Presence Of Cross-sectional Dependence Research Articles

Do digitalization and green innovation limit carbon emissions? Evidences from BRICS economies

Rapidly evolving innovation and digitalization have captured the focus of policymakers and scholars regarding their potent role in influencing environmental quality. The present research analyzes the impact of these variables on the carbon emissions of Brazil, Russia, India, China, and South Africa economies from 1990 to 2021. This research also explores the impact of economic growth, quadratic green innovation, and green energy on carbon emissions. Using several panel diagnostic tests, this research validates heterogeneous slopes, the presence of cross-sectional dependence, and significant cointegration. Due to the mixed integration order, this research uses a cross-sectional augmented autoregressive distributed lag model, and the results show that economic expansion and green innovation are significant drivers of emissions in both the short and long run. However, digitalization, quadratic green innovation, environmental policy stringency, and green energy are significant in improving environmental quality and sustainability. The long-term results are tested by employing a series of parametric and nonparametric regressions. This research recommends further investment in environmental research and development, digital technologies, green innovation, and the strengthening of environmental policies to attain sustainable development.

Environmental policy stringency and ecological footprint linkage: Mitigation measures of renewable energy and innovation

We scrutinize the environmental policies' efficacy in reducing ecological footprint by interweaving two other vibrant parameters of environmental degradation mitigation, i.e., renewable energy sources and innovation. To this end, we apply a Cross-Sectional Autoregressive Distributed Lags (CS-ARDL) approach to analyze panel time-series data (1990–2018) in the context of OECD countries. Our analysis shows that environmental policy significantly reduces ecological footprint through renewable energy and innovation channels. Our findings also support the idea that environmental policy's effectiveness is conditional on countries' bio-capacity surplus/deficit and the level of industrialization. The overall findings hold up well in the presence of cross-sectional dependence, short-run heterogeneity, and long-run homogeneity under the respective sample. Our findings underscore the need for more stringent environmental policies, supported by technological advancements and clean energy initiatives, to mitigate the impact of human economic activities on natural resources.

Effect of crypto-asset market-specific technological development on the asymmetric volume-return relationship in the presence of cross-sectional dependence and heterogeneity

Effect of crypto-asset market-specific technological development on the asymmetric volume-return relationship in the presence of cross-sectional dependence and heterogeneity

Does energy efficiency, renewable energy and effective capital promote economic growth in the emerging 7 economies? New evidence from CS-ARDL model

Gross Domestic Product is regarded as the major indicator which determines the standards of living in a country. Consequently, energy use is far regarded as one of the major determinants of economic growth in an economy. However, fossil fuel energy greatly contributes to environmental degradation, global warming and the spread of various diseases. The present-day research is aimed at examining the effect of energy efficiency, renewable energy and effective capital on Gross Domestic Product in the emerging seven countries (Brazil, Russia, Mexico, Turkiye, Indonesia, China and India), during the period 1990 to 2019. The main novelty of the research is that it examines the effect of effective capital on Gross Domestic Product, a study which has not been done. Effective capital which is the combined effect of energy and physical capital in the production process is inevitable in raising economic growth. Additionally, the effect of energy efficiency on economic growth in the emerging seven countries has been partially investigated. The findings of this research are robust and unique to those of past researches, because Cross-sectional Augmented Autoregressive Distributive Lag technique which is strong in the presence of cross-sectional dependence, heterogeneity and dynamics is employed. The outcomes provided in this research shows that, energy efficiency and effective capital significantly promotes economic growth, while non-renewable energy provides significant positive effect in the short-run, with no significant effect in the long-run. This study recommends the efficient utilization of energy, ensuring that each single unit of energy employed produces the highest possible output.

