Pooled Mean Group Estimator Research Articles

How do social and economic factors affect carbon emissions? New evidence from five ASEAN developing countries

This study analyzes the long and short-run impacts of social and economic factors on carbon emissions from five developing ASEAN countries during the period 1986–2017. Utilising a Pooled Mean Group Estimator, we find a nonlinear relationship between CO2 emissions and real GDP, confirming the Environmental Kuznets Curve. Our results indicate that energy consumption is the main driver of environmental degradation in these countries; and that FDI and urbanisation reduce carbon emissions. Our research indicates both a long-run and short-run nexus between government education expenditures and CO2 emissions. We conclude with policy suggestions to reduce CO2 emissions while attaining sustainable growth.

Can environmental tax promote renewable energy consumption? — An empirical study from the typical countries along the Belt and Road

This paper explores the effects of environmental tax on renewable energy consumption. Fifteen typical countries along the Belt and Road are selected to build panel autoregressive distributed lag model based on the data of 1998–2019 years. According to pooled mean group estimator, the short-term impact of environmental tax on renewable energy consumption in these countries is negative. In the long run, for 1% increase in environmental tax, renewable energy consumption will increase by 1.201%. Dumitrescu-Hurlin panel causality test confirms the existence of bidirectional causality between environmental tax and renewable energy consumption. For the canonical cointegration regression approach, 1% increase in environmental tax, the share of renewable energy consumption in the final energy will increase by 0.021%. The robustness of the long-term relationship is tested by fully modified ordinary least squares and dynamic ordinary least squares. Linearity tests reveal the nonlinear impact of environmental tax on renewable energy consumption. The paths of environmental tax to improve environmental quality are put forward.

Testing asymmetric influence of clean and unclean energy for targeting environmental quality in environmentally poor economies

A high proportion of nonrenewable energy in total energy consumption is leading the world economies toward severe environmental issues. This has motivated the environmentalists to come forward for encouraging masses around the world to use environmentally friendly renewable energy instead of environment-damaging nonrenewable energy. The UNDP is also playing its role in spreading the importance of clean energy in goal 7 of the SDGs. Therefore, the present study is aimed to inquire about the asymmetric influence of clean and unclean energy consumption on environmental quality in environmentally poor economies. In the present study, data from forty-two environmentally poor economies for the period from 1995 to 2019 are extracted, and a heterogeneous pooled mean group estimator is employed to estimate the results. The findings expose that the use of clean energy initially improves transport-based environmental quality while it damages industry-based environmental quality in the beginning. In the later stage, the use of clean energy hurts transport-based environmental quality while it improves industry-based environmental quality. This concludes that the use of clean energy reveals a U-shaped impact on transport-based environmental quality but it has an inverted U-shaped impact on industry-based environmental quality in the selected economies. The results further expose that use of unclean energy is leaving an inverted U-shaped influence on transport-based environmental quality while it leaves a U-shaped impact on industry-based environmental quality. These results are important from a policy perspective as these help in controlling the net carbon emissions by targeting transport-based environmental quality in environmentally poor economies.

COVID-19 Shock and Sectorial Index Response in South Africa: A Cross-sector Analysis

The prime objective of this study was to examine the impact of COVID-19 shock on sector returns of the South African Stock market. The study employed the Autoregressive Distributed Lag (ARDL) model estimated with a Pooled Mean Group estimator on a sample of daily stock returns of 10 Johannesburg Stock Exchange (JSE) sectors. The results indicate a heterogeneous behaviour in sector stock return response to COVID-19 shock. The study shows that the Pandemic negatively impacted the majority of the sectors. However, some sectors were positively affected by the outbreak, while some were resilient to the shock. The pooled ARDL panel results show a negative relationship between COVID-19 and stock market returns in the short run. The study found an insignificant relationship between stock market returns and COVID-19 cases in the long run. The study also shows that sector and stock return response to different factors is time-varying. The results imply that COVID-19 shock is short-lived, the negative impact of the Pandemic is corrected in the long run. Stock market investors should thus focus on the long-run behaviour of stock returns. The results evidence the significance of diversification in different stock market sectors for investors

Effect of Natural Disasters and Terrorism on Tourism Growth: Evidence from Top Ten Tourist’s Destination

