Slope Heterogeneity Research Articles

The growth effects of financial integration in the ASEAN countries

PurposeFinancial integration has played an essential role in achieving economic growth in the members of the Association of Southeast Asian Nations (ASEAN). However, its effects on economic growth in the region in the long run have been underexamined. This paper examines these effects for the ASEAN member countries.Design/methodology/approachA fully modified ordinary least squares (FMOLS) estimation is used to take into account two critical econometric issues in panel data analysis, including (1) cross-sectional dependence and (2) slope heterogeneity. The dynamic ordinary least squares estimation is also used for robustness analysis. The authors use the generalized least squares estimation to examine the effects in the short run.FindingsThis study’s empirical results confirm the important role of financial integration to economic growth in the ASEAN countries in the short term. However, the effects appear to disappear in the long term. The authors also find capital, labor, and human development positively contribute to economic growth in the region. International trade plays a significant role in supporting economic growth in the ASEAN in the short run. However, its effect seems to weaken in the long run.Originality/valueThe growth effects of financial integration in the ASEAN region in the long term have largely been neglected. As such, the authors examine these effects using updated data on financial integration. The authors extend this study’s analysis by considering foreign direct investment and financial depth as the alternative proxies for financial integration. Other estimation technique is also used as the robustness check.

Trade openness, globalization, and natural resources management: The moderating role of economic complexity in newly industrialized countries

Enhancing resource efficiency is the primary concern for industrialized countries. Climate susceptibility motivates the development and identification of resource efficiency drivers. Although the existing literature is evident on the factors influencing resource consumption, the role of economic complexity and trade openness is under-explored. Therefore, the study anticipates the short and long-run impact of trade openness, economic complexity, economic growth, and globalization in newly industrialized countries (NICs) from 1990 to 2019. The study utilized the Cross-section Augmented Autoregressive Distributed Lag (CS-ARDL) model to overcome the concerns of cross-section dependence and slope heterogeneity along with the Augmented Mean Group estimates to validate the outcomes. The results reveal that trade openness, globalization, and economic growth are negative, while economic complexity positively affects the material footprints in the NICs. The moderation effect of trade openness and economic complexity significantly affects resource consumption in the long run, whereas its effect is negligible in the short run. These findings signify that trade in industrialized countries is responsible for the excessive usage of materials in the region; however, resource depletion is meticulous if industrial processes are augmented with complex products. The findings imply that economic complexity neutralizes the negative consequences of globalization and revising the trade policies in the newly industrialized region could help to reduce resources consumption.

New insights from the STIPART model on how environmental-related technologies, natural resources and the use of the renewable energy influence load capacity factor

The rapid development in environmental-related technologies, economic growth and natural resources has promoted many undesirable environmental influences that affect living standards and human health. Consequently, the present research employed an inclusive indicator to quantify ecological eminence known as the load capacity factor. Considering this view, the existing body of literature has not provided a sufficiently supportive indication to discover the factors influencing the load capacity factor in terms of ecological excellence. To do this, the present study employs various panel data estimators and causality tests considering cross-sectional dependence and slope heterogeneity for the period 1990–2019 to analyze the environmental impacts of environmental technologies, economic growth, natural resources, renewable energy consumption, and urbanization for 17 Asian-Pacific Economic Cooperation (APEC) countries. The study results suggest that economic growth reduces environmental quality.In contrast, natural resources, technological development, urbanization, and renewable energy increase the load capacity factor, which indicates environmental sustainability while considering nature's supply and demand aspects. Based on these findings, APEC policymakers should take advantage of technological development, urbanization, and renewable energy. They should transform their current economic growth models into an environmentally friendly structure to achieve their environmental goals and contribute to a sustainable world order.

Bitcoin trading, economic growth, energy use, and CO2 emissions: An advanced panel study of emerging market economies

Carbon dioxide emissions pose a severe threat to the global eco-system and human health, yet at the same time the exponential growth of Bitcoin trading, unsustainable mode of current economic development, and the low efficient energy usage have become burgeoning issues in emerging market economies. By applying advanced econometric techniques, this research empirically tests the dynamic impacts of Bitcoin trading, economic growth, and energy use on CO2 emissions in the top 20 Bitcoin-trading emerging market economies from 2013 to 2020, highlighting results on the existence of cross-section dependence, slope heterogeneity, and unit roots in the panel data. Moreover, Bitcoin trading, economic growth, and energy use have a significantly positive effect on CO2 emissions from a long-term perspective. Findings further show that CO2 emissions have a bi-causal correlation with all three determinants. Relevant implications are offered as follows. For academic researchers, cross-section dependence and slope heterogeneity are important considerations, and ignoring them would lead to significantly biased inferences. Emerging market governments should introduce eco-friendly technology for Bitcoin trading, modify the present extensive mode of economic growth, and guard against unsustainable energy consumption.

