Panel Autoregressive Distributed Lag Model Research Articles

The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries

This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country’s broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies.

Relationships between economic complexity, renewable energy uptake and environmental degradation: A global study

A persistent rise in the emission of CO2 among several economies in the world makes it challenging to fulfil the aims of the Sustainable Development Goals. The present study empirically examines the connection between economic complexity, which is understood to be structural conversion headed for more refined information-based production, renewable energy demand, per capita income, trade openness, industrialisation, and CO2 emissions among income-based groups of nations from 1998–2021. It also incorporates partner economies of the One Belt One Road (OBOR) project because these cover 65% of the global population. The findings of the panel autoregressive distributed lag model confirms that virtually all of the chosen samples of the various economies, aside from high-income economies, show that economic complexity degrades the environment. On the other hand, the demand for renewable energy enhances global environmental quality. The study highlights the significance of clean energy ventures and the production of greener quality products globally to minimise environmental damage.

Climate Risk and Sustainable Investment in Asia

This study conducts an empirical analysis of the impact of climate risk on Environmental, Social, and Governance (ESG) investments in Asia. Using monthly data from 2015 to 2022 for 11 Asian countries and applying wavelet coherence analysis with a panel Auto-regressive Distributed Lag Model (ARDL) cointegration approach, the study concludes that (1) ESG and stock market returns are positively correlated during economic turmoil in China and Malaysia; (2) climate risk positively influences ESG returns, suggesting that it enhances returns during uncertain times rather than having a detrimental effect; (3) returns on conventional assets are negatively impacted by climate risk; and (4) ESG investments serve as an effective hedge against climate risk and provide a sound strategy for portfolio diversification in the Asian market.

Deciphering the shadows: an empirical exploration of corruption’s impact on SMEs credit costs in OECD countries

Purpose This study aims to investigate the intricate relationship between corruption and the credit costs faced by small and medium-sized enterprises (SMEs) in OECD countries, a critical yet underexplored area in financial crime research. The primary aim is to dissect and understand how corruption impacts SMEs’ access to credit, highlighting a significant yet overlooked aspect of financial crime. This research seeks to fill a gap in the literature by providing empirical insights into the economic consequences of corruption, specifically on SMEs financing. Design/methodology/approach This study used secondary panel data from the World Bank and OECD databases. The data covered the period 2007–2020 for 25 OECD countries. This study used interest rate for SMEs loans as a dependent variable and GDP per capita, inflation and corruption index as independent variables. This study used the panel autoregressive distributed lag (ARDL) model to examine the relationship between variables. Findings The empirical findings derived from Panel ARDL postulate an intriguing dichotomy in the effects of GDP per capita, inflation rate and corruption on interest rates in both the short and long run. It was discerned that an increase in GDP per capita and inflation rate correlates with a decrement in interest rates in the long run, suggesting a potential compromise by central banks between controlling inflation and fostering economic growth. Originality/value This paper makes a novel contribution to the field of financial crime by illuminating the often-overlooked economic dimensions of corruption in the context of SMEs financing. It provides a unique perspective on the ripple effects of corrupt practices in credit markets, enriching the academic discourse and informing practical approaches to combating financial crime.

The impact of exchange rate and exchange rate volatility on tourism demand using disaggregated data

AbstractThe present study investigates the impacts of exchange rate and exchange rate volatility on inbound tourism demand in Mauritius, using annual data covering the period 1999–2019 and a panel autoregressive distributed lag model. In particular, we consider 17 major tourism markets for Mauritius. The sample is further divided into Eurozone (7 countries) and non‐Eurozone (10 countries) for additional insights. The results show that in the long run, both the exchange rate and its volatility have negative and significant impacts on tourism demand across the three samples considered, while income in the home country has a positive and significant effect on tourism demand. On the other hand, relative price is found to have a significant and negative effect on tourism demand only for the overall sample of 17 countries, while for both the Eurozone and non‐Eurozone, the impact is insignificant. The empirical results suggest that policymakers should give consideration to stronger monetary and fiscal regulations to increase tourism demand.