Assessing the dynamics of international competitiveness based on high-tech exports: insights from a heterogeneous panel of selected G20 countries

ABSTRACT Governments have shown increasing interest in maintaining their high-tech export competitiveness by using policies designed to encourage advances in science and technology and the adoption of new techniques by industry. This article assesses the dynamics of international competitiveness based on high-tech exports, with special reference to selected G20 countries. The analysis uses longitudinal data for sixteen G20 countries over the period 1992–2019. We use second-generation panel data techniques that reveal robust results under the presence of cross-sectional dependence and cross-country heterogeneity. In line with theoretical underpinnings, the empirical results suggest that technological capability and cost advantages/disadvantages play a vital role in high-tech export competitiveness. The overall picture demonstrates that the increasing stock of highly educated individuals has important implications for enhancing G20 countries’ high-tech export market share. On the flip side, the estimated negative linkage between patent applications and international competitiveness supports the general statements of the technology-based trade models. Therefore, while technology dissemination changes the direction of technological absolute advantages, innovative countries may lose their high-tech export market share to less developed countries (LDCs) as factor endowments create a competitive advantage for LCDs.

Evaluating policy-driven capital for renewable energy investments in the presence of cross-sectional dependence: perspectives from financial institutions and markets.

Access to financing is crucial for renewable energy projects due to their high initial capital costs and long payback times. In this regard, well-performing financial institutions and markets can provide the necessary capital for investments in renewable energy sources. This study emphasizes the impact of financial institutions and markets on renewable energy investment using data from various regions (Asia, Africa, Europe, and America). The CS-ARDL model is employed for analysis during 1998-2021. The findings of the CS-ARDL highlight that financial institutions, financial markets, greenhouse gas emissions, and GDP help promote investments in renewable energy in the long run for all samples, including global, Asian, American, African, and European. However, the estimates of ICT and Trade have insignificant effects on investments in renewable energy. In the short run, most of the factors do not show any significant effect on renewable energy investments. Therefore, policymakers should try to increase the role of financial institutions and markets in promoting renewable by inducing them to ease their policies for grant of loans to invest in renewable energy sources.

Does public-private investment augment renewable energy consumption in BIMSTEC nations? Evidence from symmetric and asymmetric assessment

This study investigates the impact of public-private investment, globalization, and urbanization on the aggregation of renewable energy demand in the Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) Nations from 1990 to 2021. Various econometric tools based on panel data analysis are employed to analyze the static properties of the variables using the CADF and CIPS unit root tests and examine the long-run relationship through panel cointegration with an error correction term. The study also employs the CS-ARDL approach to establish long-run and short-run coefficients. Additionally, a panel Granger causality test is conducted. Based on the findings of the primary assessment, the study reveals that the research units exhibit common dynamic properties, indicating the presence of cross-sectional dependency. The static test demonstrates that all variables become stationary after differencing them once. The panel cointegration test confirms a long-run relationship between the variables of interest. According to the coefficients estimated using CS-ARDL, the study concludes that renewable energy consumption has been positively and significantly influenced by all three explanatory variables: public-private investment, globalization, and urbanization. Furthermore, the causality assessment reveals evidence supporting the feedback hypothesis between renewable energy consumption, public-private investment, and globalization. Because of the positive and significant impact of public-private investment, globalization, and urbanization on renewable energy consumption, it may be beneficial to implement targeted policies and investments in these areas to encourage the adoption of renewable energy. Governments and private investors need to join forces to draw investments and create a beneficial atmosphere for renewable energy endeavors which can be achieved by focusing on inventive ways of financing and implementing regulatory frameworks that provide support.

Devising strategies for sustainable development in sub-Saharan Africa: The roles of renewable, non-renewable energy, and natural resources

The Sub-Saharan African (SSA) countries are encountering difficulties in attaining sustainable development because of the non-alignment of the energy and climate policies with the human development aspects. The present study attempts to address this policy void by mainstreaming the human development aspects in the energy and climate policies of the SSA countries. In this pursuit, the impact of renewable, non-renewable energy and natural resources on sustainable development index is analyzed for 28 sub-Sahara African countries over 1990–2019. Presence of cross-sectional dependence is controlled through the application of Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimation. The results reveal that renewable energy and natural resources have positive but insignificant impacts on sustainable development, while fossil fuel significantly and negatively affects sustainable development. The study outcomes are used to develop policy recommendations for the achievement of sustainable development in the SSA countries.

