The results support cointegration links between these variables when structural breaks are considered. (2) The PMG estimation outcomes indicate that green innovation and digital finance may have a favorable long-term effect on environmental performance. (3) For better environmental performance and more green innovation, the level of digitalization of digital finance is crucial. (4) The potential of digital finance and green innovation to improve environmental performance has not been fully realized in the western region of China.

Aggregated imports and expenditure components in Bangladesh: A cointegration and equilibrium correction analysis

Even though there have been a few studies on Bangladesh's aggregate import demand, the effects of the global financial crisis (GFC) on aggregate import demand still need to be measured. The short-run determinants of import demand also remained to be identified in the country. This paper explores both short-run dynamic and long-run cointegrating relationships, capturing the impact of the GFC on aggregate import demand. This study uses annual data from 1980 to 2021 (N = 42) and employs different econometric techniques for efficient results essential for compelling policy implications. The study derives an efficient dynamic equation using the best error correction mechanism. Additionally, this study includes unconventional determinants, namely, foreign currency reserves and components of expenditure (i.e., exports, private consumption and government expenditures, and expenditures on investment goods), along with the traditional import demand function. The study finds that all conventional and unconventional determinants of import demand are significant in both the long and short run. All determinants except relative price positively influence the volume of import demand. The income elasticity reduces over time, and the price inelasticity remains non-zero and negative, which indicates the competitiveness of domestic product substitutes for importable goods in the economy. In the long run, trade liberalization and foreign currency reserves have a limited positive influence on import demand. The findings of this study would be helpful for import-related policy implications in the country.

Deficit sustainability and fiscal theory of price level: the case of Italy, 1861-2020

We test sustainability of the Italian government deficit over the period 1861-2020 using the fiscal theory of the price level (FTPL). This approach takes into account monetary and fiscal policy interactions and assumes that fiscal policy may determine the price level even if monetary authorities pursue an inflation-targeting strategy. We consider a cointegrated model with multiple structural changes to characterize the sustainability of public finances and the prevalence of monetary or fiscal dominance during subperiods. We also use recursive unit root tests for explosiveness to test fiscal sustainability and to detect episodes of potential explosive behaviour in Italian public debt. We find two structural changes for the public debt and one change in the primary budget surplus, the alternation of monetary and fiscal dominant regimes, as well as evidence of bubbles related to three episodes of the Italian fiscal performance. Our results reveal the sensitiveness of the primary balance and the debt paths to shocks hitting fiscal, macroeconomic, and financial variables.

Environmental impact of globalization: The case of central and Eastern European emerging economies

Against the backdrop of piling environmental concerns in the modern era of globalization, this study aims to check the validity of the Pollution Haven Hypothesis (PHH) in Eastern European emerging countries and the relevance of globalization. The study targets to reduce the lack of consensus on the globalization-economic complexity-environment in European countries. Besides, we also intend to explore the existence of an N-shaped economic complexity-related Environmental Kuznets Curve (EKC) controlling for the bearing of renewable energy on environmental degradation. For analytical purposes, both parametric and non-parametric quantile regression approaches are employed. Overall, we find a non-linear relationship between economic complexity and carbon emissions, and N-shaped EKC is verified. Globalization and renewable energy consumption boost and inhibit emissions, respectively. More importantly, the results confirm the moderating role of economic complexity in neutralizing the carbon emissions-boosting effect of globalization. On the other hand, the non-parametric findings show that the N-shaped EKC hypothesis does not hold for high emissions quantiles. Furthermore, for all emissions quantiles, it is found that globalization boosts emissions, economic complexity, and globalization jointly curbs emissions and renewable energy curbs emissions. Based on the overall findings, some vital environmental development policies are recommended. The conclusions support shaping policy options promoting economic complexity and renewable energy as key factors in mitigating carbon emissions.

Does unionization reduce CO2 emissions in Canada?

The existing literature is ambivalent on the relationship between unionization and climate change. There is some anecdotal evidence that in some cases, labor unions play a role in implementing climate protection measures. In other cases, unions were more concerned with saving jobs than with reducing emissions. Nonetheless, empirical studies on the relationship between unions and environmental outcomes are limited. The objective of this study is to fill the gap in the literature by examining if unionization has any impact on CO₂ emissions in Canada, after controlling for energy consumption, unemployment rate, and real GDP per capita. Cointegration techniques including Johansen methods and autoregressive distributed lag (ARDL) techniques are applied to a dataset that covers the period from 1969 to 2016. The results suggest that, on average, a 1% increase in unionization reduces CO₂ emissions by approximately 0.25%. This is the first study that examines the union-climate dynamics for Canada. One policy implication of the finding is that the governments should develop incentives for industries to implement climate measures through collective bargaining.

Can fiscal decentralization be the route to the race to zero emissions in South Africa? Fresh policy insights from novel dynamic autoregressive distributed lag simulations approach

There has been a plethora of debate on the link between fiscal decentralization and a drop in carbon dioxide (CO2) emissions, even though the evidence supporting this assertion is relatively sparse. Although the precise nature of this relationship is still up for discussion, economic hypothesis postulates that fiscal decentralization has an impact on environmental sustainability. Some researchers claim that fiscal decentralization could potentially result in a race to the top, while some believe it would lead to a race to the bottom. This analysis intends to shed light on the precise processes by which this connection may work in South Africa between 1960 and 2020 in light of current discussions in environmental and development economics. In contrary to previous studies, this paper employs a cutting-edge dynamic autoregressive distributed lag simulations methodology to evaluate the positive and negative variations in fiscal decentralization on CO2 emissions. Our findings demonstrate the prevalence of the race to the top strategy by illustrating how fiscal decentralization has a bearing on CO2 emissions reduction in the short and long terms. In accordance with the findings, greater fiscal decentralization should be implemented through the transfer of more powers to regional authorities, especially in the realm of environmental legislation considerations, in a bid to preserve South Africa's environmental integrity. By establishing a lower tier of government and defining roles at the federal and provincial divisions, South Africa could adopt strategies to improve green environment in an effort to fulfill the energy-saving tasks of fiscal expenditures.

