External and Internal Shocks and the Movement of Palm Oil Price: SVAR Evidence from Malaysia

Movements in palm oil price give important signals to various stakeholders of the palm oil industry in Malaysia. Thus, understanding external and internal factors that may affect the palm oil price is vital to the industry players for sustainability of their activities. This study investigates relative importance of external and internal shocks on the movement of palm oil price in Malaysia. Employing a structural vector autoregressive (SVAR) model on quarterly data from 1990 to 2019, the findings reveal that external shocks are more dominant in affecting the palm oil price. Shocks to the crude oil price, the prices of substitution goods (soybeans oil, rapeseed oil, and sunflower oil), the world palm oil price, and foreign income significantly affect the palm oil price in the short and medium run. The results also indicate that a shock to soybean oil price has a more profound effect on the palm oil price than a shock to rapeseed oil or sunflower oil prices, respectively. Likewise, shocks to incomes from India as well as from Netherlands create greater impacts on the palm oil price than a shock to income from the other trading partners, respectively. The study has shown the importance of external factors in affecting the palm oil industry.

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Postprandial lipoprotein, glucose and insulin responses after two consecutive meals containing rapeseed oil, sunflower oil or palm oil with or without glucose at the first meal

British Journal Of Nutrition ◽

10.1017/s0007114599001245 ◽

1999 ◽

Vol 82 (2) ◽

pp. 97-104 ◽

Cited By ~ 26

Author(s):

Anette Pedersen ◽

Peter Marckmann ◽

Brittmarie Sandström

Keyword(s):

Fatty Acid Composition ◽

Fatty Acid ◽

Acid Composition ◽

Palm Oil ◽

Sunflower Oil ◽

Rapeseed Oil ◽

Postprandial Lipaemia ◽

Young Males ◽

Insulin Responses ◽

Oil Sunflower

There is increasing evidence that the degree of postprandial lipaemia may be of importance in the development of atherosclerosis and IHD. Postprandial lipid, lipoprotein, glucose, insulin and non-esterified fatty acid (NEFA) concentrations were investigated in eleven healthy young males after randomized ingestion of meals containing rapeseed oil, sunflower oil or palm oil with or without a glucose drink. On six occasions each subject consumed consecutive meals (separated by 1·75 h) containing 70 g (15 g and 55 g respectively) of each oil. On one occasion with each oil 50 g glucose was taken with the first meal. One fasting and fifteen postprandial blood samples were taken over 9 h. There were no statistically significant differences in lipoprotein and apolipoprotein responses after rapeseed, sunflower and palm oils, whereas insulin responses were lower after sunflower oil than after rapeseed oil (ANOVA, P = 0·04). The NEFA and triacylglycerol concentrations at 1·5 h were reduced when 50 g glucose was taken with the first meal (ANOVA, P < 0·0001 and P < 0·05 respectively), regardless of meal fatty acid composition. In conclusion, the consumption of glucose with a mixed meal containing either rapeseed, sunflower or palm oil influenced the immediate triacylglycerol and NEFA responses compared with the same meal without glucose, whereas no significant effect on postprandial lipaemia after a subsequent meal was observed. The fatty acid composition of the meal did not significantly affect the lipid and lipoprotein responses, whereas an effect on insulin responses was observed.

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The Effects of Oil Price Shocks and Economic Fluctuations of Trading Partners on Iran's Ports Throughput

Transactions on Maritime Science ◽

10.7225/toms.v08.n01.001 ◽

2019 ◽

Vol 8 (1) ◽

pp. 5-17

Author(s):

Hojat Parsa ◽

Mehdi Mirzaei

Keyword(s):

