Panel Quantile Regression Approach Research Articles

Exploring how economic growth, renewable energy, internet usage, and mineral rents influence CO2 emissions: A panel quantile regression analysis for 27 OECD countries

This study aims to investigate the impacts of renewable energy consumption, internet usage, mineral rent, and economic growth on CO2 emissions across 27 OECD nations between 2001 and 2020. We employ a panel quantile regression technique to discover the heterogeneous effects of these variables for the various quantile levels of environmental destruction. The panel quantile regression approach found the Environmental Kuznets curve dominated countries in which CO2 emissions were low. Additionally, the negative relationship between renewable energy consumption and CO2 emissions yielded in the paper suggests the potential benefits of incentivizing and investing in renewable sources. Internet usage demonstrates a negative impact on CO2 emissions, showcasing the role of digital technologies in promoting sustainability. Accordingly, internet use improves environmental quality due to more efficient, sustainable, and eco-friendly practices, which increase productivity. However, a positive association between mineral rents and environmental deterioration emphasizes the necessity of strategic policies to balance economic benefits with environmental preservation. Our study provides policymakers with valuable insights into tailoring effective strategies for sustainable development, renewable energy adoption, digitalization, and natural resource utilization while addressing environmental degradation.

Heterogeneous Effects of Volunteering on Frailty in Later Life: A Panel Quantile Regression Approach.

Decades of research indicate that volunteering is associated with better health for the volunteer beyond the selection effects based on health. However, little is known about potential heterogeneity in health outcomes associated with volunteering in the context of good or poor health. This study addresses this gap by focusing on the frailty index (FI) to investigate the volunteering-health nexus across the population frailty distribution ranging from fit to frail. Using nationally representative data from the Health and Retirement Study (person N = 34,986; 198,218 person-wave observations), we estimated unconditional quantile regression models with panel fixed effects to estimate changes in FI associated with changes in the share of volunteers in the population across the frailty distribution observed across the study period (1998-2020). Our findings demonstrated that the volunteering-FI association was heterogeneous across the frailty distribution. The association was the most potent at the higher end of the frailty distribution, suggesting that efforts to promote volunteering may yield greater benefits for older adults experiencing high levels of frailty. The current study findings provide unique and compelling evidence in support of earlier calls for considering volunteering as a public health intervention. The study findings are discussed in the context of population health outcomes and health disparities.

Quantile modeling for environmental risk: SAARC's journey with green finance, policies, and regulations

Environmental risk assessment and management have become critical issues facing global climate change and its multifaceted consequences. The 2030 United Nations Sustainable Development Goal (SDG) 13 prioritizes a sustainable environment and urgent climate change mitigation. The present study aimed to make accountability of environmental risk through green finance, financial development, policies, and regulations in SAARC countries. Using data from 2005 to 2022, the panel quantile regression (PQR) approach is applied to estimate the long-run coefficients at lower, middle, and upper quantiles. Overall, the study results indicate heterogeneity in the parameters impacting the environmental risk in SAARC. The findings from the PQR unveiled that green finance contributes to mitigating environmental risk in higher quantiles. Financial development contributes to environmental risk in the middle (40th to 60th) and higher quantiles (70th to 90th). It is concluded that the appropriate business regulatory framework reduces environmental risk in higher quantiles, and poor and low-rated policies increase it in the middle, and higher quantiles. Nevertheless, foreign direct investments increase environmental risk in lower and middle quantiles. Overall, there is a heterogeneity in the results; however, the amplitude of their parameters varied substantially. The quantile slope equality (QSE), symmetric quantile (SQ) tests, and fully modified ordinary least square (FMOLS), also confirmed the robustness of the results. Finally, the empirical findings of this study have prudent policy implications for the stakeholders concerning environmental risk.

