Correlated Effects Mean Group Estimator Research Articles

Bridging the digital divide: the impact of technological innovation on income inequality and human interactions

This study seeks to understand the nuanced relationship between technological innovation and income inequality with an emphasis on the broader implications of this interplay on human–technology interactions in diverse socioeconomic settings. Using cross-country panel data from 59 nations (31 developed and 28 developing) from 1995 to 2020, the study employed the common correlated effect mean group (CCEMG) estimator. The robustness of our findings was validated using the augmented mean group (AMG) estimator and the panel causality test. The results indicate that technological innovation, while heralded for its potential to bridge communication and operational gaps, inadvertently exacerbates income disparities, with a pronounced effect in developed economies. Moreover, interactions between technological innovation and variables such as economic growth, globalisation and export trade introduce additional complexities, including both buffering and acceleration effects on the primary relationship. These findings shed light on the double-edged nature of technological advancements, underscoring the need for informed policy-making that harnesses the benefits of innovation while mitigating its unintended socioeconomic consequences. The study sets the stage for domain-specific explorations such as in education, public health and business. It also invites interdisciplinary discourse on the ethical and behavioural dimensions of technology adoption, especially user experiences and societal outcomes.

Economic integration and consumption risk sharing: A comparison of Eurozone and OECD countries

Economic theory predicts that economic integration can facilitate improvements in international consumption risk sharing. We test this proposition by comparing risk sharing among Eurozone members and members of the Organisation for Economic Co-operation and Development (OECD) using a dynamic common correlated effects mean group estimator (DCCEMG). The results reveal that the OECD members outperform the Eurozone members in terms of short run and long run risk sharing, despite the barriers to risk sharing being considerably lower among the latter. We attribute this outcome to lower business cycle synchronization and stock return correlations among OECD members, which creates better opportunities to share risk within the group. The results highlight the trade-off between the benefits of business cycle synchronization and international risk sharing. More tightly integrated economies, facilitate trade in assets that promotes better portfolio diversification, while at the same time are characterized by higher business cycle synchronization that depletes agents of risk sharing opportunities. Consequently, our results give strong support to the hypothesis of “diminishing international diversification potential”. However, the benefits associated with the improved risk sharing are increasing with the number of countries in the monetary union.

Foreign Direct Investment, Technological Innovations, Energy Use, Economic Growth, and Environmental Sustainability Nexus: New Perspectives in BRICS Economies

In the current era, economic growth is inevitable for global prosperity but achieving sustainable economic development is one of the significant challenges for the developing world. The present study explores the impacts of foreign direct investment, energy use, and technological innovations on the economic growth and environmental quality of BRICS countries for the period 1990–2018. We used the augmented mean group (AMG), the common correlated effects mean group estimator (CCEMG), and several other modern-day empirical techniques to analyze data. The findings show that foreign direct investment increases economic growth but harms the environmental sustainability of BRICS countries. Moreover, we have seen that energy use is directly proportional to economic growth and CO2 emissions. This confirms that energy use is one of the factors which harms the environmental quality in BRICS economies. Likewise, economic growth increases CO2 emissions. On the other hand, technology innovation has a direct relationship with economic growth but an inverse relationship with CO2 emissions as it improves the environmental sustainability of the BRICS region. This research adds to the existing literature by exploring the interplay between FDI, innovation, energy use, economic growth, and environmental outcomes in the context of major emerging economies. The study’s findings provide empirical evidence on the role of these factors in shaping the environmental outcomes in the BRICS economies, and they have implications for policymakers and stakeholders in addressing environmental challenges such as global warming and climate change.

Empirical linkages of the construction sector, intensive energy consumption, and economic openness with chemical oxygen demand pollution.