Dynamic common correlation effects of financial development, foreign direct investment, market size and trade openness on domestic investment: an income-level prognosis

PurposeThe study examined the impact of financial development, foreign direct investment, market size and trade openness on domestic investment for 119 countries divided into four panels that are low-income countries (LIC), lower middle-income countries (LMIC), upper middle-income countries (UMIC) and high-income countries (HIC) between 1995 and 2019.Design/methodology/approachThe present study bases its empirical procedure on the bases of the data mix. To this end, based on the presence of cross-sectional dependence, covariate-augmented Dickey–Fuller unit root and Westerlund cointegration second-generation tests were employed to validate the stationarity and cointegration of the variables, respectively. The novel Dynamic Common Correlation Effects estimator was employed to estimate the heterogeneous parameters while the Dumitrescu and Hurlin test was used to test for causality direction of the highlighted variables.FindingsThe empirical results show that market size and trade openness had a positive and statistically significant effect on domestic investment for all the income groups. Results also show that financial development had a positive and statically significant effect on domestic investment only for LMIC and HIC economies, while a positive and statistically insignificant effect was obtained for LIC, UMIC and the global panel. The causality results revealed a bidirectional relationship between domestic investment and the exogenous variables – financial development, foreign direct investment, market size and trade openness.Research limitations/implicationsIt is therefore, recommended that LIC and LMIC need to consider harmonising the financial system to lower credit limitations and adopt business-friendly policies. HIC and UMIC should seek more outward FDI policies and harmonise their trade policy, to reap more benefits from FDI and international trade.Originality/valueOn novelty, previous studies have been criticised for the effect on technical innovation of bank financing and institutional quality. This research tackles the deficiency using systematic institutional quality indicators and by taking other variables into account.

Do technical change and mechanisation negatively affect employment in the manufacturing sectors? An empirical assessment for the OECD countries

The present study is aimed at assessing the impacts of technological change and mechanisation on employment in the manufacturing sectors of the OECD countries over the 1995-2018 period. To achieve this goal, the vertically integrated labour productivity and the vertically integrated capital-labour ratio were computed as measures of technological progress and capital intensity per unit of labour, whereas the CS-ARDL and CS-DL approaches were applied to obtain robust results in the presence of cross-sectional dependence and slope heterogeneity. The findings suggest that both technical change and mechanisation may lead to a relative decrease in employment in the short-run and long-run, though for skilled workers the effects appear to be positive. This increase in demand for skilled labour, however, may not be able to compensate for the decline in medium and lesser skilled labourers.

Econometric Evidence of Catalytic Effect of Seaport Activity in OECD Countries: Getting It Right

Within the transportation sector, ships and seaports constitute a significant portion. During the last decade, there has been a rise in the containerization era. This paper quantifies the relationship between seaport activity and GDP per capita while addressing Cross-sectional Dependence and slope heterogeneity issues in 28 OECD countries from 2000 to 2019. Suitable proxies for economic development and seaport activity are subjected to panel data analysis. Cross-Sectionally Augmented Autoregressive Distributed Lag is used, and Common Correlated Effects Mean Group and Augmented Mean Group are employed for the Robustness check. Seaport activity has a positive long-term relationship with income per capita. Country-specific effects are also used to highlight the relative strength of the relationship across sample countries. Panel Granger causality shows the feedback effect between seaport activity and GDP per capita. Causality is also investigated using the Dumitrescu-Hurlin causality test, which is suitable for heterogeneous panels in the presence of cross-sectional dependence. Recommendations include the lessons for carefully appraised investments and standardization of operations in the seaport industry in OECD countries.