Revisiting the impact of renewable energy consumption on economic growth: sectoral evidence from the USA

The aim of this study is to investigate the relationship between sectoral renewable energy consumption and economic growth in the US economy for the period 1950-2020 by using the Fourier component augmented unit root, cointegration, and causality analyses for the transportation, industrial, residential, electric power, and commercial sectors. Our results reveal in the long run that renewable energy will Granger cause growth through the new jobs it will create, the restructuring of the economy which is a prerequisite for replacing fossil energy with renewable energy. On the other hand, causal relationships are less stable and methodology and sector specific in the short run. Accordingly, the electric power and industrial sectors experience conservation patterns in terms of renewable energy consumption, while the growth hypothesis is confirmed for the commercial sector. Different implications are generated for each sector, which are now more important than ever given the current energy crisis in Europe and the urgent need to reduce dependence on fossil fuels.

Revisiting the nexus between fiscal decentralization and CO2 emissions in South Africa: fresh policy insights

The argument over fiscal decentralization and carbon dioxide emission (CO₂) reduction has received much attention. However, evidence to back this claim is limited. Economic theory predicts that fiscal decentralization affects environmental quality, but the specifics of this relationship are still up for debate. Some scholars noted that fiscal decentralization might lead to a race to the top, whereas others contended that it would result in a race to the bottom. In light of the current debates in environmental and development economics, this study aims to provide insight into how this relationship may function in South Africa from 1960 to 2020. In contrast to the existing research, the present study uses a novel dynamic autoregressive distributed lag simulation approach to assess the positive and negative changes in fiscal decentralization, scale effect, technique effect, technological innovation, foreign direct investment, energy consumption, industrial growth, and trade openness on CO₂ emissions. The following are the main findings: (i) Fiscal decentralization had a CO₂ emission reduction impact in the short and long run, highlighting the presence of the race to the top approach. (ii) Economic growth (as represented by the scale effect) eroded ecological integrity. However, its square (as expressed by technique effect) aided in strengthening ecological protection, validating the environmental Kuznets curve hypothesis. (iii) CO₂ emissions were driven by energy utilization, trade openness, industrial value-added, and foreign direct investment, whereas technological innovation boosted ecological integrity. Findings suggest that further fiscal decentralization should be undertaken through further devolution of power to local entities, particularly regarding environmental policy issues, to maintain South Africa's ecological sustainability. South Africa should also establish policies to improve environmental sustainability by strengthening a lower layer of government and clarifying responsibilities at the national and local levels to fulfill the energy-saving functions of fiscal expenditures.

From Heroes to Scoundrels: Exploring the effects of online campaigns celebrating frontline workers on COVID-19 outcomes

This paper examines the effects of online campaigns celebrating frontline workers on COVID-19 outcomes regarding new cases, deaths, and vaccinations, using the United Kingdom as a case study. We implement text and sentiment analysis on Twitter data and feed the result into random regression forests and cointegration analysis. Our combined machine learning and econometric approach shows very weak effects of both the volume and the sentiment of Twitter discussions on new cases, deaths, and vaccinations. On the other hand, established relationships (such as between stringency measures and cases/deaths and between vaccinations and deaths) are confirmed. On the contrary, we find adverse lagged effects from negative sentiment to vaccinations and from new cases to negative sentiment posts. As we assess the knowledge acquired from the COVID-19 crisis, our findings can be used by policy makers, particularly in public health, and prepare for the next pandemic.

Coal mining and environmental sustainability in South Africa: do institutions matter?

This study investigates the effects of coal mining on environmental sustainability in South Africa in relation to the moderating role of institutions. To achieve the study's objectives, the fully modified least square (FMOLS), dynamic least squares (DOLS), canonical cointegrating regression (CCR), Bayer-Hanck cointegration and Toda-Yamamoto causality test are employed for the period 1984-2018. Results from the study show that coal mining contributes to environmental degradation in South Africa, while its interaction with institutional quality mitigates the severity of this negative impact. Furthermore, there is evidence that economic growth has a bidirectional causality with ecological footprint and coal mining, while institutional quality also Granger causes ecological footprint. To promote a sustainable environment, there is a need for the government and the institutions to form the foundation for the shift toward environmental sustainability, with particular attention paid to the development and implementation of greenhouse policy.

Does information and communication technologies affect economic complexity?

Information and communication technology (ICT) and economic complexity are two concepts that have been extensively used in the recent literature. However, studies linking these two concepts are still at a premature stage and few existing studies have focussed on the role of the internet in a short-term context. Indeed, ICT measures the percentage of the population with access to the internet while economic complexity quantifies the set of productive capabilities and know-how embedded in the production process. This study aims to examine for the first time the long-term effect of ICT (quality and quantity) on economic complexity in a large panel of 112 countries over the period 1986-2017. The detailed analysis explores the long run and directional relationships using the homogeneity test, the cross-sectional dependence test, stationary tests in the presence of cross-sectional dependence, the panel cointegration test, dynamic OLS (DOLS), fully modified OLS (FMOLS), and the Granger panel causality test. The study finds long-run relationships between ICT, economic complexity, per capita GDP, government spending, and natural resources. Cointegration regression shows that the quality and especially the quantity of ICT, economic growth, and government spending have a positive and significant effect on economic complexity in the long run. Similarly, the results show that natural resource rent significantly impedes economic complexity. Finally, the results of the Granger causality test confirm the existence of a bidirectional relationship between ICT and economic complexity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43546-023-00467-8.

