scholarly journals Modeling the Impact of Agricultural Shocks on Oil Price in the US: A New Approach

2019 ◽  
Vol 12 (3) ◽  
pp. 147 ◽  
Author(s):  
Vu ◽  
Vo ◽  
Ho ◽  
Van
Keyword(s):  
Crude Oil ◽  
Agricultural Sector ◽  
Oil Price ◽  
Biofuel Production ◽  
Agricultural Commodity ◽  
Agricultural Market ◽  
Demand Shocks ◽  
The Us ◽  
Agricultural Shocks ◽  
The Impact

The current literature has generally considered prices of the agricultural commodity as an endogenous factor to crude oil price. As such, the role of the agricultural market in the energy sector has been largely ignored. We argue that the expansion of agricultural production may trigger a significant increase in oil price. In addition, the world has recently witnessed a growth in biofuel production, leading to an increase in the size of the agricultural sector. This study is conducted to examine the impact of different agricultural shocks on the oil and agricultural markets in the US for the period from 1986 to 2018. The study utilizes the Structural Vector Autoregressive (SVAR) model to estimate the relationship between the agricultural market and the crude oil market. Moreover, the variance decomposition is also used to quantify the contribution of agricultural demand shocks on oil price variations. Findings from this paper indicate that different agricultural shocks can have different effects on oil price and that corn use in ethanol plays an important role in the impact of corn demand shocks on oil price. We find evidence that the agricultural market can have an impact on oil prices through two main channels: indirect cost push effect and direct biofuel effect. Of these, the biofuel channel unexpectedly suggests that the expansion of bioethanol may in fact foster the dependency of the economy on fossil fuel use and prices.

scholarly journals Crude oil price variability and its impact on ethanol prices

2011 ◽  
Vol 57 (No. 8) ◽  
pp. 394-403 ◽  
Author(s):  
J. Pokrivčák ◽  
M. Rajčaniová
Keyword(s):  
Crude Oil ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Oil Prices ◽  
Oil Price ◽  
Biofuel Production ◽  
Oil Price Shock ◽  
Price Shock ◽  
The Impact

The world annual biofuel production has exceeded 100 billion litres in 2009. The development of the biofuel production is partly influenced by the government support programs and partly by the development of oil prices. The main purpose of this paper is to analyze the statistical relationship between ethanol, gasoline and crude oil prices. We aim to check the correlation among these variables and to analyze the strength and direction of a possible linear relationship among the variables. We are interested in analyzing how each variable is related to another, so we evaluate the inter-relationship among the variables in the Vector Autoregression (VAR) and the Impulse Response Function (IRF). In order to achieve our goal, we first collected weekly data for each variable from January, 2000 to October, 2009. The results provide evidence of the cointegration relationship between oil and gasoline prices, but no cointegration between ethanol, gasoline and ethanol, oil prices. As a result, we used a VAR model on first differences. After running the Impulse Response Function, we found out that the impact of the oil price shock on the other variables is considerable larger than vice versa. The largest impact of oil price shock was observed on the price of gasoline.  

Impacts of Falling Crude Oil Prices and Reduction of Energy Subsidies on the Indian Economy: A CGE Modelling Approach

2016 ◽  
Vol 20 (4) ◽  
pp. 345-360
Author(s):  
Amrita Ganguly ◽  
Koushik Das
Keyword(s):  
Exchange Rate ◽  
Crude Oil ◽  
Oil Price ◽  
Cash Transfer ◽  
Crude Oil Price ◽  
Transfer Scheme ◽  
Indian Economy ◽  
Cge Modelling ◽  
The Impact ◽  
Energy Subsidy

This study analyzes the impacts of international crude oil fluctuations and energy subsidy (on LPG, petrol and diesel) removals on Indian economy. We have applied computable general equilibrium (CGE) modelling as our relevant methodology, following Shoven and Whalley ( J Econ Lit XXII: 1007–1051, 1984) based on energy social accounting matrix (ESAM) of India for the year 2007–2008. It is seen that the international crude oil price fluctuations has a greater effect in determining gross domestic product (GDP) and exchange rate as compared to the effect of energy subsidy removal. With decrease in international crude oil price, GDP increases and exchange rate appreciates. On the other hand, with decrease in energy subsidy, GDP decreases and exchange rate appreciates. Moreover, with introduction of direct cash transfer scheme in lieu of subsidy for LPG, it is seen that the impact on demand of LPG (substitution effect) is negligible indicating that LPG is an essential commodity.

scholarly journals Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Štifanić ◽  
Jelena Musulin ◽  
Adrijana Miočević ◽  
Sandi Baressi Šegota ◽  
Roman Šubić ◽  
...  
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Short Term Memory ◽  
Oil Price ◽  
Stationary Wavelet Transform ◽  
Crude Oil Price ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
The Impact

COVID-19 is an infectious disease that mostly affects the respiratory system. At the time of this research being performed, there were more than 1.4 million cases of COVID-19, and one of the biggest anxieties is not just our health, but our livelihoods, too. In this research, authors investigate the impact of COVID-19 on the global economy, more specifically, the impact of COVID-19 on the financial movement of Crude Oil price and three US stock indexes: DJI, S&P 500, and NASDAQ Composite. The proposed system for predicting commodity and stock prices integrates the stationary wavelet transform (SWT) and bidirectional long short-term memory (BDLSTM) networks. Firstly, SWT is used to decompose the data into approximation and detail coefficients. After decomposition, data of Crude Oil price and stock market indexes along with COVID-19 confirmed cases were used as input variables for future price movement forecasting. As a result, the proposed system BDLSTM + WT-ADA achieved satisfactory results in terms of five-day Crude Oil price forecast.