Examining the multiple impacts of renewable energy development on redefined energy security in China: A panel quantile regression approach

The increasing generation of renewable energy and its concurrent technological innovation are driving the transformations of the energy sector, but little effort has been made at the regional level to specify the heterogeneous impacts of different types of renewable energy development on multi-dimensional energy security. Therefore, this paper establishes a four-dimensional energy security assessment system based on the current energy market situation and economic context of China. Renewable energy generation and technological innovation were simultaneously used as the core proxies for renewable energy development. Then, the panel quantile regression method was used to analyze the heterogeneity of the impact of solar, hydro, and wind energy on energy security, covering 30 provinces in China from 2006 to 2019. The empirical results show that renewable energy power generation generally promotes energy security, but it cannot be effectively applicable to all levels of energy security. Renewable energy technology innovation has surprisingly hindered energy security. These results can serve as a policy and practical guide, suggesting that provincial governments in China should implement energy security and renewable energy policies in line with local characteristics.

Unlocking the potential of renewable energy and natural resources for sustainable economic growth and carbon neutrality: A novel panel quantile regression approach

As the world grapples with the dual challenge of fostering sustainable economic growth and achieving carbon neutrality, the role of renewable energy, urbanization, and financial development in shaping environmental outcomes in South Asian nations becomes increasingly critical. In this pioneering study, we delve into the heart of South Asia, encompassing a diverse range of nations – Afghanistan, Bangladesh, Bhutan, Pakistan, Sri Lanka, Nepal, the Maldives, and India – each chosen for their strategic geographical significance and the rich availability of pertinent data, offering a unique lens into the region’s energy and economic dynamics. This research uses panel quantile regression analysis to examine the relationship between the renewable energy consumption, broad money, urbanization, and natural resources and their effects on carbon emissions and economic development in South Asian (SAARC) nations. Fixed-effect panel quantile regression analysis was used to adjust for geographical variability. This study aims to investigate how urbanization, broad money, natural resources, and renewable energy affect economic growth and carbon emissions. According to our research, renewable energy consumption significantly and negatively affects CO2 emissions, especially in the distribution’s higher quantiles. Urbanization has a positive and significant effect on GDP, whereas natural resource rent has a positive impact on GDP and CO2 emissions. Broad money boosts GDP in the lower quantiles while having a negative impact in the higher quantiles. These findings show that in order to combine economic development with environmental sustainability, governments must concentrate on boosting the use of renewable energy sources and encouraging sustainable urbanization. Our policy implication is that policymakers should prioritize policies aimed at promoting renewable energy consumption and sustainable urbanization, which can help mitigate the negative environmental impact of economic growth in the SAARC region.

The Role of Renewable Energy and Human Capital in Reducing Environmental Degradation in Europe and Central Asia: Panel Quantile Regression and GMM Approach

Environmental sustainability concerns are growing worldwide. Reducing carbon dioxide (CO2) emissions is crucial to combating global warming and reaching sustainable global economic development. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to associated factors such as renewable energy and human capital. This article applies the two-step system FOD-GMM (Forward-Orthogonal Deviations-Generalized Method of Moments) to estimate the role of renewable energy and human capital in reducing environmental degradation in Europe and Central Asia. The results reveal that renewable energy consumption and human capital have a significant negative impact on CO2 emissions in the EU and Central Asian countries, government efficiency has a positive effect on CO2 emissions, and economic development has a neutral effect, confirming the strong role of renewable energy and human capital in reducing CO2 emissions in EU and Central Asian countries. The role of human capital and renewable energy in promoting CO2 reduction should be fully utilized. Policymakers should develop infrastructure for renewable energy and education to support the decrease in CO2 emissions in Europe and Central Asia.

Don’t Look Up: House Prices in Emerging Europe

Abstract This paper investigates how housing prices respond to economic, financial and demographic conditions in emerging markets in Europe. We use quarterly data covering 10 countries over the period 1998–2022 and implement a panel quantile regression approach to obtain a granular analysis of real estate markets. Overall, economic, financial and demographic developments explain real house price growth in emerging Europe, with income growth having the most significant impact. Quantile regression estimations show that income growth matters more for higher quantiles of the property market. We also find that an increase in short-term or long-term interest rates has a price-dampening impact, indicating that a higher cost of borrowing is associated with lower real house price growth. These results indicate that the downturn in house prices could deepen with the looming economic recession and soaring interest rates.