Assessing the impact of climate change on the agricultural economy in Thailand: an empirical study using panel data analysis

This study estimates the impact of climate change on the economic growth of the agricultural sector and its variability using a panel dataset from 1995 to 2019 for 76 provinces in Thailand. The panel data analysis consists of unit root tests for identifying stationary characteristics, autoregressive distributed lag (ARDL) bounds for analyzing cointegration, and pool mean group (PMG) estimation for detecting long-run and short-run effects. The cointegration results indicate the existence of long-run equilibrium in the agricultural economy and its variability to climatic and non-climatic variables. Results from the PMG estimation suggest that extreme weather events have a negative impact on the agricultural economy, but increased total rainfall has a positive association with the agricultural economy. The increases in mean average and mean minimum temperatures will reduce the variability of agricultural growth. The obtained results suggest that the productivity of agricultural households and water resources increases the agricultural revenue and reduces its variability for long-term development in the agricultural sector of Thailand.

Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

South Africa, one of the emerging markets and fast-developing economies in Sub-Saharan Africa recognised for varying world's natural assets on the international market, has recorded significant economic growth in the previous several years. However, aside from the ecological repercussions of energy generation, how economic uncertainties moderate the effects of energy intensity, renewable and non-renewable energy usage, and economic complexity on the environment has largely gone unnoticed. As a result, this paper addresses an important empirical vacuum by exploring the moderating influence of economic policy uncertainty in the environmental Kuznets curve for South Africa from 1960 to 2020. Results from the novel dynamic autoregressive distributed lag simulations framework reveal the following key findings: (i) economic policy uncertainty accelerates environmental degradation in both the short and long run; (ii) economic growth (as measured by the scale effect) increases environmental degradation, whereas the square of economic growth (as measured by the technique effect) slows it down, confirming the presence of the environmental Kuznets curve (EKC) hypothesis; (iii) environmental quality is deteriorated by energy intensity, economic complexity, non-renewable energy usage, and trade openness; (iv) the use of renewable energy and technological innovation increase environmental quality; (v) whereas the moderating effects of economic policy uncertainty on the environmental impacts of energy intensity, renewable and non-renewable energy consumption result in an increase in environmental destruction, its moderating effect on environmental implication of economic complexity plays an important role in improving environmental quality. These findings permit us to draw important policy recommendations for South Africa for improving environmental quality.

Labour market uncertainty after the irruption of COVID-19

This paper examines the evolution of labour market uncertainty after the irruption of the COVID-19 pandemic in European countries. Since uncertainty is not directly observable, we use two alternative methods to directly approximate it. Both approaches are based on qualitative expectations elicited form the consumer survey conducted by the European Commission. On the one hand, following (Dibiasi and Iselin in Empir Econ 61:2113-2141, 2021), we use the share of consumers unable to formalise expectations about unemployment (Knightian-type uncertainty). On the other, we use the geometric discrepancy indicator proposed by (Claveria in Empirica 48:483-505, 2021) to quantify the proportion of disagreement in business and consumer expectations. We find that both uncertainty measures covary across the 22 European countries analysed. Although we observe differences in the evolution across countries, in most cases the perception of labour market uncertainty peaked before the outbreak of the crisis, plummeted during the first months of the lockdown, and started rising again. When testing for cointegration with the unemployment rate, we find that both indicators exhibit a long-term relationship with unemployment in most countries. The impact of both indicators on unemployment is characterised by considerable asymmetries, showing a more intense reaction to decreases in the level of labour market uncertainty. While this finding may seem counterintuitive at first sight, it somehow reflects the fact that during recessive periods, the level of disagreement in consumer unemployment expectations drops considerably.

The Effect of Paid Maternity Leave on Child Health in the Middle East and North Africa

Background: The paid maternity leave is one of the factors affecting the health status of children, but this maternity leave in the Middle East and North Africa is not only less than in developed countries but also the mortality rate of children under 5 years is higher in these countries. Therefore, this study was conducted to investigate the paid maternity leave on children's health in the Middle East and North Africa. Methods: This descriptive-analytical and applied study was conducted by Panel data regression method with cross-sectional dependence and Common Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators for 2000 and 2019. The statistical population was 12 countries in the Middle East and North Africa, and annual time series data were extracted from World Bank databases. The study models, cross-sectional dependency tests, Pesaran unit root, Westerlund cointegration, and other required tests were estimated in Stata 16 software. Results: The average paid maternity leave for 12 countries in the Middle East and North African countries between 2000 and 2019 was 68.8 days, and in 2019, it was 78 days. The effect of maternity leave on infant mortality rate in the Augmented Mean Group and Common Correlated Effect Mean Group were -0.0018 and -0.0006, respectively, and, the effect on the under-5 mortality rate in the mentioned methods was -0.0023 and -0.0007, respectively. The coefficient of female labor force participation rate on infant mortality rate was -0.056 and the under-5 mortality rate was -0.049. Conclusion: Increasing maternity leave had a negative effect on infant and child mortality rates. Also, health expenditures and female labor force participation rates had a negative effect, and carbon dioxide production had a positive effect on infant mortality rates; therefore, policies to increase paid maternity leave for mothers, as well as policies to increase maternal employment, are proposed to increase fertility while increasing the health of infants.

Is there a trade-off between ICTs and ecological systems in Africa? Evidence from heterogeneous panel methods robust to cross-sectional dependence

Among the UN's 17 Sustainable Development Goals (SDGs), increasing infrastructure resilience (SDG₉) and combating climate change and its impacts (SDG₁₃) have been vital goals. Growing evidence supports the presence of a trade-off between expanding information and communication technologies (ICT) infrastructure and maintaining the quality of the environment. Based on an ICT index and the ecological footprint, the present study reinvestigated the influence of ICT on environmental quality for a sample of African countries, where ICT services have substantially increased over the past decades. The study employed cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and common correlated effects estimator (CCEMG) techniques on data representing 47 African economies between 1990 and 2017. The results of both methods were consistent and indicated an inverted U-shaped relationship between ICT infrastructure and environmental quality in the long and short run. The findings suggested that the expansion of ICT infrastructure could simultaneously enable African nations to achieve SDG13 and SDG9.