Does Competition Spur Innovation in North Africa? Evidence from a Panel ARDL Approach

The launch of the African Continental Free Trade Area at the beginning of 2021 provides new opportunities for North African countries to boost their economies. To conquer this vast market, innovation has become an ineluctable need. Although competition policy may serve as a salient lever for enhancing innovation, it is still not well harnessed by North African economies, even though they have one of the oldest competition law regimes on the African continent. For this purpose, this article attempts to explore the relationship between competition and innovation in four North African countries from 1995 to 2019. The second generation of panel unit root and cointegration tests have been used in our study. Based on the estimations of the panel autoregressive distributed lag model, our findings show that competition positively impacts innovation in the long run. Furthermore, our empirical results demonstrate that innovation is positively affected by economic growth and financial development while negatively affected by human capital and trade openness in the long run. The causality analysis reveals a unidirectional causal relationship running from competition to innovation. JEL Classification C32, C33, K21, O30

The short- and long-run relationship between house prices and bank credit in developed and emerging market economies: A comparative study

This study compares the short- and long-term relationships between house prices and bank credit in developed and Emerging Market Economies. This fact is an essential issue because most financing is facilitated by bank credit. Using quarterly data from 22 developed and six Emerging Market Economies and the panel autoregressive distributed lag model method, this study found that real house prices are the prominent factor of bank credit. Moreover, the magnitude of house prices and gross domestic product relationship with domestic bank credit is considerably greater in Emerging Market Economies than in developed nations. Meanwhile, the foreign interest rate on bank credit is nearly four times greater in Emerging Market Economies. Further, the exchange rate-credit relationship is positive for developed countries, whereas negative for Emerging Market Economies. Therefore, authorities maintaining financial stability must pay close attention to real house price dynamics. Moreover, Emerging Market Economies must also consider the exchange rate and foreign interest rates in managing credit growth.

Political factors, household income, under five survival, and life expectancy in the Sahel region.

In recent decades, the Sahel region has experienced ongoing health crises, including high fertility rates, declining life expectancy, and low under-five survival rates. As such, this study investigates the impact of political factors and household income on under-five survival and life expectancy in the Sahel region, using secondary data from seven countries in the area. The data for the study was extracted from the World Development Indicators, and a panel Autoregressive Distributed Lag model was applied for analysis. The findings reveal that individuals in the Sahel region have a life expectancy of approximately 57 years, with an alarming rate of approximately 102 children per 1,000 births not surviving beyond age five. Political factors significantly contribute to reduction of under-five survival and life expectancy in the region, as does household income. Therefore, addressing government effectiveness, political stability, and household income is crucial to improving health outcomes in the Sahel countries, ultimately enhancing under-five survival rates and life expectancy across the region.

Export Diversification, Financial Sector Development and Economic Growth: Empirical Evidence from West African Sub-Region

In this study, we explored the influence of trade diversification and financial sector development on economic growth of ten West African countries for the period 2007 to 2020. The study employed the panel autoregressive distributed lag (ARDL) model since some of the variables were stationary at level while others were stationary at first difference, fully modified ordinary least squares approach of estimation, and Granger causality test. The findings of the study from the ARDL model indicated that export diversification exerts a negative effect on economic growth both in the short-run and in the long-run, though such effect were insignificant. The effect of financial sector development on growth is observed to be positive and significant in the short-run, and negative and significant in the long-run. From the robustness check, the FMOLS result indicated that export diversification exerted a negative and significant effect on growth; while the effect of financial development is positive but insignificant. The Granger causality test revealed that a unidirectional causality flow between export diversification and economic growth, with the former causing the latter. The implication of this findings is that countries within the West African region should specialize in some export products in order to boost efficiency in production and the resultant effect on greater export and export earnings.