Corruption and external debt nexus in sub-Saharan Africa: a panel quantile regression approach

PurposeDebt sustainability and the growing level of external debt in sub-Saharan African (SSA) continue to be significant research priorities. This study aims to examine the corruption-external debt nexus in SSA economies and whether different levels of corruption better explain this relationship.Design/methodology/approachThe panel quantile regression approach was applied to account for the heterogeneous effect of the exogenous variables on external debts. The research covers 30 years of panel data from 30 selected SSA economies for the period spanning from 2000 to 2021.FindingsThe empirical findings of the regression analysis demonstrate the heterogeneous influences of the exogenous variables on external debt. While there was a positive impact of foreign direct investment (FDI) inflows on external debts, corruption established a negative relationship with external debt from the 10th to the 80th quantile. The findings showed a positive link between trade openness and external debt, while they also showed a negative relationship between gross fixed capital formation and external debt.Research limitations/implicationsIt is implied that corruption “sands the wheels” of external debts in the selected SSA countries. Therefore, the amount of external debt that flows into SSA is inversely correlated with corruption activity.Originality/valueTo the best of the authors’ knowledge, this study is one of the first to use panel quantile regression to analyze how corruption affects debt dynamics across different levels of debt, allowing for a more nuanced understanding of how corruption affects debt dynamics. Based on the findings of this study, SSA countries should create enabling environments to attract FDI inflows and to continue to drive domestic revenue mobilization and capital so as to be less dependent on external debts.

The relevance of political stability and exports on Türkiye’s outward direct investment in the European Union: panel quantile regression approach

ABSTRACT This study examines the factors that affect Türkiye’s outward foreign direct investment (TODI) in European Union (EU) countries across quantiles using a panel quantile regression to understand the factors that affect TODI in EU countries with the most and least direct investment from Türkiye. We document that determinants of TODI in EU countries show significant discrepancies across quantiles. Mainly, we find that the relationship between the political stability (PS) level in EU countries and TODI is positive and also stable across quantiles. We also see a strong positive and monotonically declining relationship between Türkiye’s trade exports (EXP) and TODI. On the other hand, we do find that host country market size is negatively related to TODI with a declining slope across quantiles while labour resource endowments are positively related with a small variance across quantile. Overall, we provide policymakers with further information about the growing level of TODI in EU countries. Mainly, we recommend policy makers to make effective use of the relevant trade facilitation clauses in the EU customs union, expand the scale of Türkiye’s trade exports to EU countries, deepen political relations, and strengthen reciprocal political trust.

Remittances, financial development, and income inequality: A panel quantile regression approach

Remittances, financial development, and income inequality: A panel quantile regression approach

Does climate change affect sovereign credit risk? International evidence

This paper fills a crucial research gap by investigating the connection between climate change and sovereign credit risk. While the economic implications of climate risk have long been acknowledged, limited attention has been given to understanding its impact on sovereign credit risk. To address this gap, we provide novel empirical evidence on the influence of climate change readiness and vulnerability on sovereign credit default swaps (SCDS). Utilizing a panel quantile regression approach, our study reveals the following key findings: (i) Climate change readiness harms SCDS spreads across all quantiles; (ii) Climate change vulnerability positively affects SCDS spreads, except for the extreme upper quantile; and (iii) The relationship between climate change readiness and SCDS spreads is particularly pronounced in higher quantiles. By shedding light on these relationships, our analysis offers fresh insights into the intricate dynamics between climate change and sovereign credit risk.

Eco-innovations, green growth, and environmental taxes in EU countries: a panel quantile regression approach.

The purpose of this study is to examine how environmental taxation, green growth, and eco-innovations contribute to a more sustainable environment. This study examines the influence of green growth, environmental taxes, and eco-innovations on carbon dioxide emissions in 26 environmentally responsive European Union (EU) countries from 2000 to 2020. The analysis was conducted using the second-generation panel unit root test, cross-sectional dependence, panel cointegration, and panel quantile regression. Theoretical and empirical research has demonstrated that both linear and non-linear green growth strategies are effective in reducing CO2 emissions. There is evidence that CO2 emissions can be reduced through the implementation of environmental taxes, eco-innovations, the use of renewable energy sources, and enhanced energy efficiency. In contrast, economic growth has a positive effect on carbon emissions, and its square term verifies the environmental Kuznets curve. Nevertheless, our research findings provide empirical support for the hypothesis that sustainable development contributes to the maintenance of stringent environmental standards. For the sampled countries, the study's findings have significant policy implications. These results encourage governments to prioritize green growth over traditional economic growth and to encourage eco-innovations in renewable energy technology.