Do financial development and industrialization intensify energy consumption in Turkey?

This study examines the inverted U-shape relationship between financial development and energy intensity for Turkish economy. To this end, ARDL model has been employed to estimate the short-run and long-run coefficients. The Bayer and Hanck (2013) combined cointegration technique and ARDL bounds testing were employed to examine the cointegration association among investigated variables using annual data from 1976 to 2016. The statistically significant and inverted U-shaped association was affirmed between financial development and energy intensity in Turkey. The results also show that financial development has positive and significant effect on energy intensity. The result of Hacker and Hatemi-J (2012) leveraged bootstrap causality test reveals the unidirectional relationship running from financial development to energy intensity in Turkey. However, the feedback causal effect was found between industrialization and energy intensity. Further insights into causal relationship and policy implications are provided in the Conclusion section.

Does trade openness mitigate the environmental degradation in South Africa?

The debate over the role international trade plays in determining environmental outcomes has considerably generated more heat than light. Theoretical work has been successful in identifying a series of hypotheses linking openness to trade and environmental quality, but the empirical verification of these hypotheses has seriously lagged. This study revisits the dynamic relationship between trade openness and environmental quality in South Africa using time series data over the period 1960-2020. The recently developed novel dynamic autoregressive distributed lag (ARDL) simulation framework has been used. The outcomes of the analysis indicate that (i) trade openness deteriorates environmental quality in the long run, although it is environmentally friendly in the short run; (ii) the scale effect increases CO₂ emissions, whereas the technique effect contributes to lower it, thus validating the presence of an environmental Kuznets curve (EKC) hypothesis; (iii) energy consumption, foreign direct investment, and industrial value-added contribute to environmental deterioration; (iv) technological innovation improves environmental quality; (v) the pollution haven hypothesis (PHH) exists; and (vi) InSE, InTE, InOPEN, InEC, InFDI, InTECH, and InIGDP Granger-cause InCO₂ in the medium, long, and short run suggesting that these variables are important to influence CO₂ emissions. In light of our empirical evidence, this paper suggests that the international teamwork to lessen carbon emissions is immensely critical to solve the growing trans-boundary environmental decay and other associated spillover consequences.

Energy intensity determinants based on structure-oriented cointegration by embedding a knowledge box in a time series model: evidence from Iran

Energy intensity reduction is an exigent issue for Iran, where energy consumption is so high. Therefore, finding effective policies to reduce energy intensity is essential. With this in mind, the impact of financial development, government investment, oil revenues, and trade openness on energy intensity is assessed in this study. We combined structural vector error correction model (SVECM) and directed acyclic graphs (DAG) technique to examine the relationships between study variables. The results of DAG prove that financial development, government investment, oil revenues, and trade openness influence the intensity of energy. Besides, the significant and long-run relationships among variables allowed us to apply SVECM. Impulse response functions and variance decomposition analysis indicate that government investment, oil revenues, and trade openness are negatively associated with the intensity of energy. Also, financial development positively influences energy intensity. Meanwhile, the impact of government investment is more significant than oil revenues, trade openness, and financial development impacts. So, government investment is the most effective policy regarding optimizing the consumption of energy and reducing energy intensity. We also advise policymakers to use oil revenues to increase government investment, enhance trade openness, and tax the private sector to improve the level of energy intensity.

Income inequality and environmental degradation in Egypt: evidence from dynamic ARDL approach

Over the past four decades, the Egyptian economy has suffered from both income inequality and environmental degradation. This dual problem raises the question about the nature of the relationship between inequality and the environment in a developing country like Egypt. In this regard, the study aims to examine the impact of income inequality on carbon emissions during the period 1975-2017. The analysis considers the ability of the political economy approach compared to the Keynesian trade-off approach to explain the inequality-environment relationship in Egypt. To do this, the novel dynamic autoregressive distributed lags approach is employed to capture the short-run and long-run relationships and to overcome the complications associated with the structure of the widely used autoregressive distributive lags model. The findings show that the relationship between inequality and CO₂ emissions is not a trade-off. Rather, inequality leads to environmental deterioration in the long run, but there is no significant effect in the short run. In the long run, a 1% rise in the Gini coefficient increases CO₂ emissions by 2.28%. These results support the political economy approach in explaining the inequality-environment nexus. Hence, the economic development policies adopted in Egypt during the past four decades have led to a negative impact on the environment. The study advises economic policy makers in Egypt to adopt income redistribution policies to reduce the severity of income inequality. Improving income distribution has a positive effect on the environment in Egypt.

The ever-evolving trade pattern: a global VAR approach

This paper focuses on the spillover dynamics of shocks originating in China during the last two decades. More specifically, the paper compares the effects of a shock to China's GDP and exchange rate using early 2000s trade patterns with those of two decades later. We use a global vector autoregressive (GVAR) model as it allows to consider trade interactions as well as financial linkages through interest rates, stock prices, and exchange rates. Our results indicate that the shock spillovers from China have become more pronounced over the past two decades. While the world has become more exposed to China's economy, it has become more susceptible to Chinese economic shocks. This paper contributes to the literature by evaluating the dynamics of China's spillover effects and highlights the structural changes in trade between major global trade players.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00181-021-02182-5.

The dynamic linkages among outbound tourism, economic growth, and international trade: empirical evidence from China

The aim of this research was to examine the long- and short-run relationships among real expenditures on outbound tourism from China, economic growth and international trade for the period of 1995 to 2018, applying a newly developed cointegration test—the Bootstrap Autoregressive Distributed Lag framework. Evidence of cointegration was found when expenditures on outbound tourism served as the dependent variable, and economic growth and international trade were important factors affecting outbound tourism from China. For the short-run, a two-way Granger causality relationship was detected between economic growth and outbound tourism expenditures, and the feedback was confirmed between outbound tourism expenditures and international trade. The findings have important policy implications for the growth of the outbound tourism market. Large volumes of outbound tourists result in economic losses for China and outbound tourism reduces the growth of tourism-driven international trade.

