Canonical Cointegrating Regression Research Articles

Exploring the association between the female gender, education expenditure, renewable energy consumption and CO2 emissions: Empirical evidence from Nigeria

AbstractThe significance of women's contribution to attaining the Sustainable Development Goal of net zero emissions cannot be underestimated. Therefore, employing the ecofeminism theory, this research explores the effect of female gender, education expenditure and renewable energy consumption on carbon dioxide emissions in Nigeria between 1990 and 2019. The utilised methodologies include autoregressive distributed lag (ARDL), fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegrating regression (CCR). The cointegration tests showed evidence of long‐run association. The ARDL result revealed that female gender, education expenditure, and renewable energy consumption have a negative relationship with carbon dioxide emissions in the long run. This indicates that a rise in these variables is beneficial to the environment. In the short run, female gender and renewable energy consumption have a negative link with carbon dioxide emissions. For robustness check, the results obtained from the FMOLS, DOLS and CCR methods validate the ARDL findings. Furthermore, the frequency domain causality test established that the female gender has a one‐way causal influence on carbon dioxide emissions in the long, medium, and short term. Based on these outcomes, policy recommendations are further discussed.

Nexus Between Energy Intensity and Economic Globalization in a Landlocked Country Nepal

Energy intensity, a major indicator used worldwide to measure energy efficiency, is of paramount importance to Nepal in the context of energy dependency with India in both the major energy sources: fossil fuels and electricity. In this context, this study has attempted to analyze the impact of economic globalization on the energy intensity of Nepal over the period 1990 to 2019 using dynamic ordinary least squares (DOLS), fully modified ordinary least squares, and canonical cointegrating regression (CCR) method. The results show highly significant and negative impact of economic globalization on energy intensity in Nepal.

Strategic Integration: Fostering Sustainability in Low-Income Country through Poverty Alleviation, Carbon Efficiency, Energy and Economic Resilience

This study emphasizes the critical importance of strategic integration for sustainable development goals (specifically Goals 1 and 2) in low-income countries (LICs). The research uses econometric models to focus on poverty reduction, economic resilience, energy use, and carbon emissions in Indonesia from 1996 to 2022. The study reveals a long-run co-integration among the estimated parameters, with a significant speed of adjustment at a 1.04% level. ECM models highlight a positive relationship between energy use, poverty, and carbon emissions while indicating a negative association between economic growth and carbon emissions. Robustness checks support these findings, including Fully Modified Ordinary Least Squares (FMOLS) and Canonical Co-Integrating Regression (CCR). Granger causality analysis reveals a unidirectional causality from energy use to carbon emissions and economic growth, along with one-way causation from carbon emissions to economic growth and poverty. Diagnostic tests affirm the model's reliability. The study's outcomes contribute valuable insights to the discourse on strategic integration, offering policymakers and stakeholders guidance in formulating sustainable development strategies tailored to the unique challenges encountered by low-income countries.

Digital Technologies, Environmental Governance and Environmental Performance: Empirical Evidence from China

This research conducts an empirical analysis of the relationship between digital technologies, environmental governance (assessed through environmental taxes), and China's environmental performance from 1995 to 2020. Additionally, within the framework of the STIRPAT model, the impacts of GDP and urbanization on ecological footprints are examined. This study is distinguished by its innovative approach to evaluating environmental performance via ecological footprints and the application of the Autoregressive Distributed Lag (ARDL) model along with Dynamic Ordinary Least Squares (DOLS), Canonical Cointegration Regression (CCR), and Fully Modified Ordinary Least Squares (FMOLS) as long-run estimators, methodologies not previously applied to this context in China. The findings indicate that digital technologies and environmental taxes contribute to a reduction in ecological footprints, while GDP and urbanization have an adverse effect, increasing ecological footprints. Post-estimation diagnostics confirm the absence of serial correlation and heteroskedasticity, and affirm the normal distribution of the disturbance terms. For a robustness check, the study further employs DOLS, FMOLS, and CCR methods, which corroborate the initial results regarding the beneficial impact of digital technologies and environmental governance on ecological footprints. Based on these findings, the study advises the Chinese government and policymakers to enact more effective environmental tax policies and leverage digital technologies to enhance environmental sustainability in China.

