scholarly journals Impact of FDI inflow, crude oil prices, and economic growth on CO2 emission in Tunisia: Symmetric and asymmetric analysis through ARDL and NARDL approach

2021 ◽  
Vol 12 (1) ◽  
pp. 1-13
Author(s):  
Tarek Ghazouani
Keyword(s):  
Economic Growth ◽  
Crude Oil ◽  
Carbon Emissions ◽  
Co2 Emission ◽  
Oil Prices ◽  
Oil Price ◽  
Crude Oil Price ◽  
Fdi Inflows ◽  
Crude Oil Prices ◽  
Long Run

This study explores the symmetric and asymmetric impact of real GDP per capita, FDI inflow, and crude oil price on CO2 emission in Tunisia for the 1972–2016 period. Using the cointegration tests, namely ARDL and NARDL bound test, the results show that the variables are associated in a long run relationship. Long run estimates from both approach confirms the validity of ECK hypothesis for Tunisia. Symmetric analysis reveals that economic growth and the price of crude oil adversely affect the environment, in contrast to FDI inflows that reduce CO2 emissions in the long run. Whereas the asymmetric analysis show that increase in crude oil price harm the environment and decrease in crude oil price have positive repercussions on the environment. The causality analysis suggests that a bilateral link exists between economic growth and carbon emissions and a one-way causality ranges from FDI inflows and crude oil prices to carbon emissions. Thus, some policy recommendations have been formulated to help Tunisia reduce carbon emissions and support economic development.

scholarly journals An ARDL Approach on Crude Oil Price and Macroeconomic Variables

2019 ◽  
Vol 4 (1) ◽  
pp. 68-73
Author(s):  
Seuk Yen Phoong ◽  
Seuk Wai Phoong
Keyword(s):  
Economic Growth ◽  
Crude Oil ◽  
Unemployment Rate ◽  
Positive Relationship ◽  
Oil Prices ◽  
Oil Price ◽  
Crude Oil Price ◽  
Macroeconomic Variables ◽  
Crude Oil Prices ◽  
Ardl Approach

Objective - The removal of fuel subsidies by the Malaysian government in 2014 has been implement with the managed float system for fuel prices. Methodology/Technique - This study investigates the impact of the managed floating system of crude oil prices on the Malaysian economy using ARDL approach by looking at macroeconomic variables such as inflation, economic growth and unemployment rates. Findings - The results show that all of the variables have short lived relationship with oil prices whereby inflation and economic growth are positively related to oil prices. However, unemployment rate has a negative relationship with the changes of WTI crude oil prices. Novelty - The major input in the economy of Malaysia contributes to a positive relationship between inflation and oil prices, whilst the contribution of Malaysia being an oil-producing country results in the positive relationship of economic growth and oil price. Likewise, as oil prices are high, the increase in demand results in increase in job opportunities. Lastly, the correlation test shows that inflation and economic growth have a high positive correlation while unemployment rate has a low negative correlation with oil price. Type of Paper: Empirical. Keywords: ARDL; Crude Oil Price; GDP; Inflation; Unemployment. JEL Classification: E10, E30, E39. DOI: https://doi.org/10.35609/jber.2019.4.1(8)

scholarly journals Effects of International Crude Oil Prices on Energy Consumption in China

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3891 ◽  
Author(s):  
Gaolu Zou ◽  
Kwong Wing Chau
Keyword(s):  
Energy Consumption ◽  
Crude Oil ◽  
Price Elasticity ◽  
Oil Prices ◽  
Oil Price ◽  
Crude Oil Price ◽  
The Real ◽  
Crude Oil Prices ◽  
Long Run ◽  
Oil Demand

This study aims to test the effects of changes in international crude oil prices on changes in crude oil and hydropower use from 1965 to 2016. We suggest a cointegration relationship between the consumption of coal, crude oil, and hydropower and the real crude oil price. The real price is weakly exogenous for the long-run relationship and has impacted energy consumption accordingly. The long-run crude oil price elasticity of oil use is 0.460. Our estimate suggests a positive oil price–oil use relationship in China, which is dramatically different from many previous studies but is consistent with a few past studies. The growth in external oil prices may lead to a long-run increase in hydropower use in China, with a long-run price elasticity of 0.242. The long-run crude oil price elasticity of coal use is −0.930. Hence, increased oil and hydropower use could make up the energy supply–demand gap left over by the decreased coal use. Strictly planned domestic fuel prices and rapidly growing family incomes should diminish the negative effect of external oil prices on domestic crude oil demand. In the long run, given a strictly managed energy price, the growth in external oil prices is not likely to noticeably restrain the domestic oil demand or lead to a dramatic increase in coal use. We suggest that the large-scale development and utilization of hydropower may be inappropriate. Coal utilization policies must be reviewed. The appropriate increase in clean coal consumption could reduce the consumption of crude oil and hydropower; meanwhile, carbon emissions will not increase.