Fossil fuels consumption and carbon dioxide emissions in G7 countries: Empirical evidence from ARDL bounds testing approach

This research determines the intertemporal relationships caused by the coal, oil, and natural gas consumption in the carbon dioxide emission by the G7 countries from 1965 to 2018. Auto-regressive and Distributed Lags models and Bound test were used to detect cointegration and understand the dynamic effect. Due to structural breaks occurred in the variables, two dummy variables for the periods of breaks, 1978 and 1990 were incorporated respectively. Positive causality was identified, in the sense that the consumption of fossil fuels provides an increase in carbon dioxide emissions. Short-term elasticities indicate that an increase of 1 percentage point in the consumption of oil, coal, and natural gas will cause, respectively, an increase of 0.4823%, 0.3140%, and 0.1717% in carbon dioxide emissions. In the long run, the increase of 1 percentage point in the consumption of oil, coal, and natural gas will cause, respectively, an increase of 0.4924%, 0.2692%, and 0.1829% in carbon dioxide emissions. The error correction model (ECM = -0.4739) indicates that 47.39% of a shock in the carbon dioxide emissions variable is resolved in one year and after 2 years, carbon dioxide emissions return to long term equilibrium.

Industrial growth, clean energy generation, and pollution: evidence from top ten industrial countries

Unlike the previous study, this paper employs panel cointegration and Granger causation approaches to discuss the associations among carbon dioxide (CO₂) emissions, GDP growth, clean energy generation, and industrial growth for the top ten industrial countries spanning the period 1980-2014. The primary empirical outcomes show a two-way long-run association between environmental indicator, GDP growth, and clean energy generation, while one short-run causation from clean energy generation to CO₂ emissions and from industrial growth to clean energy generation. The computed coefficients elasticity's under FMOLS, DOLS, and CCR estimates revealed that the clean energy generation statistically contributes to declining emissions of CO₂ in Australia, Austria, and Chile while statistically increase emissions of CO₂ in Denmark and the Netherlands. Industrial growth statistically contributes to reducing emissions of CO₂ in Denmark and Norway but increases emissions in Chile, France, and Sweden. For the global panel, industrial growth leads to mitigate the rate of emissions while clean energy generation raises CO₂ emissions in the long period. Investing in clean energy is needed to stimulate the growth of the industrial sector and then reduce the rate of emissions.

Can renewable energy be used as an effective tool in the decarbonization of the Mediterranean region: fresh evidence under cross-sectional dependence

Many studies in the literature confirm the validity of the technique effect, which improves the quality of the environment by investigating whether an inverted U-shaped relationship exists between environmental pollution and economic growth. Ignoring the role of the technological obsolescence effect, which may also exert influence on an economy, these studies reach an optimistic conclusion for growth policies. By controlling renewable energy, this study examines the existence of the obsolescence effect by constructing an N-shaped relationship between economic growth and environmental degradation for the most vulnerable countries in the Mediterranean region to climate change. We conducted a battery of cross-sectional dependence tests, second-generation panel unit root, and cointegration tests in 17 selected Mediterranean countries covering 1990-2017. The results provide evidence of an N-shaped relationship between economic growth and environmental degradation. The study provides important policy recommendations and discusses how renewable energy can be deployed to reduce CO₂ emissions.

The dynamic role of institutional quality, renewable and non-renewable energy on the ecological footprint of OECD countries: do institutions and renewables function as leverage points for environmental sustainability?

This article examines for the first time the impact of disaggregated energy sources and institutional quality on the ecological footprint (EF) of 29 OECD countries, by explaining how the diversification in countries' energy mix and their institutional performance are associated with sustainable environmental performance. We use panel data from 1984 to 2016 and we apply second-generation techniques to arrange the critical issues of cross-sectional dependence and heterogeneity. The applied cointegration tests expose a long-run equilibrium relationship that associates renewable/non-renewable energy consumption, economic growth, institutional quality, and the EF of OECD countries. The robust cross-sectional augmented distributed lag (CS-DL) estimator shows that economic growth and the adoption of non-renewable energies are detrimental to the environment, while the operational quality of institutions adds to ecological sustainability. Concurrently, the negative effect of renewables on EF does not seem to cause a significant beneficial impact on the environment. Moreover, there is evidence that non-renewable energy and institutional quality have a bidirectional causal association with EF. Also, a weak unidirectional causal effect is running from the EF to renewables consumption. The study further demonstrates the inefficient integration of renewable energy forms in OECD countries and the concomitant essential role of institutions on environmental sustainability by providing relevant policy orientations.

Methods for testing the income-health relative hypothesis that the distribution of income in a society affects the distribution of health

Health and income relation analysis has been the subject of controversies on the absolute income hypothesis (the higher an individual's income, the better their health status) and the relative income hypothesis (individual health is affected by the distribution of income within society). In addition, the assumed relationship has been criticised as being a statistical artefact. To overcome these issues, we formulate the hypothesis that the distribution of health in a society is correlated with the distribution of income in that society and propose the analytical method framework. The method is focused on the calculation of Foster–Greer–Thorbecke (FGT) poverty indices using health and income outcomes. Econometric time series methods, particularly the autoregressive distributed lag (ARDL) cointegration bounds test and dynamic simulation, are complementary tools used to measure the relationship between the calculated indices. Applied to the sub-sample of countries below the poverty line, the method highlights the correlation between the gaps and inequalities in health outcomes and the gaps and inequalities in income outcomes, respectively.

