Panel Quantile Regression Analysis Research Articles

Dynamic Impact of Digital Inclusive Finance and Financial Market Development on Forests and Timber in China: Economic and Social Perspective

This study investigates how digital inclusive finance, financial development, and technology influenced forest and timber outputs across 31 provinces in China from 2011 to 2021. The findings, derived from panel quantile regression analysis, indicate that digital inclusive finance significantly enhances forest economic output, particularly in regions with lower economic activity, by improving access to critical financial resources such as credit and investment. However, the positive effects diminish at higher levels of economic activity, suggesting potential diminishing returns. Through the marketization of credit distribution and diverse financial instruments, financial development is essential for promoting sustainable forestry practices and adopting new technologies. Based on the findings, the study suggests expanding digital financial services in areas with low forest activity to help people access credit and investments, boosting forest productivity. It also recommends improving financial markets and investing in new forestry technologies to support better forest management and timber production.

Gender Norms and Female Labor Supply in Sub-Saharan Africa: A Dynamic Panel Quantile Regression Analysis

Gender Norms and Female Labor Supply in Sub-Saharan Africa: A Dynamic Panel Quantile Regression Analysis

Capital structure and performance nexus: Insights from fixed-effects and quantile analysis

The research utilizes a comprehensive dataset from MENA-listed companies, capturing data from 2013 to 2022 to scrutinize the influence of capital structure (CapSt) level on corporate performance across 11 distinct countries. This study analyzed 6870 firm-year observations using a quantitative research method through static and dynamic panel data analysis. The primary analysis reveals a positive correlation between the CapSt ratio and company performance using fixed effects (FE) techniques. Hence, the preliminary results were re-examined and affirmed using a two-step system generalized method of moment (GMM) estimator to address potential endogeneity concerns. This finding aligns with most studies conducted in advanced countries, indicating a positive correlation between CapSt and corporate performance. Furthermore, it is also consistent with some research conducted in less-developed markets. This research argues that, in the MENA region, the advantages of debt, such as tax saving, may outweigh the potential financial distress cost. Furthermore, it offers insights into the monitoring role of CapSt in MENA-listed companies. We strengthen our research results by employing various methodologies and using alternative measures of accounting performance and controlling size, notably panel quantile regression analysis.

Does energy innovation heterogeneously affect renewable energy production?

Achieving long-term sustainable development is a critical global imperative, and the adoption of renewable energy sources plays a pivotal role in this endeavor, aided by the advancements of the Fourth Industrial Revolution. As a result, energy innovation has emerged as a crucial factor in realizing sustainable development goals. This study utilizes panel quantile regression analysis to investigate the relationship between energy innovation and renewable energy production in the Middle East and North Africa (MENA) region from 1985 to 2019. The findings suggest that energy innovation can effectively enhance renewable energy production, particularly in countries with higher proportions of renewable energy generation, such as Egypt, Morocco, and Tunisia. However, countries like Saudi Arabia, which have lower ratios of renewable energy production, may not experience a significant impact from energy innovation. Consequently, the study recommends implementing systematic and integrated measures that focus on raising awareness and improving conditions for the adoption of renewable energy. These measures can drive the transition towards a more sustainable energy landscape in the MENA region. Policymakers should prioritize research and development investment and incentives in countries with higher levels of renewable energy generation, while simultaneously addressing barriers and fostering knowledge sharing between countries with differing levels of renewable energy production.

The Technological Effects of Renewable and Non-Renewable Energy on Agricultural Productivity in Developed Countries

Existing literature confirms both the role of agricultural technology in elevating agricultural productivity and the positive effects of green energy on environmental sustainability; nevertheless, less attention has been paid to agrotechnology’s energy sources and their adaptability to agri-environmental conditions using econometric methods. This study examines the association between renewable and non-renewable energy agrotechnology, and agricultural productivity in 32 developed nations from 2000 to 2021. We apply a difference Generalised Method of Moments (GMM) panel data estimation and Dumitrescu and Hurlin causality test. The findings report a significant and negative coefficient for non-renewable energy agrotechnology indicating that fossil fuel agrotechnology reduces agricultural productivity and thereby causes concerns over sustaining agricultural growth in developed countries. In contrast, the coefficient of renewable energy agrotechnology is positive and highly statistically significant, confirming maximising effects on agricultural productivity. We conduct two robustness checks to assess the credibility of the results. Using panel quantile regression analysis allows for establishing various relationships between the estimated variables at different quantiles of agricultural productivity. Testing for Dumitrescu and Hurlin causality test, we find bidirectional causal links between agricultural productivity and non-renewable energy agrotechnology, renewable energy agrotechnology and FDI, but only a one-way causal relationship between the other variables. This result suggests no integrated policy among the developed countries towards agricultural sustainability, despite their commitments to the Sustainable Development Goals (SDGs). These findings emphasise the employment of sustainable renewable energy agrotechnology as a strategy to tackle the fundamental problems of sustainable agricultural growth.