Tourism is influenced by a wide range of factors and forces including exogenous ones that have no direct link to the tourism industry. Terrorism and natural disasters are two examples of such factors. Individuals, organizations and culture, all are affected by them. This study analyzes the impact of natural disasters and terrorism on tourism growth by using a panel data for the period 1995-2019 collected from a variety of sources. Tourism is the dependent variable whereas natural disasters, terrorism are independent and economic growth, tourism employment, tourism investment and alcohol consumption are the control variables of the study. This study used pooled mean group and robust least square estimation. The findings show that natural disasters and terrorism have varying degrees of impact on tourism growth. While there is a positive outcome in some situations, the overall influence is negative. Findings of the study suggest that understanding the relationship between natural disasters, terrorism, and tourism is beneficial to destination operators who are responsible for rehabilitation, restoration, and promotion.

Investigating the impact of RE consumption on CO2 emissions: evidence from the SAARC countries

Purpose. To study CO2 emissions through the use of renewable energy (RE) in the countries of the South Asian Association for Regional Co-operation (SAARC) region (Bangladesh, Bhutan, Sri Lanka, India, Pakistan, Afghanistan, Nepal, and the Maldives) using the data between 2002 and 2020. Methodology. For the purpose of the study, panel estimation methods were employed including Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed-Effect (DFE). Findings. Hausman test confirms the efficiency of PMG estimation method compared to MG estimation method and DFE estimation method. The results of PMG indicate long-run relationships among the studied variables. Besides, the outcomes of PMG reveal the negative impact of RE on CO2 emissions in the long-run, while in the short-run, the study did not reveal the impact of RE on CO2 emissions. In the case of specific countries, the results show that RE features increased CO2 emissions in a country like Pakistan in the short-run, while RE decreases CO2 emissions in Bhutan, Nepal and Afghanistan in the short-run. Originality. The study found the impact of RE consumption on CO2 emissions in SAARS countries obtained for the first time in the terms of SAARS region. Practical value. The governments of the SAARC countries can use the results of the study attempting to decrease CO2 emissions.

Assessing the role of information and communication technology in reducing the gap between rich and poor: the case of South Asia

PurposeThe widening income gap between rich and poor has gained worldwide recognition in recent decades. This income gap between rich and poor is defined as the extent of income unevenly distributed in a host country. This study provides an empirical view of the association between information and communication technology and the widening of the income gap.Design/methodology/approachThe study used panel data from 2005 to 2019. To detect unit root issues, Levin and Lin (LL) and Im, Pesaran and Shin (IPS) tests were first employed. The pooled mean group and mean group estimators were employed to investigate the short and long -term impact of information and communication technology and other control factors on reducing the gap between rich and poor in South Asia.FindingsThe results showed that the Pooled mean group's findings are more efficient and consistent as compared to mean group estimators. The results of the paper showed that the greater penetration of information and communication technologies in the economy negatively and significantly affects income inequality. Moreover, the information and communication technology, foreign remittances and foreign direct investment (FDI) significantly reduce the gap between rich and poor in the long run.Practical implicationsAt last, the findings of the study serve as an excellent roadmap for policymakers seeking to address the issue of growing income inequality in the South Asian regions and worldwide.Originality/valueBased on the findings of this study, South Asia can reduce the gap between rich and poor by investing more in the information and communication technology sector.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0638

Effect of economic uncertainty on public health expenditure in Economic Community of West African States: Implications for sustainable healthcare financing.

This study investigates the dynamic effect of economic uncertainty on public health expenditure in the Economic Community of West African States region. The investigation is motivated by the recent volatilities in the global economy in the face of increasing demand for adequate funding of health systems in the region, and the need to fill the existing gap in the literature. The study employs the panel autoregressive distributed lag model to express the theoretical relationship between public health expenditure per capita, economic uncertainty and population growth rate, and estimates the model parameters using the mean group and the pooled mean group estimators, after accounting for stationarity and cointegration. Results reveal that on the aggregate, economic uncertainty and population growth are significant determinants of per capita health spending in the long run. When the countries are disaggregated by income groups, evidence suggests that in low‐income countries, economic uncertainty is negatively associated with health spending in the short run, while a growing population reduces health spending per capita in the long run. In lower‐middle‐income countries, economic uncertainty increases health spending in the short run, but reduces it in the long run as uncertainty persists, while population growth negatively impacts health spending in the long run. We conclude that the dependence on public funding of the health system in the region appears unsustainable. Thus, health financing policies need to explore alternative funding mechanisms that entrench cost‐sharing between the public and private financiers.