• The Foster–Greer–Thorbecke (FGT) poverty indices are applied to income and health outcomes.

• Aggregate poverty indices are measured across states.

• These indices are meaningful indicators for analysing the link between the distribution of health and the distribution of income in a society.

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.

Investigating the dynamic linkages among carbon dioxide emissions, economic growth, and renewable and non-renewable energy consumption: evidence from developing countries

This research paper examines the causal relationships among carbon dioxide emissions, economic growth, and renewable and non-renewable energy consumption, for a panel of 68 developing countries over the period 1990 - 2014. We use the multivariate panel cointegration framework and apply a battery of conventional (Pedroni 1999, 2004; and Kao 1999) as well as newly developed methodologies accounting for heterogeneity and cross-sectional correlation (Westerlund's ECM panel cointegration (2007) and panel bootstrap cointegration (2007) tests). The pooled mean group (PMG), mean group (MG), and dynamic fixed effects (DFE) methodologies were further applied to trace out the short-run dynamics. The results support evidence of significant dynamic linkages among the involved variables and reveal possible differences in the magnitude of the impacts from renewable and non-renewable energy consumption on environmental quality. The issue of distinguishing by source and determining the magnitude of the detected effects could provide valuable information for a sustainable economic and environmental development, substantially helping policy makers to designate more efficient policy measures.

Environmental Kuznets curve in the presence of structural breaks: new evidence for individual European Countries

This study explores the relationships between carbon emissions and their main determinants such as energy consumption, real income and international trade, in 15 European countries, employing data for the period 1960-2015, and in Germany, for that of 1970-2015. The purpose of this paper is to examine the environmental Kuznets curve in subregimes in the presence of structural shifts. Two complementary unit root tests are employed to examine the stationarity of employed variables. The Ng and Perron Econometrica 69: 1519-1554 (2001) and the Zivot and Andrews J Bus Econ Stat, 10(3), 251-270 (1992) unit root tests, both allow for a structural break. To estimate the parameters of the regression model and to detect structural breaks in the model, the Kejriwal and Perron J Econ, 146(1), 59-73, (2008), J Bus Econ Stat, 28(4), 503-522, (2010a), J Time Ser Anal, 31, 305-328, (2010b)) structural break test is employed. When structural breaks are allowed in estimations, the empirical results provide strong evidence of fluctuating relationships between CO2 emissions and income expressed by the U-shape in every subregime, which contradicts early findings in the literature of inverse U-shape environmental Kuznets curve.

Degree of sustainability of current account: evidence from Côte d'Ivoire using a non-linear approach

The current account deficit is a macroeconomic indicator that provides information on the health of an economy. Its sustainability is particularly crucial for developing countries such as Côte d'Ivoire, one of the largest economies in West Africa. Given the country's exposure to external vulnerability, this paper analysed the degree of sustainability of its current account. Beyond this, the study looked at the resilience of the economy to external shocks by examining how exports behave following an asymmetric shock on imports plus interest on external borrowing. To this end, the model developed by Shin et al. (2014) was applied to the intertemporal approach to current account sustainability using quarterly macroeconomic data from 1985q1 to 2017q4. The study found that Côte d'Ivoire's current account balance is sustainable. However, this sustainability is weak in the sense of Hakkio and Rush (1991), thus leading to a high risk of government failure in this respect. Also, the study shows that exports react differently to asymmetric shocks on increased imports, with a return to equilibrium often very slow. Therefore, the strengthening and stability of the socio-political environment is to be encouraged, as well as the implementation of policies aimed at sound public finance management and minimising the economy's vulnerability to external shocks.

Environmental pollution of China to foreign investors: detrimental or beneficial?

This study investigates the dynamic linkage among foreign direct investment, energy consumption, and environmental pollution of China spanning from 1990 to 2014. Despite the extant literature on the FDI-energy-growth-environmental pollution nexus, most of the conclusion seems inconsistent. Hence, this study utilized recent econometric techniques such as the dynamic ordinary least square (DOLS), autoregressive distributed lag (ARDL) bounds test approach, Gregory and Hansen structural cointegration, and the bootstrap Granger causality. The study also disaggregated energy consumption into various sources to identify their respective distinct impact on the environment. Our study confirmed the presence of the EKC curve for China in a quadratic equation applying the DOLS. The result of the bootstrapped Granger causality confirmed the presence of a unidirectional Granger causality running from CO₂ emission to economic growth and export; non-renewable energy to economic growth, export to economic growth, and renewable energy; and urbanization to economic growth. Moreover, our study recognized the presence of a bi-directional connection between FDI and economic growth. Our study highly recommends that China modify its energy mix by incorporating more renewable energy resources such as hydro, wind, geothermal. Additionally, the regulatory bodies should strictly implement improved energy efficiency in the various sectors that complement total proper urban land usage as the urban population to total population significantly impelled an upsurge in environmental deterioration in China.

Small and medium-sized enterprises and economic growth in Pakistan: An ARDL bounds cointegration approach

This study examines the relationships between small and medium-sized enterprises (SMEs) and economic growth in Pakistan from 1990 to 2019. It focuses on SMEs and the other factors responsible for the economic growth by evaluating their effects in the long-run and short-run by employing the autoregressive distributed lag bounds cointegration approach. In the long-run, the SME's output, human development index, and credit to the SME sector's expansion are identified as the main driving force behind economic growth. However, in the short-run, SME's output, human development index, credit to SME, and annual export rate are the main drivers of economic development. Empirical results are important to policy makers to promote, stimulate and support the growth of small and medium-sized enterprises through their strategies.

What drives TFP long-run dynamics in five large European economies?