Though construction sector development and economic openness contribute to regional economic development, they have also been debated to pose some environmental challenges. Along these lines, we explored the long- and short-term connections of intensive energy consumption, economic openness, and construction sector development with the chemical oxygen demand throughout the scales of regional development of China's 30 provincial units over the 2004-2021 period. Theoretically, we contribute to the existing knowledge by incorporating chemical oxygen demand pollution, construction sector development, and economic openness to the Kaya identity's baseline framework. Empirically, we apply a series of advanced methods of panel data econometrics for robust results. Our key findings are as follows: First, we revealed a long-term stable cointegrating association among our variables of interest. Second, using the common correlated effect mean group estimator, we unfolded that the intensive energy consumption showed a chemical oxygen demand pollution reduction influence in both the long and short term, demonstrating the most substantial influence in the high regional development panel while expressing the least powerful influence the least regional development setting. Third, we unveiled that economic openness and construction sector development showed a linear chemical oxygen demand pollution enhancement influence in moderately and least developed regions. Nevertheless, both established an inverted U-shaped linkage with chemical oxygen demand pollution for the whole country as well as for high regional development data samples. Eventually, we found consistent estimates across long- and short-term investigations regarding signs of relationships; however, long-term effects remained more powerful than short-term ones. These findings would serve as factual scientific knowledge to help local as well as national governments create the optimal environmental regulations for the construction sector to achieve the sustainable development goals (SDGs), especially the Climate Action Plan (i.e., SDG-13).

Achieving sustainable environment through infrastructure and energy structure developments: empirical evidence from BRICS.

The development of an environment that is sustainable requires infrastructure matching this goal. Moreover, it is almost impossible to achieve this goal without the requisite energy structure. Devising an energy structure that is both effective and efficient must precede the desired infrastructure to achieve sustainability goals. Therefore, it is important to look into the nexus of energy structure, infrastructure, and carbon emissions in "Brazil, Russia, India, China, and South Africa (BRICS)" countries under the growth and environment hypothesis. To empirically estimate the said nexus, robust econometric techniques are adopted. This paper employs panel data analysis techniques to investigate the relationship between infrastructure, energy consumption, and carbon emissions in the BRICS countries. The econometric estimation methodology includes a cross-sectional dependence test, unit root attribute of the panel data using the cross-sectionally augmented Im Pesaran and Shin(CIPS) test, and estimation of co-integration among the variables, and to address the issues in the panel data, augmented mean group (AMG) technique and common correlated effects mean group (CCEMG) estimator were employed. Findings suggest the existence of a supportive role of infrastructure and energy structure in abating carbon emissions. It is suggested that the BRICS economies need to enhance their investment in infrastructure and energy structure for them to create a sustainable environment. Findings are also robust to short- and long-run policy implications. This study is a step forward toward the Sustainable Development Goals (SDGs).

The impact of natural resources on technology innovation from cross-country panel data: A comparative analysis and policy-level insights

The study aims to examine the direct impact of natural resources on technology innovation by considering the critical role of five dimensions of technology innovation (ICT development, R&D activity, skills, industry activity and access to finance). For this purpose, the common correlated effect mean group (CCEMG) estimator is applied to estimate cross-country panel data encompassing 102 countries from 2008 to 2018. Under the global sample, the empirical evidence strongly supports that natural resources hinder ICT development and R&D activity but have a positive impact on industry activity and access to finance, which shows a traceable path of the resource blessing. In addition, for overall technology innovation, ICT development, R&D and industry activity, the resource curse is effectively transformed into a resource blessing in high-income countries, which benefits from the high level of manufacturing, modern services and industrial structure. When considering the chronological evolution, natural resources show a negative effect on overall technology innovation in the first period and a positive effect in the second period in low-income countries. On this basis, challenges and initiatives in three phases are proposed to better achieve resource blessing, including resource regulation, human resource reserve, international trade adjustment, industrial structure transformation and financial investment optimization. Lastly, policy-level insights on the different dimensions of technology innovation are proposed to provide guidance and valuable reference for policymakers.