Oil Price ◽

Economic Fluctuations ◽

Oil Price Shocks ◽

Price Shocks ◽

Vector Autoregressive ◽

Long Run ◽

Trading Partners ◽

Short Run ◽

Port Throughput ◽

Oil Revenues

This study aims to estimate the effects of oil price shocks on seaborne trade in Iran; in particular, port throughput of three leading ports through economic fluctuations of three major trading partners of Iran, based on quarterly data for the period of 1999Q2 to 2018Q1. We apply a standard vector autoregressive (VAR) approach using Cholesky decomposition. The results indicate that with increasing oil revenues in short-run, seaborne trade be further directed towards Shahid Rajaei port while rising oil revenues changes the combination of goods handled in Emam Khomeini and Bushehr ports. In the long run, the share of oil price fluctuations in explaining the variations of Shahid Rajaei port throughput is higher than the other two. In fact, increases in oil revenues cause an increase in the volume of industrial and containerized seaborne cargo trade.

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Oil Price and Exchange Rate Nexus in Nigeria: Are there Asymmetries

Central Bank of Nigeria Journal of Applied Statistics ◽

10.33429/cjas.10119.1/6 ◽

2019 ◽

pp. 1-28

Author(s):

Attahir B. Abubakar

Keyword(s):

Exchange Rate ◽

Time Lag ◽

Oil Price ◽

Monthly Data ◽

Vector Autoregressive ◽

Threshold Autoregressive ◽

Svar Model ◽

Asymmetric Cointegration ◽

The Relationship ◽

Rate Threshold

This paper examines the dynamics in the relationship between oil price and exchange rate in Nigeria by utilizing monthly data spanning January 1986 to June 2018. It specifically determines asymmetries in the relationship between oil price and exchange rate and the effect of oil price shocks on exchange rate. Threshold Autoregressive (TAR), Momentum Threshold autoregressive (MTAR) and Structural Vector Autoregressive (SVAR) models were employed for the analysis. Findings of TAR and MTAR models confirm the absence of asymmetric cointegration, hence leading to the conclusion that in the case of Nigeria, there are no asymmetries in the relationship between oil price and exchange rate. Findings from the SVAR model show gradual appreciation (though with some time lag) of naira following positive shocks to oil price. The study recommends among others the need for diversification of foreign exchange earnings base of the economy, so as to minimise the effect of negative shocks to oil price.

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Rapeseed Oil and Sunflower Oil Diets Enhance Platelet In Vitro Aggregation and Thromboxane Production in Healthy Men when Compared with Milk Fat or Habitual Diets

Thrombosis and Haemostasis ◽

10.1055/s-0038-1648446 ◽

1992 ◽

Vol 67 (03) ◽

pp. 352-356 ◽

Cited By ~ 34

Author(s):

Marja Mutanen ◽

Riitta Freese ◽

Liisa M Valsta ◽

Irma Ahola ◽

Antti Ahlström

Keyword(s):

Sunflower Oil ◽

Milk Fat ◽

Rapeseed Oil ◽

Controlled Trial ◽

Collagen Concentration ◽

Aggregation Pattern ◽

Thromboxane Production ◽

Low Erucic Acid ◽

Platelet Thromboxane

SummaryIn this highly controlled trial, 26 normolipidemic men (average age 28 years, range 18 to 60) were fed a baseline diet high in milk fat (MF) (fat 36% of energy, saturates 19%, monounsaturates 11%, polyunsaturates 4%), followed by a diet high in sunflower oil (SO) (fat 38% of energy, saturates 13%, monounsaturates 10%, polyunsaturates 13%) and another diet high in low erucic-acid rapeseed oil (RO) (fat 38% of energy, saturates 12%, monounsaturates 16%, polyunsaturates 8%). All diets were mixed natural diets with the same cholesterol contents. The baseline milk fat diet was given for 14 days and the oil diets for 24 days in a blind cross-over design. The platelet in vitro aggregation (slope %/min) induced by 1, 2 and 3 pM ADP and collagen (25 pg/ml PRP) was highly significantly (p <0.001) increased after both oil diets when compared with the results from the milk fat diet. The aggregation pattern determined by threshold collagen concentration confirmed increased collagen sensitivity of the platelets after the rapeseed oil diet (p <0.001). The enhancement of platelet aggregation was associated with increased in vitro platelet thromboxane production after the oil diets vs. the milk fat diet (p <0.05 after the sunflower oil diet and p <0.001 after the rapeseed oil diet).

