Nonlinear Autoregressive Distributed Lag Model Research Articles

Effect of Monetary Policy on Food Inflation in Nigeria: A Nardl Structural Approach

Abstract The relationship between Nigeria's monetary policy and food inflation has been experimentally examined in this study. A quantitative research method based on ex-post facto research design was adopted using the non-linear autoregressive distributed lag model approach (NARDL) in order to examine the impact of monetary policy on food inflation in Nigeria between the periods of 1980 and 2021. As a dependent variable, Food Inflation (FINF) was employed in the study. Exogenous variables also included Treasury Bills Rate (TBR), Exchange Rate (EXG), Monetary Policy Rate (MPR), and Broad Money Supply (M2). The study used time series data from the World Bank data repository (WDI), the National Bureau of Statistics, and the Central Bank of Nigeria's (CBN) Statistical Bulletin. Data analysis showed that the exchange rate significantly and negatively affects the price of food in Nigeria. Similar to this, empirical data demonstrates a long-run association between Nigeria's monetary policy rates and food inflation. Both the money supply and the monetary policy rate have a favorable impact on food inflation in Nigeria, which is both positive and significant. As a result, it was advised that Nigeria's monetary policy be set up so that the goals to be attained are clearly specified. JEL classification numbers: E31, E52, E51, C5. Keywords: Inflation, Monetary Policy, Money Supply, NARDL.

Is there an asymmetric effect of exchange rate volatility on exports and imports in the Central, East and Southeast European countries?

ABSTRACT The main objective of this paper is to assess the asymmetric effect of exchange rate volatility on the exports and imports of 17 Central, East and Southeast European (CESEE) countries. For this purpose, the linear and non-linear autoregressive distributed lag (ARDL) model and annual data for the 1995–2020 period were used. Empirical results of the assessment showed an asymmetric effect of exchange rate volatility on exports in nine countries and a symmetric effect on exports in four countries. Similarly, an asymmetric effect of exchange rate volatility on the imports of 10 countries and a symmetric effect on the imports of five countries were found. Research implications of this study are important to enable policy makers to understand that results obtained in earlier studies through the linear model may lead to incorrect views about the effect of exchange rate volatility on the exports and imports of CESEE countries.

Has the Asymmetric Effect of Oil Price Change in Inflation Expectations Been Impacted by the COVID-19 Outbreak? A Comparison Between the United States and China

Economists and policymakers believe that households’ and firms’ expectations of future inflation are key determinants of actual inflation. This paper applies the ARDL model and nonlinear ARDL model to long-term inflation-targeting policy mechanisms in the United States and China to assess the impact of oil price dynamics and asymmetries on inflation expectations, as well as the difference of this impact before and after the COVID-19 pandemic. In order to show the significant role of the COVID-19 outbreak, this paper includes the data from 2010 to 2021 and takes the pandemic period as a structural break. Taking oil price changes as a variable of interest, and introducing some other significant variables, we find that during the pandemic, the positive impact of oil price shock on U.S. inflation expectations has enhanced, whereas the positive impact on Chinese inflation expectations has weakened. There is also sufficient evidence of the existence of the asymmetric effects of oil price changes on inflation expectations in both countries, but the positive oil price change in the United States has always played a larger role than the negative oil price shock. In China, the impact of positive oil price shock was greater than that of negative oil prices before the epidemic and the effect of negative oil price shocks has increased significantly in the COVID-19 regime.

Linear and nonlinear asymmetric relationship in crude oil, gold, stock market and exchange rates: An evidence from the UAE

This study examines dynamic relationship among the macroeconomic variables represented by the international oil and gold prices, exchange rates and stock market index in the context of UAE's economy. The UAE is known as a major player in trading both oil and gold in the global market. Daily data for the period ranging from 19th March 2015 to 8th October 2022 is used for this study. Autoregressive distributed lag (ARDL) model is applied in both linear and non-linear specifications to explore co-movement among the variables under study. While the estimated parameters from linear ARDL model indicate the absence of any co-integration among gold, oil and stock market, the non-linear ARDL model however, does indicate and validate the presence of long-run asymmetric relation among these markets. Exchange rates play a significant role both in the short as well as in the long run. Besides, the study observes that negative shocks do have different scale of impact than the positive ones. Therefore, the present study concludes that a non-linear approach is best suited to understand the dynamics of these markets. The findings of this study have important implications for policy makers and other stakeholders as they must ensure that the direction of shocks is taken into consideration before policy prescriptions or any other investment decisions.