Drivers of Sustainable Green Finance: Country’s Level Risk and Trade Perspective for OECD Countries

In contemporary times, developed economies are adopting environmentally friendly initiatives such as green finance and energy efficiency. However, the factors affecting energy efficiency are widely explored, and green finance remains overlooked in the empirical literature. The present research examines the drivers of sustainable green finance in OECD economies during 2004–2021. The study uses several panel diagnostic tests and validates the mixed integration order of the variables. Still, the long-run equilibrium relationship is valid between financial inclusion, energy efficiency, human capital, foreign trade, composite risk, and green finance. Using panel autoregressive distributed lag model, the study found that financial inclusion, energy efficiency, foreign trade, and composite risk significantly improve green finance in the long run. However, only energy efficiency is effective in the short run. On the other hand, human capital exhibits a significant adverse influence on green finance. The long-run results are robust due to the significant estimates offered by panel dynamic ordinary least square. Besides, there exist one-way and two-way causal associations between variables. The study recommends improving the financial sector performance to enhance financial inclusivity, increase investment in the energy efficiency sector, and encourage trade in environmentally friendly initiatives.

Energy mix diversification in emerging economies: An econometric analysis of determinants

Energy mix diversification (EMD) is recognized as a plausible strategy for emerging economies to achieve energy security targets and meet net zero carbon emissions goals by 2050. Thus, this research explores the determinants of EMD utilizing a sample panel for seven major emerging (E7) economies, including Brazil, China, India, Indonesia, Mexico, Russia, and Turkey, observed from 1995 to 2018. The Pedroni panel cointegration test investigates the long-run equilibrium, and the long- and short-run determinants are identified using a panel autoregressive distributed lag model. The findings reveal a long-run equilibrium linkage among EMD, carbon emissions, financial development, economic growth, technological progress, energy efficiency, and globalization. The long-run estimates show that energy efficiency and carbon emissions are driving forces for EMD, whereas technological progress, financial development, and globalization have insignificant effects. However, all variables - except economic growth are found to be the barriers to EMD in the short-run. The findings presented in this research are novel and add value to the energy literature by identifying the long- and short-run determinants of EMD, specifically for E7 economies. These economies are expected to take appropriate actions to stimulate the adoption of clean and green energy sources; thus, appropriate implications of the findings are discussed.

Moving toward sustainable agriculture: The nexus between clean energy, ICT, human capital and environmental degradation under SDG policies in European countries

The United Nation's adaptation of the 2030 sustainable Development Goals (SDG) agenda has swung the attention toward sustainability. However, in achieving SDGs, this study investigates the nexus between agricultural productivity, renewable energy, ICT, human capital, CO2 emissions, and natural resources in a panel of ten European Union (EU) countries from 1996 to 2019. Our study uses the panel autoregressive distributed lag (ARDL) model of the Pool Mean Group (PMG) to estimate the long-run and short-run effects and heterogeneous causality approach. The empirical results ratify that a 1 % upsurge in the coefficient of renewable energy, ICT, and human capital increases agricultural productivity by 0.174 %, 0.030 %, and 2.158 % in the long run. Whereas, CO2 emission and natural resources decrease agricultural productivity. Finally, various causality exists among variables for EU countries. Our empirical results for the EU countries are notionally reliable and offer important policy implications accordingly.

Nonlinear relationships between Foreign Direct Investment decisions and environmental degradation in high- and middle-income countries

Globalization, although beneficial in spreading knowledge and improving green technologies worldwide, is also considered one of the main drivers of global warming. Recent world events, such as the pandemic, with all its economic and social consequences, have exposed the external dependence of many countries, particularly the reliance of many developing countries on foreign investment. Although it contributes to economic growth, Foreign Direct Investment may also be harmful to the environment. Hence, this study analyses the impact of Foreign Direct Investment on emissions of Greenhouse Gases, Carbon Dioxide, Nitrous Oxide and Particulate Matter 2.5. A Panel Autoregressive Distributed Lag model was conducted for a group of 25 high-income and 10 middle-income countries from 1995 to 2019, allowing the analysis of short- and long-run impacts. Given the likelihood of nonlinear impacts, a Nonlinear Panel Autoregressive Distributed Lag model was also conducted to provide a more detailed understanding of the effects of expansion or contraction on the variables, and also to analyse short- and long-run impacts. The main findings suggest that electrification and energy transition away from fossil fuels to renewable energy may be crucial to limiting the polluting effect of Gross Fixed Capital Formation, Trade Openness and Foreign Direct Investment. However, it would be a mistake to simply reduce these three factors as the results reveal that it also contributes to increase pollution. Foreign Direct Investment and Trade Openness reduce environmental degradation in high-income countries and increase it in middle-income countries, except for Nitrous Oxide emissions.

