scholarly journals A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index

2019 ◽  
Author(s):  
David Edmund Allen ◽  
Michael McAleer
Keyword(s):  
Oil Prices ◽  
Jones Index ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
West Texas ◽  
Nonlinear Autoregressive

scholarly journals A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 4011
Author(s):  
David E. Allen ◽  
Michael McAleer
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Stationary Time Series ◽  
Bounds Testing ◽  
Jones Index ◽  
Distributed Lag ◽  
Price Series ◽  
Autoregressive Distributed Lag ◽  
West Texas ◽  
Nonlinear Autoregressive

The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag nonlinear autoregressive distributed lag (NARDL) framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from Federal Reserve Bank of St Louis (FRED), commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.

Factors Determining Gold Prices in Malaysia

2019 ◽  
Vol 1 (2) ◽  
pp. 75-82
Author(s):  
Anis Mat Dalam ◽  
Noorhaslinda Kulub Abd Rashid ◽  
Jaharudin Padli
Keyword(s):  
Crude Oil ◽  
Time Series Data ◽  
Oil Prices ◽  
Series Data ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Crude Oil Prices ◽  
Inflation Rates ◽  
Ardl Approach ◽  
Gold Reserve

Gold is a valuable asset to a country because of its liquidity. Gold reserve can stabilize the currency in a country. The objective of this paper is to identify the factors contributing to the volatility of gold prices, such as Real Malaysia GDP, inflation rates, crude oil prices and exchange rates. The data was analysed using Autoregressive Distributed Lag (ARDL) approach with time series data, with 30-year coverage from 1987 to 2016. Findings showed that only Real Malaysia GDP and crude oil prices were significantly related to gold prices. As a conclusion, this study can be used as reference by other investors. The author suggests to other researchers to further improve upon this study by adding more variables or diversifying the variables that relate to volatility of gold prices.

Consumer Confidence and Consumer Spending in Brazil: A Nonlinear Autoregressive Distributed Lag Model Analysis

2020 ◽  
pp. 097674791989890
Author(s):  
Sudeshna Ghosh
Keyword(s):  
Stock Market ◽  
Consumer Confidence ◽  
Consumer Expenditure ◽  
Consumer Spending ◽  
Financial Variables ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Autoregressive Distributed Lag ◽  
Lag Model ◽  
Nonlinear Autoregressive

The study explores the relationship between consumer confidence, household private consumer expenditure and other related macroeconomic financial variables for Brazil, a major, upper middle, income, Latin American country. It is widely discussed in the literature that the consumer confidence is an initial guide to the future behaviour of the economy based on the consumption path. Thus, a rise in the confidence of the consumer would lead to rising household consumption behaviour, which would percolate to accelerate economic growth. The study uses the nonlinear autoregressive distributed lag model (NARDL) to measure the effects of changes in consumer sentiment on private consumer spending, taking into consideration the significance of other financial variables, namely the rate of interest, stock market index, the exchange rate, inflation and unemployment trends. The study employs monthly data from the 4th month of 1995 to the 10th month of 2018. The bounds test of the NARDL suggests the presence of a cointegrating relationship among the variables. The model estimation affirms the presence of asymmetries in the behaviour of the major explanatory variables. In the short run, there are both positive and negative asymmetric impacts of consumer confidence index (CCI) on consumer expenditure, while the rate of interest has only negative asymmetries. In the long run, unemployment changes, stock market fluctuations, interest rate variation and alterations in the CCI shape the behaviour of consumer spending at the household level in Brazil. So, the consumers are able to perceive the signalling of the future behaviour of the market and contribute through consumption spending. JEL: C22; D12; E21; O54

scholarly journals Changes in Crude Oil Prices and the Flow of Government Revenue

2019 ◽  
pp. 1-12
Author(s):  
Chukwunweike Stella ◽  
Achu Tonia Chinedu ◽  
Awa Kalu Idika
Keyword(s):  
Oil Prices ◽  
Oil Price ◽  
Government Revenue ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Oil Revenue ◽  
Crude Oil Prices ◽  
Regression Techniques ◽  
The Government ◽  
The Impact

This work is set out as an investigation into the impact of change in oil prices on government revenue broken into oil and nonoil component. Drawing data from the Central Bank Statistical Bulletin and covering the period 1981 to 2018. The Autoregressive Distributed Lag (ARDL) Model was used because of its advantages over other regression techniques. It was found that changes in oil price affected oil revenue within the studied period leaving no significant impact on nonoil revenue. The result obviously reflects the Nigerian economy and its mono-product characteristic. It is therefore recommended that a conscious policy effort should be made to diversify the economy in a manner that makes revenue to the government multifarious functions.

scholarly journals Oil Price, Energy Consumption, and CO2 Emissions in Turkey. New Evidence from a Bootstrap ARDL Test

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5588
Author(s):  
Mohammed Abumunshar ◽  
Mehmet Aga ◽  
Ahmed Samour
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Oil Prices ◽  
Oil Price ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Imported Oil

The main objective of this research was to test the effect of oil prices, renewable and non-renewable energy consumption, and economic growth on Turkey’s carbon emissions by using three co-integration tests, namely, the newly-developed bootstrap autoregressive distributed lag (ARDL) testing technique as proposed by (McNown et al., 2018); the new approach involving the Bayer–Hanck (2013) combined co-integration test; and the H-J (2008) co-integration technique, which induces two dates of structural breaks. The autoregressive distributed lag model (ARDL), dynamic ordinary least squares (DOLS), canonical cointegrating regression (CCR), and fully modified ordinary least square (FMOLS) approaches were utilized to test the long-run interaction between the examined variables. The Granger causality (GC) analysis was utilized to investigate the direction of causality among the variables. The long-run coefficients of ARDL, DOLS, CCR, and FMOLS showed that the oil prices had a negative influence on CO2 emissions in Turkey in the long run. Furthermore, the findings demonstrate that non-renewable energy, which includes oil, natural gas, and coal, increased CO2 emissions. In contrast, renewable energy can decrease the environmental pollution. These empirical findings can be attributed to the fact that Turkey is heavily dependent on imported oil; more than 50% of the energy requirement has been supplied by imports. Hence, oil price fluctuations have severe effects on the economic performance in Turkey, which in turn affects energy consumption and the level of carbon emissions. The study suggests that the rate of imported oil in Turkey must be decreased by finding more renewable energy sources for the energy supply formula to avoid any undesirable effects of oil price fluctuations on the CO2 emissions, and also to achieve sustainable development.

Asymmetric relationship between tourist arrivals and employment

2020 ◽  
pp. 135481662091000
Author(s):  
Jitendra Sharma ◽  
Subrata Kumar Mitra
Keyword(s):  
Sri Lanka ◽  
Relative Stability ◽  
Annual Data ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Desirable Outcome ◽  
The Impact ◽  
The Relationship ◽  
Nonlinear Autoregressive ◽  
Reference Country

This article explores the relationship between the arrival of tourists and its impact on tourism-related employment. Considering the impact of tourist arrival on employment being asymmetric, we have analyzed the relationship using the nonlinear autoregressive distributed lag method proposed by Shin et al. The article analyzed how arrivals impact on employment taking Sri Lanka as a reference country and have used annual data of the variables obtained from the Sri Lanka Tourism Development Authority. It is found that for an increase in the tourist arrival by 1000, the tourism-related job employment rises by 83.8. On the contrary, with the decline in tourist arrival by the same number, the corresponding reduction in job employment is 29.8. The relatively lower reduction in employment with the fall of tourist arrival provides relative stability of employment to the tourism workforce and is a socially desirable outcome.

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