An Empirical Analysis of Fishery Kuznets Curve Hypothesis: Evidence from Oecd Countries

Fish farms are occasionally built on delicate natural habitats, which can have severe environmental effects. Many industrial fishing methods also devastate aquatic habitats with the addition of overfishing practices. While environmentalists and academics have been concerned about the rapid extinction of fishery resources, the existing evidence is still inconclusive. This study examined whether catching overfishing could explain the environmental Kuznets curve (EKC) hypothesis among Organisation for Economic Cooperation and Development (OECD) countries. The study used four empirical strategies, which are framed in the panel time series analysis. (a) it assessed the prior behaviour of the variables based on second-generation panel unit roots tests using Cross-sectional ADF(CADF) and Cross-sectional IPS. (b) it also assessed the potential long-run relationship among the variables using the Westerlund Panel Cointegration test. (c) it explores the fishery Kuznets curve for OECD countries using Cross-sectional Dependency - Autoregressive Distributed Lag (CS-ARDL) and Augmented Mean Group (AMG) methodology. (d) it also examines the short direction of causality among the variables using the Dumitrescu – Hurlin Panel Granger Causality test, which is built on standardised panel statistics suitable for small sample properties, even in the presence of cross-sectional dependency. Five main findings can be deduced from our analysis. Firstly, the preliminary check confirms are only stationary only after the first difference. Secondly, the analysis also suggests that there is a long-run relationship among the variables. Thirdly, the findings showed that fish exploration has a negative effect on carbon emissions. Fourthly, the quadratic term of economic growth unidirectionally Granger causes CO2 emissions. Fifthly, we found evidence in support of the EKC hypothesis across OECD countries. Finally, our results highlighted the importance of fishery control in promoting environmental quality among OECD countries. We recommend reform in public policy that encourages sustainable fishing along with innovative research into modern fishing methods that reduces emissions. A better method of fishing can be developed with the support of cutting-edge research, which can also help reduce water pollution and the threat that overfishing poses to biodiversity.

Does foreign direct investment promote renewable energy use? An insight from West African countries

Renewable energy (RE) is considered as one of the best alternative energy sources, which is friendly to the environment. The use of RE, reduces carbon emissions (CE) and its devastating effects to the environment. In line with the United Nations’ Sustainable Development Goals, nations should come up with ways to develop RE projects, in order to achieve the carbon neutrality goal. The current research is aimed at investigating factors that promote RE use in the developing countries. The major novelty of this study, is that, it seeks to investigate the impact of foreign direct investment (FDI) on RE, in the 15 west African countries, from 1990 – 2021. A review of past studies, shows a dearth of researches which examines the impact of financial development on RE development, in this region. The current research uses, second-generation methods of data analysis that are strong in the presence of cross-sectional dependence, hence robust results are obtained. Panel ARDL (PMG, MG & DFE) model is employed to obtain the short-run and long-run coefficients of the model. The major findings of the study are as follows: GDP does not significantly impact RE, in both short-run and long-run; FDI and public sector credit, have a significant positive effect on RE use in the long-run, while inflation rate and broad money have a significant negative long-run and significant positive short-run effect on RE use. Poor-financial resource countries must encourage FDI inflows to promote RE development.

Natural resources led growth and the role of financial development: Evidence from Next-11 economies

