Autoregressive Distributed Lag Approach Research Articles

Effects of urbanization and international trade on economic growth, productivity, and employment: Case of selected countries in Africa

The rapid urbanization taking place in Africa is resulting in the emergence of large urban agglomerations. Despite the potential and typical economic benefits associated with the emergence of such agglomerations elsewhere, not much can be said of Africa's urbanization. With urbanization projections pointing to a continued increase, there is a need to understand the urbanization and economic dynamics relationship in order to exploit the full potential of this wave. Using a panel data set of urbanization rate, trade, economic growth, productivity and employment in six African countries for the period 1991–2019, we explore this relationship by adopting the cross-sectional augmented autoregressive distributed lag (CS-ARDL) approach using data from six African countries. The findings show that there is a significant relationship between urbanization, international trade, economic growth, productivity, and employment. they also show a causal relationship between the variables studied. In addition, the findings of this study reveal that international trade contributes, significantly, to improving the productivity in long run and the economic growth and employment increase the productivity in short run and employment in the selected African countries. This research study, therefore, contributes to the critical argument that African urbanization and international trade have significant economic potential and therefore need to be encouraged and managed effectively. This provides evidence for planners and policy-makers to back policy geared toward sustainable urbanization and diversified international trade that will contribute to the structural transformation of African countries.

Analysis of Exports, Inflation, Exchange Rates, Interest Rates on Foreign Exchange Reserves: ARDL Approach

The purpose of this study is to describe how inflation, interest rates, exports, and currency exchange rates affect Indonesia's foreign exchange reserves in the short and long run. In order to investigate short-term relationships, this study applies an autoregressive distribution lag (ARDL) model for cointegration for long-term associations. In addition, the error correction model (ECM) is used. Foreign exchange reserves, which are based on annual statistics, are the dependent variable. The four independent variables are interest rates, exchange rates, inflation, and exports. According to the study's findings, exports and exchange rates have a significant positive short- and long-term influence on foreign exchange reserves, whereas interest rates have a negative long-term impact on reserves. Foreign currency reserves have become an increasingly crucial indicator of a country's economic health in the current global economic climate. However, few research have thoroughly examined these traits in both the short and long term. This study attempts to provide fresh insights into how these variables interact and influence Indonesia's foreign

Application of the environmental Kuznets curve hypothesis in the Indian core industries: Towards a greener economy

AbstractThe study investigates the long‐term effects of two core industries of India, namely crude oil and electricity on the environment by adopting the industry‐specific environmental Kuznets curve (IEKC) hypothesis. While crude oil is high‐polluting, the impact of the electricity industry on the environment is less severe. A traditional EKC hypothesis, described by an inverted U‐shape, demonstrates the relationship between economic growth and environmental degradation. The study tests IEKC individually for each of the two industries for time series data ranging from 1994 to 2021 for the crude oil industry and from 1994 to 2019 for the electricity industry. Carbon dioxide emission levels and the Index of Eight Core Industries are the indicators used to measure the environmental degradation and industrial growth levels, respectively. The study adopts autoregressive distributed lag approach to test the IEKC hypothesis. The findings suggest rejecting the IEKC hypothesis in the Indian crude oil industry, indicating its long‐term adverse environmental effects. In contrast, acceptance of the hypothesis in the electricity industry confirms that electricity energy can potentially lower the country's pollution level in the long run. The study adds to the existing literature by applying the IEKC hypothesis in the core industries of India to judge their environmental sustainability.

