Autoregressive Distributed Lag Procedure Research Articles

The Price and Income Elasticity of Demand for Natural Gas Consumption in Saudi Arabia

Natural gas consumption in Saudi Arabia (KSA) has grown at an annual rate of approximately 7% as a result of population growth and other economic and non-economic factors. This study aims to estimate the short- and long-run price and income elasticities of natural gas demand in Saudi Arabia using time series data from 1990 to 2020, applying the Autoregressive Distributed lag Procedure (ARDL). Employ an Error-correction model to obtain estimates of adjustment speeds with long and short-run elasticities. The elasticity of demand for natural gas was calculated by including population growth as a control variable. The short-run dynamics evaluated indicate that the speed of adjustment is 70% annually, the long-run income and the price elasticities are 0.0002 and -2.09 respectively. The short-run income and price elasticities are 0.0002, -1.17 respectively. This means that price changes have a greater impact on natural gas demand than changes in income in the short and long run. Population growth has contributed to the increase in natural gas consumption in Saudi Arabia in the short and long run. In general, based on the results, the trend of Saudi Arabia to increase the consumption of natural gas needs to maintain low prices, due to the high price elasticity of demand.

Autoregressive Distributed Lag (ARDL) Analysis of Foreign Portfolio Investments Determination in Nigeria

This study investigates the key macroeconomic variables determining foreign portfolio inflows (FPI) to Nigeria using the autoregressive distributed lag procedure that includes the bounds test of cointegration and error correction mechanism applied against time-series Nigerian data from 1986 through 2019. The results reveal the existence of long-run equilibrium relationship between FPI and exchange rate (EXR), inflation (INF), interest rate (INT), real GDP, and Tax (TXR). Short-run errors are adjusted at a speed of 77.87% per annum, in the long-run. Causality is found to jointly-flow from the explanatory variables to FPI inflows. In all the model estimations - autoregressive, short- and long-runs, exchange rate exerted negative and significant effect on FPIR. Inflation and tax significantly affected FPI inflows to Nigeria. Growth in real GDP and interest rate positively influenced FPIR, but not significantly. The results indicate that the major determinants of FPI inflows are exchange rates, inflation, and tax.

Non-Linear Effect of Government Debt on Public Expenditure in Nigeria: Insight from Bootstrap ARDL Procedure

This study employs the bootstrap autoregressive distributed lag (ARDL) approach alongside the dynamic ARDL simulations technique to investigate the non-linear effect of public debt on public expenditure in Nigeria during the 1981–2020 period. The result of the bootstrap bounds test illustrates the presence of a long-term relationship between public expenditure and public debt (along with oil rents, output growth and urbanisation). Further, the estimation results indicate that the effect of public debt on public expenditure is non-linear. In particular, public expenditure increases at early stages of rising public debt but declines at latter phases when public debt grows beyond specific threshold. This empirical outcome is further validated by the dynamic ARDL simulations approach which shows a significant decline in predicted public expenditure after short-term expansion due to counterfactual shock in public debt. Thus, policies which diversify public revenue from oil production and a reversal of the rising trend in public debt are recommended to avert the adverse welfare implications of declining public expenditure.

Agriculture, globalization, and ecological footprint: the role of agriculture beyond the tipping point in the Philippines.

This study is hinged on analyzing factors such as agriculture and globalization (de jure trade and financial) that threaten a sustainable environment using two proxies of ecological footprint: carbon and noncarbon ecological footprint in the Philippines while controlling for the influence of fossil to GDP, economic growth, urban population, and financial development using the autoregressive distributed lag (ARDL) framework. The result provides evidence of long-run stable state among the variables. The result validates inverted U-shaped pattern of EKC involving relationship between agricultural development and ecological footprint for the Philippines indicating that initially, ecological footprint increases as the agriculture develops and then declines as the agriculture matures to generate efficiency and low carbon. In addition, this study explores elasticities of the variables using ARDL, FMOLS, DOLS, and CCR procedure and found that de jure financial globalization exerts positive influence on ecological footprint in the long run. De jure trade globalization is found to be negative and significant in the long run. It is also found that agricultural level operates below the threshold level required to maximize the growth benefits of agricultural system towards mitigating environmental sustainability. Further empirical result shows a positive relationship between economic growth, fossil fuel, urban-population growth, and ecological footprint, and negative insignificant relationship between credit to private sector and ecological footprint. The government should optimize the use of agricultural land through well-articulated economic integration strategy fashioned to pave way for cleaner and low-carbon technologies sources like solar, geothermal, biomass, biogas, tidal power, photovoltaic, and wind energy in the agricultural production to avoid further deterioration of the environment.