Does Digitalization Lead to Environmental Sustainability and Energy Efficiency in China?

In the past 20 years, there has been an increased focus on the connection between investments in digitalization, environment, and economic growth, however the effects of digitalization on energy efficiency in developing nations have received little attention in empirical researches. therefore, the goal of current research is to study the effect of digitalization on environmental sustainability and energy efficiency in China over 1995-2020. For this purpose, two separate models are formulated with energy efficiency and CO2 emissions as dependent variables and digitalization (measured by ICT technologies) as the explanatory variable. The study applies three time series approaches namely, Dynamic Ordinary Least Square (DOLS), Fully Modified Ordinary Least Square (FMOLS), and Canonical Cointegration Regression (CCR) to empirically estimate the study objectives. The study findings show that ICT plays positive role in promoting energy efficiency and environmental sustainability as coefficient of ICT is negative in both models. It was concluded from the findings that ICT sector has positive implications in terms of energy and environment in China. The study recommends the Chinese government and policy makers to pay attention and device effective policies for promotion of ICT sector in the country.

The dynamic impact of non-renewable and renewable energy on carbon dioxide emissions and ecological footprint in Indonesia

The global trend of environmental degradation, marked by escalating carbon dioxide (CO2) emissions and expanding ecological footprints, poses a significant risk to the planet and leads to global warming. This decline in the environment is primarily attributed to the extensive use of non-renewable energy sources and substantial economic activities. This study investigates the dynamic impact of non-renewable energy (coal, gas, and oil), renewable energy, economic growth, and capital formation on CO2 emissions and the ecological footprint in Indonesia spanning from 1965–2022. Employing Fully Modified Ordinary Least Squares (FMOLS), Ordinary Least Squares (DOLS), and a robustness test with Canonical Cointegrating Regression (CCR) techniques, we seek to establish long-term associations among the studied variables. Preliminary findings, supported by our primary models, reveal that every increase in coal and gas directly results in higher CO2 emissions but does not affect ecological footprints. Conversely, every increase in oil affects the rise of ecological footprints but not CO2 emissions. Meanwhile, the rise in renewable energy will reduce both CO2 emissions and ecological footprints, consequently enhancing Indonesia's environmental quality. Furthermore, increasing economic growth will increase both CO2 emissions and ecological footprint, while the rise in capital formation reduces the ecological footprint. The Granger causality test showed unidirectional causality from CO2 emissions to renewable energy and also revealed bidirectional causality between ecological footprint and renewable energy. This study clarifies the patterns of energy emissions in Indonesia and provides policymakers with recommendations for maintaining environmental sustainability, including investing in renewable energy use and transitioning away from non-renewable energy, given the pressing climate challenges and the goal of achieving carbon neutrality.

An analysis of long-term and short-term impact of climate change on rice production in India

PurposeClimate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.Design/methodology/approachThis study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.FindingsThe study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.Originality/valueThe present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Exploring the dynamic capability of green technology innovation for achieving sustainable development: an empirical insight from China

ABSTRACT During the past several decades, the world has been putting strong emphasis on the role of environmental technology innovation which can reduce environmental degradation and promote sustainable development. This research sheds light on the impact of green technology or eco innovation on sustainable development for China. Additionally, the effects of other variables such as governance, information and communication technology, trade uncertainty and urban population are also analysed. The study employs Fully modified ordinary least squares (FMOLS) and Canonical Cointegration Regression (CCR) as the long run tests and Breitung and Candelon Spectral Granger-Causality as the time varying granger causality test. The results suggest that green innovation promotes sustainable development in the long run. The roles of governance quality and urbanization are also found to be positive while the role of ICT is found to be insignificant yet negative. The role of trade uncertainty is positive yet insignificant. Based on these results, the study calls for the private and public organizations and industries to invest in eco innovation. Different incentives from the government can also encourage private industries to invest in green innovation technologies.