Expression of concern: Resource curse hypothesis and economic growth: A global analysis using bootstrapped panel quantile regression analysis [Resources Policy, Volume 85, Part A, August 2023, 103790]

Expression of concern: Resource curse hypothesis and economic growth: A global analysis using bootstrapped panel quantile regression analysis [Resources Policy, Volume 85, Part A, August 2023, 103790]

Quantifying Environmental Degradation through Renewable Energy, Financial Development and Economic Sustainability: Insights from Panel Quantile Regression Analysis

The degradation of the environment is a global concern that needs serious attention, including the environmental Kuznets curve (EKC) hypothesis. This article examines the effects of renewable energy, financial development and economic sustainability on the environmental quality of newly industrialized countries (NICs) from 1998 to 2021 in light of the increasing severity of environmental problems associated with industrialization. This study utilized different panel cointegration estimation techniques and panel quantile regression (PQR) estimates to obtain robust findings by examining the variance of each quantile. The results of the cointegration tests confirm the long-run relationship among the variables. Nevertheless, the outcomes from the PQR unveiled that renewable energy negatively and significantly influences CO2 emissions in NICs, namely in the lower and middle quantiles (20th–50th). Financial development showed heterogeneity in the results of all the quantiles. It results in an increase in CO2 emissions from the 70th to 90th quantiles in NICs. The EKC hypothesis is relevant to these findings as this study presents the economic sustainability index, which postulates that when NICs achieve sustainability, they give greater importance to environmental preservation and sustainability. This shift is characterized by reduced emissions throughout all quantiles, ranging from the 10th to the 90th. Economic sustainability corresponds to the falling part of the U-shaped curve of the EKC, wherein sustainability gets priority, resulting in reduced CO2 emissions. Analogous results have been confirmed by comparing heterogeneous panel estimators; nonetheless, there was a significant variation in the intensity of their parameters. Moreover, the robustness analysis through quantile slope equality and symmetric quantiles tests proved legitimate results. The study’s findings offer policymakers with valuable policy recommendations. JEL Codes: C1, F36, F43, O44, Q56

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.

The effect of MD&A disclosures on corporate performance: a panel quantile regression analysis

PurposeThe study aims to examine how the information disclosed by the managers in the management discussion and analysis (MD&A) reports varies at the different levels of corporate performance.Design/methodology/approachTo understand this quantile effect, first OLS technique was adopted and then, the quantile regression method was applied to explore the impact of MD&A disclosures on the firm performance across the lower and upper quantiles. The sample size for the study is 490 firms’ year observations for the period 2016–2022.FindingsThe results of the study demonstrate the negative but significant relationship between MD&A disclosures and corporate performance, supporting the two management strategies of “competitive disadvantage” in case of good performance and “management impression strategy” in case of poor performance. Furthermore, with other corporate governance variables, both the size of the board and the number of independent directors on the board are positively significant only in the case of the upper quantile indicating the heterogeneity in the relationship between the performance and the MD&A disclosures. Therefore, the overall findings of the study support that these results contradict the agency theory and the stakeholders’ theory as managers are not acting well as agents on behalf of the investors and work well only when they are controlled by the large board having more independent directors.Originality/valueTo the best of the authors’ knowledge, no study so far has incorporated quantile regression to assess the effect of MD&A disclosures on company performance at various levels of the firm performance, which gives more robust insights about the viewpoint of the managers on the different level of the firm performance. In other words, this study highlights the important information as to how the information provided in the MD&A reports varies as per the good or poor performance of the companies.