Effect of exchange rate volatility on Rwandan coffee price and export volumes

The main strategy of Rwanda for having a steady growth in coffee export value and revenues was increased sales of speciality coffee. However, global coffee prices are often volatile and Rwanda has little control over the fluctuating global prices. This paper analysed the effect of exchange rate volatility on the price and exports of Rwanda coffee. In order to respond to this question, the monthly time series data on bilateral Rwanda coffee exports and real effective exchange rates from January 2001 to December 2016 were analysed. The cointegration methods and error correction model using the autoregressive distributed lag procedure andGlosten, Jagannathan, and Runkle-Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH) model were used to analyse the data. The findings showed that the exchange rate volatility resulted in an increase in Rwandan coffee export price in the long run by 1.5% and a decrease in the short run by 0.2%. The findings also showed that the exchange rate volatility affected coffee export volumes in the long run and the short run by 44.4% and 3.8%, respectively. The real income in importing countries increased coffee prices in the long run by 3.0% and coffee export volumes in the long run and the short run by 26.9% and 38.5%, respectively. A review of monetary policy to address the issue of volatility and hedging system adoption in the Rwanda coffee sector should be done in order to stabilize the exchange rate and to consequently avoid its bad effects on coffee price and export volumes.

Food and healthcare accessibility during COVID-19 pandemic

The pervasive effects of the novel coronavirus (COVID-19) have put the world to test. Its effects permeate all facets of life including healthcare services and food supplies. However, most empirical studies failed to investigate its effects on the prices of food and healthcare services, which by all standards, are essential commodities. On this background, this study evaluates the impact of COVID-19 reported cases and lockdown stringency measures on the food and healthcare prices in the six (6) worst-affected countries. For empirical purposes, daily prices of food and healthcare services between 22nd January and 31st December 2020 were regressed against daily cases of COVID-19 and lockdown stringency measures within the dynamic autoregressive distributed lag procedure. Empirical evidences reveal that prices of healthcare and food are cointegrated with COVID-19 cases and lockdown measures in all the selected countries except Italy. Equally, healthcare and food prices reinforced itself in the long-run in the US, the UK and France. Furthermore, COVID-19 cases lead to significant increases in food and healthcare prices in the US, whereas, food and healthcare prices in France and UK declined significantly as COVID-19 cases mount. Conversely, food and healthcare prices declined significantly in the US and soar in France and the UK in reactions to COVID-19 new cases. Likewise, government stringency measures and containment health measures contributed significantly to healthcare and food price hike in the US and France respectively. Meanwhile, healthcare and food prices in the other selected countries remained unaffected even as the pandemic ravages. Following this empirical discoveries, relevant policy guidelines have been communicated.

The Influence of Hydropower and Coal Consumption on Greenhouse Gas Emissions: A Comparison between China and India

This study mainly aims to investigate carbon status according to the Pollution Haven Hypothesis (PHH) in developing countries such as India and China based on annual time series data from 1980 to 2016. The recently developed bootstrap autoregressive distributed lag procedure is applied to observe the long-run effect of FDI, hydropower, and coal-based fossil fuel consumption on three repressive measures of carbon emissions. The empirical results of the analysis show that hydropower and coal consumption lead to an upsurge in carbon emissions and the size of the carbon footprint in China. Similarly, Chinese FDI increases the carbon footprint. Moreover, Indian FDI and coal consumption accelerate carbon emissions while hydropower has no impact on environmental degradation. These results suggest that the PHH exists in China and India and that the validity of the PHH varies according to differing carbon indicators. Based on the empirical results, effective policy practices can be implemented by replacing coal and hydropower with more effective renewable energy sources and allowing foreign investors to pursue environmental concerns in the fight against environmental degradation.

