Long-run Parameter Estimates Research Articles

How do energy consumption, globalization, and income inequality affect environmental quality across growth regimes?

This paper investigates the impacts of renewable and nonrenewable energy consumption, income inequality, and globalization on the ecological footprints of 49 countries for the period of 1995–2018. Panel cointegration test reveals a long-run relationship between the variables. Long-run parameter estimates derived from AMG and CCEMG, increasing income and nonrenewable energy consumption, have a significant positive impact on the ecological footprint, while countries that consume more renewable energy have seen an improvement in the quality of the environment. Conversely, neither income inequality nor globalization has a significant effect on national EFs. Evidence from the estimation of the panel threshold error correction model, where GDP growth is used as the transition variable, indicates a significant threshold effect, which supports a nonlinear relationship among the variables by identifying two distinct growth regimes: lower and upper. For the estimation sample, the positive and significant parameter estimates for economic growth in both growth regimes do not support the EKC hypothesis. The results indicate that renewable and nonrenewable energy consumption has a larger impact on the EF in the upper than lower growth regime. The threshold estimates are in line with the linear long-run estimates that do not indicate that income inequality has a significant impact on ecological footprint. However, globalization appears to negatively affect environmental quality in the lower growth regime.

Sanitation, water, energy use, and traffic volume affect environmental quality:Go-for-green developmental policies.

Carbon emissions are primarily the result of human activity in urban areas. Inadequate sanitary facilities, contaminated drinking water, nonrenewable energy, and high traffic congestion have all impacted the natural ecosystem. Using data from 1975 to 2019, the study assessed the impact of the aforementioned variables on Pakistan’s carbon emissions in light of this crucial fact. The ARDL cointegration method was used to estimate the short- and long-run parameter estimates. Urban sanitation challenges and energy consumption increase carbon emissions, which affects the natural environment by raising a country’s carbon intensity. Economic expansion confirmed the inverted U-shaped relationship between carbon emissions and economic growth to verify the Environmental Kuznets Curve (EKC) hypothesis in the long run. In contrast, the monotonically rising function of carbon emissions provides evidence of the nation’s economic development in the short run. Access to clean drinking water improves population health and encourages the purchase of eco-friendly products. The government must improve sanitation services and use renewable energy sources to enhance air quality.

The relationship between FDI, CO2 emissions, and energy consumption in Asia-Pacific economic cooperation countries.

This paper investigates the relationship between CO2 emissions, energy consumption, economic growth, and foreign direct investment for a sample of Asia-Pacific Economic Cooperation Countries (APEC) countries from 1981:Q1 to 2021:Q1 employing panel data methodology. We identify cross-sectional dependence and hence utilize the cross-sectional augmented Dickey-Fuller panel unit root test for appropriate estimation. The cointegration test developed by Westerlund (2008) reveals a long-run equilibrium between CO2 emissions, energy consumption, economic growth, and foreign direct investment. Long-run parameter estimates based on Common Correlated Effect Mean Group indicate that an increase in FDI inflows has a negative impact on air quality, supporting the pollution haven hypothesis. The cointegration test results also show that the impact of Gross Domestic Product (GDP) on CO2 emissions varies by country in the estimation sample. In contrast to the mixed evidence on the effects of other variables, the increase in energy consumption is positively and significantly affecting CO2 emissions in all APEC countries. Emirmahmutoglu and Kose Econ Model 28:870-876, (2011)'s panel causality test results show a bidirectional relationship between FDI and CO2 emissions in Japan. Furthermore, there is a bidirectional causal relationship between GDP and energy consumption in Australia, China, Japan, and Singapore. Overall, empirical evidence suggests that APEC countries should adhere to strict regulations and invest in environmental-friendly clean technologies to attract foreign direct investment.

Achieving pro-poor growth and environmental sustainability agenda through information technologies: as right as rain.

The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975-2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high-technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country's economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.

Do rural-urban migration and industrial agglomeration mitigate the environmental degradation across China's regional development levels?

Abstract This research investigates the heterogeneous dynamic impacts of rural-urban migration and industrial agglomeration on the environmental degradation across regional development levels of Chinese provinces. An aggregated data set of 31 provinces, along with three provincial-scale panels, are used from 2005 through 2018. The long-run parameter estimates are obtained employing dynamic common correlated effects mean group technique (DCCEMGT), while the heterogeneous Granger non-causality Dumitrescu-Hurlin test is employed for causal directions. The core results are as follows. Firstly, a unidirectional positive linkage is revealed from industrial agglomeration and rural-urban migration to energy utilization. These linkages showed heterogeneity across the development levels—the most substantial impacts are discovered in highly developed regions (eastern provinces), while the least substantial are found in low developed regions (western provinces). Secondly, the combined impacts of linear and non-linear parameters of both industrial agglomeration and rural-urban migration confirmed environmental Kuznets curves (EKCs) in models with the tertiary sector. However, in the model with the secondary sector, only EKC based on rural-urban migration is verified. Finally, rural-urban migration mitigated the environmental degradation more substantially in the model with tertiary sector-based industrial agglomeration. It suggests that rural to urban migration contributes less to the environmental emissions through the economy's service sector.