Transition to sustainable environment and economic growth in Tunisia: An ARDL approach

This study investigates the relationship between environmental sustainability and economic growth in Tunisia by employing the Autoregressive Distributed Lag (ARDL) approach, Principal Component Analysis (PCA), and Granger Causality on annual data from 1990 to 2022. It aims to understand how environmental sustainability influences Tunisia's economic growth, revealing a substantial positive long-term association. The research is crucial in the global discourse on sustainability, providing insights for informed policy-making and sustainable development, particularly in developing nations like Tunisia. By utilizing the PCA, the ARDL approach, and Granger causality, the analysis gains robustness, offering a comprehensive understanding of the complex relationship. The originality lies in its Tunisia-specific focus, contributing perspectives to the broader conversation on environmental sustainability and economic growth. Notably, we identify a positive long-term impact of environmental sustainability on Tunisia's economic growth, with implications for policymakers, economists, and environmental advocates. The robustness of the results to different proxies reinforces the credibility and applicability of the findings, advancing both academic understanding and providing actionable insights for policymakers aiming to balance economic prosperity and environmental sustainability in Tunisia and similar developing economies. A green economy model mut be embraced in Tunisia, that meets economic and environmental goals, particularly decarbonization through energy security, creating quality jobs through trade openness and FDI, promoting entrepreneurship and technology start-ups.

Asymmetric Effects of Investor Sentiment on Malaysian Sectoral Stocks: A Nonlinear Autoregressive Distributed Lag Approach

Asymmetric Effects of Investor Sentiment on Malaysian Sectoral Stocks: A Nonlinear Autoregressive Distributed Lag Approach

Does financial development and economic growth matter for services export? Cross-country evidence from OECD countries

The unprecedented growth in the export of services and its accompanying economic incentives has invited discussions on service export determinants. Against this background, the present article is an attempt to test whether the contemporary theories on causal links between exports, financial development and growth hold for services export. For realizing the objective, we employed the panel cointegration technique for Organization for Economic Co-operation and Development (OECD) countries over a period of 23 years (2000–22). Findings of both first and second generation cointegration test indicate a long run equilibrium between services export, financial development and growth. However, there are differences in the short and long association, as outcomes of panel auto autoregressive distributed lag (ARDL) approach show financial development to be significant determinant of services export only over long run. Additionally, granger causality test suggests a feedback mechanism prevalent between services export-financial development, services export-growth and financial development-growth. The empirical evidence offered in the study elucidates the significance of continuously developing the financial markets and institutions for achieving sustained growth in export of services. The bi-directional relationship between the variables also presents an opportunity to strengthen economic growth and financial development process through policies aimed at expanding services export.

How renewable and nuclear energy-related research and development expenditures pave the way for curbing carbon emissions in France?

Research and development expenditures on clean energy have recently become an important option for sustainable development solutions. The lack of a study examining the impact of clean energy research and development expenditures on ecological quality in France is a research gap. With this motivation, this study aims to explore the impact of energy prices, technological advancements in renewable and nuclear energy on carbon (CO2) emissions in France from 1990 to 2020. To this end, the study employs the Fourier autoregressive distributed lag approach. The study recognizes the importance of environmental quality for sustainable development and highlights the negative ecological impact of fossil fuels. It points out that nuclear and renewable energy are valuable alternatives to fossil fuels. In addition, the study points out that rising energy prices can help encourage a switch to cleaner energy sources by making fossil fuels less economically viable. However, the adoption of alternative energies depends on factors such as cost and technological infrastructure. In particular, technological advancements in renewables have a greater impact on CO2 mitigation than those in nuclear energy. The unique contribution of this study is to explore the impact of energy-related technological developments on ecological quality in France, filling a research gap.

Assessing the Impact of Technological Innovations and Trade Openness on Environmental Sustainability: An Empirical Study of South Asian Economies Using Panel ARDL Approach

This study examines the major factors that influence environmental sustainability over a 20-year period (2000–2020) in the four South Asian economies. In this study, two methods of estimation including the Pool Mean Group (PMG) estimator and the panel autoregressive distributed lag (ARDL) approach are used. The findings explore that trade openness, energy consumption, and economic expansion have a long-term positive and considerable impact on environmental deterioration, conversely technical innovation has a long-term negative impact on the environment. In short run scenario, trade openness and energy usage have significant and favourable effects on environmental degradation, whereas the economic growth and technological advancement have had a substantial negative influence on the environment. From this study, the policy makers provide the direction to the government by incentivizing technology, enforcing energy-efficient laws, promoting renewable energy, aligning trade policies with environmental goals, and enhancing regional cooperation. In order to improve South Asian environmental sustainable policies, future research should examine energy-trade-growth-technology by employing advanced techniques, and prioritizing innovation.