Climate change impacts on cereal crops production in Pakistan

PurposeThis paper aims to examine the effects of CO2emissions, energy consumption, cultivated area and the labour force on the production of cereal crops in Pakistan from the period 1971-2014.Design/methodology/approachThe study used the Johansen cointegration test, the autoregressive distributed lag (ARDL) approach and Granger causality test to estimate the long-run cointegration and direction of the relationship between the dependent and independent variables.FindingsThe outcomes of the Johansen cointegration test confirmed the existence of a long-term cointegrating relationship between the production of cereal crops, CO2emissions, energy consumption, cultivated area and the labour force. The results of the long-run coefficients of CO2emissions, energy consumption, cultivated area and labour force have a positive impact on cereal crops production. The long-run relationships reveal that a 1 per cent increase in CO2emissions, energy consumption, cultivated area and labour force will increase cereal crops production by 0.20, 0.11, 0.56 and 0.74 per cent, respectively. Moreover, the findings show that there is a bidirectional causality running from CO2emissions and cultivated area to cereal crops production. Moreover, there is a unidirectional causality running from energy consumption to cereal crops production.Originality/valueThe present study also fills the literature gap for applying the ARDL procedure to examine this relevant issue for Pakistan.

Some dynamic macroeconomic perspectives for India’s economic growth

PurposeThe purpose of this paper is to study impacts of changes in crude oil price, money supply, fiscal deficit and effective exchange rate on India’s economic growth (expressing all variables in real term).Design/methodology/approachFirst, a simple macroeconomic model is formulated to this effect. Next, linear autoregressive distributed lag procedure and vector error-correction model are applied for growth empirics. Annual data are used from 1977 through 2015.FindingsRises in real crude oil price and monetized real fiscal deficits have negative short-run and long-run effects on real economic growth. Increase in real money supply and real effective exchange rate appreciation helps promote real economic growth in both short run and long run. In all cases, there is evidence of net interactive positive feedback effects among the variables in the short run. Real effective exchange rate appreciation dampens exports, but it is helpful to imports of capital goods and crude oil that contribute to economic growth. So, the net effect on the economy may be conjecturally positive.Originality/valueTo the best of the authors’ knowledge, this paper is unique because of the formulation of macro-economic model pertaining to the topic and its subsequent empirical verification. Moreover, this paper seems more comprehensive than some other studies, cited in the literature review.

Exploring the Effect of Energy Consumption on the Economic Growth of Albania

Albania is one of the most energy-resource abundant country, however faced with high domestic electricity demand. Moreover, the country is the largest crude oil producer in Europe. In this study, we investigate the following questions: (i) Is there a long-run association between energy consumption and output in Albania? (ii) What is the magnitude of energy effect in the short- and long-run on output in Albania? (iii) Which of the four hypotheses on the energy-growth nexus describes most appropriately the energy-growth nexus in the case of Albania? (iv) How do the results compare with those of earlier studies? Thus, the study examines the effect of energy consumption on the economic growth of Albania over the periods 1980 to 2014 using a Cobb-Douglas production function whilst controlling for multiple structural breaks. The short-run and long-run estimations are carried out using the autoregressive distributed lag (ARDL) bounds procedure. Causality is examined using the vector error correction method. Also, we conduct consistency and robustness checks using other regression methods. The results from the ARDL procedure indicate that the elasticity of income with respect to energy is 0.36. This implies that ceteris paribus, a 1% increase in energy consumption will increase output by 0.36%. The causality result supports the conservation hypothesis which implies that economic growth drives energy consumption, which is consistent with some of the earlier studies.

