Nonlinear ARDL Approach Research Articles

Exploring the impact of economic growth and sources of electricity production in India: New insights from sectoral analysis using NARDL approach

This study aims to explore the asymmetric impact of renewable energy on the sectoral output of the Indian economy by analyzing the time series data from 1971 to 2019. The nonlinear autoregressive distributed lag approach (NARDL) is employed to examine the short- and long-run relationships between the variables. Most studies focus on economic growth, ignoring sectoral dynamics. The result shows that the sectoral output shows a differential dynamism with respect to the type of energy source. For instance, agricultural output responds positively to the positive shock in renewable energy, whereas industry and service output behave otherwise. Since the latter sectors depend heavily on non-renewable energy sources, they behave positively towards them. Especially, electricity produced from non-renewable energy sources significantly influences service sector output. However, growing evidence across the world is portraying the strong relationship between the growth of renewable energy sources and economic growth. However sectoral dynamism is crucial to frame specific policies. In this regard, the present paper’s result indicates that policies related to promoting renewable energy sources will significantly influence sectoral output in the long run in India.

Asymmetric Effects of COVID-19 Deaths and Oil Price Shocks on Stock Market Returns in Some Selected African Countries: Evidence From Nonlinear ARDL Approach

This study investigates the asymmetric impact of oil price shocks and COVID-19 total deaths on Kenya, Morocco, Nigeria and South Africa stock market returns. To achieve this objective employing weekly time series data from March 13, 2020 to September 23, 2022, first, we apply the BDS test which confirm the nonlinearity of each series. Second, stationarity tests are used to investigate each series for unit root. The results show that series are stationary in level and in first difference. Third, the bounds test reveals that the series have a cointegration relationship and we apply the nonlinear autoregressive distributed lag (ARDL) ARDL framework to decompose oil price into positive and negative partial sum to investigate a possible asymmetric effect of oil price on stock market returns. The main findings of the asymmetric ARDL model reveal that, in the short-run dynamic, a positive shock in the oil price have a negative and positive effect on stock market returns in Morocco and South Africa respectively. The result is insignificant for Kenya and Nigeria. A negative shock in the oil price have a negative effect on the stock returns in Nigeria, South Africa and in Kenya, Morocco with one period lag. Furthermore, in the long-run, a positive shock in oil price exerts a negative effect on the stock market performance in Morocco and Nigeria while a negative shock in oil price leads to a negative effect also on the stock market returns. The total deaths present a counterintuitive result. Both in the long-run and short-run dynamic, the total number of deaths due to COVID-19 have a significant increasing effect on stock market returns in Kenya, Morocco and South Africa except for Nigeria.

Is There a J-Curve Effect in the Korean Service Trade?

ABSTRACT In this article, we test the asymmetric J-curve hypothesis using data from 10 Korean service industries. When we tested for a symmetric J-curve using the linear autoregressive distributed lag (ARDL) approach, we found support for the J-curve in one industry and the inverse J-curve in two industries. However, when we tested the asymmetric J-curve using the nonlinear ARDL approach, we found support for the asymmetric J-curve in four industries and the asymmetric inverse J-curve in four more industries. The increase from three to eight cases is attributed to the nonlinear adjustment of the real effective exchange rate of the won.

Tourism and financial development: evidence from nonlinear ARDL approach

ABSTRACT This paper investigates the nonlinear effect of financial development on tourism demand, using Japan and Germany as two cases. Two measures, such as liquid-liabilities and credit to the private sector by banks as a percentage of GDP, work as proxies for financial development. Using monthly data over the period 1994:1–2019:12 for Germany and 1996:1–2019:12 for Japan, we have estimated for each country a parsimonious tourism demand function that incorporates both measures of financial development. The findings from the nonlinear ARDL approach show that for each country, tourism demand, price of tourism, and financial development are cointegrated, and the nonlinearity of financial development is mainly a long-run phenomenon. In the long run, a positive change in the level of financial development will positively influence tourism demand and negatively affect it following a negative change. Each country's negative effect appears to be of a slightly smaller magnitude. This might be because Japan and Germany have a better reputation among tourists owing to their higher level of financial development and concomitant lower rate of crime, which in turn minimizes the negative effect of financial development on tourism demand.

