Autoregressive Distributed Lag Research Articles

Quadrant categorization of spillover determinants of sovereign risk of BRICIT nations: a Bayesian approach

This study investigates the determinants that drive the volatility of the credit default swaps (CDS) of BRICIT (Brazil, Russia, India, China, Indonesia, and Turkey) nations as a proxy measure for sovereign risk. On the existence of cointegration, an unrestricted error correction model integrated with the autoregressive distributed lag (ARDL) model is applied to measure the short-run and long-run dynamics empirically. The study utilizes the Bayesian global vector autoregression methodology for cross-border spillover estimation. The study also suggests a strategy for policymakers for quadrant categorization to mitigate risk arising from cross-border spillover. The result of ARDL indicates that the global macroeconomic variables affect the BRICIT CDS more than domestic macroeconomic determinants, with Indian CDS being the most sensitive to Fed tapering. Notably, China’s CDS is the most sensitive to shocks, with the CDS volatility primarily driven by China’s geopolitical risk. Russian CDS is more sensitive to real effective exchange rates due to severe ruble depreciation than crude oil, despite Russia being a major oil exporter. The quadrant categorization indicates that the Indonesian stock market index is most interconnected with BRICIT CDS, while the Turkish long-term interest rates send the highest intensity spillover across BRICIT nations.

Impact of Financial Development, Renewable Energy, and Natural Resources on Macroeconomic Performance in Pakistan

The objective of this study is to investigate the impact of financial development, renewable energy consumption, and natural resources on macroeconomic performance in Pakistan. The study employs the autoregressive distributive lag (ARDL) technique to check the association among the selected variables. Macroeconomic performance is dependent and financial development, renewable energy, natural resources, and human capital uses as independent variables in this study. Data taken from the World Development Indicator (WDI) range from 1990 to 2023. Unit root tests Augmented Dickey-Fuller and Phillips Parron employs to check the variable's stationarity. The results found that in the short run natural resources has negative and insignificant and renewable energy has a negative but significant impact on macroeconomic performance. However financial development and human capital have positive and significant impacts on macroeconomic performance. In the long run financial development, renewable energy, natural resources, and human capital have a positive and significant impact except human capital on macroeconomic performance in Pakistan.

Dynamics of Interest Rates, Inflation and Forex in ARDL Framework: Evidence from India in an SDG Context

Objective: This study examines the dynamic causal relationship between the exchange rate, inflation, and interest rate from 2011 to 2023. Method: Using both the linear autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) methods, the results show that exchange rate and inflation have an equilibrium relationship over the long term. Results and Discussion: However, the connection between the interest rate and the exchange rate is unstable. As the inflation rate changes, the exchange rate displays its dynamic behavior. As opposed to this, interest rates shouldn't always affect how currencies behave. Policy ramifications of this study are evident. Price stability can only be attained with accurate fundamentals. Central banks that promote environmental sustainability and align with the United Nations' Sustainable Development Goals (SDGs) frequently use a Sustainability-Linked Monetary Policy (SLMP) framework. Contributions: This framework targets emission activities through interest rates or loan-to-value ratios, with the goal of influencing liquidity for greener production. Conclusions: However, the welfare implications of such policies are still unclear (MAS, 2021; LMA, 2019; DBS, 2021; BOJ, 2021; Mizuho, 2021).

How Does Inward FDI Lead to Trade Performance and Sustainable Growth In India?

Objectives: The purpose of this study is to examines the relationship between Foreign Direct Investment and trade performance (Export and Import) in India from 1991-2022. The purpose of the study is Causality analysis also, between FDI and trade with other considered variables. Methods: This study utilizes annual data from 1991 to 2022 from the World Bank (2022) and the Reserve Bank of India (2022). Data on GDP, Export, Inflation and interest rate, and FDI are collected from the World Bank. Autoregressive Distributive lag Model procedure has been used for the study in order to establish relationship between trade performance and FDI. Results and discussion: The Auto-regressive distributive lag-bound-co-integration (ARDL) method confirms a long-run association between FDI and export. Coefficient indicates significant and negative relation establishes between FDI and Export but the coefficient between FDI and import represent weak relation. Causality analysis reveals unidirectional relation between FDI and Export, and the direction of causality is from export to FDI. It means export causes FDI, FDI does not causes Export. A negative coefficient indicates that there is a need for efficiency-seeking and export-oriented FDI but negative relations support that Foreign Direct investors prefer market seeking FDI and they focused more on the domestic market opportunity of India. Research Implication: This result supports the market-seeking approach and FDI trade substitute theorem which confirms that the inflow of FDI in India is only for utilizing domestic market opportunity instead of exporting goods to other countries. Therefore, there is a need for efficiency-seeking or export-oriented FDI. The government should facilitate and accordingly create their policy to increase export-oriented FDI to improve technology and productivity of India as well as increases foreign exchange and infrastructure dvelopment in order to sustain growth of india. Originality: India’s FDI situation is presently seeing a growth with liberalized reforms over the recent two decades, several changes like ease of doing, infrastructural development, increased the limit of FDI in several sectors create alluring investment atmosphere having a beneficial outcome of the inflows. Result contributed towards trade and FDI relation that FDI comes from the other countries in india to capture our market potenials so government should try to enhance export oriented FDI in order to know the techniques and improves the export potential as well. Investment and export both simultaneously create a path for sustainable development.

