Autoregressive Distributed Lag Method Research Articles

The Use of Auto-Regressive Distributed Lag Method in Investigating The Impact of Interest Rate on Foreign Direct Investment in Yemen for the Period 1990-2018

Foreign direct investment has seen increasing interest worldwide, especially in developing economies. However, statistics have shown that Yemen received fluctuating FDI inflows during the period under study. Against this background, this research seeks to determine the relationship and impact of interest rates on FDI flows. The study also found other determinants that greatly affected FDI inflows in Yemen for the period 1990-2018. Study data collected from the World Bank and International Monetary Fund databases. It also ensured that the time series were made balanced and interconnected, and then the Auto Regressive Distributed Lag method used in the analysis. The results showed that the interest rates and inflation rate harmed FDI flows and, therefore, could not be used for policymaking purposes. The research also discovered that GDP growth and trade openness are the main determinants of foreign direct investment in Yemen. Trade openness policies should be encouraged, and GDP growth facilitated if the economy is to achieve long-term FDI flows.
 Purpose –The purpose of the paper is to discover the impact of interest rate on foreign direct investment with a combination of the exchange rate, inflation, gross domestic product, and trade openness.
 Design/methodology/approach – The paper implements the Auto Regressive Distributed Lag (ARDL)-Bounds testing approach to analyze maintaining the time series properties in terms of stationarity.
 Findings – The results indicate that there is a long-run equilibrium between the Foreign Direct Investment and the explanatory variables. Furthermore, the significant factors influencing, positively, FDI in Yemen are Growth domestic product, Exchange rate, and Trade openness. In contrast, both the Interest rate and Inflation rate have a substantial negative impact on Foreign Direct Investment.
 Practical implications – Policymakers in Yemen advised reconsidering many of the general state policies, including investment policies, financial and administrative governance, and monetary policy that focuses on maintaining an adequate interest rate and reduce the rate of inflation.
 Originality/value – As for the case of Yemen, this the first study empirically explores the impact of interest rate and the foreign direct investment using the Auto Regressive Distributed Lag method aiming for more reliable results.

Armed conflict, militarization and ecological footprint: Empirical evidence from South Asia

Environmental degradation as a consequence of military activities largely remains a neglected subject, especially in South Asia. To fill this gap, we have investigated the impact of armed conflicts and militarization on the environmental dilapidation of South Asian countries from 1984 to 2019. A second generational unit root test has been applied to check the problem of cross-sectional dependency. Westerlund panel cointegration method is used to analyze the cointegration between selected variables. Long-run and short-run estimates have been calculated using the panel autoregressive distributed lag (ARDL) method. Besides, the Granger Causality test is employed and results indicate the causality runs from armed conflict and militarization to ecological footprint. Empirical estimates also confirm that the military expenditures, internal conflict as well as external conflict have a positive impact on ecological footprint and these results are highly significant both in the long run and short run. Our study also confirms the presence of the Environmental Kuznets Curve in South Asia. South Asia is marred by the aggressive posturing bitterness as witnessed by the sour relationship that exists between Pakistan and India, the two strongest nations in the region. This animosity left them with consistent and incremental growth in defense expenditure. To achieve sustainable development in South Asia it is imperative to initiate peace talks and to impose necessary restrictions on hazardous military operations contaminating the environment.

The effect of minimum wage and inflationary pressure on youth unemployment in Nigeria

This study carried out an empirical investigation on the impact of minimum wage and inflationary pressure on youth unemployment in Nigeria from 1991 to 2019 using the Autoregressive Distributed Lag method to estimate the multiple regression model. The model captured the impact of Inflation, GDP Growth Rate, FDI, Government Expenditure, and Minimum Wage as determinants of youth unemployment in Nigeria. The results show that minimum wage exerts a significant impact on youth unemployment in the country, whereas inflation does not significantly influence youth unemployment. These results disapprove argument in the literature that supports minimum wage as an income policy to improve the welfare of workers in Nigeria because it raises the youth unemployment level in the country. Hence, the study concludes that minimum wage determination should be market-based. With this, the study recommends that the Nigerian government seek alternative measures of improving workers’ welfare and reduce youth unemployment in the country. Keywords: Minimum Wage, Inflation, Youth Unemployment