Does public debt matter for human capital development? Evidence from Nigeria

An inquiry into the impact of external and domestic borrowings is considered timely for Nigeria, given the growing public debt profile amid deteriorating human capital development. Using data from 1990 to 2021, the study estimates the effects of domestic and external debts on Nigeria's human capital development. The study employed the fully modified ordinary least squares and canonical cointegration regression as the main estimation technique and the robustness check, respectively. The study discovered that domestic and external debt, economic growth and debt servicing exert positive and significant influence on human capital development in Nigeria while environmental pollution has an inverse and significant impact on human capital development in Nigeria. Premised on the outcomes, policy suggestions aimed at enhancing human capital development in Nigeria have been put forward.

Oil rent, corruption and economic growth relationship in Nigeria: evidence from various estimation techniques

Purpose Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period. Design/methodology/approach Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality. Findings The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth. Originality/value Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.

Energy efficiency investment in a developing economy: financial development and debt status implication

Purpose This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy. Design/methodology/approach This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis. Findings The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods. Research limitations/implications The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management. Practical implications The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency. Originality/value The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.

Empowering tomorrow: unleashing the role of technology driven energy efficiency for Sustainable Development in China

The underlying objective of the study is to investigate the energy efficiency improvement potentiality of total technological innovation and its components, such as residential and non-residential technological innovations, by controlling for economic growth and energy prices in China. To this end, the study employs Dynamic Ordinary Least Squares (DOLS), Canonical Cointegrating Regression (CCR), and Fully Modified OLS (FMOLS) based on the unit root testing and Johansen and Juselius cointegration test outcomes. Thus, the results confirm the long-run relationship among the series under investigation. Further, it shows that total technological innovation and its components, i.e., residential and non-residential technological innovations, have the potential to improve energy efficiency. However, economic growth and energy prices are reducing energy efficiency. Moreover, these findings are stable while applying the other alternative methods for robustness. Therefore, the study suggests policy recommendations aimed at promoting technology that may be either residential or non-residential technological innovations to increase energy efficiency. Additionally, it urges designing national-level energy policy to boost economic progress by conserving energy along with measures to stabilize energy prices.

Awareness of Unpredictability in Economic Policy, Fiscal Decentralisation, and Innovative Approaches for the Preservation of The Environment in South Africa

The paper aimed to examine the awareness of unpredictability in economic policy, fiscal decentralization, and innovative approaches to preserve the environment in South Africa using annual recurrence data from 1961 to 2021 in South Africa. Dynamic ordinary least squares, completely adjusted ordinary least squares, and canonical cointegration regression are used in this study. The Maki cointegration test shows how the factors maintain an equilibrium relationship throughout the period under consideration. Data from empirical results support the environmental Kuznets curve paradigm. These findings show that the environment must be compromised during the early phases of economic growth to achieve economic success (scale phase). Long-term exponential growing economies decrease pollutants by 0.162%, but a 1% increase in economic expansion raises pollutants by 0.791%, according to the environmental Kuznets curve hypothesis. Similarly, in South Africa, long-term economic globalization, as well as unpredictability in economic policy, reduce the sustainability of the environment. In contrast, long-term fiscal decentralization and sustainable development increase it. These findings have far-reaching environmental implications. The current analysis encouraged environmental penalties and funding for projects transitioning from an energy electrical utility basis to renewables.