Sustainable Development in Africa: A Comprehensive Analysis of GDP, CO2 Emissions, and Socio-Economic Factors

The fight against climate change is gaining momentum, with a growing focus on reducing carbon dioxide (CO2) emissions and mitigating environmental impacts. Africa, the continent most vulnerable to global warming, faces unique challenges in this context. This study examines the long-term association among CO2 emissions, economic growth, and different socio-economic factors in 36 African countries from 1990 to 2020. Employing the Pooled Mean Group (PMG) estimator with Autoregressive Distributed Lag (ARDL) model, along with U-test and Dumitrescu and Hurlin causality analyses, our study reveals substantial long-term connections amongst CO2 emissions and factors such as economic growth, trade openness, renewable energy consumption, urbanization, and population dynamics. The findings support the Environmental Kuznets Curve (EKC) hypothesis, indicating that CO2 emissions initially increase with GDP per capita growth but begin to decline after a turning point at approximately 10,614.75 USD. However, the evidence for this turning point remains weak, suggesting that most African countries have not yet achieved decoupling. Renewable energy consumption and urbanization are negatively associated with CO2 emissions, while trade openness and GDP per capita show positive correlations. Causality analysis reveals bidirectional relationships among most variables, except for population growth and CO2 emissions, which may involve other moderating factors. The findings highlight the urgent need for integrated policies that advance sustainable development by focusing on renewable energy adoption, sustainable urbanization, and green growth strategies. Policymakers should prioritize initiatives that harmonize economic growth with environmental sustainability, ensuring a lasting balance between development and ecological preservation across Africa.

Do education, urbanization, and green growth promote life expectancy?

IntroductionEducation (EDU) enhances life expectancy (LEF) by improving health literacy and access to healthcare, leading to healthier lifestyles. Urbanization (URB) fosters better healthcare infrastructure and access to essential services, although it must be managed to avoid negative environmental impacts. Green growth (GG) ensures sustainable development, reduces pollution and environmental risks, and contributes to longer, healthier lives. Therefore, this study examines the impact of EDU, URB and GG on LEF in China from 1990 to 2022.MethodsThis study utilizes the unit root, cointegration test, and Auto Regressive distributed lag (ARDL) model, and for robustness analysis, we use the Fully modified ordinary least squares (FMOLS) and Dynamic ordinary least squares (FMOLS) methods.ResultsThe results show that education, urbanization and green growth have a positive and significant effect on life expectancy, while C02 emissions negatively affect life expectancy.DiscussionThese findings suggest that more resources should be allocated to public education systems to ensure access to quality education from early childhood through higher education and integrate comprehensive health education into school curricula to raise awareness about healthy lifestyles, nutrition, and disease prevention. Promote intelligent urban planning incorporating green spaces, recreational areas, and safe walkways to encourage physical activity and reduce pollution. The findings significantly contribute to health economics and provide a new avenue of research for the academic community and policymakers.

Exploring the Impacts of Economic Policies, Policy Uncertainty, and Politics on Carbon Emissions

Abstract Addressing climate change challenges through managing and mitigating CO2 emissions has taken center stage in shaping economic policies. This paper analyzes the intricate interplay among economic policies, their uncertainty, political dynamics, and CO2 emissions by utilizing the U.S. data from 1973 to 2024. Our empirical results derived from the autoregressive distributed lag (ARDL) model with dummy variables indicate that expansionary monetary policies and higher corporate tax rates may increase CO2 emissions. Political factors, including economic policy uncertainty and the political climate, yield long-term impacts on CO2 emissions. The dominant party in the legislative branch, but not the presidency, emerges as a key determinant in carbon dioxide emission control, underscoring the significance of consensus-building in democratic processes, yet with variation in effects across different chambers. The robustness of these key findings is reaffirmed through different models. The findings suggest that party affiliation does not always dictate environmental policy outcomes, emphasizing the complexity of policy formulation and its representation within legislative bodies, providing insight to decision-makers when economic policies are considered.