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Expanding N. I. Palm Oil Industry Depends on U. S.

Far Eastern Survey ◽

10.1525/as.1938.7.13.01p0576c ◽

1938 ◽

Vol 7 (13) ◽

pp. 153-154

Author(s):

G. vE.

Keyword(s):

Palm Oil ◽

Oil Industry

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PEMETAAN TEKNOLOGI INDUSTRI KELAPA SAWIT NASIONAL DAN KEBIJAKAN PENGEMBANGANNYA

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v13i1.876 ◽

2013 ◽

Vol 13 (1) ◽

Author(s):

Subiyanto Subiyanto

Keyword(s):

Palm Oil ◽

Government Policy ◽

Value Chain ◽

Raw Materials ◽

Value Added ◽

Oil Industry ◽

Missing Value ◽

Technology Capability ◽

The Government

Palm oil industry in Indonesia has been growing rapidly. But, unfortunately the growth is only effective on upstream industry with low value products, such that potential downstream value added are not explored proportionally. The government is therefore in the process of developing an appropriate policy to strengthen the national palm oil downstream industry. This paper proposes that an approriate policy for developing palm oil downstream industry could be derived from the maps of value chain and existing technology capability of the industry. The result recommends that government policy should emphasize on the supply of raw materials, infrastructure and utilities, as well as developing the missing value chain industry, especially ethoxylation and sulfonation.

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Examining the Forecasting Movement of Palm Oil Price Using RBFNN-2SATRA Metaheuristic Algorithms for Logic Mining

IEEE Access ◽

10.1109/access.2021.3054816 ◽

2021 ◽

Vol 9 ◽

pp. 22542-22557

Author(s):

Shehab Abdulhabib Saeed Alzaeemi ◽

Saratha Sathasivam

Keyword(s):

Palm Oil ◽

Oil Price ◽

Metaheuristic Algorithms

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MORTALITY FORECASTING WITH A SPATIALLY PENALIZED SMOOTHED VAR MODEL

Astin Bulletin ◽

10.1017/asb.2020.39 ◽

2020 ◽

pp. 1-29

Author(s):

Le Chang ◽

Yanlin Shi

Keyword(s):

Population Data ◽

Coefficient Matrix ◽

Gradient Algorithm ◽

Var Model ◽

Vector Autoregressive ◽

Mortality Forecasting ◽

Dependency Structure ◽

Svar Model ◽

The Uk ◽

Sparsity Structure

Abstract This paper investigates a high-dimensional vector-autoregressive (VAR) model in mortality modeling and forecasting. We propose an extension of the sparse VAR (SVAR) model fitted on the log-mortality improvements, which we name “spatially penalized smoothed VAR” (SSVAR). By adaptively penalizing the coefficients based on the distances between ages, SSVAR not only allows a flexible data-driven sparsity structure of the coefficient matrix but simultaneously ensures interpretable coefficients including cohort effects. Moreover, by incorporating the smoothness penalties, divergence in forecast mortality rates of neighboring ages is largely reduced, compared with the existing SVAR model. A novel estimation approach that uses the accelerated proximal gradient algorithm is proposed to solve SSVAR efficiently. Similarly, we propose estimating the precision matrix of the residuals using a spatially penalized graphical Lasso to further study the dependency structure of the residuals. Using the UK and France population data, we demonstrate that the SSVAR model consistently outperforms the famous Lee–Carter, Hyndman–Ullah, and two VAR-type models in forecasting accuracy. Finally, we discuss the extension of the SSVAR model to multi-population mortality forecasting with an illustrative example that demonstrates its superiority in forecasting over existing approaches.

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