The nexus between female unemployment and labor supply: evidence from Arab countries

With an emphasis on groups like women who have an elastic labour supply, this study examines the link between unemployment and labour market participation in Arab countries from 1991 to 2021. The bootstrap panel Granger causality method is used to determine the causal direction, considering cross-sectional dependency, slope heterogeneity, and structural breaks. The results provide mixed evidence for the invariance, discouraged worker, and additional worker hypotheses, which qualify earlier findings. Of the 17 countries, only 4 are in favour of the unemployment invariance theory. Policies that raise the growth path of capital, productivity, and increase the effective working-age population may influence the unemployment rate.

None-linear nexus between natural resources dependency, foreign direct investment, and environmental sustainability in newly industrialized countries

This study explores the non-linear effect of natural resource rents and foreign direct investment (FDI) on consumption-based carbon emissions in Newly Industrialized Economies (NIEs) from 1995 to 2020. Furthermore, this study examines the interactive effect of mineral resources and FDI, coal resources, and FDI using the method of moments quantile regression (MMQR). It also apply dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), and fixed effect-ordinary least square (FE-OLS) for the robustness. The preliminary findings confirm that cross-sectional units are interdependent with slope heterogeneity and panel cointegration. The subsequent results through MMQR reflect that mineral rents and coal rents tend to increase the carbon emissions across all the quantiles (0.10th to 0.90th); however, the average change in the dependent variable is higher at higher-order quantiles (0.60th-0.90th) and lower at lower order quantiles (0.10th to 0.30th). FDI tends to control trade-adjusted carbon emissions in all three ranges of quantiles. The interactive effect of mineral resources and FDI and coal resources and FDI support a significant reduction in carbon emissions. These findings suggest promoting the international flow of investment in the energy-efficient and natural resource industry for sustainable development.

Correlates of human development in Africa: Evidence across gender and income group

Gender inequality is high in Africa compared to other regions of the world. This disparity jeopardises the efforts targeted at improving human development and economic growth in the continent. This study provides empirical evidence on the drivers of human development in Africa across gender and country income groups, covering 54 countries over the period 1990 to 2019. It employed the Mean Group estimator for analysis to accommodate slope heterogeneity and cross-sectional dependence. The paper used Human Development Index (HDI) to proxy human development, while HDI across gender was employed to capture gender differences in human development. Country income grouping followed the World Bank country classification into low, lower-middle and upper-middle-income economies. The findings showed more determinants of HDI when disaggregated across gender than otherwise. The drivers of HDI are similar across gender for each country income group, with infrastructure, particularly ICT shown to have a positive effect in the long run for all country groups. For lower-middle and upper-middle income countries, fertility rate induced a significant negative effect on HDI and gender human development but only in the long run. However, the effect was insignificant for male and female HDI in low-income countries. Moreover, an increase in real Gross Domestic Product (GDP) promotes human development regardless of a country's income classification. A larger positive effect of GDP was observed on the HDI for low-income countries. Therefore, in the bid to improve human development in Africa, efforts should continually be intensified towards promoting GDP growth regardless of the level of growth in macroeconomic income. Policies targeted at reducing fertility rates and increasing ICT are also encouraged as these will improve HDI and close the gap in HDI across gender.

Assessing technological innovation and sustainable environment: Tourism perspective of advanced panel methods

The current study aims to analyze the influence of technological innovation, economic growth, tourism and renewable energy consumption on the carbon emissions in four South Asian economies covering the period 1990-2020. This study employed the cross-sectionally augmented autoregressive distributed lag model – a the third-generation estimator as it tackles the issues of slope heterogeneity, panel cross-section dependency, endogeneity, and stationarity. Also, this study uses the augmented mean group as a robustness test and Granger panel causality heterogeneity test. The results display that economic growth significantly enhances emissions level, whereas achievement of the threshold income level significantly reduces environmental degradation – validating the environmental Kuznets curve hypothesis in the region. Besides, tourism, renewable energy consumption, and technological innovation substantially reduces carbon emissions in the regions in short- and long-run. These findings are robust, and a bidirectional causal association exists between the explanatory variables and carbon emissions. The findings suggest policy concerning the adoption of renewable energy, considering industrial sector’s structural transformation, investment in technological innovation and promotion of tourism in the region.