Forecasting Crude Oil price using Artificial Neural Network model

2021 ◽  
pp. 321-326
Author(s):  
Sivaprakash J. ◽  
Manu K. S.
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Crude Oil ◽  
Back Propagation ◽  
Oil Prices ◽  
Oil Price ◽  
Back Propagation Algorithm ◽  
Crude Oil Price ◽  
Propagation Algorithm ◽  
Crude Oil Prices

In the advanced global economy, crude oil is a commodity that plays a major role in every economy. As Crude oil is highly traded commodity it is essential for the investors, analysts, economists to forecast the future spot price of the crude oil appropriately. In the last year the crude oil faced a historic fall during the pandemic and reached all time low, but will this situation last? There was analysis such as fundamental analysis, technical analysis and time series analyses which were carried out for predicting the movement of the oil prices but the accuracy in such prediction is still a question. Thus, it is necessary to identify better methods to forecast the crude oil prices. This study is an empirical study to forecast crude oil prices using the neural networks. This study consists of 13 input variables with one target variable. The data are divided in the ratio 70:30. The 70% data is used for training the network and 30% is used for testing. The feed forward and back propagation algorithm are used to predict the crude oil price. The neural network proved to be efficient in forecasting in the modern era. A simple neural network performs better than the time series models. The study found that back propagation algorithm performs better while predicting the crude oil price. Hence, ANN can be used by the investors, forecasters and for future researchers.

The optimal thermal causal path analysis on the relationship between international crude oil price and stock market

Kybernetes ◽  
2018 ◽  
Vol 47 (6) ◽  
pp. 1242-1261 ◽  
Author(s):  
Can Zhong Yao ◽  
Peng Cheng Kuang ◽  
Ji Nan Lin
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Prices ◽  
Oil Price ◽  
Chinese Stock Market ◽  
Crude Oil Price ◽  
Content Type ◽  
Crude Oil Prices ◽  
Causal Path

Purpose The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets. Design/methodology/approach The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method. Findings The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices. Originality/value China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

scholarly journals Relationship between International Crude Oil Price and Indian Stock Market (NSE)

2011 ◽  
pp. 63-73
Author(s):  
Rajendra Mahunta
Keyword(s):  
Crude Oil ◽  
Global Economy ◽  
Stock Exchange ◽  
Oil Prices ◽  
Oil Price ◽  
Raw Material ◽  
Crude Oil Price ◽  
New Era ◽  
Crude Oil Prices

In this new era of economic growth, the exceptional increase in the crude oil prices is one of the significant developments that affect the global economy. Crude oil is an important raw material used for manufacturing sectors, so that increase in the price of oil is bound to warn the economy with inflationary inclination. The study examine the long-term relationships between CNX NIFTY FIFTY index of National Stock Exchange and crude price by using various econometric test. The surge in crude oil prices during recent years has generated a lot of interest in the relationship between oil price and equity markets. The study covers the period between 01.01.2010 and 31.12.2014 and was performed with data consisting of 1245 days. The empirical results show there was a cointegrated long-term relationship between CNX index and crude price. Granger causality results reveal that there is unidirectional causality exists and crude oil price causes NSE (CNX) but NSE (CNX) does not cause oil price.

scholarly journals Test for asymmetry on the ex-pump price of premium gasoline in Ghana, Kenya, and Colombia

2021 ◽  
Vol 4 (1) ◽  
pp. 73-89
Author(s):  
Senanu Kwasi Klutse ◽  
Gábor Dávid Kiss
Keyword(s):  
Exchange Rate ◽  
Crude Oil ◽  
Oil Prices ◽  
Oil Price ◽  
Dollar Exchange Rate ◽  
Fuel Prices ◽  
Crude Oil Prices ◽  
Long Run ◽  
The Us ◽  
Us Dollar

Once again, the World has been faced with an oil price shock as a result of the SARS-CoV-2 coronavirus pandemic. This has resurrected an old debate of whether retail fuel prices adjust significantly to either increases or decreases in international crude oil prices. With many countries moving towards the deregulation of their petroleum sub-sector, the impact of the US dollar exchange rate on retail fuel prices cannot be overlooked. This study investigates the rate at which positive and negative changes in international Brent crude oil prices and the US dollar exchange rate affected the increases or decreases in the ex-pump price of premium gasoline between February 2012 and December 2019. Using a non-linear auto-regressive distributed lag model, the exchange rate was found to play a significant role in fluctuations in the retail price of premium gasoline in Ghana and Colombia in the long run, howev-er, the rate of adjustment between the negative and positive changes was not significant, dispelling the perception of price asymmetry. There was no significant relationship between the ex-pump price of premium gasoline and the international Brent crude oil price in Ghana and Kenya in the long run. This study recommends that the aforementioned countries prioritise the creation of ex-change rate buffers to prevent exchange rate shocks that may affect retail fuel prices.