Monetary Policy and Financial Performance of Deposit Money Banks in Nigeria

This study considered the influence of monetary policy on the financial performance of deposit money banks in Nigeria. The study engaged the use of a time series data for 35 years, from the period 1984 to 2018; all deposit money banks as captured by the Central Bank of Nigeria Statistical Bulletin (2015) were considered. The effect of liquidity ratio, lending rate, loan to deposit ratio and cash reserve ratio were examined on the financial performance of deposit money banks measured by their net worth and total credits. The data was analyzed using descriptive and inferential statistics. Based on the result of stationarity test, the ordinary least square method and the Autoregressive Distributed Lag method were employed. A short run model of net worth and long run model for both the log of net worth and the log of total credits were estimated. The results revealed that the mean of net worth and total credits are 5455.27 and 79608.63 respectively. In the long run, monetary policy variables including liquidity ratio, lending rate, loans to deposit ratio and cash reserve ratio had no significant effect on the log of net worth. However in the short run, variations in the liquidity ratio, loans to deposit ratio and the cash reserve ratio for previous years had significant effect on the log of net worth in the current year. When financial performance is measured as total credits, the liquidity ratio and loans to deposit ratio had positive significant effect in the long run. The cash reserve ratio had a negative significant effect in the long run. The log of lending rate was insignificant in both the long and short run. The study concluded that monetary policy significantly explains the financial performance of deposit money banks both in the short and long run.

VERİMLİLİK YANLILIĞI HİPOTEZİNİN GELECEK 11 ÜLKESİ İÇİN İNCELENMESİ

One of the reasons of deviation from Purchasing Power Parity is the Productivity Bias Hypothesis (PBH) that is also known as Balassa-Samuelson Hypothesis which is based on Balassa (1964) and Samuelson (1964). Productivity Bias Hypothesis implies that productivity causes a real appreciation in currency of a relatively more productive country. Mechanism can be briefly summarized as follows: Productivity increase in tradable sector increases wages in this sector and due to labor mobility across sectors wages in non-tradable sectors rise. Then, prices increase and finally exchange rates rise. Due to relatively high growth rates and productivity increases emerging countries can be good samples to investigate the hypothesis. The purpose of this study is to investigate the validity of Productivity Bias Hypothesis for Next 11 countries (Bangladesh Egypt, Indonesia, Iran, South Korea, Mexico, Nigeria, Pakistan, Phillipines, Turkey and Vietnam). Autoregressive Distributed Lag method (ARDL) of cointegration is used to analyze time series data. Empirical results suggest that the hypothesis is supported in Bangladesh, Indonesia, Turkey and Vietnam for the considered period of time. The policy implications are provided as well.

Oil Prices and Terms of Trade of Saudi Arabia: An Empirical Analysis

Terms of trade is an important indicator of the welfare gains from international trade to the exporting country. Terms of trade of oil-exporting countries are hypothesized to depend primarily on oil prices. The study assesses the relation between oil prices and the terms of trade of Saudi Arabia. The study uses the Autoregressive Distributed Lag method to determine the cointegration between the country's terms of trade and oil prices for the period 2000-2018. The data for net barter terms of trade is taken from World Development Indicators and oil price is taken from Saudi Arabian Monetary Agency. The results show that oil prices and terms of trade are cointegrated and any disequilibrium between the two variables is corrected by 35% in a year. The study also reports a positive relationship between the two items, both in the short run and long run. Diagnostic tests indicate the model to be fit. The results suggest that, for a primarily oil-producing country like Saudi Arabia, the terms of trade depend on oil prices. The study fills the gap in the literature on the study of terms of trade for Saudi Arabia for the last few years, where there has been a high volatility in oil prices.

Export bias related to its long-run equilibrium in China

ABSTRACT This article investigated export bias related to its long-run equilibrium. By using the autoregressive distributed lag method, a dynamic econometric model was built to isolate export bias from its equilibrium. Using China’s dataset for 1982–2018, we found that export size deviated from its equilibrium level, and export bias accounted for a share of −22% to 35% of the equilibrium. Moreover, the results also confirmed that export size was cointegrated with the main explanatory variables, and export bias tended to fade in the long-run.

Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries.