Linkages between renewable energy, financial development, and environmental sustainability in Asian countries

Financial development and green technologies are imperative to accomplish sustainable development goals in developed and developing economies. Therefore, this study examines the dynamic influence of renewable energy consumption, financial development, and green technology innovations on carbon dioxide emissions using selected Asian countries’ data from 1990 to 2019. It applies the Cross-Sectional Augmented Distributed Lag model to address the slope heterogeneity and the cross-sectional dependency issues in our panel. The long-run results revealed that financial development increases carbon emissions while green innovation and renewable energy consumption reduce emissions. Nevertheless, the emissions mitigating effects of both variables significantly varied, and green innovation possesses a more substantial impact on emissions reduction. The short-run results also produce similar outcomes; however, their coefficient’s magnitude is relatively lower. Moreover, the error correction term is significantly negative, suggesting a 25% speed of adjustment in case of any deviation from steady-state equilibrium. These results suggest integrating renewable energy and green technology innovation into the financial sector to neutralise its negative consequences.

Achieving green environment in Brazil, Russia, India, China, and South Africa economies: Do composite risk index, green innovation, and environmental policy stringency matter?

AbstractThe Paris Accord has brought the world's governments together to begin implementing plans for their individual economies to become carbon‐free. The goal of attaining low‐carbon growth is not, however, as simple as it would appear since the world economies, which are dependent on fossil fuels and are fast expanding, are concentrated on accelerating economic expansion at the price of worse environmental effects. In light of this, the study aims to investigate the combined effects of the composite risk index (CRI), green innovation (GINOV), and environmental policy stringency (EPS) on carbon dioxide (CO2) emissions in the context of Brazil, Russia, India, China, and South Africa (BRICS) countries while controlling for gross domestic product (GDP) and renewable energy research and development (RERD) over the period from 1960 to 2020. The research addresses the problems of cross‐sectional dependence and slope heterogeneity in the data set used for analysis by using the second‐generation cross‐sectionally augmented autoregressive distributed lags framework to evaluate long‐ and short‐run models. The corresponding findings show cointegrating relationships between the research variables. Additionally, the results of the regression demonstrate that EPS, GINOV, and RERD contribute to a long‐term decrease in CO2 emissions. CRI and GDP, however, increase CO2 emissions. It is suggested that environmental policies be tightened, GINOV and RERD expenditures be promoted, political stability and institutional quality be maintained, and clean economic growth strategies be adopted in order to help the BRICS countries reduce sectoral risks, create a sustainable environment, and decarbonize their respective economies.

Technological pathways to decarbonisation and the role of renewable energy: A study of European countries using consumption-based metrics

To decarbonise Europe in the post-COP26 era, current policies must be adjusted to account for the cross-border consequences of its consumption pattern. Using consumption-based Kaya identity metrics adjusted for emissions and energy embodied in traded goods and services, this study examines the nexus between technological factors defining energy transition progress, specifically energy and carbon intensities of the consumption mix, and carbon dioxide (CO2) emissions, in a sample of 20 European countries from 1995 to 2019. The empirical steps rely on panel-data estimators that are robust to cross-sectional dependence and allow for heterogeneous slope coefficients. The results show that energy and carbon intensities of the consumption mix have a positive relationship with CO2 emissions but a negative relationship with renewable energy consumption. The findings also verify an inverted U-shaped relationship between affluence and CO2 emissions through the energy and carbon intensity metrics. Additional tests show a unidirectional causality from carbon intensity of the energy mix to CO2 emissions and from renewable energy to the carbon intensity. Also, bidirectional causality exists between CO2 emissions and per capita GDP and energy intensity, and between renewable energy and energy intensity. By implication, renewable energy provides the technological path to mitigating consumption-induced emissions in Europe.

Interconnecting Sustainable Development Goals 7 And 13: The Role of Renewable Energy Innovations Towards Combating the Climate Change

This research examines the trends in environmental footprints through energy innovations, digital trade, economic freedom, and environmental regulation from the context of G7 economies. Quarterly observations from 1998-2020 have been utilized for the advanced-panel model entitled Method of Moments Quantile Regression (MMQR). The initial findings confirm slope heterogeneity, interdependence between the cross-sectional units, stationarity properties, and panel cointegration. The results through FM-OLS, D-OLS, and FE-OLS justify that energy innovations, digital trade, and environmental regulations control ecological damages. In contrast, economic freedom and growth are causing more damage to nature, like ecological footprints (EFP). Similarly, the results through MMQR confirm that the impact of energy innovations, digital trade, and environmental regulations is accepted as a panacea to control environmental degradation in G7. However, the magnitude of the coefficient varies across different quantiles. More specifically, the findings show that the impact of energy innovations is highly significant at 0.50th quantile. In contrast, through digital trade, the impact on EFP is only significant under medium and higher order quantiles (i.e., 0.50th, 0.75th-1.0th). Contrarily, economic freedom is causing more EFP across all the quantiles, where the findings are highly significant at 0.75th quantile. Besides, a few other policy implications are also discussed.

