Nonlinear Autoregressive Distributed Lag Model Research Articles

The Effects of Interest Rates on Bank Risk-Taking in South Africa: Do Cyclical and Location Asymmetries Matter?

We examine the nonlinear relationship between interest rates on bank risk-taking behavior in South Africa between 2008:q1 and 2022:q3 using nonlinear autoregressive distributive lag (NARDL) and quantile autoregressive distributive lag (QARDL) models. Whilst the preliminary estimates from linear ARDL produce results adhering to conventional theory, the NARDL and QARDL analysis shows that the relationship between the variables is more complex. On one hand, the NARDL model shows that the phase of monetary policy (cyclical asymmetries) is important in determining the pass-through effects of interest rates on bank risk behavior. We find that both contractionary and expansionary monetary policy increases long-term risk through decreased liquidity for the former and increased non-performing loans for the latter. On the other hand, the QARDL model shows that the level of bank risk behavior (location asymmetries) is also important in determining the impact of interest rates on bank risk behavior. We find that interest rates affect bank risk behavior in ‘medium-to-high risk environments’ for unsecured loans and lending and in ‘medium-to-low risk environments’ for liquidity. Overall, these results enable us to recommend ways in which the SARB can strengthen its monitoring mechanisms given the multifaceted impact of interest rates on bank risk-taking.

Integrating fintech in natural resource management: Assessing the EKC hypothesis for sustainable development in E7 countries

The main objective of the study is to examine the impact of green finance, fintech and mineral resources on environmental sustainability is of great importance in the E7 nations namely Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. The E7 countries are selected as these countries are mineral rich countries and account for a major portion of global mineral export. The data of twenty-five years spanning from 1998 to 2022 is used for the analysis. The study has employed the three measures namely carbon dioxide emissions, ecological footprint, green economic growth to conceptualize the sustainable growth. For the data analysis the study has employed the nonlinear auto-regressive distributed lag (NL-ARDL) model. The results of the study highlights that encouraging and promoting the green finance, and fintech in E7 countries promote sustainable growth, by reducing CO2 emission, improving economic growth, and reducing ecological footprints. The results of the study are in line with the proposition of EKC hypothesis. Moreover, the results of the study also highlight that mineral resource abundance have significant impact of environment sustainability. The study suggests that E7 countries should establish dedicated funds or subsidies to help businesses transition to green technologies and practices, especially for small and medium-sized enterprises. Fintech is seen as a transformative tool in advancing environmental sustainability by improving financial service efficiency and offering new green investment platforms in E7 countries. This could help mitigate initial costs associated with green technology adoption.

AN ANALYSIS OF THE LONG-TERM ASYMMETRIC RELATIONSHIP BETWEEN GOLD PRICES, EXCHANGE RATES, YIELDS OF GOVERNMENT BOND, AND THE BIST100 INDEX

This study examines the asymmetric effects of the gold price, the USD/TRY exchange rate, the corporate governance index, and the 10-year government bond yield on the BIST100 index, thus delving into the intricate web of financial markets. Using weekly data from September 2007 to September 2023, we employed the nonlinear ARDL model to examine the asymmetric effects of the variables on the BIST100 index. As a result, the nonlinear ARDL bound test proved the long-term cointegration between the BIST100 index and the explanatory variables used in the analysis. All asymmetric variables except the negative variable of gold price had statistically significant long-run effects on the BIST100 index. Government bond yields and gold price had negative effects on the stock index, while USD/TRY exchange rate and corporate governance index had positive effects on it. The Wald test's null hypothesis of no long-term asymmetries was rejected for government bond yields, the USD/TRY exchange rate, and the corporate governance index. On the other hand, the test for short-term asymmetry was rejected only for the corporate governance index. Accordingly, the corporate governance index has both short-term and long-term asymmetric effects on the BIST100 index, while government bond yields and the dollar exchange rate have only long-term asymmetric effects on it.

