Nonlinear Autoregressive Distributed Lag Research Articles

Asymmetric role of the informal sector on economic growth: Empirical investigation on a developing country

The role of the informal sector in economic growth still remains an issue of debate. This study contributes to resolving this by taking into account the asymmetric effect of the informal sector on economic growth. The study applies the Non-linear Autoregressive Distributed Lag (N-ARDL) model to capture the asymmetric relationship between the informal sector activity and economic growth for the period 1982–2018 in Bangladesh. The estimation of the N-ARDL model reveals that the informal sector asymmetrically affects the domestic output and economic growth in Bangladesh for both the short-run and the long run. The study has observed an asymmetrically larger effect on output and economic growth from the falling contribution of the informal sector. Urbanization and capital growth also contribute to an increase in economic growth. Therefore, proper incentives and careful policy measures are suggested to effectively diminish the prevalence of informality and promote its transition towards a more formalized framework.

Asymmetric impact of microfinance on economic growth: Evidence from Bosnia and Herzegovina

This study explores the correlation between microfinance loans (MFL) and economic growth in Bosnia and Herzegovina (Bosnia). It utilizes the non-linear Autoregressive Distributed Lag (NARDL) method to examine cointegration and short-run dynamics by analyzing quarterly data spanning from 2010 to 2022. The findings underscore the link between MFL shocks and long-term economic growth. The study unveils the unique effects of both positive and negative MFL shocks on growth, suggesting a non-linear relationship between microfinance loans and economic growth in Bosnia. However, the study concludes that the impact of MFL on Bosnia's GDP is adverse. Short-term fluctuations in MFL show no substantial influence on Bosnian economic growth. The coefficient of the error correction model is both negative and significant indicating the stability of the long-term relationship. This implies a rapid correction, with 46.4 % of the previous quarter's imbalance rectified within the current quarter. While our results are based on a single country, they align with recent criticisms of microfinance practices. Furthermore, our study offers a novel approach as it represents the first examination of the asymmetric relationship between MFL and GDP in Bosnia, providing valuable policy recommendations.

Asymmetric nexus between economic policy uncertainty and the Indian stock market: Evidence using NARDL approach

This study examines linkages between the stock market and uncertainty in the real economy generated by unpredictability of economic policies. We investigate the asymmetric effect of economic policy uncertainty (EPU) on India’s stock market performance through the non-linear autoregressive distributed lag (NARDL) approach for the period ranging from 2003 to 2022. A sub-sample analysis of the pre-covid period is also done to confirm that EPU had an impact on the stock market even prior to the pandemic. Our findings support the existence of asymmetry in the variables as the stock prices’ response to rising and declining EPU is not identical in both sample periods. It is observed that falling EPU’s positive impact on stock prices is greater than rising EPU’s adverse impact. The study suggests that government officials and policymakers must ensure consistency in policymaking and prevent the adverse effects of EPU as it impedes the long-term development of the securities market.

The role of the tourism sector in creating direct employment in Mexico: evidence from linear and nonlinear ARDL frameworks

This paper analyzes the role of the tourism sector in creating direct employment in Mexico by measuring the output elasticity of tourism employment from both linear and nonlinear perspectives. Although using such elasticity is a common practice for calculating the impact of economic growth on employment, it has been neglected in the context of the tourism labor market. Using Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) models, this study analyzes the impact of both the quarterly indicator of tourism gross domestic product (GDP) and the multilateral real exchange rate on tourism employment from the first quarter of 2006 to the first quarter of 2021. The results of the linear models show that tourism employment is elastic to variations in tourism GDP. Conversely, the NARDL model illustrates that tourism employment is inelastic to both positive and negative changes in tourism GDP. However, the NARDL model also shows that tourism employment is resilient to the negative phases of growth in the sector, as it grows more during the expansive episodes than it is reduced during the contractive phases. Meanwhile, the models including the multilateral real exchange rate show that tourism employment positively responds to the depreciation of the Mexican peso.

The distortion in the EU feed market due to import constraints on genetically modified soy

Feed importers in some EU member states face constraints on imports of genetically modified (GM) soy, a practice that may compromise the interests of EU livestock farmers. Using the cases of Sweden and Austria, we analyzed price transmission in the soy supply chain originating from Brazil, applying an asymmetric non-linear auto-regressive distributed lag (ARDL) model to identify short-run and long-run asymmetries. The results revealed significant asymmetric effects in how positive and negative price changes are absorbed within the feed industry. Notably, increases in the cost of Brazilian soy swiftly affect the prices for EU farmers, while cost reductions fail to trigger corresponding price decreases. Consequently, stronger constraints on GM soy imports are likely to exacerbate the competitiveness challenges faced by livestock farmers, primarily due to their reliance on non-GM soy. This implies that the restrictions on GM imports need to be relaxed or that low-cost local protein alternatives need to be developed.

