The indicated results (1) in the production model, the NR price and the total planted area of NR both have a positive relationship with the NR production; 2) in the NR consumption model, NR price and NR stock both have a negative relationship with NR consumption; (3) In the NR SMR20 price model, NR world production, Shanghai NR price and SR price are positively related to NR SMR20 price, while NR world consumption is negatively related to NR SMR20 price. The government should implement policies to enable North Korea's stable and sustainable growth in the countries.
INTRODUCTION
Background of the NR Market
Thus, due to the optimal conditions for Hevea trees, extensive plantations existed in many parts of mainland Southeast Asian countries. Due to its favorable physical and chemical properties, it has various uses in many industries (Herath, Samita & Wijesuriya, 2012).
Current Situation of the ASEAN and World NR Market
- Natural Rubber Production
- Natural Rubber Total Planted Area
- Natural Rubber Consumption
- NR SMR20 Price, Shanghai NR Price and the SR Price…
- NR Price and Real Exchange Rate
- NR Price and Crude Oil Price
In addition, the movements of the exchange rate can cause the NR price to fluctuate in the short term. This means that any fluctuation in the crude oil price will directly affect the SR price.
Problem Statements
The increase in the price of electricity from 2016 onwards has a positive effect on the fact that the NR price went back up. This would be suitable for studying the NR pricing model as a whole in the world market.
Objective of the Study
Research Questions
What is the relationship between NR price and NR stock with NR consumption in China, India, Japan and USA. Is there any relationship between world NR production, world consumption, Shanghai NR price, real exchange rate, crude oil price and world SR price with NR SMR20 price.
Significance of the Study
Furthermore, consuming countries should be aware of the issue of overconsumption of NR in the market. Therefore, in this research, the SR price will be set as one of the independent variables in the NR world price model.
Organization of the Study
LITERATURE REVIEW
Conceptual Reviews
- Conceptual Framework for NR Production Model
- Conceptual Framework for NR Consumption Model
- Conceptual Framework for NR Price Model
For SR, since it is a substitute product of NR, an increase in the price of SR (SRPRICE) will have a positive effect on the consumption of NR. Therefore, they will spend more NR to stabilize their costs and thus increase their NR consumption (Arunwarakorn et al., 2017).
Empirical Reviews
- Natural Rubber Production
- Natural Rubber Consumption
- Natural Rubber Price
Fluctuations and variations in the NR price were the crucial factor hurting the NR market. It was also found that these variables were related to the NR price.
Conclusion
Therefore, after reviewing previous research, panel data may be a suitable method to study the production and consumption pattern of NR in the study where the combination of cross-sectional and time-series data is allowed, instead of studying only time series data. Moreover, for the NR price model, VECM can be a suitable method to study the world NR price model since the model will be studied using time series data instead of panel data.
RESEARCH METHODOLOGY
Conceptual Framework
Moreover, by using panel data analysis, it can provide more informative data and results (more elaboration of the methodology will be discussed later). By doing a panel data analysis to study both producer and consumer countries, it would be good to add another methodology to study the global market, as the previous studies would have done.
Empirical Model Specification
- NR Production Model
- NR Consumption Model
- NR Price Model
Finally, the NR price and its total planted area are set as independent variables in the model. Thus, the NR price is set as one of the independent variables and another independent variable is the domestic stock of NR in the countries.
Research Hypotheses
- NR Production Model
- NR Consumption Model
- NR Price Model
H03: There is no significant relationship between NR prices and NR consumption in China, India, Japan and the USA. H04: There is no significant relationship between NR inventory and NR consumption in China, India, Japan, and the United States.
Research Procedure
If the series is stationary in the level data, a VAR model will be appropriate and sufficient for the analysis. Then, the three models will be studied using the Granger Causality test to find the causal relationships between the variables in the different models.
Data Collection
Panel Data Model
- Fixed Effect Model
- Random Effect Model
- Hausman Test
- Panel Cointegration Test
Hausman (1978) proposed a test to investigate whether FEM or REM is preferred for the panel data analysis. The null hypothesis is that the preferred model is a REM and the alternative is that the FEM is preferred.
Vector Error Correction Model (VECM)
- VECM Equation
- Cointegration Equation
- Cointegration Rank Test
If two variables are said to be cointegrated, it means that there is a long-run equilibrium relationship between them. The maximum eigenvalue statistic examines the null hypothesis that there are r cointegrating vectors against the alternative hypothesis of r+1 cointegrating vectors.
Granger Causality Test
Conclusion
The results showed that in the NR consumption model, NR price and NR consumption are negatively related. Therefore, this may be the reason for the insignificance of the exchange rate variable in the NR price model in this study.
DATA ANALYSIS AND RESULTS
Descriptive Analysis
In the five producing countries, the maximum production of NR was 4755 thousand tons and the minimum production was only 52.3 thousand tons. In the four consumer countries, the maximum consumption was 9591.6 thousand tons, while the minimum consumption was only 968 thousand tons.