The Roles of Insurance on Economic Growth in Malaysia: An ARDL Approach

Malaysia’s economic growth has been rising steadily over the years and one of the main contributors is the insurance sector. The literature has recorded mixed findings on the relationship between insurance and economic growth. This paper examines the relationship between the insurance sector and economic growth in Malaysia over an extended period of 1990-2021. This paper uses three proxies for the insurance sector i.e. life insurance premiums, nonlife insurance premiums, and total insurance premiums. The Autoregressive-Distributed Lag (ARDL) and Error Correction Model (ECM) approaches are employed to achieve the objective. While controlling for foreign direct investment, export, and import, this paper found that there is a positive long-run relationship between non-life insurance premiums and economic growth. Conversely, a negative short-run relationship is observed between life insurance premiums and economic growth. The total insurance premium has a negative short-run relationship with economic growth yet is insignificant for the long-run. The non-life insurance sector has a larger contribution compared to life insurance on Malaysia's economic growth as the market depends more on capital formation and investments, particularly in infrastructure, real estate, and capital markets. The insurance sector provides financial expansion in terms of payment for protection which results in an economic boost.

The Carbon Conundrum: Exploring CO2 Emissions, Public Debt, and Environmental Policy

This study addresses a critical gap in the literature by examining the impact of CO2emissions on public debt in Malaysia, employing a non-linear autoregressive distributed lag (ARDL) approach spanning from 1980 to 2020. This methodology captures the non-linear relationship between CO2 emissions and public debt, providing nuanced insights into how environmental factors shape fiscal dynamics. Despite encountering challenges arising from the limited body of literature on this specific relationship, the study highlights key findings with profound implications for policymakers. The inverse correlation between trade openness and public debt underscores the influence of international trade on Malaysia's fiscal landscape, while a positive association between investment and public debt emphasizes the importance of prudent debt management for economic growth. Furthermore, the negative relationship between higher foreign direct investment and long-term public debt highlights the need to foster an investor-friendly environment. A pivotal contribution is the confirmation of a positive link between CO2 emissions and public debt, urging policymakers to prioritize emission reduction strategies, implement carbon pricing, and promote green technologies. This research offers a comprehensive understanding of the intricate interplay between CO2emissions and public debt, providing valuable insights for informed policy decisions in the Malaysian context. Doi: 10.28991/ESJ-2024-08-03-08 Full Text: PDF

Foreign divestment, financial development, and economic growth nexus in selected African countries: Autoregressive Distributed Lag (ARDL) Approach

There is a limited amount of literature and data available on the topic of foreign divestment in African countries. The majority of research examining international divestment have primarily concentrated on a single-country context and have utilised factors at the level of individual firms. Unlike other papers, this study took a comprehensive approach by examining foreign divestiture across multiple countries on a continental scale. We analyse the correlation between foreign divestment, financial development, and economic growth over both short and long periods using annual data from 2000 to 2020 in 35 African nations. The principal estimating technique employed was the autoregressive distributed lag (ARDL) co-integration approach. The study's primary findings revealed a favourable enduring correlation between foreign divestiture and financial development, while indicating an unfavourable enduring correlation between foreign divestment and economic growth. Furthermore, the study found that there is a negative correlation between international divestiture and financial development in the short term. On the other hand, there is a positive and significant correlation between foreign divestment and economic growth. Thus, it is imperative for policymakers to implement rules with efficiency and promote foreign direct investment (FDI) inflows in order to enhance economic growth and development in African countries. Additionally, it is imperative for authorities to establish a surveillance system to monitor these connections and adapt policy accordingly in light of evolving economic conditions. The results of this study will not only enhance scholarly discussions, but also offer valuable insights to policymakers, practitioners, businesses, and foreign investors on how to effectively execute policies that promote economic growth and foreign investment in Africa. Moreover, this study provides suggestions for future investigations in the field of foreign divestment.