Testing the Pollution Haven Hypothesis with the Role of Foreign Direct Investments and Total Energy Consumption

The main objective of this study was to examine the nonlinear relationship between environmental deterioration and foreign direct investment for subpanels based on the country’s income level. In this study, the model’s determinants were total consumption of energy and electricity consumption, the share of renewable energy, and economic growth. Due to the observation of cross-sectional dependence, utilization of cointegration tests and panel data unit root were incorporated, which confirmed a mixed integration order. For the compliance of long-run and short-run relationships among the variables, a pooled mean group estimator panel auto-regressive distributed lag approach was incorporated. The results of long-run development support the pollution haven hypothesis; hence, ecological footprint is increased by the activities related to foreign direct investments. The obtained findings depend on the different subpanels based on the income level of countries. For the assurance of economic development sustainability in the energy sector, along with the electrical energy sector, customized policymaking is suggested by this study based on the particulars of each subpanel.

The short‐run and long‐run effects of trade openness on financial development: Some panel evidence for Europe

AbstractThis paper analyses the short‐ and long‐run effects of trade openness on financial development in a panel including data on 35 European countries over the period 2001–2019. For this purpose, it uses the pooled mean group (PMG) estimator for dynamic panels developed by Pesaran et al. (Journal of the American Statistical Association, 1999;94:621). The results differ depending on the income, governance and financial development level of the countries considered. In particular, it appears that in the middle‐income countries trade openness tends to strengthen financial development in the long run but to have an adverse effect in the short run. By contrast, in the case of high‐income countries with better institutions and a higher level of financial development, there is a positive and significant impact in the short run. Some policy implications of these findings are drawn.

Asymmetric linkages between renewable energy, technological innovation, and carbon-dioxide emission in developed economies: non-linear ARDL analysis.

Although economic development has been strong in the world's 18 most developed economies, carbon-dioxide emission (COE) has been steadily declining in recent decades. As a result, the purpose of this research is to investigate the role of variables that contribute to the reduction of COE in these economies by using a dataset 1990 to 2019. GDP, [Formula: see text], renewable energy use (REC), and technical innovation (INNO) have been selected as the independent variables for this study. A strategy based on asymmetric ARDL (NARDL) technique is utilized in conjunction with a pooled mean group (PMG) estimation technique to investigate the asymmetrical relationships between COE and the exogenous variables under consideration. For the purpose of determining the direction of causality, the Granger non-causality test is utilized. Furthermore, a unidirectional causality is discovered between GDP and CO2 emissions as well as between GDP and technological innovation. An environmental Kuznets curve hypothesis has been confirmed to exist, and renewable energy has been identified as a significant variable in reducing COE. The study also confirmed that COE is reduced by positive technological innovation shocks and increased by negative shocks. As a result of the findings, the study did a causality test and came up with policy recommendations.

Environmental performance, green finance and green innovation: What's the long-run relationships among variables?

What are the relationships among environmental performance, green finance, and green innovation in developing countries? Existing literatures support the impact of green finance or green innovation on environmental performance, but rare studies query the cointegration among such three variables. We thus utilize the yearly data of 57 developing countries from 2002 to 2016 to empirically examines the relationships among environmental performance, green finance, and green innovation, via panel covariate-augmented Dickey-Fuller unit root test and the Westerlund and Edgerton (2007) cointegration test. Overall, this study confirms the existence of cointegration relationships among these variables. Moreover, the results of pooled mean group estimation suggest that environmental performance can positively affect the green innovation in the long term in the non-emerging countries and countries with better green innovation or environmental performance. Furthermore, green finance positively affects green innovation in the emerging countries and countries with lower level of green finance, while green finance negatively affects green innovation in the countries with better green innovation or environmental performance. Our empirical findings offer important policy implications for the sample of developing countries to promote green innovation and improve environmental performance.

The Role of Corruption in Natural Resource-Financial Development Nexus: Evidence from MENA Region

This paper contributes to the literature on resource curse by investigating the impact of natural resource abundance on financial development while accounting for the interactive effect of natural resources and corruption in 11 resource-rich MENA countries over the period of 1987 to 2015. Using pooled mean group (PMG) estimation technique, our results show that abundance of natural resource weakens the pace of financial development in countries with high level of corruption. Thus, resource rich countries in the MENA region will boost the level of financial development through minimising the degree of corruption in their financial sectors. Therefore, policymakers should control the corruption, which plays a significant role to mitigate the adverse effect of natural resources on financial development. This is through building strong institutions, which help to check corruption, enhancing rule of law and protecting investors. Our results are consistent and robust to alternative measures of natural resource abundance and financial development.