Asymmetric effects of exchange rate volatility on trade flows in Nigeria

Purpose — This study assesses the symmetric and asymmetric effects of exchange rate volatility on trade flows in Nigeria.Method — The study employs quarterly data and covers the period 1995q1 to 2020q4. The data were sourced from International Financial Statistics (IFS) and Central Bank of Nigeria (CBN) websites. The paper applies both linear ARDL and non-linear ARDL (NARDL) models. These methods are employed to evaluate the symmetric and asymmetric effects of exchange rate volatility.Result — The results from linear ARDL model show that exchange rate volatility has only significant short-run effect on export while it has both short-run and long run effects on the imports. The findings from the non-linear ARDL suggest that exchange rate volatility has neither short run nor long run asymmetric effects on exports. However, the non-linear ARDL model reveals short run and long run asymmetric effects of exchange rate volatility on imports. The findings show that increase in volatility reduces imports while decrease in volatility boosts imports.Contribution — Previous studies have only investigated the symmetric effects of exchange rate volatility on trade balance in Nigeria. This study contributes to the literature by examining the symmetric and asymmetric effects of exchange rate volatility on trade flows, using the GARCH-based measure of exchange rate volatility.

Exploring the Nexus Between the Shadow Economy, Finance, and Economic Growth in Tunisia

This study aimed to assess the effect of the shadow economy on the finance-growth relationship in Tunisia over the period 1984-2020. The authors used a nonlinear autoregressive distributed lags (NARDL) model to verify the impact of the informal economy as measured by Tanzi's method on the finance-growth relationship. The results suggest that in the long term, with a positive change at the level of the shadow economy, the effect of financial development on growth becomes negative. The opposite is also true. However, in the short run, asymmetric effect of the shadow economy is only detected on economic growth and not on the financial development-economic growth nexus. Indeed, the level of the informal economy has an important role in the Tunisian economy. The significant and positive impact of financial development on the economy is strongly influenced by the size of the informal economy.

Evaluating the trilemma nexus of digital finance, renewable energy consumption, and CO2 emission: evidence from nonlinear ARDL model.

It has been established in2030 sustainability objectives as per SDGs that highlight the critical importance of access to affordable, renewable energy, robust, long-term industrial progress, and digital financing in CO2 emission. The intent of study is to test the trilemma nexus between digital finance, renewable energy consumption, and carbon emission reduction with nonlinear ARDL tests. The study acquired the data and applied the nonlinear ARDL test, split analysis tests, and vector-error correction model (VECM) tests. The results of the study highlighted that the increase of digital finance positively enhances the renewable energy and negatively reduces the CO2 emissions which we calculate to be 11.4% of the digital finance funding on renewable energy goods. For this, a 39% increase in digital financing is noticed by the research findings during the COVID-19 crisis period. Such robust study findings present the latest insights that digital financing is an eminent and viable source of financing for the trilemma nexus with renewable energy consumption and the CO2 emissions. Following these, multiple research implications are also presented for the key stakeholders.

Asymmetrically examining the impact of green finance and renewable energy consumption on environmental degradation and renewable energy investment: The impact of the COVID-19 outbreak on the Chinese economy

The recent global recession due to Covid-19 has led to a drop in natural resource prices, which has contracted energy demand. Amid this concern, environmentally sustainable renewable energy projects have become uncompetitive and an obstacle to achieving the Sustainable Development Goals (SDGs). Following the nonlinear autoregressive distributed lag (NARDL) model proposed by Shin et al. (2014), to asymmetrically explore the impact of green bonds on renewable energy investment and environmental pollution and the impact of renewable energy consumption on environmental degradation in China over the period 1970–2020.​ The results show that the expansion of green bonds (GB+) significantly promotes renewable energy investment and reduces environmental pollution, while the contraction of green bonds (GB−) significantly reduces renewable energy investment and stimulates environmental damage. Likewise, expansion of renewable energy consumption (REC+) significantly reduced environmental degradation, while contraction of renewable energy consumption (REC−) significantly contributed to environmental degradation. Moreover, the result also validates the existence of inverted U-shaped EKC hypothesis in China The VECM Granger causality test indicate that renewable energy investment, green finance, renewable energy consumption, CO2 emission, and Gross Domestic Product (GDP) have long term causality. Chinese policymakers must focus on strengthening green finance, which will encourage renewable energy investment and renewable energy generation. Moreover, renewable electricity output greatly facilitates renewable energy investment, so China must innovate policies to take into account renewable electricity rather than fossil fuel generation in order to achieve the Sustainable Development Goals (SDGs).