Asymmetric impact of climatic parameters on hemorrhagic fever with renal syndrome in Shandong using a nonlinear autoregressive distributed lag model

Hemorrhagic fever with renal syndrome (HFRS) poses a major threat in Shandong. This study aimed to investigate the long- and short-term asymmetric effects of meteorological factors on HFRS and establish an early forecasting system using autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models. Between 2004 and 2019, HFRS exhibited a declining trend (average annual percentage change = − 9.568%, 95% CI − 16.165 to − 2.451%) with a bimodal seasonality. A long-term asymmetric influence of aggregate precipitation (AP) (Wald long-run asymmetry [WLR] = − 2.697, P = 0.008) and aggregate sunshine hours (ASH) (WLR = 2.561, P = 0.011) on HFRS was observed. Additionally, a short-term asymmetric impact of AP (Wald short-run symmetry [WSR] = − 2.419, P = 0.017), ASH (WSR = 2.075, P = 0.04), mean wind velocity (MWV) (WSR = − 4.594, P < 0.001), and mean relative humidity (MRH) (WSR = − 2.515, P = 0.013) on HFRS was identified. Also, HFRS demonstrated notable variations in response to positive and negative changes in ∆MRH(−), ∆AP(+), ∆MWV(+), and ∆ASH(−) at 0–2 month delays over the short term. In terms of forecasting, the NARDL model demonstrated lower error rates compared to ARDL. Meteorological parameters have substantial long- and short-term asymmetric and/or symmetric impacts on HFRS. Merging NARDL model with meteorological factors can enhance early warning systems and support proactive measures to mitigate the disease's impact.

THE ASYMMETRİC EFFECT OF PRODUCER PRİCES ON CONSUMER PRİCES İN TURKİSH ECONOMY

The aim of the study is to evaluate the asymmetric impacts of producer price on consumer prices and cointegration relationship between two price indexes for Turkish economy from 2003.M1 to 2022.M12. Another aim is to analyze the causality between Producer Price Index (PPI) and Consumer Prıce Index (CPI). The Autoregressive Distributed Lag Model (ARDL) and Non-Linear Autoregressive Distributed Lag Model (NARDL) is estimated to determine relation between PPI and CPI and asymmetric effects of PPI on CPI. The causality relation is examined using Toda-Yamamoto Granger Causality method. According to the results, there is a cointegration relation between CPI and PPI. The ARDL model implies that PPI has a positive impact on CPI both in the short time period and in the long time period. The NARDL model indicates that although positive shocks to the PPI have positive effects on CPI, negative shocks do not have statistically significant effect on CPI. In addition to these results, Toda-Yamamoto Granger Causality method indicates that a bidirectional causality is found between two price indexes.

An analysis of the geopolitical and economics influence on tourist arrivals in Russia using a nonlinear autoregressive distributed lag model

PurposeThe COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.Design/methodology/approachWe employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.FindingsOur research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.Originality/valueOur study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

Does crude oil price volatility respond asymmetrically to financial shocks?

Recent literature has explored the effect of monetary and financial shocks, along with oil supply and global demand shocks, in determining oil price volatility. This paper elucidates whether the change in oil price volatility in response to financial shocks differs over quantiles over the period 1993–2021. First, we disintegrate the structural innovations to oil price volatility, originating from crude oil production, global demand, oil demand, oil inventories, interest rates, and financial market volatility, using the SVAR approach during pre-crisis and post-crisis phases. Furthermore, using quantile autoregressive distributed lag models (QARDL) and nonlinear autoregressive distributed lag (NARDL) models, we analyze the plausible asymmetric effects of these shocks. The findings indicate the significance of supply-side and global demand shocks on oil price volatility in the pre-crisis periods, followed by the increase in the explanatory power of financial shocks on oil price volatility after the crisis. It also suggests that oil price volatility responds asymmetrically to oil supply, inventories, and financial shocks.