The contradictory literature concerning the impact of natural resources (NR) on economic growth (GDP) nurtures a new debate among scholars and policy-makers to examine the real impact of NR on the economy's growth. Therefore, this study aimed to analyze the specific influence of NR rents indicators on GDP in the Next-11 economies from 1990 to 2020. This study also tends to explore financial development's role in GDP. This study uses advanced panel data approaches such as panel cross-section dependence, slope coefficient heterogeneity, and cointegration estimators to achieve the stated objective. These estimators asserted the slope heterogeneity, presence of cross-section dependence, and the validity of cointegration between the variables. The mixed integrating order of variables led to adopting the third generation econometric approach – cross-sectionally augmented autoregressive distributed lags (CS-ARDL). The estimated results asserted that NR heterogeneously affects GDP, where natural gas rents enhance GDP, while oil rents and forest rents adversely affect the growth of the concerned economies. Also, financial development is found to be a significant and positive factor in GDP in the region. The estimated results are found robust and consistent by utilizing the mean group (MG) and augmented mean group (AMG) estimators. Following the outcomes, this study suggests efficient exploitation and utilization of NR, increased investment in the renewables sector, and financial sector development achieve sustainable GDP.

Heterogeneous effects of renewable energy and structural change on environmental pollution in Africa: Do natural resources and environmental technologies reduce pressure on the environment?

The global economy today faces the most devastating effects of global warming than what is evident in the pre-industrial age. Consequently, governments across the globe are making diligent efforts towards halting this undesirable menace through many avenues in which structural change stands out. Hence, this study examines the impacts of structural change, natural resource dependence, environmental technology, and renewable energy in selected five top carbon-emitting African countries, Algeria, Egypt, Morocco, Nigeria, and South Africa, from 1990 to 2019. The study employs second-generation estimators comprising cross-sectional auto regressive distributive lag (CS-ARDL), common correlated effects mean group (CCEMG), augmented mean group (AMG), and quantile regression (QR). The choice of the second-generation estimators was motivated by the presence of cross-sectional dependence and slope heterogeneity in the model leading to the adoption of the Westerlund cointegration test for the long-run evaluation. The empirical results based on CS-ARDL are presented thus. The indicators of structural change significantly reduce carbon emissions. Similarly, environmental technology and renewable energy mitigate the surge in carbon emissions. In contrast, natural resource dependence induces a substantial increase in carbon emissions. Besides, the findings are robust based on the outcomes reported from common correlated mean group (CCEMG), augmented mean group (AMG), and QR tests. Moreover, the causality from the Dumitrescu Hurlin test provides empirically backed the nexus based on unidirectional and bidirectional causalities. Promoting service-led structural change, environmental technology practices, and investment in renewable energy are among the prominent policy insights.

Temperature and Residential Electricity Demand for Heating and Cooling in G7 Economies: A Method of Moments Panel Quantile Regression Approach

The global energy system is highly vulnerable to climate variability and change. This results in a vast range of impacts on the energy demand sector and production and supply channels. This article aims to estimate the impacts of variables such as heating and cooling temperatures, income, population, and price on residential electricity demand in G7 countries. Methodologically, this study uses the second-generation panel unit root and cointegration approaches (which are robust in the presence of cross-sectional dependence), a panel fixed effects model with Driscoll–Kraay standard errors, and a novel method of moments quantile regression (MM-QR) to determine long-run elasticities. The results suggest that the residential electricity demand of G7 countries is statistically and positively responsive to cold days rather than hot days. This study also presents some policy-relevant issues based on the results.

Analysis of the Dynamic Relationships among Renewable Energy Consumption, Economic Growth, Financial Development, and Carbon Dioxide Emission in Five Sub-Saharan African Countries

This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions.

A DCCE Approach to the Governance-growth Nexus: Global Perspective

This study, being one of its kind by method and scope, delves into the effects of governance indicators on economic growth, using large panel datasets spanning from 2002 to 2020 for the world’s economies, income level economies, Organisation for Economic Co-operation and Development (OECD) members, and regional level economies that include 218 countries. In the presence of cross-sectional dependence and mixed integrating orders of the predictors, the results confirm a long-run nexus between governance and economic growth in the world and other panels. Using the dynamic common correlated effects model, the results indicate that governance predictors postulate significantly positive effects on economic growth, while the critical findings highlight that the scale of governance effects on growth varies in relation to the income level of the underlying economies in the panels, implying that the larger the economy, the higher the governance effects will be. Moreover, the results of the heterogeneous panel causality test reveal significantly strong unidirectional causality that runs from governance predictors to economic growth, while little evidence is found for feedback response and interdependencies between governance predictors in most of the panels. Based on the findings, appropriate policy recommendations are discussed.