Do Islamic banks have their benchmarks for financing rates in the dual-banking system?

This study examines whether conventional bank lending rates influence Islamic bank financing rates in Indonesia and Malaysia that apply the dual-banking system. We employ the ARDL, the non-linear ARDL (NARDL) model, and the Pooled Mean Group (PMG). Evidence of the long-run link between Islamic financing rate and conventional lending rate is found. However, instead of symmetry, the link between them is asymmetry. The asymmetric pricing of the Islamic financing rate and some specific contracts such as Mudharaba and Murabaha rates in Indonesia strongly follow the decrease in conventional lending rate, but it is sticky against the increase in conventional lending rate. The asymmetric pricing of the Islamic financing rate in Malaysia is obviously pegged to the conventional lending rate. The PMG results strengthen the asymmetric findings where the effect of a reduction in the conventional lending rate is larger than the effect of an increase in the conventional lending rate on the Islamic financing rate. These findings imply that Islamic bank borrowers are profit-driven borrowers in a dual-banking system. Accordingly, the Islamic financing rate is pushed to follow the conventional lending rate due to the uncompetitive Islamic financing rate.

Exploring the Asymmetric Effect of Internal and External Economic Factors on Poverty: A Fresh Insight from Nonlinear Autoregressive Distributive Lag Model

Objective: This study examines the asymmetric impact of both internal (military, education, and health expenditures) and external (trade opening and foreign direct investment) factors that contribute to poverty reduction. Methodology: To find an asymmetric relationship between the proposed variables, we used a non-linear ARDL co-integration approach for the period ranging from 1981-2019. Findings: The findings of the study confirm the asymmetric impact of internal (education, military, health expenditures, quality of governance) and external (foreign direct investment, openness) factors on poverty. The finding confirms that ignoring nonlinear or asymmetric properties of macroeconomic variables may mislead inferences. This study has policy implications for government officials to reduce poverty. Novelty: theeconomic theory of poverty is studied from different perspectives by using internal and external factors that have direct and indirect effects on poverty. Furthermore, for in-depth analysis, a nonlinear approach is used to determine which factor has a strong contribution to eliminating poverty. Doi: 10.28991/ESJ-2023-07-03-07 Full Text: PDF

Does U.S. Economic Policy Uncertainty Influence Chinese Domestic Inflation?: Evidence from China’s 31 Provinces

Purpose - This paper empirically analyzed how China’s domestic inflation responds to foreign uncertainties, especially U.S. economic policy uncertainties. This paper helps to fill the gap in the research on the impact of one country’s economic uncertainty on the others economy. Design/Methodology/Approach - In this paper, we were first to collect disaggregated data on China’s 31 provinces from Q1 2001 to Q4 2021, adopting the nonlinear autoregressive distributed lag (NARDL) approach, to study the impact of U.S. economic policy uncertainty (EPU) on Chinese inflation. Given that the economic structures of China’s 31 provinces are different, such as the level of economic development, industrial structure, economic scale, population scale, and so on, this paper uses China‘s regional data for the first time. We employ the nonlinear autoregressive distributed lag (NARDL) approach proposed by Shin et al. (2014), which has recently attracted attention. Findings - The main findings are as follows. First, the impact of U.S. EPU on inflation in China’s provinces is prominently presented by the short-run (26 provinces) versus the long-run (19 provinces). Second, an increase (decrease) in U.S. EPU causes a decrease (increase) in Chinese inflation in the long-run. Third, short-run asymmetry in U.S. EPU was demonstrated in 20 provinces, and long-run asymmetry was demonstrated in 17 provinces. Moreover, the characteristics of asymmetry develop from short-run to long-run in 15 provinces. Research Implications - The estimation result of the NARDL model shows that the long- and short-run asymmetric effects of the U.S. EPU on domestic inflation are not exactly the same in terms of China’s 31 provinces. This paper also suggests that province-specific phenomena should not be ignored when the Chinese government formulates policies to deal with foreign uncertainty.