An asymmetric analysis of overall globalization on financial inclusion

Purpose Financial inclusion is acknowledged as a critical facilitator of the United Nations Sustainable Development Goals agenda for 2030. Therefore, this study aims to examine the asymmetric role of overall globalization on financial inclusion by controlling economic growth, urbanization and population for the selected South Asian countries. Design/methodology/approach Applying the nonlinear autoregressive distributed lag approach to cointegration explores the impact of overall globalization on financial inclusion in the presence of additional variables like economic growth, urbanization and population in the designed financial inclusion function. Findings The estimated econometric outcomes show that increasing overall globalization fosters financial inclusion while decreasing overall globalization reduces financial inclusion. Furthermore, a positive (negative) change in economic growth leads to an increase (decrease) in financial inclusion while varying short-run findings. Moreover, both positive and negative changes increase financial inclusion in the long run in connection with urbanization. Although the short-run results are not significant, the study finds that an increase (decrease) in population leads to a decrease (increase) in financial inclusion. Finally, to support the promotion of financial inclusivity throughout South Asia, several policies pertaining to financial inclusion are suggested. Originality/value To the best of the authors’ knowledge, this is the first study to examine the asymmetries related to overall globalization on financial inclusion by controlling economic growth, urbanization and population.

The asymmetric effects of exchange rate volatility on UK–Pakistan trade flows: New evidence from nonlinear ARDL approach

Using the nonlinear autoregressive distributed lag (NARDL) method, the current study explores the effects of exchange rate variations on commodities trade between Pakistan and the United Kingdom. The current study contends that the limiting assumption of symmetry between the exchange rate and the trade flows may have hampered the empirical results, despite the fact that earlier studies primarily used the symmetric cointegration approach. From 1980 to 2020, the study examines the symmetric and asymmetries effects of exchange rate variations on 35 sectors in Pakistan that import from the UK and 35 industries that export to the UK. The findings suggest that there is evidence of a considerable influence of asymmetric exchange rate variations on trade flows in both the short and long term in over half of the importing and exporting industries that participate in trade with the UK. By highlighting the significance of taking into account asymmetry in the analysis and exposing the sector-specific effects of exchange rate changes on trade flows, the study adds to the body of current work.

Health care expenditure, economic growth, and population ageing in Japan: empirical evidence using the nonlinear ARDL approach

ABSTRACT In Japan, health care expenditure (HCE) has increased with the rapid ageing of the population. It raises concerns on how the public health care insurance system should be sustained in the future, since the dependence on public burdens is growing under the government’s difficult financial conditions. This study investigates the cointegration relationship between HCE, GDP, and the population ageing rate (AGE) in Japan for the period 1960–2019 by using the nonlinear ARDL approach. The results revealed that per capita HCE may increase more significantly during an economic downturn than during an economic improvement in the long-run. Moreover, an increase in AGE has a positive effect on per capita HCE. These findings show the need to achieve stable economic growth and seriously address the issue of ageing for policymakers in Japan.

Asymmetric shocks of the COVID-19 pandemic on the Australian stock market: Evidence from multiple threshold nonlinear ARDL (MTNARDL) approach

This study investigates the asymmetric effects of the COVID-19 pandemic on the Australian stock market using a novel methodology (multiple threshold nonlinear ARDL). We find that, in the short-term, the pandemic's impact is statistically insignificant for moderate levels of pandemic intensity (30–70% range). However, for both more severe outbreaks (above 70%) and less intense initial stages (below 30%), the pandemic shows short-term negative effects. Interestingly, these adverse effects become consistent across all intensity levels in the long-term. Additionally, our analysis reveals counterintuitive relationships between daily economic activity and stock market performance at different pandemic intensity thresholds.

Achieving climate sustainability in the Republic of Congo: The role of economic growth, biomass energy consumption, rule of law and government effectiveness- a NARDL Approach

This study explores the relationship between economic growth (GDP), biomass energy consumption (BEC), Rule of Law, and Government Effectiveness on climate change (CO2 emissions) in the Republic of Congo from 1990 to 2020. We employed a nonlinear autoregressive distributed Lag (NARDL) model to analyse data from World Bank databases. Higher GDP leads to lower CO2 emissions in the long run. Increased BEC also reduces emissions, but a decrease can have a small negative impact. Interestingly, a stronger Rule of Law and Government Effectiveness is associated with higher CO2 emissions in the short run, potentially due to relaxed environmental regulations. However, a stronger Rule of Law and Government Effectiveness leads to lower emissions in the long run, suggesting a potential shift towards sustainable practices. These findings provide valuable insights for policymakers aiming to achieve economic growth and climate stability in the Republic of Congo.