Pathways for China's sustainable energy transition: Examining the effects of exchange rate volatility on renewable energy investment

The relationship between exchange rate volatility (ERV) and other macroeconomic factors, including trade flows, domestic production, inflation, money demand, and economic growth, has remained a topic of a large number of studies in international finance. However, the research question that the past empirics have overlooked is whether ERV has any role in helping an emerging economy like China in its journey toward a renewable energy transition. To answer this question, this analysis intends to scrutinize the nexus between ERV and renewable energy investment (REI) in China over 1991Q1-2021Q4. Moreover, due to the asymmetric behavior of ERV, we have based our analysis on the asymmetric assumption. For analyzing the short and long-run impacts of ERV on REI in China, we used the linear autoregressive distributed lag (ARDL) and nonlinear ARDL methods. In the long term, the ARDL model predicts that stricter environmental policies and higher GDP will lead to more investment in renewable energy. As far as the nonlinear model is concerned, the long-term negative change in ERV does not affect REIs, whereas a long-term positive change in ERV reduces such investments. Likewise, unfavorable short-term exchange rate shocks encourage REI while positive short-term shocks discourage such development. Moreover, investment in renewable energy is bolstered by GDP, environmental policy strictness, and financial development, but is dampened by CO2 emissions in the short term in both models. On the basis of these results, we suggest that policymakers should consider implementing measures to stabilize exchange rates to promote investment in renewable energy.

Assessing the asymmetric influence of ICT on the tourism development: fresh insights from a tourist destination economy

ABSTRACT The United Nations’ ‘Sustainable Development Goals (SDGs)’ recommended seventeen viable strategies aimed at eradicating poverty, maintaining the quality of the natural environment, and assuring everyone's prosperity. Travel and tourism are the primary stream segments by which all three of the above-mentioned United Nations agendas may be effectively addressed. However, India's long-term vision is also in accordance with the SDGs, which place considerable attention on tourism expansion, invention, and sustainable development through the ‘information and communication technology (ICT)’ renaissance. In this milieu, considering annual data from 1990 to 2017, this research aims to examine the asymmetric linkage between tourism (no. of tourist arrivals), ICT (ratio of the population using the internet), and economic growth in India. We employed the ‘non-linear autoregressive distributed lag (NARDL)’ bounds approach to explore the asymmetric cointegration among the drivers under investigation and confirmed long-run cointegration. Results from NARDL elicited that a positive shock in the partial sum of ICT dwindles tourist arrivals, whereas a negative shock to the ICT fosters tourist visits in the long run. Furthermore, it seems that the expansion of the Indian tourist industry is positively correlated with economic growth. The single Fourier Frequency Granger causality test revealed ICT and Tourist Arrivals (TA), and GDP and TA have a feedback loop.

Capital flight and the real exchange rate: evidence from resource scarce MENA countries

ABSTRACT We analyze the determinants of capital flight in three resource scarce MENA countries namely Egypt, Morocco, and Tunisia. Our methodology involves both the linear and nonlinear autoregressive distributed lag (ARDL) cointegration approaches, with a focus on asymmetric relationships between capital flight and the real exchange rate, to distinguish the impact of real appreciation and depreciation of domestic currency on capital flight. The results based on nonlinear ARDL approach using annual data between 1977 and 2019 indicate that in Egypt, financial openness is negatively related with capital flight, while real depreciation seems to increase it in the long run. Our findings also reveal that the real GDP growth rate, institutional quality as well as inflation are important factors affecting capital flight in Morocco, whereas financial openness and the real exchange rate influence capital flight significantly in Tunisia.

Do the asymmetric effects of eco-digitalization amidst energy transition make or mar the strides toward environmental sustainability in the USA?