Price Interaction Between Crude Oil, Selected Grains, and Oilseeds in South Africa

The dynamic interaction between crude oil prices and the prices of grains and oilseed is critical yet a complex issue in agriculture given the potential impact of the energy sector price fluctuations on production costs, transportation, and processing. This study explores the interactions between prices of crude oil, key grains, and oilseeds (maize, soybean, and wheat) in South Africa from 2018 to 2022. Utilising monthly data, this study employs the Auto-Regressive Distributed Lag (ARDL) model to assess the short-term and long-term relationships, and the Granger causality test to determine the causality directions. Results revealed a mixed long-term cointegration wherein crude oil prices and the prices of maize as well as soybean have a relationship, but no evidence of such a relationship exists for wheat prices. Additionally, no short-term effects were observed, suggesting that immediate fluctuations in crude oil prices do not influence the prices of maize, soybean, and wheat. Instead, short-term prices movements of the grains and oilseeds may be driven by other factors that could be of interest to policymakers. Furthermore, the Granger causality findings show no causality direction between prices of crude oil and the selected grain and oilseed. These findings challenge the presumed direct connection between energy and agricultural prices, thus offering policymakers a perspective to redirect their focus to formulate short-term price policy strategies that decrease dependability on crude oil to promote sustainability in the agricultural sector without disrupting the progress towards achieving Sustainable Development Goal 2 of ending hunger.

Succeeding in Energy Transition in Sub-Saharan Africa: Does Institutional Quality Matter?

The objective of this article is to examine the effect of the quality of institutions on energy transition in 19 sub-Saharan African (SSA) countries over the period 1996-2016. To achieve this, we proceed in two steps. We first use the principal component analysis (PCA) to construct a composite indicator of institutional quality, from Kaufmann’s (1996) six indicators of governance. Then, we estimate an autoregressive distributive lag model (ARDL) on panel data using the pooled mean group (PMG) estimation technique. Our results show that the quality of institutions determines the energy transition in SSA. The associated coefficient is positive and statistically significant. In addition, our results show that economic growth and trade openness promote energy transition. On the other hand, it emerges that CO2 emissions hinder energy transition, due to the high dependence of the countries considered on fossil fuels. We suggest an improvement in the quality of institutions and the implementation of political incentives favorable to the adoption of new technologies.

Historical geopolitical risk acts and world crude oil production: evidence from the international level

Purpose The purpose of this study is to empirically investigates the influence of geopolitical risk acts (GPR) on world crude oil production. GPRs are a proxy for waging wars and military actions, thus it is expected to have a clear impact on world crude oil production (WCOP). Design/methodology/approach The current study formulates a theoretical model, and its parameters are estimated using three methodologies – traditional autoregressive distributed lag (ARDL) model, Dynamic ARDL model, and Frequency domain causality test – across the period 1973–2023 to ensure robust findings. Findings The results illustrate that GPRs constrain the global crude oil supply. The final impact relies on the positive interaction term between GPRs and international economic activity from one side and the negative interaction term with crude oil prices from the other. Likewise, the findings show that geopolitical threats reduce producing crude oil. Furthermore, this research deliberates on policy implications stemming from these findings. Originality/value Examining existing literature reveals a gap in understanding the relationship between geopolitical risk and crude oil production. Most of the studies in this research strand focus on investigating the impact on oil price volatility.

Examine the long run effect of corporate governance on Ghana SIC’s financial performance