Advancing environmental sustainability in the G-7: The impact of the digital economy, technological innovation, and financial accessibility using panel ARDL approach

This study examines the impact of the digital economy, technological innovation, financial accessibility, and urbanization on CO2 emissions in the G-7 region from 1990 to 2019. The analysis employed Cross-Sectional Dependence (CSD) and Slope Homogeneity tests, revealing the presence of CSD issues and heterogeneous slope coefficients. First- and second-generation panel unit root tests indicated no unit root problem within the dataset, with variables showing mixed integration orders. Panel cointegration tests confirmed that the variables are cointegrated over the long run. To assess the short-run and long-run impacts of the explanatory variables on CO2 emissions, the study utilized the Panel Autoregressive Distributed Lag (ARDL) model. The findings indicate that the digital economy significantly reduces CO2 emissions, while economic growth, technological innovation, financial accessibility, and urbanization increase CO2 emissions in the G-7 region. The robustness of the Panel ARDL results was validated using Driscoll-Kraay standard errors, Augmented Mean Group (AMG), and Common Correlated Effects Mean Group (CCEMG) estimations. Additionally, the Dumitrescu-Hurlin causality test revealed a unidirectional causal relationship between the digital economy and CO2 emissions, GDP and CO2 emissions, and CO2 emissions and technological innovation. Furthermore, bidirectional causality was found between financial accessibility and CO2 emissions, as well as between urbanization and CO2 emissions. These findings provide comprehensive insights into the dynamic interactions between economic, technological, and environmental variables in the G-7 region, highlighting the complexity of achieving sustainable development.

Effect of Major Determinants on Gross Domestic Saving in India: An Application of ARDL Approach

This study investigated the determinants of gross domestic saving in India. Secondary data were extracted from the World Development Indicator (WDI) and the Economic Survey of India from 1972 to 2020. The Augmented Dickey-Fuller (ADF) and Autoregressive Distributed Lag (ARDL) bounds tests were used for stationary and cointegration analysis, respectively. The Cumulative Sum of Residuals (CUSUM) test was also applied to confirm stability. The results indicated that HSV and PBSV positively and significantly impact GDS, while DPR had a significant negative impact in the short and long run. Further, GDP and inflation were insignificant in the long run. The ECT coefficient was found to be -0.53 per year, which suggested that the short-term disequilibrium transforms into long-term equilibrium at a remarkable rate of 53 per cent per year.

Population, carbon dioxide emissions and renewable energy consumption nexus: New insights from Vietnam

This academic paper investigates the intricate relationships among population dynamics, carbon dioxide (CO2) emissions and renewable energy consumption in Vietnam. The study used the Autoregressive Distributed Lag approach and fixed panel data method to examine the nexus between population, CO2 emissions and renewable energy consumption in Vietnam. The data is collected at the World Bank from 2000 to 2023. As the nation undergoes rapid economic development and urbanization, understanding the nexus between population growth, environmental impact and the transition to renewable energy sources becomes crucial. The study employs a multidimensional analytical approach that integrates demographic trends, environmental science and energy economics to unveil novel evidence into the complex interplay of these factors. The significant findings indicate a positive trajectory in renewable energy consumption, with notable contributions from solar, wind and hydropower sources. Concurrently, population growth, particularly in urban centres, correlates with increased CO2 emissions, emphasizing the role of demographic shifts in environmental impact. Policy implications derived from these results underscore the need for integrated strategies. Targeted policies promoting renewable energy in urban centres, incentivizing cleaner industrial practices and fostering community engagement emerge as crucial avenues for sustainable development. In essence, this study contributes valuable insights into the dynamic relationships among population dynamics, CO2 emissions and renewable energy consumption in Vietnam, offering a foundation for evidence-based policymaking and guiding future research endeavours in sustainable development.