Do real estate investment companies profit from house price growth? Evidence from Portugal

PurposeThis study aims to study the sensitivity of nonlisted real estate investment companies’ accounting earnings to house prices. This study evaluates whether house price changes determined these companies’ return on equity (ROE) or if other factors influenced the industry’s profitability beyond house price growth.Design/methodology/approachThe authors collected a ten-year sample with the aggregate ROE of Portugal’s real estate investment companies, split by regions, and data on house prices and the per capita gross domestic product as a control variable. The authors ran a national-level time series with the canonical cointegrating regression estimator, which is robust to a small sample size; the authors also performed a regression on regional-level panel data with the common correlated effects mean group estimator, thus allowing slope coefficient heterogeneity and controlling for cross-sectional dependence. The authors also ran ordinary least squares regressions as a means of comparison.FindingsThis study found that an increase in the house price is not translated into an increase in the aggregate ROE. The results are robust with a reduced survivorship-biased sample, meaning that even the best-succeeded real estate investment companies do not have their accounting ROE dependent on house price growth.Research limitations/implicationsThe sample size is small and specific to one country. This paper did not study the housing market structure to verify whether it operates under monopolistic competition, which could further explain the attained results.Practical implicationsPolicy decision-makers should know that there are no excess profits in the real estate investment companies’ industry because of house price growth that could be subject to windfall taxes.Originality/valueTo the best of the authors’ knowledge, the connections between house prices and real estate investment companies’ accounting earnings have never been studied.

Identifying the roles of energy and economic factors on environmental degradation in MINT economies: a hesitant fuzzy analytic hierarchy process.

Globally, research communities have been studying the different determinants of environmental degradation or pollution using different contexts and methods. In this study, we identify several energy and economic factors, such as energy consumption (EC), gross domestic product (GDP), energy production (EP), urbanization (URB), and foreign direct investment (FDI) as the most effective factors of environmental degradation by obtaining several environmental researchers' opinions and using the hesitant fuzzy analytic hierarchy process. In the later stage of the analysis, we use these variables as regressors of the ecological footprint (EF) as a proxy for environmental degradation. Since we find evidence of cross-sectional dependence among the members of the variables, we use second-generational panel tests. First, we test the stationarity of the variables using the cross-sectionally augmented IPS (CIPS) panel unit test. The results show that the regressors have different orders of integration. So, we employ the Durbin-Hausman panel cointegration test to test the existence of a long-run relationship between the variables. Having found a long-run relationship, we estimate the long-run coefficients using the common correlated effects mean group estimator, which reveals that energy consumption has an increasing effect on the EF in Indonesia and Turkey, while energy production has a negative impact in Mexico and Turkey. While GDP has an increasing effect in all countries, FDI has a similar effect in only Indonesia. Moreover, URB decreases the ecological footprint in Nigeria, while it increases in Turkey. Our approach to the evaluation of environmental degradation can be generalized to other regions as well as where there is a significant need to understand the roles of different drivers on environmental degradation or pollution.

Revisiting the Environmental Kuznets Curve Hypothesis in the MENA Region: The Roles of International Tourist Arrivals, Energy Consumption and Trade Openness

This paper employed advanced panel methods to examine the effects of international tourist arrivals on CO2 emissions in the Middle East and North Africa (MENA) region over the period of 1995–2018. To analyze the predictive power of tourist arrivals for CO2 emissions, the panel Granger non-causality test was employed. Employing the common correlated effects mean group estimator showed that tourist arrival reduces CO2 emissions, while energy consumption and trade openness are the main contributors of CO2 emissions. Results also showed that although first-generation estimators confirmed the Environmental Kuznets Curve (EKC) hypothesis, according to the CCE-MG estimator, an inverted U-shaped association between economic progress and CO2 emissions does not exist. Furthermore, the null hypothesis of non-Granger causality from tourist arrivals to CO2 emissions was rejected. The findings suggest taking a more sustainable approach to tourism development and energy conservation in the long run.

Evaluating the effect of urbanization and foreign direct investment on water use efficiency in West Africa: application of the dynamic slacks-based model and the common correlated effects mean group estimator

Evaluating the effect of urbanization and foreign direct investment on water use efficiency in West Africa: application of the dynamic slacks-based model and the common correlated effects mean group estimator

Renewable energy consumption a panacea for Sustainable economic growth: panel causality analysis for African blocs