Assessment of the Factors Impacting on Export-led Growth Policy Performance of East African Countries: The Panel-Autoregressive Distributed Lag Model

Exports play a crucial function in a country's economy and financial system, figuring out the extent of employment economic growth, along with the balance of payments. East African Countries have installed numerous trade coverage or policy reforms to promote and improve the export sectors. However, their proportion in general world exports continues to be very low. Despite its massive resource potential, the region's balance of trade stability for multiple years is in deficit; its export-led growth performance persisted poor notwithstanding governments' promotion and support. Hence, it's worthy of looking at the fundamental factors impacting East African countries' export performance. The present study dominantly applied the data of Africa and the Global development indicator of 20 years (2001 to 2020) for 9 East African countries, using a panel-ARDL econometric model. The descriptive outcomes of the research depict that in East Africa, the exports were low; the external trades denoted a continuous deficit in the business, industrial items dominated in the import basket, and primary items were overlooked in the export basket. The pooled mean group (PMG) estimation result also suggests that all the macroeconomic factors (independent variables) FDI, GDP, REER, INF, TOT, and IND are notably affected export in East Africa in the long run. Whereas GDP is the single variable that substantially influences export from East African nations in the short run. The results advise that inflation rate, foreign direct investment inflows, and the effective actual exchange rate had statistically detrimental or negative impacts on export performance in the study countries. To this end, the outcomes stand important for redesigning export trade policies/strategies to boost the performance of exports and the overall ultimate economic growth in East Africa. Keywords: East Africa, Export performance, Export-led growth policy, Macroeconomic factors, Panel data, PMG/ARDL DOI: 10.7176/DCS/12-4-01 Publication date: April 30 th 2022

The Effects of Information and Communication Technology, Economic Growth, Trade Openness, and Renewable Energy on CO2 Emissions in OECD Countries

This study examines the relationships between information and communication technology (ICT) usage and CO2 emissions considering economic growth, trade openness, and renewable electricity in the Organization for Economic Co-operation and Development countries for the period 1990–2018. It adopts pooled mean group (PMG) estimation based on the autoregressive distributed lag model. The PMG estimates indicate that although the coefficient value is small, ICT progress acts as a factor in increasing CO2 emissions in the long run. However, there is no significant short-run relationship between these two variables. Furthermore, economic growth increases CO2 emissions in the short and long run. The expansion of renewable electricity and trade openness reduces CO2 emissions in the long run. To mitigate the CO2 emissions originating from ICT, energy-saving technologies that use ICT as an energy management system should be further enhanced. The expansion of renewable electricity and the promotion of trade openness will also contribute to the mitigation of CO2 emissions in this region.

Heterogeneity Effect of Central Bank Independence on Inflation in Developing Countries

This research investigates the relationship between central bank independence and inflation for 37 developing countries during the period from 1972 to 2019. Given that most developing countries experienced high inflation, many opted for central bank independence to enhance their focus on inflation. Central bank independence reforms were anticipated to create a higher level of independence, which would result in a low inflation rate. We employed pooled least square with the assumption of homogeneity of co-efficients; the result showed no significant relationship between central bank independence and inflation. We checked the homogeneity assumption of the panel by applying Chow and Roy–Zellner tests; results showed that the model was not homogeneous. Furthermore, we performed the panel heterogeneity model with the pooled mean group estimator which indicated that a reverse relationship exists between central bank independence and inflation. This finding is robust as we split the sample into two groups: moderate and high inflation countries; the negative relationship between those variables still exists.