Industry 4.0 and Renewable Energy Production Nexus: An Empirical Investigation of G20 Countries with Panel Quantile Method

In line with the fourth industrial revolution, most countries have imposed a variety of regulations or policies for the goals of energy conservation, sustainable development, and industrial transition. Renewable energy production and its production process, which is widely discussed, especially in the context of sustainable energy, has become more important with Industry 4.0. This paper tested the relation among economic growth, renewable electricity generations (% of GDP), Industry 4.0, industrial structure, trade openness, financial development, and research and development expenditure for G20 countries in 2000–2021 by employing a panel quantile regression approach and various panel cointegration tests in addition to investigation of panel Granger causality among the analyzed variables. The variables of industrial structure, trade openness, and financial development were selected as control variables. Since this study is the first study on this topic, it will contribute to the development of the literature by providing resources for future studies about I4.0, renewable energy production, and economic growth. Furthermore, this study will not only contribute to the literature by revealing the theoretical and empirical relationship between these variables but will also shed light on the policies that G20 countries will produce in this regard. According to results, all variables examined have significant causal effects: unidirectional causality from economic growth to Industry 4.0, to research and development, and to renewable energy output and, also, from research and development to renewable energy output. Bidirectional causality and feedback effects between renewable energy and Industry 4.0 are determined. Further, unidirectional causality from industrial structure, from openness to trade, and from financial development to renewable energy output are determined. Results indicate renewable-enhancing effects of Industry 4.0.

The Nexus between Macroeconomic Factors and Tourism Receipts for Oic Countries: Panel Quantile Regression Approach

The current paper investigates the relationship between macroeconomic factors and tourism receipts for OIC countries. Based on the panel quantile regression analysis conducted, it is demonstrated that the impact of macroeconomic factors on tourism receipts is heterogeneous depending on the levels of tourism spending towards the OIC host countries. The exchange rate and income exhibit a positive relationship with tourism receipts. Meanwhile, inflation presents a negative relationship towards tourism receipt at the lower level of tourism receipt yet positively related at the higher level of spending. On the other hand, trade openness is negatively related to tourism receipts in general and the strength of the relationship decreases at a higher level of spending. The current research believes that to develop the tourism sector, proper plans should be made including improving the infrastructure, tourism facility, travel safety, and ease of entry considering the positive impact of economic development and trade openness. Relevant strategies should also be made to attract tourists from countries with higher purchasing power and strong currency value since it implies to be important in explaining the movement of tourism receipt. Keywords: Tourism Demand, Macroeconomic Factors, OIC countrie

Bank Risk, Bank competition and Monetary Policy in the Indian Banking Industry: A Panel Quantile Regression Approach

Bank Risk, Bank competition and Monetary Policy in the Indian Banking Industry: A Panel Quantile Regression Approach

Do ESG disclosures lead to superior firm performance? A method of moments panel quantile regression approach

AbstractWe verify the effect of ESG disclosures on firm performance using NSE 500 index listed companies spanning from 2010 to 2020. The study employs a method‐of‐moments quantile regression approach to test whether ESG disclosures lead to superior firm performance. We find evidence that environmental, social, and governance disclosures positively influence firm performance. Higher quantiles of ESG disclosures are associated with better market performance (Tobin's Q), and the same lead to lower profitability (ROA). The present study suggests that companies aspiring to improve their financial performance may pay more attention to ESG disclosure practices.