Does financial development improve economic growth? The role of asymmetrical relationships

This paper investigates the impact of financial development on economic growth in India, a major emerging economy. We estimate more flexible models than typically found to capture potentially asymmetric relationships while accounting for trade openness, foreign direct investment, and technological development. We document a cointegrating and asymmetric relationship between the key variables using nonlinear and standard autoregressive distributed lag models. We find a consistently negative impact of financial development and foreign inflows on economic growth in India in the long and short run, while trade liberalization and technological development have positive effects. Our findings, therefore, suggest caution regarding financial market liberalization in India.

Understanding the role of efficiency in the electricity generation process for promoting human development in India: Findings from the novel multiple threshold nonlinear ARDL modelling

The present paper seeks to examine the effects of electricity generation efficiency on the index of human capital in India over 1980–2021 through the novel multi threshold non-linear autoregressive distributed lag model. We find strong evidence that the effects of efficiency in the generation of electricity on human development have varied across thresholds/quantiles. We suggest that, for improving human development in India by suitable energy policies, both policy makers and the public sector managers will need to make directed efforts to use most robust and energy saving technologies in the electricity generation process.

Analyzing the Consequences of Long-Run Civil War on Unemployment Rate: Empirical Evidence from Afghanistan

This article aims to uncover the asymmetric labor-market consequences of the long-run civil war in Afghanistan by employing a non-linear autoregressive distributed lags (NARDL) model and an asymmetric causality technique over the period from 2004Q3 to 2020Q4. The findings from the NARDL model reveal that the positive asymmetric shocks from the cost of war, GDP growth, final government expenditure, foreign direct investment, and the rule of law significantly decrease the unemployment rate, while their negative asymmetric shocks increase the unemployment rate in the short and long runs. Innovatively, the composite financial inclusion index has been incorporated into the model, which provides interesting results. It demonstrates that enhancing the outreach of financial services plays an important role in reducing the unemployment rate during wartime in Afghanistan, while its exclusion is found to increase the unemployment rate both in the short and long runs. Moreover, the results of the asymmetric causality test reveal that an asymmetric causality runs from both the positive and negative components of the cost of war, the composite financial inclusion index, GDP growth, foreign direct investment, inflation rate, population growth, and the rule of law to the unemployment rate, while no evidence is found to support a causality nexus between the unemployment rate, final government expenditure, and the secondary school enrollment rate. The results entail several policy implications that are discussed.

Do remittances have an asymmetrical effect on financial development? Empirical evidence from Turkey

The purpose of this study is to reveal the long- and short-term asymmetric effects of remittance, economic growth and inflation on Turkey's financial development using the 1974–2019 period data. For this purpose, long- and short-term asymmetric effects were investigated with the non-linear autoregressive distributed lag (NARDL) model. NARDL findings revealed that there are long- and short-term asymmetrical relationships among variables. Long-term findings show that increases in remittances and economic growth increased financial development, but increases in inflation reduced financial development. The short-term findings show that increases in remittances, economic growth and inflation increased financial development. In addition to ensuring macroeconomic stability, policy makers in Turkey should formulate regulations that encourage remittance entry in order to attract more remittances to the country and channel them into the financial system.

Spatial price transmission in the onion markets of Bangladesh: An application of NARDL approach.

As the price of local onions is greatly impacted by the price of imported onions at these two levels of the supply chain, the goal of this study was to ascertain whether onion prices in Bangladesh are transmitted asymmetrically at the wholesale and retail levels. To analyze asymmetry, the study employed the nonlinear autoregressive distributed lag (NARDL) model in the short and long run using monthly time series data from January 2006 to December 2020. The NARDL model captures the effects of both positive and negative shocks in the short as well as in the long run. The empirical results from the NARDL indicate that the wholesale price of local onion shares a short-run relationship with the wholesale price of imported onion while the local retail price of onion shares a long-run relationship with the imported retail price of onion. In addition, the short-run impact of local wholesale and imported wholesale prices is asymmetric. Long-run evidence supports the existence of an asymmetric effect between the local and imported retail onion prices. Using the Pairwise Granger causality test, we examined the causal relationships between wholesale and retail prices. The direction of the casual relationship indicates that the wholesale and retail prices of imported onions lead to the wholesale and retail prices of local onions. A clear understanding of the onion market, how prices move between market actors, and its role in determining market price interaction could be gained by analyzing the asymmetric relationship between the local and imported onion prices. As a result, significant policy recommendations could be made to control the onion price in Bangladesh.