ABSTRACT The issue of increased renewable energy consumption has been widely debated, and this has become a central energy policy concern for developing and developed countries. The existing literature provides evidence that there is a positive relationship between energy consumption and economic growth in developed economies. However, findings in respect of developing/emerging economies remain inconclusive. Thus, this paper aims to investigate the impact on renewable energy consumption on economic growth by controlling other macroeconomic variables for regions of Sub-Saharan Africa (East, Central and West) covering the 1990–2018 sample period. For this purpose, common correlated effects mean group estimator (CCEMG) and Dumitrescu-Hurlin Granger causality test approach are used to consider both cross-sectional dependency and cross-country heterogeneity across countries. The CCEMG result indicates that an increase in renewable energy consumption led to reduction in economic growth even when the sample is analyzed based on geographical locations as East, West, and Central Africa. Granger causality results validate the feedback hypothesis for only Central Africa; the growth hypothesis is supported for East and West Africa. The empirical results suggest that energy planners, governments, and policy makers must act together to increase the renewable energy consumption share in her energy mix to promote economic growth for regions of Sub-Saharan Africa.

Beyond the environmental Kuznets Curve in E7 economies: Accounting for the combined impacts of institutional quality and renewables

This study explores the applicability of conventional environmental Kuznets curve (EKC) with an extension for the case of emerging industrialized economies, comprised of China, India, Brazil, Mexico, Russia, Indonesia, and Turkey, for annual time frequency from 1995 to 2016. This study is distinct from that already documented in the extant literature by extending the traditional EKC phenomenon by accounting for the combined impact of institutional quality and renewables in E7 blocs. The countries under review are known to be emerging and still at their scale stage of their growth path. As such, the need to explore the theme is pertinent for stakeholders. Empirical framework is built on second-generational panel econometrics strategies that consist of Augmented Mean Group, Common Correlated Effects Mean Group estimator, Driscoll-Kraay and Dumitrescu and Hurlin Causality analysis, which is superior to first-generation methods. Our study validates the EKC phenomenon in E7, i.e., where emphasis is placed on economic expansion relative to the quality of the environment. The EKC phenomenon is validated by the deteriorating effect of fossil-fuel energy consumption in the bloc. However, renewables are seen as a panacea to reduce pollution emission as renewable energy exerts a negative and statistical relationship with CO2 emission over the sampled period. Additional results show that weak institution also dampens the quality of the environment in E7. These outcomes are suggestive to policy makers to reinforce their commitment to the quality of the environment in terms of growth and energy transition from fossil fuel to clean energy sources. Further policy prescriptions are presented in the concluding section.

Determinants of foreign direct investment in BRICS- does renewable and non-renewable energy matter?

The prime objective of the current research is to investigate factors affecting foreign direct investment (FDI) inflows into BRICS countries with a special focus on energy impact on FDI inflows from 1990 to 2018. The empirical results of pane fully modified ordinary least squares (F.M.O.L.S.), dynamics ordinary least squares (D.O.L.S.), Cross-sectional autoregressive distributed lag estimators (CS-ARDL), Augmented Mean Group estimator (AMG), and Common Correlated Effects Mean Group Estimator (CCEMG) exhibits that all variables have statistically positive, while inflation rate has negative effect on FDI. The long-run results suggest that both types of energy utilization (i.e., renewable & non-renewable) are positively contribute to FDI inflows. In terms of magnitude, the effect of renewable energy utilization is higher as compared to non-renewable energy utilization on FDI. Moreover, market size (GDP), trade, and tourism are the key driver of FDI inflows. In contrast, economic de-stability measured through inflation rate discourages FDI inflows into BRICS countries. These findings recommend that the legislature of BRICS countries need to extend the global and national plan to manage the FDI inflows, but it also needs to increase the utilization of renewable energy in the BRICS region and thereby bolster social welfare.

Nexus Between Carbon Emissions, Energy Consumption, Urbanization and Economic Growth in Asia: Evidence From Common Correlated Effects Mean Group Estimator (CCEMG)