The present era faces adverse effects of the strides recorded in economic advancements of the prior generations thus leading the present generation to growth dilemma. Consequently, there is a conscientious consideration for the ecological effects of economic growth. To resolve the preceding issue, due consideration must be given to harmless growth of which eco-digitalization, green financing, green technology, energy transition, and regularity quality are key determinants. Despite the aforesaid importance, empirical studies advancing this nexus are scarce. Hence, this study contributes to environment empirics by providing empirical evidence for the impacts of the highlighted indicators on sustainable environment in the USA. The study explores quarterly data from 1996Q1 to 2019Q4 based on the novel non-linear autoregressive distributed lag (ARDL) model. The pretests' outcomes show that long-run nexus exists among the variables, whereas the Zivot-Andrew uncovers breakpoint years in the observations. The main findings show that eco-digitalization, green financing, green technology, and renewable energy promote sustainable environment. On the flip side, non-renewable energy and regulatory quality hinder the pathways to sustaining the environment in the USA. Robustness analyses conducted based on FMOL, DOLS, and CCR provide substantial support and validity for the main results. Furthermore, the causality nexus lends empirical support for the existence of bidirectional and unidirectional causalities in the empirical model. Policy insights that drive the paths to sustainability in the US are suggested based on the findings.

Impact of geopolitical risk on tourism demand: evidence from asymmetric NARDL approach

PurposeMany tourism academics have investigated the linkages between tourism, power and space; few have specifically addressed the profound links between tourism and geopolitics. In view of the restrictive assumptions of the linear framework used in the earlier studies, and hidden asymmetries present in the time series data. Against this backdrop, the study tries to find out how tourists may respond differently to favourable and unfavourable shocks in geopolitical risk (GPR).Design/methodology/approachIn order to capture this asymmetric nature of the problem, the study employs the non-linear autoregressive distributed lag (NARDL) model to evaluate data from 2001Q1 to 2019Q4.FindingsThe results show that both positive and negative shock to GPR does not produce results of equal magnitude. A positive shock to GPR has a more detrimental effect on foreign tourist arrivals (FTA) than a beneficial effect a negative shock produces. Besides this, the present study also looks at the effect of other macro-economic variables on FTA. An ascend in the real effective exchange rate (REER) i.e. appreciation of the domestic currency has an unfavourable impact on foreign visitor arrivals, while an increase in world gross domestic product amplify it. The results of the study are robust to alternative measures of the control variable.Practical implicationsThe study is significant for policymakers in understanding the short and long-run implications of GPR on FTA in India. The present study can assist policymakers, and destination managers to manage the external and internal risks and minimise the consequences of geopolitical threats on the Indian tourism industry. Consequently, destination managers can utilise the study's findings in calibrating their operations and designing crisis marketing strategies within the geopolitical dynamics of the Indian state.Originality/valueThe study tries to find out how tourists may exhibit distinct reactions to positive and negative disturbances in GPR. The study provides first-hand evidence of how GPR impacts tourism demand. The paper also includes the existing body of literature related to GPR factors and their effect on tourist influx, specifically in the framework of the Indian tourism sector.

Dynamics of property prices and asymmetrical impacts of economic policy uncertainty: new evidence from Indian cities

Purpose This research study aims to delve into the enduring relationship between housing property prices and economic policy uncertainty across eight major Indian cities. Design/methodology/approach Using the panel non-linear autoregressive distributed lag model, this study meticulously investigates the asymmetric impact of economic policy uncertainty on apartment and house (unit) prices in India during the period from 2000 to 2022. Findings The findings of this study indicate that economic policy uncertainty exerts a negative influence on property prices, but noteworthy asymmetry is observed, with positive changes in effect having a more pronounced impact than negative changes. This asymmetrical effect is particularly prominent in the case of unit prices. Originality/value This research reveals that long-run price trends are also influenced by factors such as interest rates, building costs and housing loans. Through a comprehensive analysis of these factors and their interplay with property prices, this research paper contributes valuable insights to the understanding of the real estate market dynamics in Indian cities.

Symmetric and Asymmetric Effects of Exchange Rate on Indonesia Stock Prices

Understanding the effect of exchange rates on stock prices is essential essential because of how they are tied to various aspects of the economy. This study examines the symmetric and asymmetric effects of exchange rate changes on stock prices in Indonesia using both auto regressive distributed lag (ARDL) and nonlinear ARDL (NARDL) techniques. To determine short run and the long run association between the study variables. This study using Indonesia monthly data collected from January 2022 to December 2022. The study discovered a long-run equilibrium for both the ARDL and NARDL models, showing a symmetric short and longrun relationship between exchange rates and stock prices. Exchange rates have a negative effect on stock prices, which lowers investor trust in the market. Even in linear and nonlinear analysis, inflation has a negative impact on stock prices over the and long terms. High inflation can reduce consumer purchasing power, which can result in a drop in sales and profitability for businesses that significantly rely on consumer spending. authorities and investors require taking consider the relationship between exchange rates and stock prices to manage foreign exchange and stock markets.