The stability of food supply chains is crucial to the food security of people around the world. Since the beginning of 2020, this stability has been undergoing one of the most vigorous pressure tests ever due to the COVID-19 outbreak. From a mere health issue, the pandemic has turned into an economic threat to food security globally in the forms of lockdowns, economic decline, food trade restrictions, and rising food inflation. It is safe to assume that the novel health crisis has badly struck the least developed and developing economies, where people are particularly vulnerable to hunger and malnutrition. However, due to the recency of the COVID-19 problem, the impacts of macroeconomic fluctuations on food insecurity have remained scantily explored. In this study, the authors attempted to bridge this gap by revealing interactions between the food security status of people and the dynamics of COVID-19 cases, food trade, food inflation, and currency volatilities. The study was performed in the cases of 45 developing economies distributed to three groups by the level of income. The consecutive application of the autoregressive distributed lag method, Yamamoto’s causality test, and variance decomposition analysis allowed the authors to find the food insecurity effects of COVID-19 to be more perceptible in upper-middle-income economies than in the least developed countries. In the latter, food security risks attributed to the emergence of the health crisis were mainly related to economic access to adequate food supply (food inflation), whereas in higher-income developing economies, availability-sided food security risks (food trade restrictions and currency depreciation) were more prevalent. The approach presented in this paper contributes to the establishment of a methodology framework that may equip decision-makers with up-to-date estimations of health crisis effects on economic parameters of food availability and access to staples in food-insecure communities.

The Effects of Unstable Macroeconomic Indicators on Stock Price Behavior of Banking Sector in the Nigerian Stock Market

The research aimed to investigate the stock price behavior of banking sector in response to unstable macroeconomic variables in the Nigerian stock market. The research employed ex-post facto research design, and the data were subjected to Autoregressive Distributed Lag method of analysis to examine both the short and long run of the studied variables between 2009 and 2018. The findings reveal significant negative effects of interest rate and foreign reserves on the stock price behavior of the banking sector in the long run. Meanwhile, the inflation rate has a significant positive influence on stock price behavior. Then, the exchange rate is not statistically significant in influencing stock price behavior in the Nigerian stock market. It can be concluded that the stock price behavior of banking sector is influenced by foreign external reserve, interest rate, and inflation rate. It is recommended that the monetary policy rate should be reduced to decrease the cost of borrowing and enhance liquidity level in the stock market.

Asymmetric Dynamics of Oil Price and Environmental Degradation: Evidence from Pakistan

The main objective of the study is to explore asymmetric impact of oil price on environmental degradation in Pakistan over the period 1975-2018. The study employs the nonlinear autoregressive distributive lag (NARDL) method to check the asymmetric connection of oil price with carbon dioxide (CO2) emissions which represents environmental degradation along with gross capital formation, energy consumption, foreign direct investment and population. The NARDL result expresses that there is different effect of oil price as we break it into positive and negative changes, and decrease in oil price has a greater effect on environmental degradation in Pakistan. The other variables, FDI and energy consumption and population, have a positive and significant effect on CO2 emission. The study provides the policies for policymakers and government officials after uncovering the asymmetric relationship between oil and other variables with an environment that would be helpful in policymaking for Pakistan.

Exchange rate pass‐through to restaurant and hotel prices in the United States: The role of energy prices and tourism development

This study incorporates energy prices and tourism development into the standard purchasing power parity doctrine to investigate exchange rate pass‐through to restaurant and hotel prices in the United States over the period 2001:Q4 to 2017:Q4. We apply the multiple structural breaks cointegration test and flexible autoregressive distributed lag (ARDL) method. Our empirical results provide evidence that exchange rate appreciation reduces restaurant and hotel prices while an increase in energy prices and tourism development causes the prices of restaurant and hotel to rise. However, the pass‐through of exchange rate, energy prices, and tourism development is incomplete in both the long‐ and short‐run with the long‐run pass‐through having a stronger effect. Furthermore, the causality results show that restaurant and hotel prices have predictive power for exchange rate. Causality between restaurant and hotel prices and tourism development has a feedback effect. We also find that exchange rate Granger causes not only energy prices but tourism development while tourism development causes energy prices. The policy implications for these results are carefully outlined in the study.