Exploring the Nexus among Environmental Pollution, Economic Growth Energy Use and Foreign Direct Investment in Sub Sahara Africa

This research seeks to enhance the current literature by exploring the nexus among environmental contamination, economic growth, energy use and foreign direct investment in 6 Selected Sub-Saharan-African-nations for a time of 34 years (1980-2014). By applying, panel unit root (CADF and CIPS, Cross-sectional independence test), panel cointegration (Pedroni and Kao cointegration test, Panel PP, Panel ADF), Hausman poolability test and an auto-regressive distributed lag procedure in view of the pooled mean group estimation (ARDL/PMG), experimental findings discloses that alluding to the related probability values, the null hypothesis of cross-sectional independence for all variables is rejected because they are not stationary at levels but rather stationary at their first difference. The variables are altogether integrated at the same order I(1). Findings revealed that there is a confirmation of a bi-directional causality between energy use and CO2 in the short-run as well as one-way causality running from energy use to CO2 in the long run. There is additionally a significant positive outcome and uni-directional causality from CO2 to foreign direct investment in the long-run yet no causal relationship in the short-run. An increase in energy use by 1% causes an increase in CO2 by 49%. An increase in economic growth by 1% causes an increment in CO2 by 16% and an increase in economic growth squared by 1% diminish CO2 by 46%. The positive and negative impact of economic growth and its square approve the EKC theory. To guarantee sustainable economic development Goal, more strict laws like sequestration ought to be worked out, use of sustainable power source ought to be stressed. GDP ought to be multiplied to diminish CO2 by the utilization of eco-technology for instance carbon capturing, to save lives and also to maintain a green environment.

RETRACTED ARTICLE: Investigating the nexus among environmental pollution, economic growth, energy use, and foreign direct investment in 6 selected sub-Saharan African countries

This research seeks to enhance the current literature by exploring the nexus among environmental contamination, economic growth, energy use, and foreign direct investment in 6 selected sub-Saharan African nations for a time of 34 years (1980–2014). By applying panel unit root (CADF and CIPS, cross-sectional independence test), panel cointegration (Pedroni and Kao cointegration test, panel PP, panel ADF), Hausman poolability test, and an auto-regressive distributed lag procedure in view of the pooled mean group estimation (ARDL/PMG), experimental findings disclose that alluding to the related probability values, the null hypothesis of cross-sectional independence for all variables is rejected because they are not stationary at levels but rather stationary at their first difference. The variables are altogether integrated at the same order I(1). Findings revealed that there is a confirmation of a bidirectional causality between energy use and CO2 in the short-run and one-way causality running from energy use to CO2 in the long run. There is additionally a significant positive outcome and unidirectional causality from CO2 to foreign direct investment in the long run yet no causal relationship in the short run. An increase in energy use by 1% causes an increase in CO2 by 49%. An increase in economic growth by 1% causes an increment in CO2 by 16% and an increase in economic growth squared by 1% diminishes CO2 by 46%. The positive and negative impacts of economic growth and its square approve the EKC theory. To guarantee sustainable economic development goal, more strict laws like sequestration ought to be worked out, use of sustainable power source ought to be stressed, and GDP ought to be multiplied to diminish CO2 by the utilization of eco-technology for instance carbon capturing, to save lives and also to maintain a green environment.

Exploring the effect of ICT and tourism on economic growth: a study of Israel

In this paper, we explore the impact of information and communications technology (ICT) and tourism on per worker output over the period 1960–2016 by using an augmented Solow (Quart J Econ 70(1): 65–94, 1956) framework estimated through the autoregressive distributed lag procedure for cointegration (Pesaran et al. in J Appl Econ 16(3):289–326, 2001). The results show that mobile cellular subscriptions (measure of ICT pervasiveness) and visitor arrivals as a percent of workers (measure of tourism) are cointegrated and positive, however, only ICT is statistically significant in the long-run. The long-run elasticity coefficient of ICT and tourism is 0.03 and 0.05, respectively. We note a unidirectional causality from ICT to output per worker, from tourism to output per worker, from capital per worker to tourism, and from ICT to tourism. From the results, we emphasize that focusing on technology advancement and tourism expansion will provide the necessary support for economic growth in the country.