Statistical Models to Measure the Impact of Intellectual Property Rights Protection on Foreign Trade in Egypt

This study aims to estimate the relationship between the Protection of intellectual property rights indices and the foreign trade index in Egypt from 1995 to 2022. The comparison has been made between many models such as full modified ordinary least squares (FMOLS) model, dynamic ordinary least squares (DOLS) model , canonical co-integration regression (CCR) model and autoregressive distributed lag (ARDL) model. The results of the study showed that the best model was the ARDL model to increase its interpretive capacity. The study also showed that the most important property rights protection indicators affecting the foreign trade index are the number of applications and registrations of brands, the number of patents registered and granted, the number of applications and registrations of industrial designs, and the proportion of expenditure on research and development as a proportion of gross domestic product (GDP). The estimated model also passed all diagnostic tests and showed that there was no autocorrelation, no Heteroskedasticity. In addition, it was found to follow a normal distribution and to be stable.

Taking flight: Exploring the relationship between air transport and Malaysian economic growth

All facets of the tourism business, especially air travel, have been affected by the COVID-19 pandemic. The aviation industry continues to contribute to international economic expansion significantly. The article aims to identify the impact of the development of air transport on the economic development of the Malaysian economy. Therefore, the air-transportation-led growth hypothesis (ALGH) was investigated by examining whether airline travel boosts the Malaysian economy. The effects of air passengers (a stand-in for tourism) on Malaysia's GDP were examined in the long and short term. This study analyzed Data for Malaysia using an autoregressive distributed lag (ARDL) technique. The time covered was from 1970 to 2020. Certain control variables (i.e., energy consumption, financial development, social globalization, and urbanization) were also analyzed to see how they influenced economic expansion. Statistically significant effects of air travel on GDP were found in both the short and long term of this study, suggesting that this mode of transportation contributes to the sustained expansion of Malaysia's economy. Several methods, including Canonical Cointegration Regression (CCR), Dynamic Ordinary Least Squares (DOLS), and Fully Modified Ordinary Least Squares (FMOLS), were used to verify the results independently. The article offers legislative suggestions for improving the aviation industry's productivity, security, and bottom line.

Linking per capita income, renewable energy, natural resources, trade, and Urbanisation to material footprint: insights from Saudi Arabia

In view of growing greenhouse gases and climate change, this paper investigates the effect of per capita income, renewable energy, natural resources, trade, and urbanisation on the material footprint of Saudi Arabia. This study uses data from 1990 to 2019. Autoregressive Distributed Lag, Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Canonical Cointegrating Regression are used as estimation techniques. The result hints that per capita income, renewable energy, natural resources, trade, and urbanisation are determinants of material footprint in Saudi Arabia. Furthermore, the short- and long-run results show that per capita income, trade, and urbanisation increase material footprint, contributing significantly to Saudi Arabia's ecological damage. However, renewable energy and total natural resources rent reduce the material footprint in both periods. Other cointegration techniques also support the long-run estimates. The implications of the result for a sustainable environment were discussed.

Promoting sustainable development: Evaluating the influence of natural resources, high-tech export and corruption on CO2 emissions in developing economies

Natural resources accelerate climate change resulting in exacerbating the frequency and intensity of extreme weather events, ecosystem disruption, and rising sea levels, with significant consequences for both human and natural systems. The extraction and combustion of fossil fuels, such as oil, gas, and coal, release vast amounts of greenhouse gases into the atmosphere, primarily carbon dioxide (CO2). The present article explores the impact of natural resource rents (NRR), export of high-technology (High-Tech), renewable energy (RE), Gross Domestic Product (GDP), and corruption (CR) on CO2 emissions for a panel of 141 developing economies between 2000 and 2021. The Westerlund co-integration test confirmed a long-run co-integration connection among the study variables. Based on the Method of Moment Quantiles Regression (MMQREG), renewable energy (RE) and control of corruption (CR) are the two key factors that can effectively reduce CO2 emissions. Contrarily, the outcomes illustrate that High-Tech, GDP, and natural resource rents (NRR) increase CO2 emissions. Moreover, the robustness checks of Fully-Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS), Canonical Co-integration Regression (CCR), and the Augmented Mean Group (AMG) confirmed and supported the main outcomes of MMQREG. These findings have significant implications for sustainable environment. Consequently, most energy utilization required in developing economies is presently met by the use of fossil fuels, exploitation of natural resource rents (NRR) and industrialization policies will be at odds with a sustainable environment.