Impact of natural resources, trade openness, and economic growth on CO2 emissions in oil‐exporting countries: A panel autoregressive distributed lag analysis

AbstractThis study explores the impact of natural resource exploitation, trade openness, and economic growth on carbon emissions in a sample of oil‐exporting nations for the period 1971–2014. To examine this relationship, we used the panel autoregressive distributed lag model and a set of econometric techniques accounting for cross‐sectional dependence. Our results indicate that the exploitation of natural resources and trade openness have a long‐term negative impact on environmental quality. Furthermore, our analysis confirms the validity of the Kuznets Environmental Curve for oil‐exporting countries. An assessment of causality reveals a bidirectional link between natural resources, economic growth, and CO2 emissions, as well as a unidirectional link between trade openness and CO2 emissions. In the light of our findings, appropriate policies could include the imposition of more stringent regulations on the exploitation of natural resources, the application of taxes on carbon emissions, and the promotion of clean and renewable technologies. Greater international cooperation is also needed to address these environmental issues on a global scale.

Do FDI and Trade Openness Matter for Economic Growth in CIS Countries? Evidence from Panel ARDL

For the purpose of this paper, we examine the association between foreign direct investment, openness to trade, infrastructure, innovation, and economic development in 10 members of the Commonwealth Independent States between 2000 and 2020 using a panel Autoregressive Distributed Lag model. According to the results, none of the elements that are researched for this paper has a statistically significant influence on economic growth over the short term. On the other hand, in the long run, each of the variables, including foreign direct investment, infrastructure, innovation, and trade openness, has a statistically favorable and substantial impact on economic growth; furthermore, the findings are in line with the findings of the baseline static panel data models.

The 15 West African countries as an optimum currency area and the role of labour mobility in the adjustment to asymmetric shocks

This paper assesses the nature and correlation of shocks in Economic Community of West African States (ECOWAS) countries and investigates the readiness of member countries for the formation of a monetary union. It also assesses the role of labour mobility as an adjustment mechanism to asymmetric shocks. Structural vector autoregression (SVAR) models are used in assessing the nature and correlation of shocks while cointegrated panel autoregressive distributed lag (ARDL) models are employed to examine the role of labour mobility in the adjustment process to asymmetric shocks. The results show that the ECOWAS region is characterised by asymmetric shocks. The study also finds that most countries failed to consistently meet the convergence criteria for the formation of the monetary union and that labour mobility in the region is low to act as an efficient adjustment mechanism to asymmetric shocks. It takes about 2–5 years for member countries to adjust to asymmetric shocks through labour mobility.

The effects of national and international tourism on income inequality: evidence from Asia-Pacific economies

PurposeThis paper explores the effect of tourism (national and international) indicators on income inequality in a sample of 21 Asia Pacific economies.Design/methodology/approachThis study uses panel data set from 1995 to 2020 and employs panel autoregressive distributed lag (ARDL) method for the empirical investigation.FindingsThe empirical findings from the panel ARDL models suggest that all of the considered tourism indicators have significant negative impacts on income inequalities. The results remain consistent with alternative indicators and methods.Social implicationsThe findings of this study will be critical for the policymakers to take effective measures to reduce the income inequality. Such measures could include promoting tourism in general, focusing on attracting international tourists or domestic tourists, and putting more weight on developing leisure or business tourism, which will boost the overall economic performance and alleviates inequalities in the society.Originality/valueThis is the first study to consider various forms of tourism indicators to see their impact on income inequality in the Asia–Pacific region, and offers important implications for the policy actions.