Impact of trade, technology, and tourism on resources depletion across Belt and Road Node countries

Trade, tourism, and technology significantly impact the environment, and maintaining a balance between resource conservation and economic growth has been one of the most difficult challenges in recent years. The curtailing of resource consumption is decisive for halting and reversing natural resource depletion and decarbonization. Therefore, there is a need to identify the factors that drive or reduce resource consumption. This study investigates the role of trade, technology, tourism, and economic growth in reducing/inhibiting resource depletion in selected Belt and Road Node (BRI) countries from 2003 to 2019. After confirming the data's cross-sectional dependency, slope heterogeneity, stationarity, and cointegration among variables, the study applied the “Cross-Sectionally Augmented Autoregressive Distributed Lag” (CS-ARDL) for the panel estimates. The study results suggested that trade, tourism, and economic growth increase the trade-adjusted material footprint (proxy of resource depletion) in the BRI countries, whereas technology upgradation limits resource depletion. Interestingly, technology development reduces the adverse effects of trade on the material footprint. Thus, integrating technology in trade and tourism is imperative to ensure long-term resource sustainability in the BRI region.

Environmental quality and energy transition prospects for G-7 economies: The prominence of environment-related ICT innovations, financial and human development

Energy transition and reducing greenhouse gas emissions are fundamental to achieving sustainable development and ensuring a bright and healthy future. To contribute to the empirical literature on these objectives, this study explores the long-term influence of environment-related ICT innovations (EICT) on energy transition and greenhouse gas emissions (GHGE) in G-7 economies for the first time, while considering financial development (FD) and human development (HD). Additionally, the study investigates the moderating role of FD with EICT and HD in energy transition and GHGE. Using a Cross-Sectional Augmented Distributed Lag (CS-ARDL) technique to tackle the issues of cross-sectional dependency and slope heterogeneity, the study evaluated data from 1990 to 2020. The results indicate that EICT, FD, and HD have a significant positive effect on long-term energy transition, and mitigate GHGE in G-7 economies. Furthermore, the influence of EICT and HD on energy transition and GHGE is amplified in the presence of financial development, as evidenced by the moderating effect of FD. Based on these facts, the study suggests various policy measures, such as investing in clean technologies and education, to promote the energy transition and environmental quality in G-7 economies to achieve sustainable development goals.

Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects

A large literature on modelling cross-section dependence in panels has been developed through interactive effects. However, there are areas where research has not really caught on yet. One such area is the one concerned with whether the regressors are correlated with factor loadings or not. This is an important issue because if the regressors are uncorrelated with loadings, we can simply use the consistent two-way fixed effects (FE) estimator without employing any more sophisticated econometric methods such as the principal component (PC) or the common correlated effects estimators. We explore this issue, which has received surprisingly little attention and propose a Hausman-type test to address the matter. Further, we develop two nonparametric variance estimators for the FE and PC estimators as well as their difference, that are robust to the presence of heteroscedasticity, autocorrelation and slope heterogeneity. Under the null hypothesis of no correlation between the regressors and loadings the proposed test follows the chi ^{2} distribution asymptotically. Monte Carlo simulation results confirm satisfactory size and power performance of the test even in small samples. Finally, we provide extensive empirical evidence in favour of uncorrelated factor loadings. In this situation, the FE estimator would provide a simple and robust estimation strategy which is invariant to nontrivial computational issues associated with the PC estimator.

Technology innovations and carbon neutrality in technologically advanced economies: imperative agenda for COP26

This article aims to fill the literature gap while examining the role of green innovation, climate change adaptation technologies, technological diffusion, and environmentally related tax revenues in dealing with carbon neutrality among seven technologically advanced economies (T.A.E.-7) from 1990 to 2018. We employ advanced panel estimators to address slope heterogeneity and cross-sectional dependency issues. The long-run results show that green technological innovations and technological diffusions have significantly and negatively impacted carbon emissions in sample countries. Meanwhile, the role of environmental policy is also significant in addressing environmental vulnerabilities. These findings suggest that climate tech is imperative to ensure carbon neutrality in the long run; however, their marginal effects vary in magnitude, particularly concerning diffusion and adaptation. Similar results are endorsed using alternative estimators addressing endogeneity issues and recommending climate tech’s inclusive framework to support the green growth agenda.

Relating economic openness and export diversification to eco‐efficiency: Is green innovation critical?