Protocol to Assess the Impact of Crude Oil Price Fluctuations on Future Asphalt Prices

2021 ◽  
pp. 036119812199207
Author(s):  
Kaylyn M. Cardinal ◽  
Mohamed Khalafalla ◽  
Jorge Rueda-Benavides
Keyword(s):  
Crude Oil ◽  
Price Index ◽  
Oil Price ◽  
Crude Oil Price ◽  
Statistical Process ◽  
Economic Implications ◽  
Price Fluctuations ◽  
Time Gap ◽  
The Impact ◽  
The Relationship

It is clear for the transportation industry that asphalt prices are heavily affected by changes in the crude oil market. This occurs because asphalt is a byproduct of the process of refining crude oil. However, there is still a lack of research on assessing the economic implications of this relationship. This paper assesses those implications through an innovative statistical process designed to quantify the economic correlation between asphalt and crude oil price fluctuations in Alabama. The proposed statistical process is used in this paper to model the relationship between the Alabama Department of Transportation’s (ALDOT’s) monthly asphalt price index and a national crude oil index published by the US Energy Information Administration. The process quantifies the relationship between these two commodities in relation to two metrics: (1) the time gap between an observed change in the crude oil index and its corresponding impact on the asphalt price index and (2) the magnitude of that impact. It was found that the most likely time gap between crude oil and asphalt price fluctuations in Alabama is 3 months, with a change ratio of 0.58. This means that a 1% increase in the price of crude oil would most likely affect the Alabama asphalt market 3 months later with a price increase of about 0.58%. Recognizing that these are just average values, the paper also presents a risk assessment tool that provides ALDOT with the probability of occurrence of different scenarios taking into consideration the observed variability in time gaps and change ratios.

The impact of rising international crude oil price on China's economy: an empirical analysis with CGE model

2007 ◽  
Vol 27 (4) ◽  
pp. 404 ◽  
Author(s):  
Ying Fan ◽  
Jian Ling Jiao ◽  
Qiao Mei Liang ◽  
Zhi Yong Han ◽  
Yi Ming Wei
Keyword(s):  
Crude Oil ◽  
Empirical Analysis ◽  
Oil Price ◽  
Cge Model ◽  
Crude Oil Price ◽  
The Impact ◽  
China’S Economy

PESTICIDE AND GREENHOUSE GAS EXTERNALITIES FROM US AGRICULTURE — THE IMPACT OF THEIR INTERNALIZATION AND CLIMATE CHANGE

2013 ◽  
Vol 04 (03) ◽  
pp. 1350008 ◽  
Author(s):  
NIKOLINKA SHAKHRAMANYAN ◽  
UWE A. SCHNEIDER ◽  
BRUCE A. McCARL
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Agricultural Sector ◽  
Greenhouse Gas Emission ◽  
Production Costs ◽  
Net Income ◽  
Gas Emission ◽  
Emission Mitigation ◽  
The Us ◽  
The Impact

Climate change may affect the use of pesticides and their associated environmental and human health impacts. This study employs and modifies a partial equilibrium model of the US agricultural sector to examine the effects of alternative regulations of the pesticide and greenhouse gas emission externality. Simulation results indicate that without pesticide externality regulations and low greenhouse gas emission mitigation strategy, climate change benefits from increased agricultural production in the US are more than offset by increased environmental costs. Although the combined regulation of pesticide and greenhouse gas emission externalities increases farmers' production costs, their net income effects are positive because of price adjustments and associated welfare shifts from consumers to producers. The results also show heterogeneous impacts on preferred pest management intensities across major crops. While pesticide externality regulations lead to substantial increases in total water use, climate policies induce the opposite effect.

scholarly journals Crude oil, natural gas, and economic growth: impact and causality analysis in Caspian Sea region

2018 ◽  
Vol 54 (3) ◽  
pp. 169-184 ◽  
Author(s):  
S M Rashed Jahangir ◽  
Betul Yuce Dural
Keyword(s):  
Economic Growth ◽  
Natural Gas ◽  
Crude Oil ◽  
Caspian Sea ◽  
Oil Price ◽  
Crude Oil Price ◽  
Causality Test ◽  
Oil And Natural Gas ◽  
Gas Price ◽  
The Impact

Abstract The main objective of this study was to investigate the impact and causality of crude oil and natural gas on economic growth in the Caspian Sea region. Here, the study applies ordinary least square (OLS) method and Granger causality test using time series data from 1997 to 2015 to ascertain the impact and causality of crude oil and natural gas on economic growth. The results, according to the OLS method, evince that crude oil and natural gas have a significant impact on economic growth of the region. Alongside, considering causality test, gross domestic product (GDP) does Granger cause (unidirectional) crude oil price and export which denotes that GDP can help to forecast crude oil price and export; however, crude oil price and export cannot help to forecast GDP. Surprisingly, this direction is unlikely for GDP and natural gas. GDP and natural gas have unidirectional, but opposite causal relationship, i.e., natural gas price and export do Granger cause GDP which signify that natural gas price and export can help to forecast GDP; however, GDP cannot help to forecast crude oil price and export.

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