Examining the asymmetric effects of fossil fuel consumption, foreign direct investment, and globalization on ecological footprint in Mexico

AbstractThis paper investigates the asymmetric effects of fossil fuels, foreign direct investment (FDI), and globalization on the ecological footprint (EFP) in Mexico from 1975 to 2020. To this end, the Autoregressive Distributed Lag (ARDL), Nonlinear Autoregressive Distributed Lag (NARDL), and the wavelet coherence approach are conducted. Based on the outcomes of the ARDL method, economic growth and fossil fuel consumption lead to ecological degradation, while foreign direct investment improves environmental conditions. Globalization has no impact on the environment. The NARDL approach illustrates that a positive shock to fossil fuels, FDI, and globalization degrades the environment. The wavelet coherence results emphasize the adverse environmental influence of economic growth and fossil fuels. These results imply that the Mexican government should conduct its economic expansion considering the principle of sustainable development. In this context, policymakers should propagate carbon taxes and similar instruments to promote clean energy sources that can replace fossil fuels and are compatible with sustainable development policies.

Assessing the Impact of Oil Price Volatility on Food Prices in Saudi Arabia: Insights From Nonlinear Autoregressive Distributed Lags (NARDL) Analysis

Abstract This research investigates the impact of oil price fluctuations on food prices in Saudi Arabia between 1979 and 2020 using Nonlinear Autoregressive Distributed Lags (NARDL) methodology. The study employs Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests to determine the integration order of the variables and Bounds testing to confirm the existence of long run cointegration relationships between each variable. The results indicate that oil shocks influence food prices through several mechanisms. Firstly, the cost of energy increases due to the rise in oil prices, affecting the agricultural commodity market, including farm equipment, food processing, packaging, and distribution costs. Secondly, the demand for agricultural commodities to produce biofuels affects food availability and thus food prices. Thirdly, as an oil-based economy, the oil price shock affects food prices through its impact on government spending, which affects aggregate demand and liquidity. Therefore, Saudi Arabia should adopt appropriate policies to mitigate the impact of oil price shocks on food prices, including investing in renewable energy sources, diversifying its economy, and improving food production and supply chain efficiency. Additionally, implementing appropriate fiscal policies to ensure sufficient budget allocation for food support programs is crucial. However, Investing in groundwater exploration can contribute significantly to the development of Saudi agriculture and to gradually achieving food self-sufficiency.

Does Renewable Energy Transition in the USA and China Overcome Environmental Degradation?

The use of fossil energy highly contributes to the CO2 emissions. Compared to other countries, China and the USA were responsible for approximately half of the global CO2 emissions in 2022. The SDG7 agenda, which aims to preserve the use of renewable energy, has made people aware of the need to switch from fossil-based to renewable energy sources by 2030. Thus, this paper aims to analyze the implications of fossil and renewable energy consumption on environmental degradation in the USA and China. This study uses the linear and nonlinear autoregressive distributed lag (ARDL) model to examine the cointegration of the fossil and renewable energy toward the CO2 emissions from 1985 to 2021. The estimation results for USA using linear ARDL shows that fossil energy lead to higher CO2 emissions, meanwhile renewable energy reduces the CO2 emissions. Similar finding in the nonlinear ARDL, most of the models for China and the USA found significant impact of renewable energy consumption, where higher renewable energy transition contributes in lowering environmental degradation. This provide justification for policymakers in both countries to continue their efforts in renewable energy transition to archive the SDG7 agenda in 2030.

On the Asymmetry of the Nexus between Governance and Environmental Pollution

Governance has attracted the attention of researchers as a multifaceted and effective variable in the economic performance of countries during last three decades. On the other hand, with the intensification of environmental concerns of governments, the analysis of the relationship between governance and the worsening of environmental sustainability indicators, such as the volume of pollutant emissions, has also become one of the study primacies of environmental economists. The present study aimed to investigate the aforesaid relationship for a group of developing and developed countries for the period 1990 to 2020. To this end, the Nonlinear Autoregressive Distributed Lag (NARDL) model based on panel data was used, which permits examination of the existence of non-linear relationships between variables. Main results show asymmetry in the magnitude of the effects of governance indicators on carbon dioxide emissions in developed and developing countries as the coefficient of the positive shock to economic governance for developed countries (0.52) is almost twice that of developing nations (0.27). We found that economic governance enhancement has a stronger impact on reducing environmental pollution and thus protecting the environment.