Nexus between construction sector and economic indicators for Turkey and European Union evidenced by panel data analysis

PurposeThe research aims to study the regression, cointegration and causality between the construction sector (CS) and the Gross Domestic Product (GDP), considering other variables in the study such as interest rate, taxation, industry sector, investment and Foreign Direct Investment (FDI), which are analyzed through unique panel models. The study was conducted in Turkey and the ten other countries of the European Union (EU) from 1988 to 2019.Design/methodology/approachRegression, cointegration and causality methods were used to investigate the different types of relationships between variables in the models. Data were obtained from official databases and the study contains four main stages, which are explained in detail in the methodology section.FindingsThe study used the analysis methods of regression, cointegration and causality tests and found that the CS and GDP have long-run estimates and the relationship between the two for different countries is negative in a two-way direction. Results are detailed in the analysis section.Research limitations/implicationsNo data were available for the variables before 1988 for most countries, which led to a limited number of observations and issues in statistical analysis methods.Originality/valuePreviously, only input and output tables were used in the analysis. The impact of interest rate, taxation, investment and FDI has not been analyzed. Key variables are very relevant for Turkey, which suffers from chronical inflation and taxation regimes. These show variability with the EU countries for comparative analysis and have not been explored to date, remaining as a major gap for the construction industry. No attempts were made to use regression, cointegration and causality methods with variables. These analysis methods enable an understanding of the differences in variance (heteroscedasticity) and the presence of cross-sectional dependence (CSD), both critical for the reliability of the comparison of data sets and analysis.

PETROLEUM RESOURCE AND ECONOMIC WELFARE OF FIVE SELECTED LOWER-MIDDLE INCOME OF OIL PRODUCING COUNTRIES (i.e. NIGERIA, PAKISTAN, INDONESIA, EGYPT, INDIA).

Purpose – Economic welfare is one of the macroeconomic goals every country seeks to achieve, be it developed, least-developed or developing one. Some countries with abundant natural resources still suffer from achieving this goal. Based on this reason, this study was carried out to empirically look into the relationship between petroleum resource as measured by oil rent, and official exchange rate, and economic welfare as measured by gross domestic product per capita of five-selected lower-middle-income of oil producing countries (i.e. Nigeria, Pakistan, Indonesia, Egypt and India), using annual time-series data sourced from World Bank for the periods 2010-2020.
 Design/methodology/approach – This objective was achieved with the utilization of static panel data method coupled with other linear models such as; Pooled OLS, Fixed effects, and Random effects models.
 Findings – The results of the findings of Pooled OLS revealed that petroleum resource as measured by oil rent and official exchange rate had significant bearings on economic welfare as measured by gross domestic product per capita by 103.3 per cent and 0.14 per cent respectively on the average. The result further displayed that fixed effects model was an appropriate model to explain the significant fixed effects oil rent and official exchange rate had on improving gross domestic product per capita, when choice was made between Pooled OLS and fixed effects model. More so, the result further demonstrated that random effects model was the best model to explain the random effects oil rent and official exchange rate had on contributing positively to the gross domestic product per capita, when choice was made between fixed effects and random effects models. Finally, Panel Diagnostic residual test results showed that the series were normally distributed, hence the presence of cross-section dependence was not found in the model.
 Conclusion/Policy Implication – The study concluded that for these five-oil producing countries to achieve their economic welfare, they must adopt mixed effects model as portrayed by the findings of this study for policy inference. As this is geared towards enabling these countries to achieve policies that are aimed at pegging their exchange rate to the value of dollars, and increasing the value of crude oil production, so as to improve their economic welfares.