Exchange Rate Volatility, Inflation and Economic Growth in Developing Countries: Panel Data Approach for SADC

In the Southern African Development Community, the relationships between exchange rate instability, inflation and economic growth remain at the forefront of economic debate because of the historical antecedent and economic clustering of member countries. Nonetheless, much is not known regarding the complexity, complementarity or substitutability of exchange rate instability and inflation on economic growth for SADC countries. This article examined the influence of exchange rate instability on the inflation–growth nexus of the region for the period of 2000 to 2018. Three major techniques of analyses, Pooled Mean Group (PMG), Generalised Moments (GM) and Dynamic Fixed Effect (DFE), were employed in achieving the goal of the study, but the Pooled Mean Group estimator of the Panel Autoregressive Distributed Lag was favoured by the Hausman test as the main instrument. The GARCH (1, 1) was also employed to generate exchange rate instability. The findings of the study showed that exchange rate instability and inflation have a negative relationship with economic growth of the region. Results further show evidence that economic growth of the region is adversely influenced by the consequential effect of exchange rate instability on inflation: the higher the level of instability in exchange rate, the worse the inflationary-growth relationship of the region. This confirms the menu cost theory of price setting: the higher the rate of inflation, the quicker the exchange rate pass-through effect. It is therefore recommended that policies to ensure appreciation of local currencies should be the priority of member nations.

Impact of External Debt on Economic Growth in Western Balkan Countries

This paper investigates the average impact of government debt on long-term GDP growth in four Western Balkan countries of Albania, Serbia, Macedonia, and Bosnia & Herzegovina over a 23-year period from 1997-2019. It examines the use of financing through debt on short- and long-term economic growth for these economies using a dynamic common correlated effects model with heterogeneous coefficients. The model's methodology estimation mimics Chudik and Pesaran and the pooled mean group estimator is used. The conclusion of this study, with respect to the average impact of government debt on long-term GDP growth in the four Western Balkan countries, is consistent with the literature in that in the long-term external debt does not contribute to long-term growth and, in fact, tends to have a negative impact. The COIVD-19 pandemic has exacerbated the long-term growth outlook for the four Western Balkan countries.
 
 Received: 21 December 2021 / Accepted: 22 February 2022 / Published: 5 March 2022

Reduction of CO2 emissions: The role of renewable energy, technological innovation and export quality

In the 22 well-developed countries of the world, the level of CO2 emissions has been reducing over the years despite positive economic growth. This study therefore attempts to explore the role of contributory factors for CO2 emissions reduction in these countries. Selecting the data period of 1990–2018, our chosen independent variables are gross domestic product (GDP), square of the gross domestic product (GDP2), renewable energy, technological innovation and export quality. Adopting a panel non-linear autoregressive distributed lag (NARDL) approach, a pooled mean group (PMG) estimation technique is used to explore the asymmetric linkages between CO2 emissions and these independent variables. The panel heterogeneous causality test is used to examine the direction of causality. The estimated results have confirmed the existence of environmental Kuznets curve (EKC) hypothesis; and renewable energy and export quality are found as contributory factors for the reduction of CO2 emissions. Positive stimuli of technological innovation measured by research and development expenditure and export quality index reduce, whereas the negative shocks or counter incentives of these variables increase CO2 emissions. In regards to causal relationship, bidirectional causality is found between renewable energy and CO2 emissions, technological innovation and CO2 emissions, GDP and renewable energy, and renewable energy and technological innovation. In addition, a unidirectional causality is also revealed from GDP to CO2 emissions, export quality and technological innovation, and from technological innovation to export quality. Policy recommendations are made following the findings.

Workers' remittances in Central America: where does the money go?

PurposeThe purpose of this study is to examine two issues about remittances in Central American countries (Costa Rica, El Salvador, Guatemala, Honduras and Nicaragua). First, whether the inflow of remittances impacts income in the long run. Second, what motivates migrants to send remittances? The first issue is analyzed in the context of a permanent income hypothesis, while the second is analyzed in the context of altruism versus self-interest motives.Design/methodology/approachA panel cointegration method is used to establish the long-run relationship between the variables under consideration. Further, this study uses the fully modified ordinary least squares method (FMOLS) to estimate the impact of remittances on income and consumption. The pooled mean group (PMG) estimation is used.FindingsThe test results indicate that remittances into Central American countries do not promote growth in the long run. Central American families may perceive remittances as a permanent income stream and will increase their current consumption. Additionally, the test results indicate that sending remittances of the Central American migrants is mainly driven by altruism. Their primary motive is to support left-behind families at times of economic hardship.Research limitations/implicationsFindings provide an important implication for these Central American countries, as they have potential to boost income by utilizing remittance money in productivity-enhancing activities. This study could also provide valuable information for the governments of labor-exporting countries around the world to encourage and incentivize remittance recipient families to utilize those funds for income-generating activities.Originality/valueIn Central America, this is probably the first attempt in the literature to analyze the impact of remittances in the context of permanent income hypothesis and the motivation of Central American workers to send remittances to their countries of origin.