Asymmetric effects of oil demand and oil supply shocks on New Zealand's trade

We analyze how different types of oil price shocks affect trade and whether these effects are asymmetric. Our focus is on New Zealand, which has historically been a net oil importer but recently transitioned to an import-only model to meet its needs for finished petroleum products. The analysis proceeds in two stages. First, we identify oil supply shocks, aggregate demand shocks, and oil-specific demand shocks using a recursive structural vector autoregression model. Then, we study whether the effects of these shocks on New Zealand's exports to and imports from its key trading partners—Australia, China, and the United States—are asymmetric using nonlinear autoregressive distributed lag models. The results show differences in the effects of different types of oil price shocks on exports and imports in the short and long run; however, there is limited evidence of asymmetries in these effects, especially in the case of exports. Exports to Australia and China, the most critical markets for New Zealand's exporters, are largely insensitive to oil price shocks.

Unlocking the dynamic linkages between sustainable equity investment and economic policy uncertainty: An empirical analysis for G‐20 countries

AbstractThe study examines the dynamic relationships between sustainable equity investment and economic policy uncertainty of G‐20 countries using monthly environmental, social, and governance (ESG) equity and economic policy uncertainty (EPU) indices. Using the autoregressive distributed lag model and nonlinear autoregressive distributed lag model models, the study finds a negative long‐run relationship between sustainable equity investments and economic policy uncertainties in Australia, Canada, the USA, Brazil, Mexico, Germany, Italy, and Japan. Investors in these G20 countries may perceive that companies with higher ESG performance are more likely to face regulatory scrutiny, legal action, or reputational damage if they are associated with high levels of economic policy uncertainties. As a result, ESG market indices may underperform when EPU is high and vice versa. It supports prospect theory and suggests that individuals are more sensitive to potential losses than gains. On the contrary, the relationship is positive in the case of the USA, Brazil, China, and to some extent India. This might be because firms with high ESG performance could manage risks better and seize opportunities associated with EPU, which helps ESG market indices to outperform when EPU is high. It is supported by the legitimacy theory that says to maintain the legitimacy and credibility of the company, the investment must be invested in ESG initiatives, which can lead to improved long‐term financial performance and market value.

Nonlinear effect of Islamic financing on economic stability: A Case of equity and debt financing

The main purpose of this study is to differentiate between the effects of two major categories of financing of Islamic banks on the economic stability of the selected countries. This study determines the nonlinear effect of equity-based and debt-based financing of Islamic banks to assess how the stability of the economy can be achieved. This study acquires the data on Islamic banking product-wise financing at a national level from the Islamic Financial Service Board (IFSB), and the data on industrial production index is selected from International Financial Statistics for selected countries. The sample size comprises of all the countries included in the IFSB. The data ranges from 2014Q1 to 2019Q4. The economic stability is estimated using the GARCH volatility approach, and the nonlinear ARDL model is used to determine the causal effect of Islamic banking product wise financing. This study clarifies the empirical relationship between Islamic banking equity-based financing and debt-based financing and whether macroeconomic stability is linear or quadratic in terms of the marginal effect of financing, which helps policymakers to constitute strategies for expanding the size of Islamic banking financing. The results identified the inverted U-shaped effect of equity-based financing types on output instability. At the same time, both financing types are not causing price instability. The outcomes are instruments for the central bank to optimize the Islamic banking financing structure to achieve the goal of product-wise financing of economic stability.

Asymmetric Effects of Uncertainty and Commodity Markets on Sustainable Stock in Seven Emerging Markets