The Impact of Port Total Factor Productivity on Carbon Dioxide Emissions in Port Cities: Evidence from the Yangtze River Ports

This paper investigates the relationship between port productivity and carbon dioxide (CO2) emissions in port cities. The study initially employs the global Malmquist productivity index (MPI) to measure productivity growth in 16 major inland ports along the Yangtze River, obtaining data on the ports’ total factor productivity (TFP). Through an analysis using the panel data model with two-way fixed effects, we find a positive correlation between the improvement of port TFP and the increase in CO2 emissions in port cities. Further panel quantile regression analysis reveals the heterogeneity of this impact, especially in cities with medium and higher CO2 emissions, where the positive effects of TFP on carbon emissions are particularly significant. The study also indicates a threshold effect of port size in the relationship between TFP and CO2 emissions: in smaller ports, the impact of TFP improvement on CO2 emissions is less significant; however, once the port size exceeds a certain threshold, the growth in TFP significantly promotes an increase in CO2 emissions. These findings provide theoretical justification and decision-making references for policymakers to adopt effective measures to mitigate the growth of CO2 emissions while promoting the efficiency of port production.

Influence of foreign institutional holding on corporate risk-return profile: a panel quantile regression analysis

Influence of foreign institutional holding on corporate risk-return profile: a panel quantile regression analysis

Impact of Financial Integration on Economic Development: A Dynamic Panel Quantile Regression Analysis

This paper investigated the impact of financial integration on economic development using the dynamic panel quantile estimator on a sample of 95 countries from 2004-2019. The results showed that the impact of financial integration on economic development varied across income levels. This study found that financial integration impacted economic development negatively in middle and high-income countries. However, financial integration did not significantly affect economic development in low-income countries.

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.

Healthcare Systems and COVID-19 Mortality in Selected OECD Countries: A Panel Quantile Regression Analysis.

The pandemic caused by coronavirus disease 2019 (COVID-19) has exerted an unprecedented impact on the health of populations worldwide. However, the adverse health consequences of the pandemic in terms of infection and mortality rates have varied across countries. In this study, we investigate whether COVID-19 mortality rates across a group of developed nations are associated with characteristics of their healthcare systems, beyond the differential policy responses in those countries. To achieve the study objective, we distinguished healthcare systems based on the extent of healthcare decommodification. Using available daily data from 2020, 2021, and 2022, we applied quantile regression with non-additive fixed effects to estimate mortality rates across quantiles. Our analysis began prior to vaccine development (in 2020) and continued after the vaccines were introduced (throughout 2021 and part of 2022). The findings indicate that higher testing rates, coupled with more stringent containment and public health measures, had a significant negative impact on the death rate in both pre-vaccination and post-vaccination models. The data from the post-vaccination model demonstrate that higher vaccination rates were associated with significant decreases in fatalities. Additionally, our research indicates that countries with healthcare systems characterized by high and medium levels of decommodification experienced lower mortality rates than those with healthcare systems involving low decommodification. The results of this study indicate that stronger public health infrastructure and more inclusive social protections have mitigated the severity of the pandemic's adverse health impacts, more so than emergency containment measures and social restrictions.

Tax Revenues and Economic Growth: Evidence from Panel Quantile Regression Analysis

Changes in countries tax policies can affect many macroeconomic factors, such as production, investment, employment, income distribution, and economic growth. Governments often resort to fiscal policy tools to steer the economy. One of the fiscal policy tools is taxes. However, there is no consensus on how tax changes affect economic growth. Therefore, this study analyzes the relationship between tax revenues and economic growth by quantile regression analysis with annual data for 37 OECD countries from 1995-2020. According to the findings obtained from quantile regression analysis, it is found that taxes have a negative and statistically significant effect on economic growth in countries with low economic growth and also in the panel average. In addition, it is determined that tax revenues have a positive impact on economic growth in countries with high economic growth and a negative but statistically insignificant effect in other quantiles. Based on these results, it can be said that tax increases in OECD countries with low economic growth will reduce economic growth. Therefore it is essential for these countries that want to grow economically must restructure their tax policies by taking this into account.