Correlation of air quality with population aging, industrial structure upgrading, and research and development in China based on empirical analysis

China’s population has been aging quickly in recent years, putting pressure on the environment. Population aging has also amplified the role of industrial upgrading and research and development (R&D) on environmental quality. Against this backdrop, we investigated the long-run and short-run relationships among population aging, industrial structure upgrading, R&D, and air quality in 30 Chinese provinces from 2006 to 2020. The panel autoregressive distributed lag (ARDL) model was first applied in this study. The results revealed that population aging temporarily harmed air quality but improved it over time. The favorable impact of industrial upgrading on air quality was enhanced by population aging, but the positive impact of R&D investment on air quality was reduced. Furthermore, Dumitrescu and Hurlin (D-H) Granger causality tests were adopted to confirm that population aging had a single-way causal link with air quality, whereas industrial upgrading and R&D had dual-way causal associations with air quality.

The efficacy of government strategies to control the COVID-19 pandemic

PurposeThis study aims to explore the efficacy of government policy directions in mitigating the effects of the COVID-19 pandemic by employing a panel of 22 countries throughout the 2020-second quarter of 2022.Design/methodology/approachThe panel autoregressive distributed lag (ARDL) model is employed to examine this phenomenon and to investigate the long-run effects of government policy decisions on infection and mortality rates from the pandemic.FindingsThe study reveals the following key findings: (1) Income support and debt relief facilities and stringent standards of governments are associated with reduced infection and death rates. (2) The response of governments has resulted in decreased mortality rates while simultaneously leading to an unexpected increase in infection rates. (3) Containment and healthcare practices have led to a decrease in infection rates but an increase in mortality rates, presenting another counterintuitive outcome. Despite the expectation that robust government responses would decrease infection rates and that healthcare containment practices would reduce mortality, these results highlight a lack of health equity and the challenge of achieving high vaccination rates across countries.Research limitations/implicationsTo effectively combat the spread of COVID-19, it is crucial to implement containment health practices in conjunction with tracing and individual-level quarantine. Simply implementing containment health measures without these interconnected strategies would be ineffective. Therefore, policy implications derived from containment health measures should be accompanied by targeted, aggressive, and rapid containment strategies aimed at significantly reducing the number of individuals infected with COVID-19.Practical implicationsThis study concludes by suggesting the importance of implementing economic support in terms of income, and debt relief has played a crucial role in mitigating the spread of COVID-19 infections and reducing fatality rates.Social implicationsTo effectively combat the spread of COVID-19, it is crucial to implement containment health practices in conjunction with tracing and individual-level quarantine. Simply implementing containment health measures without these interconnected strategies would be ineffective. Therefore, policy implications derived from containment health measures should be accompanied by targeted, aggressive, and rapid containment strategies aimed at significantly reducing the number of individuals infected with COVID-19.Originality/valueThis research makes a unique contribution to the existing literature by investigating the impact of government responses on reducing COVID-19 infections and fatalities, specifically focusing on the period before COVID-19 vaccinations became available.

Examining the Impact of Innovations on Economic Growth in BRICS Countries

The study investigated the causal nexus between innovations and economic growth of Brazil, Russia, India, China and South Africa (BRICS) countries using panel data for the period 2004–2019. The total number of patent applications, the total number of trademark applications and percentages share of research and development expenditures to GDP are used as a proxy to measure innovations. The study used a panel regression with a fixed and random effect model, panel vector autoregression (VAR) model and impulse response function for the analysis. Further, the study checked both the symmetric and asymmetric impacts of innovations on economic growth using the panel autoregressive distributed lag (ARDL) model. The results from different econometric approaches are consistent and found that innovations positively and significantly impact economic growth. The results have also shown that there is a unidirectional causality running from innovations to per capita GDP in the short run. Finally, the results have shown the asymmetric causal linkage between innovations and economic growth. The study suggests that policymakers must encourage more investments in innovations for high economic growth in BRICS countries.