This study investigates the dynamic relationships between carbon emission, urbanization, energy consumption, and economic growth in a panel of 42 Asian countries for the period 2000–2014 using dynamic common correlated effects panel data modeling. This study employs second generation cross-sectional Pesaran (J. Appl. Econom., 2007, 22(2), 265-312) panel unit root, Westerlund panel cointegration tests (Econom. Stat., 2007, 69(6), 709-748), and Pesaran’s (Econometrica, 2006, 74(4), 967-1012) common correlated effects mean group estimation technique. These approaches allow for cross-sectional dependence, and are robust to the presence of common factors, serial correlation, and slope heterogeneity. The Common Correlated Effect Mean Group test reveals a high average coefficient of 0.602 between carbon emission and energy consumption while low coefficients of 0.114 and 0.184 for the pairs of carbon emission-urbanization and carbon emission-GDP, respectively for the panel as a whole, suggesting a cointegration between carbon emission, urbanization, energy consumption, and economic growth. The results indicate that there is relatively high carbon emission especially for highly populated and geopolitical risk Asian countries in the short run. Findings reveal long run relationships between the variables, which is attributed to the on-going carbon taxation and energy prices. Our results are robust to PMG-ARDL estimator. Overall, these findings cast important implications on renewable energy policy and urban planning insights for the policymakers.

Testing the effect of sustainable energy and military expenses on environmental degradation: evidence from the states with the highest military expenses.

This paper aims to define the effects of military expenses and renewable energy consumption on carbon dioxide emissions for the ten countries with the highest military expenses, namely, Saudi Arabia, Israel, Russia, the USA, South Korea, India, France, Australia, China, and the UK from 1993 to 2017. The research applied the common correlated effects mean group estimator (CCEMG), dynamic CCEMG, and cross-sectional augmented autoregressive distributed lag (CS-ARDL) approaches. These dynamic techniques elucidate slope heterogeneity and cross-sectional dependency and solve the problem of unit root bias. It is found that the environmental Kuznets curve (EKC) hypothesis does not apply for this region. The findings demonstrate that military expenses increase carbon dioxide emissions; thus, the treadmill theory of destruction is valid for the panel of these countries, and it is also found that the consumption of sustainable energy decreases CO2 emissions. This suggests that a reduction in pollution can be achieved by increasing sustainable energies in the use of military vehicles to decrease emissions. Further important policy implications for the 10 countries with the highest military expenses are provided at the end of the paper.

EKONOMİLERDE YAPISAL DÖNÜŞÜM VE BELİRLEYİCİLERİ: SEÇİLMİŞ GELİŞMİŞ VE GELİŞMEKTE OLAN ÜLKELER ÜZERİNE BİR PANEL VERİ ANALİZİ

In this study, the structural transformation phenomenon and its determinants, which are of great importance for economic growth and development, are examined by panel data analysis. For this purpose, the structural transformation that occurred between 1970-2017 in 19 selected developed and 24 developing countries is analysed through the calculated Structural Transformation Index. It is determined that the structural transformation index values in the developing countries are higher than the developed country values. Then, Panel Data Analysis is applied to country groups to determine the impact of determinants of structural transformation on structural transformation. As a result of Driscoll-Kraay estimation, it is observed that the impact of foreign trade and population in developed countries is positive and life expectancy at birth is negative. The effects of variables of gross domestic product per capita and globalization on structural transformation are found to be statistically insignificant. In developing countries, the negative impact of foreign trade and the positive and meaningful effect of gross domestic product per capita are observed, while other variables are determined to be insignificant. Finally, an asessment is made on a country basis with the Common Correlated Effect Mean Group Estimator.

The Feldstein–Horioka hypothesis for African countries: Evidence from recent panel error‐correction modelling

AbstractThis paper, by applying the recent panel data error‐correction modelling developed by Gengenbach et al., Panel error correction testing with global stochastic trends, 2008 University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 tests the validity of the Feldstein–Horioka puzzle (1980) in a panel of 27 African countries for the period 1965–2015. Unlike the existing studies in the literature, this paper, for the first time, addresses several important panel data econometric issues such as slope heterogeneity, cross‐section dependence, unobservable common factors, non‐stationarity and endogeneity that would yield inconsistent and biased estimates of the parameters of interest. Unlike the previous residual‐based error‐correction modelling that has low power, the Gengenbach et al., Panel error correction testing with global stochastic trends, 2008, University of Maastricht, Working Paper, RM/08/051:1–51 and Gengenbach et al., Journal of Applied Econometrics, 2016, 31, 982–1004 estimator explicitly considers structural dynamics in modelling a cointegrated panel that allows for the presence of non‐stationary unobserved common factors. As the GUW modelling depends on the Pesaran Common Correlated Effects Mean Group Estimator (CCEMG; 2006) and the Chudik and Pesaran Dynamic Common Correlated Effects Mean Group Estimator (DCCEMG; 2015), we report the results based on these estimators. The econometric exercises performed in the paper show that slope heterogeneity; cross‐section dependence and non‐stationarity are present in the panel data sample used in the estimation. Estimations yield a relatively low magnitude of the savings retention coefficient for the panel members included in the study with a negative error‐correction term that is statistically significant at the individual and panel levels. The empirical evidence rejects the presence of the Feldstein–Horioka puzzle in the panel of 27 African countries studied.