Determinants of foreign and domestic non-listed real estate fund flows in India

PurposeReal estate forms an important part of any economy and the investment in real estate, in turn, is impacted by the macroeconomic environment of that country. The purpose of the present research is to examine macroeconomic determinants of foreign and domestic non-listed real estate fund (NREF) flows and to examine whether they are similar or different for an emerging economy like India.Design/methodology/approachThe long and short-run cointegration between the time-series variables is estimated using the autoregressive distributed lag (ARDL) bounds test and error correction model (ECM) using quarterly data across the 2005–2017 period. ARDL is a suitable method for short time-series data.FindingsThe empirical results indicate that domestic NREF flows are positively and significantly impacted by real GDP and performance of listed real estate stocks (i.e. BSE realty index). Whereas, foreign NREF flows are positively and significantly impacted by the exchange rate, performance of listed real estate stocks and domestic NREF flows.Practical implicationsThe empirical results have significant implications for academicians, policy makers and real estate market practitioners. In the context of these results, some interesting insights are gained that would help in the implementation of the policies aimed toward increasing the fund flows in the real estate sector, which in turn would have a significant trickle-down effect on the Indian economy.Originality/valueThe existing literature looks at macroeconomic and other drivers of foreign investment in international real estate investments. However, there are very few studies on the determinants of domestic real estate investment flows and on determinants of NREFs' investment flows; particularly in emerging markets. The present study, in contrast, evaluates simultaneously the macroeconomic determinants of the domestic and foreign NREFs' investment flows in India. The ARDL and ECM method used has been applied for the first time to the study of NREFs.

Eco-innovation and energy productivity: New determinants of renewable energy consumption

This study provides new empirical evidence on the determinants of renewable energy consumption in the case of OECD economies over the period from 1990 to 2017. To examine the long run relationship among variables of renewable energy consumption and its determinants, this study uses the Durbin Hausman group mean cointegration test. The long-run and short-run coefficients are estimated via the cross-sectional Autoregressive Distributive Lag (CS-ARDL) method. The significant cointegration vector confirms the long-run equilibrium among the variables presented in the model. The results show that income, human capital, energy productivity, energy prices, and eco-innovation are important factors in explaining renewable energy consumption. This study adopts the Augmented Mean Group (AMG) method to check the robustness of the model. The results are found to be consistent with the estimates of the cross-sectional Autoregressive Distributive Lag Model method. To offer viable solutions to environmental problems and to achieve the targets set in the Paris Climate Agreement, policies and strategies should be devised to increase the share of renewable energy in the overall energy mix.

Do fluctuations in crude oil prices have symmetric or asymmetric effects on the real exchange rate? Empirical evidence from Indonesia

AbstractCurrent research on the oil price impacts on exchange rates typically relies on the assumption that fluctuations in crude oil prices have symmetric impacts on a country's real exchange rate. Thus, the contribution of the paper is to use the non‐linear autoregressive distributed lag (ARDL) method of Shin, Yu, and Greenwood‐Nimmo (2014) and examine whether crude oil prices are asymmetrically passed on to the real exchange rate in the case of Indonesia. We uncover that oil price changes indeed asymmetrically affect the Indonesian rupiah in both the long and short run; i.e., the movement in the Indonesian rupiah appears to be more responsive to rising oil prices than to declining oil prices.

Dynamic relationship among agriculture-energy-forestry and carbon dioxide (CO2) emissions: empirical evidence from China.

This study aims to explore the dynamic association among crop production, livestock production, power consumption in agriculture, forest area, and carbon dioxide (CO2) emissions. Based on the annual data of China, spanning the period 1990 to 2016, the study applied the auto-regressive distributed lag (ARDL) bounds testing approach. In addition, the fully modified ordinary least squares (FMOLS) canonical cointegration regression (CCR) and the Granger causality tests are employed to check the robustness of the ARDL estimations. The ARDL-bounds testing approach indicated that all variables share a long-run connection. The long- and short-run ARDL estimations confirmed that crop production, as well as livestock production, has a significant positive effect on CO2 emissions in both cases. However, power consumption in agriculture and forest area has a negative effect on it, indicating that both variables reduce CO2 emissions in the long and short run. These results stood robust under various regression estimators and confirmed the findings of the ARDL method. Additionally, the results of the causality approach specified that a unidirectional causality is running from crop production, power consumption in agriculture, and forest area to CO2 emissions. The causality between livestock production and CO2 emissions is bidirectional. Therefore, the directions of this connection also validate the outcomes under various techniques used for robustness. These findings suggest that the government must reconsider its policies related to agricultural and livestock production and adopt environment-friendly practices in the agriculture sector that may reduce the carbon footprints in the long run.

Symmetric and asymmetric effect of energy consumption and CO2 intensity on environmental quality: using nonlinear and asymmetric approach.