Toward a sustainable environment within the framework of carbon neutrality scenarios: Evidence from the novel Fourier‐NARDL approach

AbstractSustainable energy policies are directly proportional to countries' achievement of the Sustainable Development Goals (SDGs). Economies that want to achieve their 2030 and 2050 targets are looking for alternative energy sources until renewable energy sources mature. In this context, this study models the environmental quality of France, which is the leader in the use of nuclear energy in Europe, from a different perspective through nuclear energy technologies. This study empirically uses the novel Fourier asymmetric autoregressive distributed lag approach. It confirms that increases and decreases in nuclear technology have different effects on the load capacity factor within the framework of the load capacity curve (LCC) hypothesis. It also provides evidence for the existence of the LCC hypothesis and offers sustainable energy policies for France. The French government should allocate funds to cleaner energies instead of investing in nuclear energy technologies. Thus, the long‐term transition to a low‐carbon economy can be accelerated instead of short‐term targets. By eliminating nuclear energy, a severe burden on the French economy, infrastructure can be created for alternative energy sources. Finally, the French government can gain momentum in achieving SDGs 7 and 13 by withdrawing support from nuclear energy technologies.

BITCOIN PRICE AND CHINESE GREEN BONDS: EVIDENCE FROM THE QARDL METHOD

This article primally explores the short-term fluctuation and long-term implications of the international Bitcoin price (BP) on the Chinese green bond (GB) market, within the sample period of 2014:M10–2023:M07. Bitcoin is the most important cryptocurrency and has a carbon-intensive feature, and its price suffers from great volatility and is closely related to the green finance market. Meanwhile, although China is the largest bitcoin mining state, it is pursuing a dual carbon target, which promotes its green bond market’s development. Thus, it is valuable to investigate the influence of BP on GBs in China. Based on the quantile autoregressive distributed lag approach, this paper indicates that the positive and negative impacts of BP on the GB market are significant in the long-term but not apparent in the short-term. These results emphasize the importance for market participants to obtain a better understanding of how BP affects GB under various market circumstances. Implementing specific policies, such as regulatory mechanisms for Bitcoin trade, market-oriented reform for the bond market, and information disclosure, can alleviate shocks from BP and accelerate the development of the GB market.

Disentangling the effects of globalization on growth: Evidence from Ethiopia using an ARDL approach

Globalization is a complex phenomenon with far-reaching and multidimensional influences on national growth trajectories. Previous studies examining these effects have often relied on overly simplistic measures that mask heterogeneity across contexts. This paper aims to overcome such limitations by disentangling the impacts of different globalization dimensions on Ethiopia’s economic development over 1981–2021 using an autoregressive distributed lag (ARDL) approach in order to assess the long-term and short-term effects of Ethiopia’s economic growth rates and a comprehensive globalization index encompassing the economic, social, and political dimensions of globalization. Long-run and short-run relationships are estimated via ARDL to analyze these relationships in the context of factors like investment, workforce, trade, and capital stock, while the robustness of findings is ensured through dynamic ordinary least squares, fully modified ordinary least squares, and canonical cointegrating regression techniques. Key results indicate that overall and economic globalization exhibit negative long-term associations with growth when analyzing these relationships taking into account other factors, suggesting a need for a cautious, sequenced approach to integration to optimize benefits as local capacities develop over time. However, political globalization carries positive long-run effects. Social globalization displays no clear linkage. Short-run impacts also differ by dimension. Gross capital formation, trade openness, and capital stock remain consistently growth-enhancing. The negative correlation in the labor force likely reflects structural challenges. Robustness analyses substantiate these conclusions, enhancing confidence. Findings imply a cautious, sequenced approach to integration may optimize potential benefits as local adaptive capacities develop over time. This investigation’s tailored nature provides contextually grounded empirical knowledge with broader policy applications. More refinement of country-level analyses remains warranted to fully uncover globalization’s complexity. Overall, incremental global ties alone proved insufficient for development acceleration. Findings carry relevance for managing integration strategies towards inclusive, sustainable development nationally and beyond.