Investigating Asymmetric Effects of Electronic Payment on Money Supply for India using Non-linear ARDL Model

Money supply in India is analysed using a non-linear autoregressive distributed lag (NARDL) model to see how several factors, such as electronic payments, exchange rate, interest rates and inflation, affect the money supply. The Augmented Dickey–Fuller unit root test and the Phillips–Perron unit root test are utilized to confirm that the variables are stationary. In the bounds test of the NARDL as well as Johansen–Juselius cointegration test, this study finds evidence of cointegration amongst variable used in the study. NARDL testing model is employed to investigate the dissimilar influences on variables with short- and long-run dynamics. Short-term estimates suggest that the money supply ( M1) is most responsive to positive shocks involving retail payments, the exchange rate and interest rates, but negative shocks involving card payment and prepaid payment instruments. A reduction in card payment, as well as a positive increase in retail payment, the prepaid payment instrument, the exchange rate and the interest rate, would all have major effects on M3 in short run. In addition, a long-term finding demonstrates that all of the variables have a significant influence on the money supply ( M1) in its mixed form while all of the factors, with the exception of the one involving card payments, have a considerable impact on the money supply ( M3). Wald test results confirm the existence of asymmetric influences which can have significant lessons for policymakers.

Asymmetric Exchange Rate Pass-through in India: A Non-linear ARDL Approach

This study makes an attempt to examine the exchange rate pass-through (ERPT) to domestic prices in India from 1993M4 to 2021M3. In the empirical literature, the relationship between the exchange rate and the price was found to be linear. However, in emerging economies recently the asymmetric relationship between these variables is noticed: the effect of appreciation on price is found to be negligible while the effect of depreciation is found to be significant. To study this behaviour, we have used non-linear autoregressive distributed lag (NARDL) model by employing five variables (viz., exchange rate, consumer price, output gap, money supply and oil prices). The structural break techniques are used to examine the differential effects of the pass-through. It found that exchange rate shocks do not lead to significant changes in consumer prices in the long run. In terms of policy, this means that the ERPT has insignificant consequences for monetary policy, and depreciation might pose a little threat to price stability. It is also established that oil price shocks are not one of the major determinants of inflation in the country and they do not pose serious challenges to price stability. Economic growth and monetary expansion also do not seem to pose any risks to price stability in the long run. JEL Classification: E31, E37, E52, F31

Reinvestigating the U.S. Consumption Function: A Nonlinear Autoregressive Distributed Lags Approach

Abstract This article examines the asymmetric aspect of U.S. consumption using disaggregated quarterly consumption expenditure data, including durables, nondurables, and services from 1994 to 2019. We apply a novel nonlinear autoregressive distributed lag analysis considering a regime-switching mechanism and find that U.S. consumers behave differently during economic upturns and downturns, with asymmetry existing for the consumption of durables (in the long run) and services (in both the short and long-run), but not for nondurables. Since services account for more than 40% of U.S. aggregate output, the slow adjustment toward equilibrium and the elasticity less than unity proves that services are more of a necessity than a luxury for U.S. consumers. The results indicate that the consumption of services is the primary determinant of U.S. consumer behavior, and monetary policy has a limited effect on U.S. consumption.

Exploring the impact of energy consumption on poverty in Pakistan: evidence from the asymmetric ARDL approach.

This research work contributes to the literature by examining the role of energy consumption in mitigating poverty via decomposing energy consumption into its positive and negative components, covering the period spanning from 1985 to 2017. To accomplish this objective, this study employs the nonlinear autoregressive distributed lag (NARDL) approach recently popularized by Shin et al., (2014). The NARDL approach iswell-suited to our study becuase of its capability to delineate hidden asymmetries. The empirical findings reveal the prevalence of long-run associations among the studied variables. The outcomes show that an increase (decrease) in energy consumption combats (augments) poverty in Pakistan. The empirical findings underscore that the decreasing effect of energy consumption on poverty is found to be more promising than its increasing effect, both in the long and short run. Based on the empirical outcomes, we suggest that the policymakers, and other stakeholders should consider the asymmetric or nonlinearbehavior of the studied variables for better poverty policy-making in Pakistan.