The aim of this paper is to study the long-run cointegrating relationship of TFP in a panel of five large European economies, namely France, Germany, Italy, Spain, and UK. We test whether TFP is determined by the so-called "capital misallocation effects, scale effects, and labor market effects". By considering aggregate data, over the period 1983-2017, we employ dynamic panel cointegration techniques to identify the long-run component of TFP. We get two main results. First, the interest rate, the real compensation and the real exchange rate have a positive impact on TFP. Then, the incidence of temporary employment (a proxy of labor market flexibility) has a negative effect on TFP. Moreover, for robustness, we run a panel VECM to check for causalities among the variables. Notably, this further excercise confirms the existence of a strong and positive long-run relationship between TFP and prices. We conclude that coordinated policies on the issue of interest rate, exchange rate, labour cost and regulation, may allow to reassemble the productivity slowdown puzzle and strengthen the European economic structure.

The recovery of global stock markets indices after impacts due to pandemics

The COVID-19 brings back the debate about the impact of disease outbreaks in economies and financial markets. The error correction terms (ECT) and cointegration processing tools have been applied in studies for identifying possible transmission mechanisms between distinct time series. This paper adopts the vector error correction model (VECM) to investigate the dynamic coupling between the pandemics (e.g., the COVID-19, EBOLA, MERS and SARS) and the evolution of key stocks exchange indices (e.g., Dow-Jones, S&P 500, EuroStoxx, DAX, CAC, Nikkei, HSI, Kospi, S&P ASX, Nifty and Ibov). The results show that the shocks caused by the diseases significantly affected the markets. Nonetheless, except for the COVID-19, the stock exchange indices reveal a sustained and fast recovering when an identical length time window of 79 days is analyzed. In addition, our findings contribute to point a higher volatility for all financial indices during the COVID-19, a strong impact over the Ibov-Brazil and its poor recover when compared to the other indices.

Agricultural production and CO2 emissions from two sources in the ECOWAS region: New insights from quantile regression and decomposition analysis

Agriculture being the dominant economic activity of the West African economies is responsible for the most greenhouse gasses emitted in the region. Are there heterogeneous determinants of environmental degradation across low, intermediate, and high CO2 emitters in West Africa? Considering the significance of agriculture, industrial activities, renewable energy consumption and economic growth in West-Africa, this paper investigates the conditional determinants of environmental degradation from two sources (per-capita CO2 emission and CO2 emission from liquid sources) using panel data from 15 ECOWAS countries for the period 1990-2015. The study adopts a panel quantile regression technique with non-additive fixed effects as well as quintile decomposition techniques to explore if the relationship between agricultural and economic factors differs across low, intermediate, and high CO2 emitters and the extent of CO2 emission gap between Low Income Group (LIG) and Lower-Middle Income Groups (LmIG). Results from the mean estimators show that while agricultural production impedes CO₂ emissions from liquid sources, it however increases total emissions implying a shift from mechanized farming to more traditional farming methods and the burning and use of biomass from agricultural produce as an energy source. Estimates of the conditional determinants of environmental degradation vary along the quantiles signifying heterogeneity of the determinants of environmental degradation across, low, intermediate, and high CO2 emitters. Additionally, results emanating from the quantile decomposition procedure show that lower-income West African economies have superseded their lower-middle income counterparts at higher quantiles of CO₂ emissions.

Determinants of gold price movements: An empirical investigation in the presence of multiple structural breaks

This study investigates the short- and long-run determinants of gold price movements in financial markets by taking into account multiple structural breakpoints using an ARDL-based error correction approach. The study used daily time series data from December 19, 2018 to May 15, 2020. The key variables used include international stocks and bond funds that are frequently traded on stock exchanges around the world. The results, based on the fourth breakpoint regime, reveal a significant positive relationship between gold price movements and LSE, Nikkei stocks, T.Rowe global multi-sector bond funds, and CBOE volatility index; and a significant negative association with Gmo emerging country debt and Pimco emerging markets local currency bond funds both in the short- and long-run. Other stocks, like NASDAQ, DJI, S&P500, only revealed negative short-run relationships; except for NYSE that was found to have a positive short-run association with gold price movements. Conversely, Goldman Sachs bonds revealed a significant positive long-run relationship with gold price movements. These results have significant policy implications for gold producers and investors, as both stocks and bonds are an important source of information in the determination of gold price movements both in the short- and long-run.

Impact of increasing temperature anomalies and carbon dioxide emissions on wheat production

Climate change is one of the serious issues humankind is currently facing. It impacts almost all the processes in nature and threatens the existence of species and biodiversity; hence, the whole process of the food cycle. To mitigate the influence of climate change on vital processes in nature, we need to understand the pattern and magnitude of the relationship between climate change and impacted processes in nature. In this article, we explore the impact of climate change on wheat production in terms of short and long-run relationships between world wheat production, carbon dioxide emissions, and surface temperature anomalies. We present new information on the nexus between climate change and wheat production using autoregressive distributed lag (ARDL) models and ARDL bounds test of cointegration. We observe a significant cointegration relationship among world wheat production, carbon dioxide emissions, and surface temperature anomalies series. Lagged short-run impacts of temperature anomalies and carbon dioxide emissions are found significant. The long-run impact of both series on world wheat production is significant with a high correction speed to any instability between wheat production and the proxies of climate change.

What role do futures markets play in Bitcoin pricing? Causality, cointegration and price discovery from a time-varying perspective?

Recent papers that have explored spot and futures markets for Bitcoin have concluded that price discovery takes place either in the spot, or the futures market. Here, we consider the robustness of previous price discovery conclusions by investigating causal relationships, cointegration and price discovery between spot and futures markets for Bitcoin, using appropriate daily data and time-varying mechanisms. We apply the time-varying Granger causality test of Shi, Phillips, and Hurn [2018]; time-varying cointegration tests of Park and Hahn [1999], and time-varying information share methodologies, concluding that futures prices Granger cause spot prices and that futures prices dominate the price discovery process.