An empirical analysis of energy intensity and the role of policy instruments

The reduction of energy intensity is important for sustainable economic growth, especially in non-OECD countries where energy demand growth is high. Understanding the impact of policies on energy intensity can help policy-makers to reduce energy intensity. Using empirical methods and cross-country data from 44 countries over the period 1990–2016, we study the determinants of energy intensity. The common correlated effects mean group estimator is employed since it addresses nonstationarity, cross-sectional dependence, and heterogeneity—all three of which exist in the data. Both GDP per capita and economy-wide energy prices are shown to be negatively associated with energy intensity. The empirical results provide evidence that several policy instruments are effective in reducing energy intensity: (i) standards, and labeling; (ii) government direct investment; (iii) strategic planning and support; (iv) fiscal measures/taxes; and (v) grants and subsidies. The duration of the policy is more important than the mere existence of the policy in demonstrating the policy's effectiveness.

Modeling heterogeneous dynamic interactions among energy investment, SO2 emissions and economic performance in regional China.

Massive investments in energy industry may either promote or mitigate the air pollution which is likely to influence the economic performance. In light of this, the current work is an empirical examination of heterogeneous dynamic causal interactions among energy investment, sulphur dioxide (SO2) emissions and economic growth in regional China. A modified STIRPAT model is developed to introduce energy investment as a determinant of technology. Based on a modified model, a simultaneous equations system has been established to examine the three-way causal interactions among the variables of interest. As a first step, an error-correction-based second generation Westerlund (Oxford Bulletin of Economics and Statistics 69: 0305-9049, (2007). cointegration has been employed and found the long-run relationship. The simultaneous equations have been estimated by employing second generation dynamic common correlated effects mean group estimator (DCCEMGE) for 30 Chinese provinces and cities from 2001 to 2017. The empirical analysis has revealed that the energy investment induces emissions promotion effect while economic growth introduces emissions curtailment effect. However, the emissions curtailment effect remained slightly stronger than emissions promotion effect both at country and regional levels. Further, the energy investment growth uncovered economic performance enhancement effect. Furthermore, the SO2 emissions growth induced economic performance deterioration effect. In this regard, the economic performance deterioration effect exceeded the economic performance enhancement effect. Besides, there is a bidirectional causality operative between SO2 emissions and gross regional product (GRP) growth for the country as well as regional samples. On the contrary, a positive bilateral causal relationship between energy investment and GRP growth is found for the country as well as regional samples. Similarly, it has been found that there exists a positive bilateral causal association between SO2 emissions and energy investment. Graphical abstract.

Does energy consumption, financial development, and investment contribute to ecological footprints in BRI regions?

This study applies augmented mean group (AMG) along with common correlated effect mean group (CCEMG) estimator and panel heterogeneous causality to examine the interrelationship between GDP, energy consumption, financial development, foreign investment, and ecological footprints for five Belt and Road initiative (BRI) regions and in aggregated panel of BRI over the time 1990-2016. Using a multivariate framework, this study examines four alternative and conceivable hypotheses, including Pollution haven hypothesis, environmental Kuznets curve hypothesis, energy push emission hypothesis, and finance push emission hypothesis. The empirical results supported all four hypotheses for the panel of BRI and partially supported the existence of these hypotheses across the regions. Moreover, a variety of causal nexuses has been discussed in the study. Based on these results, the current research has proposed policy implications to combat the ecological footprints of BRI countries and across the regions.