The influence of tourism on the road to achieving carbon neutrality and environmental sustainability in Malaysia: The role of renewable energy

As the effects of climate change on the environment become more apparent, numerous initiatives have been launched to achieve carbon neutrality and environmental sustainability. Travelers may be adding to global warming by engaging in climate–altering practices like flying or staying in hotels. Thus, this study examined the connection between tourism and carbon emissions, considering a few additional unique aspects. The long–run and short–run coefficients were calculated by applying the autoregressive distributed lag (ARDL) method using data spanning 1990–2019. According to projections, tourism in Malaysia makes it more difficult to reach carbon neutrality. Traveler numbers along with fossil fuel energy use, economic growth, financial development, gross fixed capital formation, and population have a positive association with long–term carbon emissions. However, the findings revealed a negative link between renewable energy consumption and carbon emissions. Several methods, including Canonical Cointegration Regression (CCR), Dynamic Ordinary Least Squares (DOLS), and Fully Modified Ordinary Least Squares (FMOLS), were used to independently verify the results. The results of this research have important policy implications for achieving carbon neutrality and promoting sustainable tourism development in Malaysia by boosting renewable energy use.

A Deep Dive into Indonesia's CO2 Emissions: The Role of Energy Consumption, Economic Growth and Natural Disasters

This study examines the influence of non-renewable energy consumption, renewable energy consumption, economic growth, and natural disasters on Indonesia's carbon dioxide (CO2) emissions spanning from 1980 to 2021. The Autoregressive Distributed Lag (ARDL) model is employed, with supplementary robustness checks utilizing Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR). The findings reveal that economic growth, along with non-renewable and renewable energy consumption, significantly affects CO2 emissions in both the short and long term. Robustness checks confirm the positive impact of non-renewable energy consumption and economic growth, while renewable energy consumption has a negative effect on CO2 emissions. Moreover, natural disasters exhibit a positive short-term impact on CO2 emissions. Pairwise Granger causality results further underscore the intricate relationships between the variables. To mitigate climate change and curb CO2 emissions in Indonesia, the study recommends implementing policies that foster sustainable economic development, encourage the adoption of renewable energy, and enhance disaster resilience.

Economy-energy-environment nexus: the potential of agricultural value-added toward achieving China’s dream of carbon neutrality

Agriculture is one of the major sources of global emissions that cause climate change while agricultural value added helps to boost the economy in developing countries like China. Therefore, this study aims to investigate the long- and short-term influences of agricultural value added, economic growth (GDP), and energy use on carbon dioxide (CO2) emissions in China. The autoregressive distributed lag (ARDL) method was used by using annual time series data from 1990 to 2021. The empirical outcomes revealed that a 1% increase in the agricultural value added would cut CO2 emissions by 1.37% in the long-run and 0.65% in the short-run. However, this study found that both GDP and energy consumption have a positive and statistically significant effect on CO2 emissions. Furthermore, an inverted U-shaped association between economic growth and environmental pollution was discovered by spotting the positive coefficient of GDP and the negative coefficient of GDP squared, which proved the validity of the environmental Kuznets curve (EKC) hypothesis. The robustness of the ARDL outcomes was verified by using the fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegration regression (CCR) approaches. This study offers a comprehensive set of policy recommendations aimed at enhancing agricultural value added in China. These suggestions focus on the promotion of climate-smart agriculture, the integration of renewable energy sources in agricultural production, and the adoption of advanced technologies within agricultural systems. Implementing these measures would contribute to the achievement of China’s goal of carbon neutrality.Graphical