Determinants of renewable and non-renewable energy consumption in hydroelectric countries

In the past decades, renewable energy consumption has grown considerably because of environmental degradation caused by non-renewable energy consumption. This research aims to find the causal link between renewable and non-renewable energy consumption, human capital, and non-renewable energy price for the 53 most renewable energy-consuming countries worldwide (hydroelectric) during the period 1990-2017. We use data collected from the World Bank ( http://data.worldbank.org/data-catalog/world-development-indicators , 2018) and Statistical Review of World Energy ( https://www.bp.com/ , 2018). We test simultaneously two types of regressions in order to measure the degree of elasticity of the two types of energy by using econometric techniques for panel data. The results of the GLS models indicate that human capital has a stronger significant effect on renewable energy consumption at the global level, in the middle high-income countries and low-middle income countries, compared with non-renewable energy consumption. Besides, at the global level, there is a positive and statistically significant relationship between the non-renewable energy price and the two types of energy consumption. There is a long-run consumption of both types of energy. On the other hand, the one-way relationship between human capital and non-renewable energy price and renewable energy consumption is stronger than the relationship with non-renewable energy consumption. The policy implications derived from this study should be designed to promote human capital development in order to promote renewable energy consumption and increase the investment in renewable energy sources to guarantee their access to lower prices that reduce non-renewable energy consumption.

The relationship between shale gas production and natural gas prices: An environmental investigation using structural breaks

This paper investigates the long-run cointegration relationship between shale gas production and natural gas prices during the period from January 2007 to December 2016 for 16 states in the U.S., by utilizing the Generalized Least Squares (GLS) based univariate unit root test, the PANICCA panel unit root test, the cointegration tests of Gregory and Hansen (1996), Westerlund and Edgerton (2008) as well as Banerjee and Carrión-i-Silvestre (2015) tests with structural breaks. The empirical finding shows that the mean-reverting property exists in both variables, and most structural breaks emerge around 2007-2009 and 2011-2014, during the period when shale gas production sharply increased, the global financial crisis erupted, and external energy shocks emerged. We also find a strong cointegrated relationship, denoting a long-run equilibrium property appears among the variables. Overall, we demonstrate an interaction nexus between price and production variables and put forward some vital implications for authorities and gas market participants.

Unfolding the relationship between mortality, economic fluctuations, and health in Italy

Despite the long-run strong negative association between economic development and mortality, their short-run relationship remains controversial. In the present work, we study co-movement between mortality growth (overall, gender- and cause-specific) and economic fluctuations in Italy over the period 1862-2013. To this aim, we use Johansen (Econometrica 59:1551-1580, 1991) procedure to jointly estimate the short- and long-run dynamics of the two variables, avoiding omitted variable bias in the cyclical co-movement extraction or spurious association attributable to trends. We also take into account possible asymmetric responses of mortality growth to shocks in GDP. We find that an increase of 1% in real GDP per capita induces a reduction in mortality rate of 0.27% for total population. Moreover, we observe that business cycle fluctuations do not affect mortality in the pre-wars era, where only the long run decreases matters driven by reduction in infections and accidents mortality. On the contrary, in the post-wars period, expansive phases of business cycle are associated with reduction in mortality growth and periods of recession generate an ever-deeper decrease. However, in this period, mortality for cancer is procyclical and significantly increasing in expansion: this reinforces the debate for controlling environmental factors.

Investigating Rates of Food and Drug Administration Approvals and Guidances in Drug Development: A Structural Breakpoint/Cointegration Timeseries Analysis

BACKGROUND

The number of original and supplemental ANDAs, BLAs, NDAs, and Biosimilars FDA drug/biologic approvals (Approvals) has risen dramatically in the recent years, incidentally, so has the number of issued FDA guidances (Guidances). It is hypothesized that if the structures of the two timeseries are similar and/or concomitantly co-evolving, then there is a relationship between the two variables that may be worthy of further investigation.

METHODS

Structural breakpoint (SBP) and cointegration (CI) analyses are used to provide insights into the relatedness of the two timeseries (Approvals, Guidances). Various descriptive statistics (e.g., nonparametric correlation testing, decomposition, unit testing, stationarity, and maximum order of integration) were also performed to better understand the nature of the timeseries understudy.

RESULTS

Structural breaks were identified with the following dates: Approvals (1983, 1989, 1996, 2004, and 2012) and Guidances (1995 and 2012). Approvals and Guidances were (medium) correlative, nonstationary, and cointegrated with a maximum order of integration of one (I(1)). Descriptive statistical markers suggest additional similarities (e.g., seasonal variation) between the two timeseries.

CONCLUSIONS

To the author's knowledge, this is the first work to empirically investigate Guidances and their relationship with Approvals. The similarity in the structure of the timeseries (e.g., seasonal variation, SBPs and CI) suggests a deeper relationship between Guidances and Approvals, including the existence of a "long-run" equilibrium (wherein one or more exogenous factors restrain the divergence) between the two variables. This work offers an exciting opportunity for further research into the processes influencing the rates of Approvals and Guidances. A discussion on the limitations of the approach is also presented.

Socio-economic, macroeconomic, demographic, and environmental variables as determinants of child mortality in South Asia

The study empirically examines the effects of socio-economic (human capital), macroeconomic (per capita GDP), demographic (fertility rate, urbanization), and environmental variables (carbon emissions) on child mortality in South Asia. For empirical analysis, panel cointegration technique is used by using data for five South Asian countries for the period 1973 to 2015. First, it is found that the variables have unit roots at levels but are stationary at first differences, which indicates the possibility of cointegration. Cointegration test results show that long-run cointegrating relationship holds among variables. Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) methods are applied to find the parameter estimates. The results of long-run estimates show that human capital, per capita income, and urbanization reduce child mortality while high fertility rate and environmental degradation increase child mortality in the region. It is also found that trade openness, immunization, food security, and high life expectancy also decrease child mortality and that population density increases child mortality.