This study examine the long run effect of corporate governance on Ghana SIC’s financial performance. The study employs the Autoregressive Distributed Lag (ARDL) technique to investigate the multifaceted relationship between corporate governance and the financial performance of SIC (Sampled Industrial Company). Using time-series data spanning from 2017 to 2021, the study examines both the long-term and short-term impacts of corporate governance on SIC's financial performance while considering the influence of a control variable, firm size. The dependent variables in this analysis are return on assets, while the independent variables encompass board size, board composition, and CEO tenure at SIC. The control variable utilized was firm size. To assess the hypotheses, regression analysis was conducted, resulting in the identification of long-run equilibrium relationships among the variables. In terms of the long-term effects, the study found board size and board composition do not exert significant influences on SIC's financial performance. Conversely, CEO tenure at SIC was found to have a statistically significant negative impact on financial performance in the long run. Moreover, when considering the control variable, firm size demonstrates a highly significant negative impact on return on assets at SIC in the long run. The findings of this study provide valuable insights into the complex interplay between corporate governance and financial performance, shedding light on the nuanced effects of board size, board composition, CEO tenure, and firm size on SIC's financial outcomes. The study recommend that, by prioritizing stability in CEO leadership, focusing on board effectiveness beyond composition, and actively managing the challenges associated with firm growth, SIC can enhance its financial performance and ensure sustained success in the long run.

Korea–China Trade Dynamics: Exploring the Role of Crude Oil Prices

ABSTRACTThis research examines the short‐ and long‐term impacts of macroeconomic variables, such as real income levels and exchange rates, on Korea's trade flows with China, focusing on 33 specific commodity groups. By employing the Autoregressive Distributed Lag (ARDL) methodology, this study incorporates oil‐related factors – namely crude oil prices and their volatility – into traditional export and import models. The results demonstrate that real income levels in Korea and China considerably influence trade dynamics, affecting exports and imports across various periods. The bilateral exchange rate has a significant impact, with its effects being more pronounced on exports in the long term and imports in the short term. Furthermore, the research highlights that crude oil prices and their volatility significantly, yet varied, affect trade flows, contingent on the trade's nature and duration. These findings offer valuable insights for policymakers, particularly in understanding the recent shifts in Korea's trade balance with China and in formulating economic and trade strategies to manage fluctuations in the trade balance.

Effect of Tax Incentives on Non-Oil Tax Revenue: Econometric Case Study from Nigeria (1981-2022)

The non-oil tax income in Nigeria is low and contributes less than 10% of the GDP. Also, non-oil export in Nigeria contributes less than 15% to the GDP reflecting an abysmal performance over the years. This study therefore empirically examined the effect of tax incentives on non-oil tax revenue in Nigeria from 1981-2022. Tax incentives was measured by export expansion grant while non-oil tax revenue was measured by total tax revenue, non-oil export, tax rate and real effective exchange rate. Unit root test was conducted using Augmented Dickey Fuller (ADF), Phillip Perron statistics and Kwiatkowski-Phillips-Schmidt-Shin test statistic and it was found that the variables are not in the same order of integration. Bound test result indicated long run significant relationship within the variables. Autoregressive Distributive Lag Model (ARDL) found that Export expansion grant had short run significant negative effect on non-oil tax revenue in Nigeria (β9 = -0.07, p-value = 0.0299 < 0.05) but had an insignificant positive effect in the long run (α8 = 1.29, p-value = 0.3738 > 0.05). Tax rate had positive significant effect on non-oil tax revenue in the short run (β3 = 0.01, p-value = 0.0027 < 0.05). However, in the long run, tax rate had negative insignificant effect on non-oil tax revenue (α2 = -0.28, p-value = 0.4822 > 0.05). the study concluded that export incentives have become a drain to government resources over the years. Based on the result, we recommended that export expansion grant processing time frame and payment should be improved.

Assessing the role of production capacity in mitigating carbon emissions: a case study of Algeria

This study examines the relationship between productive capacity and CO2 emissions in Algeria, addressing the pressing challenge of sustainable development in the context of climate change. The aim is to explore how enhancing production capacity can influence environmental outcomes, particularly in terms of carbon emissions. To achieve this, the study employs an Auto Regressive Distributed Lag (ARDL) model, with results validated through an Error Correction Model (ECM), using data from 1990 to 2023. The findings reveal that improvements in productive capacity contribute to a long-term reduction in CO2 emissions per capita. However, an increase in energy consumption has the potential to undermine these gains, underlining the need for greater energy efficiency. Key policy recommendations suggest prioritizing investments in energy-efficient technologies, thereby enhancing Algeria’s productive capacity while minimizing environmental impact. This framework provides a valuable pathway for aligning economic growth with sustainable environmental practices, offering actionable insights for policymakers aiming to balance development with climate goals.