scholarly journals MODEL KOMBINASI ARIMA DALAM PERAMALAN HARGA MINYAK MENTAH DUNIA

2018 ◽  
Vol 7 (1) ◽  
pp. 54-63
Author(s):  
Eka Setiyowati ◽  
Agus Rusgiyono ◽  
Tarno Tarno
Keyword(s):  
Crude Oil ◽  
Everyday Life ◽  
Oil Prices ◽  
Oil Price ◽  
Ensemble Method ◽  
Economic Conditions ◽  
Arima Models ◽  
Crude Oil Price ◽  
Crude Oil Prices

Oil is the most important commodity in everyday life, because oil is one of the main sources of energy that is needed for other people. Changes in crude oil prices greatly affect the economic conditions of a country.  Therefore, the aim of this study is develop an appropriate model for forecasting crude oil price based on the ARIMA and its ensembles. In this study, ensemble method uses some ARIMA models to create ensemble members which are then combined with averaging and stacking techniques. The data used are the price of world crude oil period 2003-2017. The results showed that ARIMA (1,1,0) model produces the smallest RMSE values for forecasting the next thirty six months. Keywords: Ensemble, ARIMA, Averaging, Stacking, Crude Oil Price

scholarly journals Structural Effect of Oil Price Shocks and Food Importation on Economic Growth in Nigeria Using SVAR Model

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Sani Abdulrahman Bala ◽  
Ali Alhassan
Keyword(s):  
Economic Growth ◽  
Exchange Rate ◽  
Crude Oil ◽  
Oil Price ◽  
Oil Price Shocks ◽  
Crude Oil Price ◽  
Price Shocks ◽  
Long Run ◽  
Svar Model ◽  
Food Imports

The study empirically examines the effect of oil price shocks and food importation on economic growth in Nigeria along with two control variables i.e. exchange rate and inflation using Structural Vector Autoregressive (SVAR) Model covering the period of 1970 to 2015. The result from SVAR short-run pattern and long-run pattern indicate that GDP has recently been affected by all variables in the model. More also, it indicates a significant permanent effect of crude oil price shocks and food imports on economic growth, while the result further indicates a transitory effect of exchange rate and inflation on economic growth. For significant t-value of the long run SVAR estimate matrix, confirms long effect of crude oil price shocks, food imports, exchange rate and inflation on economic growth in Nigeria. The results from structural response indicate that crude oil have high positive impact on GDP at the initial period and negative impact at the end of the period. Furthermore, food imports have high negative effect on GDP, while GDP response negatively to exchange rate and inflation rate from the period. The result from the structural decompositions indicates that crude oil price and food imports and exchange rate contribute more variability to GDP, while inflation contribute less variability in explaining the variation of GDP in Nigeria. The study recommends that government should come up with a policy that will focus on alternative sources of government revenue by investing more in real sectors especially agriculture in order to withstand vicissitudes of oil shocks in future.

Modelling Crude Oil Prices Volatility in India

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Khyati Kathuria ◽  
Shikha Gupta ◽  
Nand Kumar
Keyword(s):  
Crude Oil ◽  
Linear Time ◽  
Price Volatility ◽  
Oil Prices ◽  
Oil Price ◽  
Crude Oil Price ◽  
Volatility Clustering ◽  
Price Series ◽  
Crude Oil Prices ◽  
Increasing Demand

Crude oil is a crucial component of India’s energy basket after coal. The increasing demand for crude oil in India is met through imports. Crude oil price changes affect the social stability, economic development, and national security of the country. Therefore, it is crucial to devise suitable methods to forecast crude oil price movements accurately.Thus, the purpose of this study is to evaluate the forecasting performance of linear and non-linear time series models. In the study Box Jenkins methodology is used to obtain a best fit ARIMA and GARCH type models and further use it to forecast the crude oil (Brent) prices. The study shows that the crude oil price series is volatile over the time trend and therefore uses the GARCH class models as well which are capable of capturing volatility clustering typical of oil price series. Performance of ARIMA & GARCH class modes is then compared to find out which model better forecasts the crude oil prices. Indian economy being vulnerable to volatility in the international crude oil market requires a methodology to accurately forecast the price volatility and therefore to fill this gap this study for forecasting and studying the behavior of crude oil price series was conducted.

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