AbstractA critical debate on whether macro economies would achieve sustainability targets via green innovations could reach some informed consensus, given it is explicit how those innovations, directly and indirectly, interact with both economic and ecological systems through international economic activities. To unriddle this puzzle, this work is the initial attempt to examine how green innovation moderates the influence of economic openness and export diversification on eco‐efficiency in selected 13 European Union (EU) economies from 1995 to 2014. We employ advanced second‐generation econometric approaches robust to cross‐section dependence, slope heterogeneity, and the omitted variable bias concerns in panel data. The main results are firstly, economic openness and export diversification tend to deteriorate eco‐efficiency in the absence of a green innovation moderator. Secondly, in green innovation moderation models, both economic openness and export diversification are likely to improve eco‐efficiency. Thirdly, green innovation not only directly promotes eco‐efficiency but also positively moderates the influence of economic openness and export diversification on eco‐efficiency. Fourthly, a one‐way causality exists from green innovation moderators to eco‐efficiency, while economic openness, export diversification, green innovation, and other control variables establish a two‐way causal relationship with eco‐efficiency. Finally, for green innovation in place, the policy shocks of economic openness and export diversification are predicted to achieve the eco‐efficiency effects in more than 1 year in the EU members, while green innovation catalyses this convergence speed. Besides, economic openness and export diversification policies should be integrated with the green innovation framework to achieve eco‐efficiency for sustainable development

Inclusivity between digital trade, human development, and environmental quality: moderating role of green innovations in BRICS countries

This research investigates the role of digital trade, human development, globalization, and green innovations on ecological footprints (EFP) for BRICS countries. Unlike the earlier studies, this research expands the empirical contribution while examining the moderating effect of green technologies on the relationship between stated explanatory variables and EFP. Initially, we testify the presence of cross-sectional dependence, unit root tests, cointegration, and slope heterogeneity and subsequently apply cross-sectionally augmented autoregressive distributed lags (CS-ARDL) using annual data from 1995 to 2019. The empirical findings exhibit the significance of digital trade, human development, and green technology innovations in complementing low EFP in the long run. However, globalization tends to increase ecological footprints. Moreover, the findings in the short run provide a symmetrical (positive/negative) effect of stated explanatory variables on EFP; however, their marginal impact is lower. Additionally, the moderating effect of green technologies on the relationship between digital trade and EFP and between human development and EFP is significantly negative, supplementing the existing association. Therefore, an inclusive digital and human development policy is imperative to ensure sustainable ecology.

Fiscal decentralization, environmental policy stringency, and resource sustainability: Panacea or Pandora's box in high resource consuming countries

Improving fiscal management and resource efficiency has become one of the imperative policy agendas, particularly for resource-rich economies. Due to ecological susceptibility and resource scarcity, exploring the core factors of resource consumption is critical for designing an effective climate policy. Manifestly, fiscal decentralization has an enormous potential to pursue sustainable development. Therefore, this study investigates the impact of fiscal decentralization and ecological policy stringency on consumption-based resource footprint (RF) in resource-intensive countries from 1990 to 2019. It applies a cross-section augmented distributive lag estimator in resolving the issues of cross-section dependency and slope heterogeneity. The study's long and short-run outcomes reveal that revenue decentralization and environmental governance significantly reduce RF. However, the contradictory results are examined by expenditure decentralization, which promotes RF. Moreover, strict environmental regulations moderate the positive influence of expenditure decentralization, implying that the resource-decoupling effect of expenditure decentralization on RF is reduced when the countries are embodied with effective environmental governance systems. Similarly, the alternative methods endorsed identical findings, and this study offers valuable policy suggestions to strengthen the environmental protection system and formulate sound ecological policies for efficient resource utilization under the decentralization framework.

How does the travel and tourism industry contribute to sustainable resource management? The moderating role of ICT in highly resource-consuming countries

This study applies moments quantile regression (MMQR) to investigate the asymmetric impact of the travel and tourist industry, information communication technologies (ICT), and economic growth on consumption-based material footprints (CMF) in high-resource consuming economies from 1995 to 2019. Preliminary tests confirm the slope heterogeneity, cross-sectional dependency, non-stationarity, and panel cointegration in sample data. The long-run coefficients show that travel and tourism industries lead to higher CMF, and ICT neutralizes these negative consequences. MMQR results imply that tourism and travel services increase CMF across major quantiles (0.25th-1.0th). However, their impact on CMF is highest under higher-order quantiles (0.9th) and lower at lower and medium-order quantities (0.25th, 0.50th, and 0.75th). The findings illustrate that digitalization leads to sustainable tourism and eventually lower resource depletion.