Asymmetric Effect of Monetary Policy on Asset Prices: Contractionary VS Expansionary Regimes

This research study seeks to investigate the asymmetrical impact of monetary policy on asset prices (stock price and house prices as indicators of asset prices). Understanding this asymmetry is crucial for policymakers and central banks to evaluate the implications of expansionary and contractionary monetary policies on asset price dynamics. The study examines both interest rates and the money supply, which are key tools of monetary policy, to determine if they have similar effects on asset prices across various economic regimes in 51 countries with diverse income levels for the period of 2009 to 2021. Using a linear and non-linear ARDL (NARDL) approach this study analyze the short-run and long-run impacts of monetary policy on stock and house prices, besides comparing the symmetric and asymmetric impacts of monetary policy shocks on these prices. The outcomes accentuate the importance of policymakers being cognizant of the impacts of different policy regimes on asset prices. Notably, the study reveals a significant and negative short-term impact of interest rates on asset prices under contractionary monetary policy. Conversely, expansionary monetary policy does not demonstrate a significant short-term effect on asset prices. This study makes substantial contributions by deepening insights into the efficacy of monetary policy, offering practical guidance for policymakers, and addressing a pivotal void in the extant scholarly discourse.

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

The role of fintech, mineral resource abundance, green energy and financial inclusion on ecological footprint in E7 countries: New insight from panel nonlinear ARDL cointegration approach

This main objective of the study is to examine the impact of green energy, financial inclusion, fintech, and mineral resource abundance on the ecological footprints (EFP) of the top seven emerging economies. The research mainly explores the role of mineral resource abundance and fintech advancements in promoting environmental sustainability, while also analyzing the benefits of green energy in reducing ecological footprints in E7 countries. This research employed the panel Nonlinear ARDL approach to gain a deeper understanding of positive and negative variations of the data of E7 countries from 2000 to 2020.The study employed the robust and second-generation panel unit root test to enhance the understanding of the estimated model. There are many benefits to using these most robust second-generation techniques; such as they possess an ability to recognize patterns and correlations in panel data. In addition, these second-generation tests provide enhanced estimators in comparison to first-generation methods. To ensure utmost precision and to ensure reliability and validity of the data analysis, the authors have employed process underwent comprehensive testing with both CIPS and CADF. Furthermore, the HASIO test is used to evaluate uniformity in data. The findings of the study reveal that green energy has a significant and complex relationship with the ecological footprint, indicating that investments in green technologies can have immediate beneficial effects on environmental quality, albeit with varying impacts over time. Financial technology emerges as a pivotal factor with both positive and negative shocks displaying a substantial influence on the ecological footprint, suggesting that technological advancements in the financial sector can lead to sustainable economic practices that are crucial for environmental health. The results of the study imply that strategic investments in green energy and innovative financial technologies are essential for achieving the SDGS, particularly SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). The results of the study further imply that these investments not only reduce the ecological footprint but also promote sustainable economic growth in emerging economies, demonstrating the interconnectedness of economic advancement and environmental stewardship.

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.

Assessing the influence of research and development, environmental policies, and green technology on ecological footprint for achieving environmental sustainability

Recently, there has been rising global concern regarding the importance of achieving environmental sustainability. Consequently, researchers and policymakers have focused on identifying and evaluating the various elements that contribute to an individual's ecological footprint and environmental consequences. Therefore, this study provides an in-depth understanding of the roles of green technology, research and development (R&D), and environmental policies that help attain environmental sustainability in Ghana. The present study utilized both the nonlinear autoregressive distributed lag (NARDL) and autoregressive distributed lag (ARDL) techniques to evaluate the long and short-run relationships between explanatory variables from 1990 to 2022. The study compares the results of NARDL and ARDL techniques. The findings reveal that the NARDL (0.999) analysis had a greater impact on the ecological footprint in Ghana than the ARDL (0.996) analysis. Under the ARDL technique, green technology has a negative impact on ECF in both the short and long run, and R&D also decreases ecological footprint (ECF) in the long run. Environmental policies had a negative impact on ECF in both the short and long run. Based on the NARDL approach, an adverse change in GT had a negative impact (0.004) on the ECF in both the short and long run. In contrast, a negative change in R&D has a negative impact (0.007) on the ECF in the short run, and a positive change in R&D negatively affects the ecological footprint in the long run. Notably, a positive change in environmental policies had a significant negative impact (0.040) on the ECF in the short and long run. This study suggests that policymakers should encourage and support the adoption and application of green technology and the development of robust environmental policies, as these measures can significantly contribute to decreasing the ecological footprint and fostering environmental sustainability.