Correlation Test
A value of -0.1793 means that there is a weak negative correlation between NR price and NR consumption; where -0.2434 means that there is a weak negative correlation between overhead inventory and overhead consumption; and -0.1655 means that there is a weak negative correlation between NR stock and NR price in 4 major consuming countries (China, India, Japan, USA). The value of 0.3086 indicates a moderate positive correlation between NR production and NR price SMR20; -0.1733 indicates a weak negative correlation between NR consumption and NR SMR20 price; 0.9785 indicates a strong positive correlation between Shanghai NR price and SMR20 NR price; - 0.6709 means a moderate negative correlation between the real exchange rate and the price of NR SMR20; -0.6437 indicates moderate negative correlation between SR price and NR SMR20 price; and finally, 0.6162 indicates a moderate positive correlation between crude oil price and NR SMR20 price.
Unit Root Tests
All three variables are then stationary at the ln and first difference level and is statistically significant at the = 0.01 level. However, all variables are only stationary after the first difference and statistically significant at the = 0.01 level.
Panel Data Model Selection
For the world production model NR, the test result from the Hausman test shows that the p-value is equal to 0.8511, which is greater than = 0.05. Similarly, for the NR world consumption model, the test result from the Hausman test shows that the p-value is equal to 0.9261, which is less than = 0.05.
Panel Data Models of NR Production and Consumption
- REM of Panel NR Production Model
- REM of Panel NR Consumption Model
Therefore, in five NR producing countries, namely Thailand, Indonesia, Malaysia, Vietnam and Myanmar, NR price and total NR planted area are positively related to NR production, which are statistically significant at the = 0.01 level. In the short term it may benefit consumers, but in the long term it will seriously harm the NR industry.
Panel Cointegration Test
Furthermore, the results of Trace and Max-Eigen values of Johansen's cointegration test indicate that there are more than two cointegrating equations, where the null hypothesis is rejected at the = 0.05 level. Furthermore, the Trace and Max-Eigen values of Johansen's cointegration test indicate that there are more than two cointegrating equations, where the null hypothesis is rejected at the = 0.05 level.
VECM of NR Price Model
- Cointegration Equation
- VECM Equation
Therefore, every one unit (‘000 ton) increase in world NR production will, on average, have a positive effect on the increase in world NR price by 0.3334 units (USD/ton), holding other variables constant; every one unit ('000 tons) increase in world NR consumption will, on average, have one. Furthermore, the results show that there is no short-run relationship between the real exchange rate and the price of crude oil with world NR.
Cointegration Rank Test of NR Price Model
Trace test and Maximum Eigenvalue test results indicate that there are two cointegrating relationships in the NR pricing model. Briefly, it is suggested that there is the existence of cointegration relationships in the NR price model.
Granger Causality Test
- NR Production Model
- NR Consumption Model
- NR Price Model
The results indicate that there are two unidirectional causal relationships in the model ranging from (1) SMR20 price to the NR production at = 0.05 level and (2) NR production to the total planted area of NR = 0.05 level. Basically, there are eight unidirectional and two bidirectional causal relationships in the NR SMR20 pricing model.
Residual Diagnostics
The results in Table 4.17 show that for the normality test the p-values in both models are greater than 0.05. Therefore, we do not reject H0; the residuals are normally distributed. Therefore, the residuals are normally distributed and there is no evidence of problems with heteroskedasticity and serial correlation in the model.
Model Evaluation
Figures 4.1, 4.2 and 4.3 illustrate the model evaluation graphs for the NR models for world production, world consumption and world price, respectively. Figures show that all three models contain a low value of RMSE, MAE, MAPE and Theil's U statistic is less than 1 and close to 0.
Hypothesis Testing
- NR Production Model
- NR Consumption Model
- NR Price Model
Furthermore, SR price was found to be positively related to NR price in the NR world price model. There is a negative relationship between NR prices and NR consumption in China, India, Japan and the USA.
Conclusion
NR production was the function of NR price and the total planted area of NR in Thailand, Indonesia, Malaysia, Vietnam and Myanmar. The impact of the changes in world crude oil prices on the NR industry in Malaysia.
DISCUSSION, CONCLUSTION AND IMPLICATIONS
Summary of the Study
Both independent variables, namely NR price and NR inventory, had a weak negative correlation with NR consumption. The REM equation showed that in the four major NR consuming countries (China, India, Japan, USA), NR price and inventory had negative relationships with NR consumption, which were statistically significant at .
Implication of the Study
As consumer countries like China and India, the government should take this seriously as it affects the global NR market. Although it is not in accordance with the theory, it reflects the real situation that is happening in the NR market.
Limitation of the Study
But perhaps due to the sample period of the study, they are insignificant in this case. The sampling period of both panel data models (NR world production and consumption models) are annual data from 2004 to 2017.
Recommendation for Future Study
Furthermore, researchers could also apply the ex-ante forecast to the future forecast of the NR economy in a particular country or the world market. One of the research methods, which is the simultaneous equation, could be used in this type of study, where production and consumption were investigated.
Conclusion
Retrieved from Financial Express: http://www.financialexpress.com/. 2002), Exchange rates and prices of natural rubber, the effect of the Asian crisis. Identifying Common Trends in Natural Rubber Prices, Demand and Supply: An Approach Using Dynamic Factor Modeling. http://www.globalsources.com/gsol/I/Automotive-manufacturing/.