Public spending and the resource curse in WAEMU countries: An asymmetry analysis using the hidden cointegration and non-linear panel ARDL framework

In this paper, we analyze the long-run effect of natural resource endowment on total public spending, public education spending, and public health spending in WAEMU member countries. After checking the cross-section dependence and unit root of the variables, this study uses the pooled mean group estimation technique within linear and non-linear panel ARDL models to investigate (a)symmetry effects in the relationship between variables. empirical results suggest that the resource curse hypothesis holds, meaning that natural resources adversely affect public spending. Across multiple specifications, our results support also the crowding-out effect and the institutional channel through which natural resources impact public spending. It seems therefore that the WAEMU countries still fail to transform the resource wealth advantage into favorable development outcomes. In light of the results, a few policy options are discussed in this paper.

Asymmetric impacts of ICT and energy intensity on agricultural productivity: Evidence from Asia‐Pacific region

AbstractIn the contemporary times of rising food insecurity and malnutrition, the agricultural sector needs more attention. This study aims to investigate the asymmetric impacts of information and communication technologies (ICTs), energy intensity, urbanization, and inequality on agricultural productivity for 20 Asia‐Pacific countries from 1990 to 2020. To investigate asymmetric impacts, the study employs the panel nonlinear autoregressive distributed lag (NARDL) model. The estimated results revealed that positive and negative shocks in ICT, energy intensity, and urbanization have asymmetric impacts on agricultural productivity in the long run, whereas symmetry is observed in short‐run impacts. It is found that a 1% increase (decrease) in ICT and urbanization increases (decreases) agricultural productivity by 0.292% (0.662%) and 2.717% (2.759%), respectively, whereas a 1% increase (decrease) in energy intensity decreases (increases) agricultural productivity by 0.252% (0.216%) in the long run. Furthermore, the results of the Dumitrescu‐Hurlin panel causality test point out the existence of bi‐directional causality between agricultural productivity and the independent variables (ICT, energy intensity, urbanization, and inequality). Based on the findings, the study suggests that the Asia‐Pacific countries should increase the application of ICT and use energy more efficiently in agriculture to boost agricultural productivity.

A nonlinear autoregressive distributed lag analysis on the macroeconomic effect of global oil price in the Philippines

AbstractStudies have pointed out that oil price volatility influenced economic output and growth among developing and net oil‐importing countries. More than a quarter of the Philippines’ energy demand depends on crude oil, and 99% of the crude oil demand is imported mainly from the Middle East. This study was conducted to determine if there is a nonlinear or asymmetric output response to oil price movements and examine which economic sector in the Philippines is the most vulnerable to oil shocks. This contributes to the literature for a case of developing, oil importing, inflation targeting and post‐oil industry deregulated economy. A nonlinear autoregressive distributive lag model was applied to observe quarterly data from 1998:Q1 to 2019:Q4 of the relevant economic variables. Results revealed an asymmetric effect of non‐oil variables on sectoral performance. World oil prices affect economic sector outputs symmetrically or linearly. The service sector is found to be the most vulnerable sector to oil price shocks. The absence of asymmetry can be attributed to increased competition in the Philippines’ domestic oil industry brought about by oil market deregulation. Improving the energy mix and reducing oil intensity is vital to offset any oil price shock transmission to an oil‐importing economy like the Philippines.

The impact of oil price changes on inflation and disaggregated inflation: Insights from Ghana

Numerous studies have examined the impact of changes in oil price on economic activities in both developing and developed countries. Yet, studies on the impact of oil price on various sectors of the economy are limited, particularly in Ghana. To contribute to the literature and inform policy actions, we examine the impact of oil price changes on aggregated and disaggregated inflation where the disaggregated inflation comprises energy CPI, food CPI, Core CPI, and transport CPI. We applied Nonlinear Autoregressive Distributed Lag (NARDL) Model to quarterly data spanning from 2000Q1 to 2021Q1. The NARDL model was suitable for analysis because it accounted for asymmetries inherent in oil prices. Our results from the NARDL model suggest evidence of the asymmetric impact of oil price change on both aggregated and disaggregated inflation. However, the asymmetric effect of oil price changes on Transport CPI was statistically higher in magnitude than the other sub-indexes of inflation, suggesting that oil price changes affect the transport sector more than the other sectors of an economy. From a policy point of view, these findings imply that to stabilize inflation, policies should be designed to strengthen the transport sector to contain oil price shocks.