Oil and Food Price Before and During COVID-19 Pandemic in Nigeria: A Non-Linear ARDL Approach

Abstract This paper analyzes the relationship between food and oil prices in Nigeria before and during the COVID-19 pandemic, using monthly data from January 2018 to December 2021. The ARDL and NARDL models are applied to estimate the symmetry and asymmetric relationship that exists in food price behavior. The NARDL confirms the presence of asymmetries, and the bound test affirms the co-integration and long-run relationship among the variables. In the long run, there is a significant positive relation between oil price increases and food prices, but the long-run impact of oil price reductions on food prices is not significant. In the short run, only increases in oil prices exert a significant influence on food prices, while decreases in oil prices do not. Furthermore, the COVID-19 period exerts a positive and significant impact on food prices, while COVID-19 cases do not influence food prices in Nigeria.

Asymmetric Effect of Market Sentiment on Banking: A Nonlinear ARDL Approach

Asymmetric Effect of Market Sentiment on Banking: A Nonlinear ARDL Approach

Asymmetric Effect of Market Sentiment on Banking: A Nonlinear ARDL Approach

Asymmetric Effect of Market Sentiment on Banking: A Nonlinear ARDL Approach

Evaluating the waste management greenhouse gas emissions effects of domestic material biomass and raw material productivity consumption in Denmark

The planet is currently grappling with ecological upheaval as a consequence of the relentless surge in global warming. In response, the Danish government has undertaken a commitment to environmental decarbonization, setting a goal for the year 2030. This study contributes to these efforts by assessing the extent to which domestic material biomass and raw material productivity consumption impact ecological sustainability in Denmark. This assessment is based on data spanning from 1990 to 2020. Furthermore, the study takes into consideration the additional effects of economic advancement and domestic consumption of fossil fuels. These factors are addressed using a nonlinear auto-regressive distributed lag approach, which captures their respective positive and negative influences. The outcomes of the study affirm that positive (negative) shifts in domestic consumption of biomass and raw materials productivity contribute to increased (decreased) ecological sustainability in Denmark. Similarly, positive (negative) shifts in economic growth and domestic consumption of fossil fuels lead to decreased (increased) environmental sustainability. These conclusions are further substantiated by the causality results in the frequency domain. Drawing from these empirical findings, the study presents various strategies aimed at advancing diverse sustainable development goals, offering potentially beneficial avenues for Denmark's progress.

Revisiting the debt–growth nexus in sub-Saharan Africa: fresh evidence from panel nonlinear ARDL approach

PurposeWhile some countries have used debt to drive economic growth, the asymmetric effect on sub-Saharan African (SSA) countries has received little attention in the empirical literature. This paper therefore examines the asymmetric effect of external debts on economic growth.Design/methodology/approachThe panel nonlinear autoregressive distributed lag (NARDL) approach was employed in the study for 29 sub-Saharan African countries from 1990 to 2021. The cross-sectional dependence test was used to determine the presence of cross-sectional dependence, while the second-generation panel unit root tests was used to examine the unit-root properties.FindingsThe empirical results show that external debt has an asymmetric effect on economic growth in both the short and long run. In the long run, a positive shock in external debts of 1% triggers an upturn in economic growth by 0.216% while a negative shock triggers 0.354% decline in economic growth. This implies that the negative shock of external debts has a much stronger impact on economic growth than the positive shock. In the short run, a positive shock in external debts by 1% triggers a decline in economic growth by 0.641%, while a negative shock of 1% triggers a fall in economic growth of 0.170%.Originality/valueThe paper used the NARDL model to examine the asymmetric impact of external debt on the economic growth of SSA countries, which has not been extensively studied. It is recommended that governments in the selected countries in sub-Saharan Africa should drive economic growth by promoting domestic revenue mobilization since external debts impede economic growth.

A nonlinear autoregressive distributed lag approach to remittances and access to financial inclusion in Jordan

A nonlinear autoregressive distributed lag approach to remittances and access to financial inclusion in Jordan