This paper investigates the asymmetric impact of energy consumption and carbon dioxide (CO2) intensity on the environmental quality in Russia. The ecological footprint (a proxy for environmental quality) was used as a dependent variable, while independent variables include energy consumption, CO2 intensity, and gross fixed capital formation as a proxy of capital for time series data spanning from 1992 to 2016. To examine the asymmetric cointegration between the selected variables, the nonlinear autoregressive distributed lag (NARDL) method was used. The structural break unit root and BDS tests were used to check data stationarity and nonlinearity, respectively. Besides, the asymmetric causality test in Gauss software was employed to check the causal relationship among the variables. Among the considered variables, the asymmetric cointegration was found. A significant unidirectional symmetric causality was found running from energy consumption to ecological footprint (Wald test = 3.956*) and from ecological footprint to capital (Wald test = 10.115**), while asymmetrically, ecological footprint granger cause energy consumption (Wald test = 6.054**) and capital (Wald test = 6.739**) respectively. On the contrary, a neutral effect was found between environmental quality and CO2 intensity. From these findings, environmental policies are also discussed. Specifically, policymakers should support modern, controlled emission technologies, including nuclear and renewable energy sources and green portfolio investment. Graphical abstract.

FDI and environmental degradation: the role of political institutions in South Asian countries

This study examines the impact of foreign direct investment (FDI) on environmental degradation by keeping in view the role of institutional quality (IQ) in the South Asian region. Second-generational unit root test is used to address the issue of cross-sectional dependency. Mixed order of integration enabled us to use panel autoregressive distributed lag (ARDL) method to investigate short-run and long-run association. Moreover, this study also employs Granger causality test to explore causalities among the selected variables. Empirical results reveal that FDI has a positive and statistically significant effect on environmental degradation. Institutional quality is measured as rule of law has insignificant impact on ecological footprint both in short run as well as long run. However, government stability decreases environmental degradation while corruption enhances environmental hazards tremendously. This study also supports environmental Kuznets curve (EKC) for the South Asian countries. This study emphasized the role of political institutions in environmental degradation. South Asian countries must focus on the implementation of environmental laws and regulations by improving the quality of institutions to achieve the goal of sustainable development.

Do oil price changes really matter to the trade balance? Evidence from Korea‐ASEAN commodity trade data

AbstractThe contribution of this article is to assess the effect of oil prices have on the trade balance in the framework of bilateral commodity trade data between Korea and each of the four ASEAN member countries—Indonesia, Malaysia, Singapore, and Thailand. To examine this subject thoroughly, we first assume the effects of oil price changes to be symmetric and apply the linear autoregressive distributed lag (ARDL) method to the subject. We find that the price of crude oil indeed has an important role in affecting Korea's trade balance with those four ASEAN economies in both the long‐ and short‐run. We then separate oil price hikes from oil price plunges and implement the nonlinear ARDL method to reveal that there is evidence that changes in oil prices appear to have asymmetric effects on the trade balance for certain products in the long‐ and short‐run.

Education and the Challenge of Poverty Alleviation in Nigeria

Using Vector Autoregressive and Autoregressive Distributed Lag methods to examine the impact of education on poverty level and the interactive effect of education and economic growth on poverty level in Nigeria between 1985 and 2016, our results show that education promotes poverty level, instead of reducing it. We found significant cointegrating relationship among poverty, economic growth, education, employment rate, population growth rate, real physical capital formation, education level and real GDP. In the short-run, employment rate reduces poverty level, population growth rate increases poverty level both in the short and long-run. The results of interactive effect of economic growth and education on poverty growth show that jointly economic growth and education reduce poverty, although the results are not statistically significant. This shows that they have minimal impact on poverty level in Nigeria. Our findings may not be surprising, given the current slow-down in Nigeria educational system and the wide gap between the few rich and the larger poor. The study suggests improvement in Nigeria educational system so as promote employment and curb rising poverty level.

A new look at the crude oil prices and economic growth nexus: asymmetric evidence from Alaska

The existing research on the oil price-growth nexus in oil-exporting regions typically assumes that the oil price impacts are symmetric. In this article, therefore, we attempt to make an incremental contribution to the literature by empirically studying whether or not oil price changes have asymmetric impacts on economic growth in the case of an oil-exporting region, specifically Alaska. After applying the nonlinear autoregressive distributed lag (NARDL) method to quarterly data between 1998: Q1 and 2017: Q2, we uncover that oil price changes indeed asymmetrically affect Alaska’s economic growth in both the short and long run.