On the nexus between real income, renewable energy consumption, and environmental sustainability on life expectancy for BRICS‐T countries: Accessing evidence from quantile regression

AbstractThis study is aimed at establishing the impact of real income, renewable energy consumption, and carbon dioxide (CO2) emission on life expectancy for annual frequency data from 1990 to 2019 for BRICS‐T (Brazil, Russia, India, China, South Africa, and Turkiye) economies. In addition, the effects of real income, renewable energy consumption, and life expectancy on CO2 emissions are given by establishing a second model. To this end, different econometric approaches such as fixed effects model, random effects model, panel quantile regression, and the Dumitrescu and Hurlin panel causality test were used. We found in our empirical evidence that renewable energy consumption and real income positively affect life expectancy. At the same time, it was seen that real income has a positive effect on CO2 emissions, but renewable energy consumption has a negative effect. According to the panel quantile regression analysis results, while the effect of income on life expectancy is similar to other estimation results, that of renewable energy consumption is different. However, the effect of renewable energy consumption and real income on CO2 emissions is similar to other estimation results. The findings of the study show that policy makers need to promote renewable energy in order to extend life expectancy which is an important determinant of economic growth.

Natural resources-environmental sustainability-socio-economic drivers nexus: Insights from panel quantile regression analysis

In order to achieve the Sustainable Development Goals (SDGs), it will be difficult for many countries especially developing countries, to increase economic growth while promoting environmental sustainability. The main purpose of the study is to investigate the relationship of KOF, GDP, GDP2, HDI, MFG, NRE and PD on CO2 emissions in 64 countries during 2000–2020. The findings showed that the EKC hypothesis was valid up to the 70th quantile in full sample. However, in the higher quantiles, a turning point was observed. High-income countries exhibited an N-shaped relationship, while upper-middle-income countries showed an inverted U-shaped relationship. Lower-middle-income countries displayed a U-shaped relationship until the 30th quantile, followed by an inverted U-shaped relationship from the 40th to 80th quantile, and an insignificant relationship after the 80th quantile. Low-income countries exhibited a U-shaped relationship. The study found that globalization mitigated CO2 emissions in high-income countries. However, in lower-middle- and low-income countries, it shows the pollution heaven hypothesis. The industrialization and non-renewable energy significantly degrade the environment. The HDI mitigated CO2 emissions in the progressive quantiles of high- and upper-middle-income countries, but in another sub-samples.

The Relationship between Macroeconomic Factors and Tourism Demand for OIC Countries

Objective – The current paper investigates the relationship between macroeconomic factors and tourism demand for OIC countries. Methodology – The current paper employed the panel quantile regression analysis to assess the relationship. Findings – It is demonstrated that the impact of macroeconomic factors on tourism receipts is heterogeneous depending on the levels of tourism spending in the OIC host countries. The exchange rate and income exhibit a positive relationship with tourism demand. Meanwhile, inflation presents a negative relationship towards tourism demand at the lower level of tourism demand yet is positively related to the higher level. 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 demand. Novelty – Compared to previous studies, the impact of the macroeconomic factors was assessed across different levels of tourism demand. Type of Paper: Empirical JEL Classification: L83, Z32, O10 Keywords: Tourism Demand; Macroeconomic Factors; OIC countries; Quantile Regression Reference to this paper should be made as follows: Pinjaman, S; Jemin, S; Ridzuan, A.R; Lada, S. (2023). The Relationship Between Macroeconomic Factors and Tourism Demand for OIC Countries, J. Bus. Econ. Review, 8(2), 60–68. https://doi.org/10.35609/jber.2023.8.2(2)

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

A different look at the environmental Kuznets curve from the perspective of environmental deterioration and economic policy uncertainty: evidence from fragile countries.

Environmental degradation is one of the most significant issues that developing nations confront and needs to be resolved right away in order for them to achieve sustainable development. Government policies are crucial in this situation since emerging nations frequently struggle with the issue of policy ambiguity, which can result in environmental deterioration.In this context, this study investigates how policy uncertainty affects environmental degradation in the five fragile emerging economies known as the Fragile Five-Brazil, India, Indonesia, South Africa, and Turkey. Using data from 1996 to 2019, we estimate a Panel Quantile Regression analysis. The empirical findings indicate that economic policy uncertainty and technology innovation increases the environmental degradation whereas environmental degradation is slowed down by financial development and renewable energy consumption. Empirical evidence also confirms the presence of EKC hypothesis in fragile economies. Based on the findings, we suggest both a policy and an environmental framework for achieving sustainable development in fragile economies.