Navigating the nexus: unraveling technological innovation, economic growth, trade openness, ICT, and CO2 emissions through symmetric and asymmetric analysis

In Malaysia’s rapid economic growth and industrialization, environmental degradation and carbon emissions pose significant challenges. As urbanization continues to rise, there is a growing recognition of the imperative to tackle CO2 emissions. Trade openness and globalization drive economic activity but also heighten environmental pressures, including CO2 emissions from transportation and industry. Information communication technology (ICT) usage, shaped by infrastructure and regulations, can either improve energy efficiency or increase energy consumption. The study examines the impacts of economic growth (EG), trade openness (TON), technological innovation (TIN), and ICT on CO2 emissions in Malaysia, using both symmetric and asymmetric methods from 1985 to 2021. While many studies have explored environmental degradation, focusing on CO2 emissions and ecological footprint indicators, only a limited number have delved into the combined impact of sustainable EG, TON, ICT, and TIN on Malaysia’s CO2 emissions. Notably, these studies have often neglected the utilization of both symmetric and asymmetric methodologies. Hence, this study employed auto-regressive distributed lag (ARDL) and non-linear ARDL approaches to investigate the dynamic effects of the studied variables. The key findings from the symmetric analysis demonstrate that EG, TON, and ICT together take part in the increase of CO2 emissions in both the short and long run. Particularly, technological innovation plays a significant role in reducing CO2 emissions in the short term through the adoption of cleaner technologies. However, the results of the NARDL bound test reveal asymmetric long-term consequences of technological innovation, economic growth, and ICT on CO2 emissions. The study underscores the need for CO2 reduction policies in Malaysia, advocating for measures, such as incentivizing cleaner technologies and upgrading energy infrastructure. It also recommends implementing carbon pricing mechanisms for production and trade, alongside awareness campaigns to foster behavioral changes aimed at reducing emissions.

How price and non-price factors influence the market price of major carp: Findings from the dynamic ARDL approach

Recently, fish prices in Bangladesh have been growing, particularly the market price of major carp, even though the factors that may be contributing to this trend are unexplored. Therefore, this study considers some price and non-price factors to explore the market price dynamics of major carp species in Bangladesh. To explore the factors impacting the market price of carp fish, we apply advanced time-series econometric modeling, such as the recently devised dynamic simulated autoregressive distributed lag (ARDL) model using publicly available data on fish prices from 2005 M1 to 2021 M12. This period is attributed to the rapid transformation from mostly low-intensity farming to commercialization due to a rise in productivity and market price. Among the price factors, the findings demonstrate that the price of corn, soybean, and oilcake, and fisheries wage rate have a positive significant impact on fish price in both the short and long term. In addition, among the non-price drivers, GDP per capita, inflation rate, and fish consumption all have a significant positive influence on fish prices in the long run, whereas total production has a detrimental effect on fish prices in the long run. These results have significant policy ramifications for attaining the fish farmers' profit maximization and consumers' welfare maximization goals.

Harnessing artificial intelligence‐driven industrial robotics for sustainability: Insights from leading green economies

AbstractIn 2023, global temperatures witnessed an alarming escalation, reaching an unprecedented 1.46°C above preindustrial levels, marking it as the hottest year on record. Simultaneously, atmospheric carbon dioxide surpassed 420 ppm, exceeding a stability maintained for over 6000 years by more than double. This troubling surge in CO2 intensifies global warming, leading to an increased frequency of extreme weather events and contributing to 24% of global deaths attributed to environmental concerns. These alarming environmental challenges demand urgent attention and the implementation of innovative policies. Responding to this imperative, the study examines the impact of artificial intelligence‐based industrial robotics (AIIR) and other control variables such as green energy, green finance, and green energy investment on CO2 emissions in economies supporting green initiatives, including Canada, Denmark, China, Japan, New Zealand, Norway, Sweden, and Switzerland. Using monthly data from 2008 to 2021 and a novel nonlinear autoregressive distributed lag approach, the results indicate that AIIR significantly reduces CO2 emissions in the sample economies. Additionally, green energy, green finance, and green energy investment also significantly decrease CO2 emissions. The study's outcomes bear policy implications for decision‐makers in the sampled economies, offering tangible insights for effective environmental management.