The increase in global economic policy uncertainty (EPU), volatility or stock market uncertainty (VIX), and geopolitical risk (GPR) has affected gold prices (GD), crude oil prices (WTI), and stock markets, which present challenges for investors. Sustainable stock investments in emerging markets may minimize and diversify investor risk. We applied the non-linear autoregressive distributed lag (NARDL) model to examine the effects of EPU, VIX, GPR, GD, and WTI on sustainable stocks in seven emerging markets (Thailand, Malaysia, Indonesia, Brazil, South Africa, Taiwan, and South Korea) from January 2012 to June 2023. EPU, VIX, GPR, GD, and WTI showed non-linear cointegration with sustainable stocks in seven emerging markets and possessed different asymmetric effects in the short and long run. Change in EPU increases the return of Thailand’s sustainable stock in the long run. The long-run GPR only affects the return of Indonesian sustainable stock. All sustainable stocks are negatively affected by the VIX and positively affected by GD in the short and long run. Additionally, long-run WTI negatively affects the return of Indonesia’s sustainable stocks. Our findings contribute to rational investment decisions on sustainable stocks, including gold and crude oil prices, to hedge the asymmetric effect of uncertainty.

Modeling the influence of mineral rents and low‐carbon energy on environmental quality: New insights from a sustainability perspective

AbstractIn recent decades, the detrimental impacts of climate change have been increasingly felt worldwide. This is due to the extreme consumption of natural resources to fuel economic activity. Confronting a widening ecological deficit, humanity must urgently accelerate its journey toward sustainable development goals (SDGs). This demands active efforts to curb environmental pollution and protect natural resources, safeguarding the planet for future generations. Since Brazil has high biocapacity and ecological areas, the impact of energy resources on ecological sustainability policies cannot be excluded. Moreover, Brazil holds a vital position in the world for global foreign direct investment flows. In this regard, this paper considers the asymmetric impact of mineral rents and foreign direct investments when investigating Brazil's environmental sustainability. In addition, it evaluates elements like economic growth and low‐carbon energy consumption from 1970 to 2021. To this end, the research applies the Fourier nonlinear autoregressive distributed lag model and draws three significant conclusions. First, resource extraction undermines environmental sustainability. Second, the inflow of foreign direct investment reduces the load capacity factor, implying that the pollution haven hypothesis holds for Brazil. Third, low‐carbon energy consumption contributes to environmental sustainability. Our findings highlight the critical role of regulating mineral resource rents in achieving SDGs in Brazil. Moreover, increasing investment in clean energy sources and transitioning toward low‐carbon energy can promote sustainable development in Brazil. The Brazilian government should abandon mineral extraction, focus on low‐carbon energy consumption, and prevent companies from destroying nature by introducing strict environmental regulations for foreign investment flows.

Tourism and Economic Misery: Theory and Empirical Evidence from Mexico

The misery index (MI) was devised to summarize the most evident costs for a society, attempting to objectively measure the loss in general welfare. It has been remarked in the literature that economic growth exerts a negative impact on the MI; however, analyses of this relationship in the tourism field have been neglected. This study assessed the effectiveness of the tourism sector at improving welfare conditions by measuring the impact of tourism GDP on the misery index and providing a theoretical framework for the relationship between tourism and the MI. A quantitative analysis was conducted using quarterly time series data for the period 2005Q1–2021Q2. Firstly, the existence of a long-term relationship was tested by using the Toda–Yamamoto procedure, and secondly, by applying linear and nonlinear ARDL models. The main results show that tourism can help to reduce the loss of welfare mirrored by the MI. These findings have policy implications, as they provide evidence that expanding the tourism sector counters the MI, and, consequently, the economic malaises derived from it.

Natural resource development, economic policy uncertainty and urban residents’ consumption in China: a nonlinear ARDL and time-varying parameter vector autoregressive with stochastic volatility approach