Dynamic interaction between financial development and natural resources: Evaluating the ‘Resource curse’ hypothesis

The role of natural resources in promoting economic and financial activities is important for attaining country's economic growth. The study used different natural resource rents, domestic investment, trade openness, per capita income and their resulting impact on financial development in order to assess ‘financial resource curse’ hypothesis in Pakistan by using a consistent time series data from 1975 to 2017. The study employed ARDL-Bounds testing approach that is fairly worked under different order of integrated variables and displayed short- and long-run parameter estimates. Further, the study used VAR decomposition analysis to generate Impulse Response Function (IRF) and Variance Decomposition Analysis (VDA) to assessed forecasted variance and error shocks over a next 10 year time period. The results show that, in the short-run, initial level of forest rents and oil rents supported the ‘natural resource abundance’ hypothesis, as both the rents substantially increases country's financial development, however, in the long-run, there is a negative relationship of coal rents, forest rents, natural gas rents, and oil rents with domestic credit to private sector (DCPS), which confirmed the ‘natural curse hypothesis’ in a country. The domestic investment in the form of gross fixed capital formation (GFCF) largely supported the financial activities with all given resource rents in the models, while country's per capita income unable to signify its positive impact on DCPS under the resource curse environment during the study time period. The other results show that coal rents and oil rents decreases broad money supply whereas natural gas rents decreases market capitalization to validate ‘financial resource curse’ hypothesis in a country. The results of IRF and VDA approach confirmed the viability of both the competing natural resource theories (i.e., financial resource curse and financial resource blessing hypothesis) under financial development in the next 10 year time period.

Renewable and fossil energy, terrorism, economic growth, and trade: Evidence from France

To the best of our knowledge, there is no econometric study on the causal relationship between renewable or fossil energies and terrorism, nor on terrorism in France. This paper tries to fill this gap and considers other variables as economic growth and trade openness. The autoregressive distributed lag approach and Granger causality are used for annual data on France covering the period 1980–2015. The Wald test confirms the existence of long-run relationships between the considered variables. Granger causality reveals long-run bidirectional causalities between all the variables. Interestingly, in the short-run, there are unidirectional causalities running from renewable energy to terrorism, and from terrorism to trade openness, and there is bidirectional causality between terrorism and economic growth. Long-run parameter estimates show that more renewable energy consumption and more trade increase both terrorism and economic growth. However, economic growth reduces terrorism in the long-run and appears as a powerful tool to combat terrorism in France. In addition, France is recommended to continue encouraging the use of renewable energies, and at the same time, to make more diplomatic efforts to resolve political and military conflicts in the world, and particularly in the Middle East.

Urbanization and industrialization impact of CO2 emissions in China

This study investigates the causal linkage among CO2 emissions per capita, energy intensity, real GDP per capita, industrialization (share of industrial value added in GDP), urbanization (share of urban population in total population), and share of renewable energy consumption in China over the period from 1970 to 2015. We employ autoregressive distributed lag (ARDL) technology to test the co-integration and short- and long-run estimates, and apply the vector error correction model (VECM) to analyze the directional causality among the time series data. The estimates of long-run parameters indicate that 1% augments of energy intensity, real GDP, industrialization, and urbanization increase CO2 emissions by 1.1%, 0.6%, 0.3%, and 1.0%, respectively. Long-run feedback Granger causalities exist among emissions, real GDP, and industrialization. Thus, our main policy suggestions are as follows: (i) to encourage green and sustainable urbanization, as it increases economic growth but not at the expense of environmental degradation; (ii) to strategically adjust and optimize the industrial structure; (iii) to improve the efficiency of energy use and technological innovation; and (iv) to increase the proportion of renewable energy in total energy consumption.

The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North Africa countries

This paper uses panel cointegration techniques and Granger causality tests to investigate the dynamic causal links between per capita renewable energy consumption, agricultural value added (AVA), carbon dioxide (CO2) emissions, and real gross domestic product (GDP) for a panel of five North Africa countries spanning the period 1980–2011. In the short-run, Granger causality tests show the existence of bidirectional causality between CO2 emissions and agriculture; a unidirectional causality running from agriculture to GDP, from GDP to renewable energy consumption, and from renewable energy consumption to agriculture. In the long-run, there is bidirectional causality between agriculture and CO2 emissions; a unidirectional causality running from renewable energy to agriculture and to emissions, and from output to agriculture and to emissions. Long-run parameter estimates show that an increase in GDP or in renewable energy consumption (including combustible and waste) increases CO2 emissions, whereas an increase in agricultural value added reduces CO2 emissions. As policy recommendation, North African authorities should encourage renewable energy consumption, and especially clean renewable energy such as solar or wind, as this improves agricultural production and help to combat global warming.