Asymmetric effects of monetary policy on non-bank financial intermediation (NBFI) assets: a panel quantile regression approach

PurposeThe purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI) assets.Design/methodology/approachThe authors utilized panel data from 29 countries for the period of 2012–2020 and used the quantile regression estimation. In addition to simultaneous quantile regression (SQR), the authors also employ quantile regression with clustered data (Parente and Silva, 2016) and the generalized quantile regression (GQR) method (Powell, 2020).FindingsThe empirical results show a significant heterogeneous impact of MP. While there is a positive relationship between MP and NBFI assets (“waterbed effect”) at lower quantiles of NBFI assets, at middle and higher quantiles, MP has a negative impact on NBFI assets (“search for yield” effect). The authors further find that negative impact strengthens as the quantile levels of NBFI assets rise from mid to high. Findings also reveal that “procyclicality” (except higher quantile) and “institutional demand” hypotheses hold. However, regarding “regulatory arbitrage,” mixed results are observed indicating the impact of Basel III requirements.Originality/valuePrevious empirical studies have concentrated on either the Dynamic Stochastic General Equilibrium (DSGE) framework or conditional mean regression approaches and delivered mixed findings of the MP effects on NBFI. The current paper takes a step toward dealing with this issue by deploying quantile regression methodology, which shows the impact of MP on NBFI at different conditional distributions (quantiles) of NBFI assets instead of just NBFI's conditional mean distribution.

The Potential Relationship Between Income Inequality and Environmental Quality in Iran: The Panel Quantile Regression Approach

This paper addresses the relationship between income inequality and environmental quality in the agriculture sector as the most related sector to the environment. In this context, we used a panel data set for 28 provinces of Iran during 2003-2017 and implemented panel quantile regression. To choose the best econometric specification the Taylor diagram is used. To explore whether the effect on income inequality on CO2 emission is different for rich and poor provinces, we consider the GINI × GDP interaction term in the model. Results confirmed that EKC in the agriculture sector of Iran, and a major and significant effect of energy consumption on CO2 emission. Findings indicated a threshold per capita income ($ 17.60 thousand) from which the effect of income inequality on carbon emissions changes. Based on these results, Marginal Properties to Emit (MPE) is more significant for poor people in low-income provinces than rich ones. Therefore, the government should adopt appropriate policies to increase the income of farmers so that the policy of income distribution, along with social justice, also improves the quality of the environment.

Tourism-income inequality Nexus in Africa: evidence from SADC countries

ABSTRACT The tourism sector is one of the fastest-growing services sub-sectors worldwide and promises to unlock job opportunities and improve social inclusion outcomes in developing countries. We focused on the Southern African Development Community (SADC) region, which houses developing countries with high income inequality and constitutes attractive tourist centres in sub-Saharan Africa. We employed both the disaggregated and composite indicators of tourism development to investigate the tourism-income inequality nexus in the SADC region from 2010 to 2019. Utilizing the panel quantile regression approach, our overall results suggest that tourism development is inequality-worsening, and this is robust to both the composite tourism index and the individual tourism indicators (except in a few instances). While we established that net FDI inflows improve the inequality outcomes in the region, less corruption worsens inequality (except in a few cases). Accordingly, we offer relevant policy options for the governments of the SADC region.

The nonlinear relationship between poverty and financial globalisation: A panel quantile regression approach

AbstractUsing data from 109 countries from 1980 to 2018, we examine the nonlinear relationship between financial globalisation and poverty. Financial globalisation is further segregated into de facto and de jure dimensions to study their differential impact on poverty. We have two main findings with important implications. First, our results point to significant nonlinearities, indicating that the relationship between financial globalisation and poverty is non‐monotonic. There exists a threshold above which the marginal effect of financial globalisation on poverty is negative. Moreover, the effect of financial globalisation on poverty is stronger for countries with high institutional characteristics. Second, we also show that the effect of financial globalisation is non‐monotonic and heterogeneous across different quantiles of poverty distribution. The effect of financial globalisation is relatively stronger at the higher quantile of poverty distribution for the overall sample. However, we find the existence of a U‐shaped and an inverted U‐shaped relationship between financial globalisation and poverty across quantiles, conditional on a country's economic development and institutional quality. The results are robust to alternative measures of poverty and financial globalisation. We account for unobserved heterogeneity and use multiple econometric approaches to validate our results.