AbstractIncreased risks of economic policy uncertainty and overexploitation of natural resources exist in China. At the same time, the growth rate of urban residents’ consumption has generally declined. The paper analyses the role of economic policy uncertainty (EPU) and natural resource exploitation on the urban residents’ consumption in China. Based on the data from the first quarter of 2002 to the third quarter of 2021, the paper uses a nonlinear autoregressive distributed lag model to verify the asymmetric effects. Then the paper constructs a time-varying parameter vector autoregressive model with stochastic volatility term to analyze the nonlinear responses. Impulse response analysis was used to further explain the relationship between the three. The negative impact of rising EPU on urban residents’ consumption is larger than its reduction. Negative shocks to natural resource development increase the urban residents’ consumption. Positive shocks reduce the urban residents’ consumption. There is a time-varying non-linear effect of EPU and natural resource development on urban residents’ consumption in China. The negative impact of EPU on urban consumption has been further exacerbated by major crises such as the financial crisis, COVID-19 and the post-crisis period. The negative impact of natural resource development diminished after the government introduced industrial upgrading policies and environmental regulations. This study provides constructive suggestions for the optimization of economic policies and the improvement of urban consumption. This study also enriches consumer theory and provides new evidence for the resource curse hypothesis.

Importance of natural energy, and blue resources to address environmental challenges in view of the Saudi Vision 2030

AbstractThe purpose of this study is to scrutinize the impact of natural resources, energy, and blue economic indicators on the ecological footprint of Saudi Arabia over the period from 1993 to 2022 by employing a nonlinear autoregressive distributed lag model. We have simulated the missing data using the Markov Chain Monte Carlo algorithm. The study encompasses the effects of post‐Vision 2030 and post‐COVID‐19 policies and their assistance in minimizing the environmental footprint. The observed results determine that non‐renewable energy consumption increases the ecological footprint, whereas natural resources and biocapacity drop the ecological footprints in the case of pre‐ and post‐Vision 2030. For variable fisheries production, the post‐ and pre‐Vision 2030 results demonstrate a boosted ecological footprint in Saudi Arabia, with the highest coefficient among all results. This research offers valuable insights into how Saudi Arabia's energy consumption and natural resource management impact its ecological footprint, highlighting the effectiveness of Vision 2030 and post‐COVID policies in promoting environmental sustainability. The study's findings provide crucial guidance for policy making to reduce environmental impact while considering the role of fisheries and biocapacity in ecological balance. Based on empirical findings, this study commends some policy understandings that assist in being effectively implemented towards a sustainable environment.

Unveiling the asymmetric effects: global value chain participation and income inequality

ABSTRACT This study employs a panel nonlinear ARDL model to analyse the asymmetric effects of global value chain participation and its components (forward and backward participation) on income inequality across 29 economies spanning from 2004 to 2018. The findings reveal that global value chain participation is negatively associated with income inequality in the long run, as it stimulates employment opportunities, economic growth, and access to markets. Concomitantly, our study sheds light on whether the effects of global value chain participation vary across its components within the selected economies. Both positive and negative changes in backward participation have positive and significant effects on income inequality in the long run. Simultaneously, adverse changes in forward participation contribute to an upward trajectory in income inequality over the same period. The comprehensive analysis highlights the multi-faceted dynamics between a country’s involvement in global value chains and income disparities within that nation. Given the findings, policymakers need to make it a top priority to boost their economies’ participation in global value chains. This can be accomplished through a multi-pronged strategy that includes trade liberalization policies, measures to attract foreign direct investment, and robust infrastructure development initiatives.

Private and Public Investment: Are they Substitute or Complementary in Driving Economic Growth in Nigeria?

The paper investigates the relationship between government and private investment with a view to ascertaining their complementarity or substitutability in driving economic growth in Nigeria for the period of 1981-2021. To achieve the objective, nonlinear autoregressive distributed lags (ARDL) models and nonlinear Granger causality tests were employed to analyze annual secondary data which were sourced from the Central Bank of Nigeria Statistical Bulletin. Findings show that government investment expenditure displayed a positive and long-term influence on private investment, suggesting a “crowding-in” effect where increased public investment stimulates private investment thereby fostering overall economic growth. Economic adversities or reduced public investment exerted a substantial negative impact on private investment, underscoring the complementarity of government investment expenditure in driving economic growth in Nigeria. Also, the nonlinear Granger causality tests reveal unidirectional relationship as government investment expenditure causes private investment across various embedding dimensions, emphasizing the positive influence of government investment on private investment. The findings generally suggest the need for balanced fiscal policies, prioritizing productive government investments, encouraging private investment, controlling inflation, and making time-sensitive policy decisions to promote economic growth in Nigeria.