The linear and non-linear relationship between of tourism demand and output per worker: A study of Sri Lanka

Linear and non-linear long-run association between tourism and economic growth is examined using the autoregressive distributed lag procedure with Sri Lanka as a reference country over the sample period 1978–2014. Linear estimation results indicate that a 1% increase in tourism receipts result in an increase in the output per worker by 0.10% in the long run. The net effect in the short run is marginally negative and generally mixed. Non-linear relationship explains the effectiveness of the tourism industry depends strongly on public infrastructure which is subject to congestion like the public transport, airports, road system or telecommunications. A long-run U-shape relationship is detected with the minimum necessary tourism receipts of 1.26% of GDP. The causality results indicate that higher tourism receipts causes growth. The method applied here can be used to examine other countries in the similar domain.

Price linkages between the GCC stock markets: a bounds test using an Auto Regressive-Distributed Lag model

This paper examined the linkages between the equity markets in the Gulf Cooperation Council's (GCC) region. Specifically, we applied a bounded test using an Auto Regressive–Distributed Lag (ARDL) model to determine if the markets are co–integrated. In contrast to traditional co–integration analysis, the ARDL procedure does not require the prior determination of the order of integration of the variables. The co–integration tests showed that the GCC markets are segmented. However, the subset of the markets comprising the oil and gas economies of Saudi Arabia, Kuwait and Qatar, along with Oman and Dubai share a common trend.

Augmented Quantity Theory of Money and Bangladesh Taka – U.S. Dollar Exchange Rate Dynamics

This paper studies the dynamics of the Taka-U.S.Dollar exchange rate for Bangladesh by augmenting the Quantity Theory of Money. The standard cointegration methodology (Engle and Granger, 1987) is employed in addition to the ARDL (Autoregressive Distributed Lag) procedure. The ADF and KPSS tests reveal data nonstationarity, but with different orders of integration. As a result, the ARDL procedure is invoked following (Peseran et al., 2001) to search for cointegrating relationship among the variables. On the evidence of cointegration, the vector error- correction model (VECM) is estimated. The negative sign of the coefficient of the error-correction term and its statistical significance in terms of the associated t –value confirm unidirectional causal flow from broad money supply and real GDP to Taka-U.S.Dollar exchange rate and long-run convergence with short–run interactive feedback effects. Furthermore, impulse response analyses are performed for additional visual insights.

Trade-GDP Nexus in Iran: An Application of the Autoregressive Distributed Lag (ARDL) Model

This study employed annual time series data (1960- 2003) and unit root tests with multiple breaks to determine the most likely times of struct ural breaks in major factors impacting on the trade - GDP nexus in Iran We found, inter alia , that the endogenously determined structural break s coincided with important events in the Iranian economy, inclu ding the 1979 Islamic revolution and the outbreak of the Iraq-Iran war in 1980. By applying the Lumsd aine and Papell (1997) approach, the stationarity of the variable under investigation was examined an d in the presence of structural breaks, we found that the null hypothesis of unit root could be reje cted for all of the variables under analysis except one. Under such circumstances, applying the ARDL procedure was the best way of determining long run relationships. For this reason, the error correctio n version of the autoregressive distributed lag procedure (ARDL) was then employed to specify the short and long-term determinants of economic growth in the presence of structural breaks. The r esults showed that while the effects of gross capit al formation and oil exports were important for the ex pansion of the Iranian GDP over the sample period, non-oil exports and human capital were generally le ss pivotal. It was also found that the speed of adjustment in the estimated models is relatively hi gh and had the expected significant and negative sign. JEL classification numbers: C12, C22, C52.