Does ASEAN–India Trade Stimulate Income? A Cointegration Analysis Using the ARDL Approach

This article aims to address the extent of income that has been attributed by trade between India and the ASEAN-5 countries (namely, Indonesia, Malaysia, the Philippines and Thailand) from the year 1970 till 2014. This study adopts the autoregressive distributed lag (ARDL) bound test approach to cointegration, with long- and short-run parameter estimates to investigate the impact of regional trade between India and ASEAN-5. The cointegration test results confirmed the presence of a long-run relationship only for India, and no cointegration evidence was found for the ASEAN-5 economies. The long-run parameter estimates showed no influence of ASEAN–India trade on India’s income and a positive impact of India’s trade to the rest of the world on India’s income by about 0.58 per cent in the long run. Interestingly, ASEAN–India trade is positively influencing India’s income in the short run, and the extent of the impact tends to be small. This article concludes that there is limited evidence to support the claim that ASEAN–India trade stimulates income for the case of India and ASEAN-5 countries.

Economic freedom and income inequality: further evidence from 58 countries in the long-run

This study employs panel data for 58 countries from 1980-2010, to investigate the dynamic relationship between economic freedom and income inequality. Both linear and non-linear (Panel Smooth Threshold Regression) cointegration estimation methods are used to identify a long-run equilibrium relationship between the overall economic freedom index and its components, and income inequality. The linear long-run parameter estimates for the entire panel of countries show that the association is negative, while the non-linear long-run parameter estimates indicate that above a threshold point the association between economic freedom and income inequality is negative, while below this threshold point the association is positive.

Long Run Elasticities of Demand for Natural Gas: OECD Panel Data Evidence

Natural gas consumption has been analyzed intensively especially within the last three decades due to its growing environmental and economical impacts among other consumption goods. This article aims at first observing the outputs of literature evidence regarding the demand for natural gas and, second, estimating the parameters of function for natural gas consumption. To this end, this article employs the panel data for eight Organization for Economic Cooperation and Development countries to seek responses of per capita natural gas consumption to per capita income and natural gas price. Therefore, panel unit root tests, panel cointegration analyses and panel ordinary least squares (OLS), fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations are conducted to obtain long-run parameter estimates of the function. Throughout analyses of cointegration, FMOLS, and DOLS regressions with homogeneous and heterogeneous variance-covariance structures, this work obtains slightly higher than unit elasticities together with expected signs throughout majority of estimations for the period of 1979–2006.

Electricity demand analysis and forecasting: A panel cointegration approach

This article analyzes the demand for electricity and provides out-of-sample forecasting at the sectoral level using a panel cointegration approach. The econometric model permits cross-sectional heterogeneity within a dynamic framework that incorporates information on relevant income and prices of domestic and foreign goods. Both the short-run dynamics and the long-run slope coefficients are allowed to vary across cross-sections. Also, the testing for unit roots and cointegration in panels allows for heterogeneous fixed effects and deterministic trends. Using Egyptian data, it is shown that the empirical model produces reliable ex-post forecasts near the end of the full sample period. These pseudo forecasts are representative of what one would expect if the forecasting relationship is stationary. The long-run parameter estimates are then used to conduct ex-ante forecasting under plausible assumptions for policy making.

Impact of terrorism on tourism in Turkey: empirical evidence from Turkey

This article aims at investigating the causal impact of terrorist attacks on the tourism industry in Turkey based on the Autoregressive Distributed Lag (ARDL) bounds testing procedure for the period between 1986 and 2006. The ARDL bounds test reveals that tourism is in a long-run equilibrium level relationship with terrorism. The evidence obtained from the long-run and short-run parameter estimates indicates the existence of a negative causal effect of terrorism on tourism.

Services sector and economic growth in India

This study examines the long-run equilibrium and short-run dynamic relationship between services sector and Gross Domestic Product (GDP) and between services and nonservices sectors in India. The model is estimated using the optimal single-equation and the maximum-likelihood system estimators. All the estimators consistently suggest the cointegrating relationship between services sector and GDP as well as between services and nonservices sectors. The estimates of long-run elasticity parameters are statistically significant and dimensionally consistent across the estimators. The conventional Cumulative Sum (CUSUM) and the new CUSUM and Moving Sum (MOSUM) tests suggest the stability of the equilibrium residuals and reinforce the cointegrating relationship between the model series. The error correction model provides some support for unidirectional Granger-causality from services sector to GDP. The impulse response and variance decomposition analyses instead suggest the bidirectional causality between services sector and GDP and between services and nonservices sectors. The stable growth of services sector is essentially crucial to absorb the adverse effects of exogenous weather shocks in agriculture and industry and provide resilience to the economy.