Dynamics of cereal product price transmission between markets in Burkina Faso

PurposeEffective agricultural product price regulation policies depend on market integration and the degree of symmetry in the transmission of agricultural product price signals. This study analyzes the transmission and asymmetry of the price series between the Ouagadougou consumer market and assembly markets considering three primary cereal products in Burkina Faso.Design/methodology/approachThis study applies the nonlinear autoregressive distributed lag (NARDL) econometric model, which is an asymmetric extension of the ARDL cointegration model. The price series examined covers the period extending from January 2005 to December 2020.FindingsOur analysis provides novel insights regarding short- and long-term asymmetric effects in the transmission of price signals between assembly markets and the consumer market. We also determine that the effects of negative shocks are more persistent than those of positive shocks in several markets.Research limitations/implicationsFor markets that exhibit symmetrical responses of assembly market prices to consumer market prices, the results could reflect the continuous efforts of market players, particularly the government, to eliminate market failures and ensure the long-term efficiency of cereal markets. To this end, an agricultural market information system can have a crucial role in easing information access for all market players.Originality/valueThis study provides new evidence regarding the nature of the transmission and asymmetry of price information on primary cereal products in the largest markets in Burkina Faso. Applying the NARDL model makes it possible to simultaneously estimate short- and long-term asymmetry.

Testing Okun’s Law for Turkey (1923-2019)

This study tests Okun’s law for Turkey using annual data gathered for almost a century (1923–2019). In contrast to the rest of the literature focusing on a linear relationship between unemployment and output levels, we argue for a cointegrating nonlinear autoregressive distributed lag (NARDL) model. We find clear evidence of an asymmetric cointegrating relationship between unemployment and output as well as asymmetric short-run impacts. Interestingly, these relationships are positive. Asymmetric cumulative dynamic multipliers confirm the results, which can be explained by the structural features of the Turkish unemployment such as the high female and youth unemployment rates, a large agricultural sector, high firing costs, and the high level of informal employment as well as hysteresis. Therefore, effective labour market reforms should consider asymmetries in the long-run unemployment and output relationship as well as asymmetries in their short-run impacts in order to handle jobless recoveries in Turkey.

Untangling the entanglement of US monetary policy uncertainty and European natural gas and carbon prices

Owing to the Russia–Ukraine conflict, the price of natural gas in Europe fluctuated significantly in recent years. As natural gas in Europe is highly dependent on imports, import prices are inevitably affected by monetary policy uncertainties. Additionally, monetary policy uncertainty has a significant impact on financial markets. As a unique financial market, the carbon market is affected by monetary policy uncertainties, but the mechanism of the impact is not yet clear. Therefore, we conduct a systematic study of the relationships between monetary policy uncertainty, European imported natural gas prices, and carbon prices in the last three phases of European Union emission trading scheme. This study uses the dynamic conditional correlation generalized autoregressive conditional heteroskedastic (DCC-GARCH) model and nonlinear auto-regressive distributed lag (NARDL) model to comprehensively analyse the correlation between these three variables, including volatility correlations and trend correlations. The results show that the dynamic conditional correlations between carbon and gas prices are mostly positive, as is the dynamic conditional correlations between natural gas prices and monetary policy uncertainty. However, the dynamic conditional correlations between carbon prices and monetary policy uncertainty gradually decreases and changes from positive to negative in 2015. In addition, the findings indicate the asymmetry of the short-term impact and long-term impact of monetary policy uncertainties and imported natural gas prices on the carbon prices trends. Monetary policy uncertainty has asymmetric effects on carbon prices in each phase of the research. However, the natural gas prices have asymmetric effects only in Phases 2 and 4. Based on the findings, some policy proposals are provided for the development of the carbon markets.