Impact of Foreign Direct Investment from Multinational Corporations on Economic Growth in Nigeria (2015-2022): Evidence from Autoregressive Distributed Lag and Vector Error Models

Impact of Foreign Direct Investment from Multinational Corporations on Economic Growth in Nigeria (2015-2022): Evidence from Autoregressive Distributed Lag and Vector Error Models

The Role of Monetary and Fiscal Policies in Ensuring Financial Stability

This study examines the effects of monetary and fiscal policies on financial stability in the Turkish economy for the period 2005Q1-2024Q1. For this purpose, a comprehensive Macro-Financial Stability Index reflecting the changes in the financial stability of the Turkish economy is calculated. Monetary policy interest rate and tax revenue data were used as monetary and fiscal policy variables, respectively. According to the results of the Autoregressive Distributed-Lag (ARDL) model, it is seen that increases in policy interest rates negatively affect financial stability in the short and long term. It is determined that the increase in tax revenues has negative effects on financial stability in the short term and a positive impact in the long term. Sudden and sharp increases in interest rates can disrupt financial stability in the short term. Increasing tax revenues will help sustain public debt and finance public expenditures. Policymakers can maintain financial stability by carefully managing interest rates and tax policies.

OIL PRICE FLUCTUATIONS AND MACROECONOMIC INDICATORS: AN ARDL AND NARDL APPROACH

This study investigates the effects of oil price fluctuations on Nigeria’s macroeconomic indicators from 2015 to 2023, focusing on inflation and economic growth. Utilizing Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models, we analyze the short-term and long-term impacts of variables such as Premium Motor Spirit (PMS) prices, exchange rates, money supply, interest rates, and economic uncertainties. Results reveal significant short-term effects of oil price increases on inflation and GDP, with asymmetric influences observed in exchange rate movements. The long-term analysis confirms cointegration relationships but underscores slow adjustment speeds for inflation and GDP equilibrium. Recommendations include strengthening monetary policy, stabilizing the exchange rate, and adopting strategies to mitigate oil price volatility’s adverse effects.

Tác động của hiệu quả sử dụng năng lượng đến lượng khí thải CO2 ở Việt Nam

Pollution is a challenge for humanity in general and for developing countries in particular. Effective use of energy sources is expected to be the solution to reduce the burden on environmental quality. This study aims to assess the impact of economic growth, biomass consumption, and energy efficiency on CO2 emissions in Vietnam during 1971- 2022. Linear autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) approaches are applied simultaneously to answer the question of whether the influence of energy efficiency on CO2 emissions in Vietnam is symmetric or asymmetric. The empirical results show that the influence of energy efficiency on CO2 emissions is asymmetrical in the long term. Increasing energy efficiency will reduce CO2 emissions, but negative changes are smaller than positive changes. The new findings enrich the literature, but more importantly, they help policymakers have more empirical evidence for designing energy development policies while exploring the possibility of making energy efficiency requirements mandatory for organizations and residents.

Do green foreign direct investments promote environmental innovation in European countries?

Environmental innovation (EI) plays a critical role in helping a country pursue sustainable development, while green foreign direct investment (GFDI) impacts creative local green innovation. However, there is a lack of research on this link. This paper aims to conduct an empirical investigation into how GFDI affects EI. The estimation findings demonstrate that GFDI has had positive effects on EI—by applying multiple econometric methods, including a panel-corrected standard error modelling (PCSE), a feasible generalized least squares model (FGLS), and autoregressive distributed lag (ARDL) model, to a globally representative sample of 15 European countries between 2012 and 2021. To clarify the connection between GFDI and EI, we present examples of the effects of the latter in both the short and long term. The results show that GFDI has an important beneficial impact on the environment for early-stage investments in the short term. Notably, our findings indicate that GFDI’s long-term effects are more likely to be favourable. Furthermore, we analyze interactions between variables representing institutional quality and the impact of GFDI on EI. Our findings suggest that the positive effects of GFDI may be greater in nations with highly developed institutional systems.

A step toward the attainment of carbon neutrality and SDG-13: Role of financial depth and green technology innovation

Following the recommendations of COP28 and Sustainable Development Goal -13 (Climate Action), the present study examines the role of financial depth and green technology innovation in carbon neutrality and climate change. This study measures the relationship between green innovation, technological innovation, ICT, financial depth, economic growth, carbon emission, and ecological footprint from 1990-2021 in the USA. The autoregressive distributed lag (ARDL) model examines the relationship between the above-mentioned variables and their impacts on each other. Results reveal that green innovation, technological innovation, ICT, and financial depth significantly negatively impact ecological footprint and carbon emissions in both the short and long run. In contrast, economic growth positively impacts carbon emissions and ecological footprint. Green and financial innovation-centric policies are suggested to the USA to attain net zero emission and SDG-13.