ECONOMETRIC HURRICANE
The
US gas is average price of wholesale gasoline in US, gulf gas is price of
wholesale gas in Gulf Coast, Cap is refinery capacity utilization, Stock is
total US gasoline stocks, and Kat dummy and Ivan dummy are dummy variables for
the time period where Hurricanes Katrina and Ivan occurred was used for the
computation of the effect. The researcher cluster the variables based on US and
Gulf Coast gasoline price. The calculation of
ratio of different variable was done to suit the model.
The
researcher investigated if there is no significant effect on crude ratio and US gas
, Gulf gas, Cap, stocks in term of the Hurricane Katrina and Ivan TSP_Sample_econometric_1
informational data under Jan 7, 2000 to Dec 29, 2006. The researcher also used Frequency
distribution and analysis of variance (ANOVA). The Multiple Regression was to
test heteroskedasticity of the elastic variables. The computation of the
analysis of variance of US and Gulf
Coast was also used for
differentiation and analysis of the data. The researcher also computed the Mean
Square Error, Standard Error of Estimate and the Multiple coefficient of determination.
The result of this findings will testify the goodness of the predictors of this
study.
This section presents the analysis
of the data on the study to find out if there is no significant effect on time
series and US
gas , Gulf gas, Cap, stocks in term of the Hurricane Katrina and Ivan TSP_Sample_econometric_1
informational data.
The
researcher found out that there was a significant effect on time series and US gas , Gulf
gas, Cap, stocks in term of the Hurricane Katrina and Ivan TSP_Sample_econometric_1
informational data under Jan 7, 2000 to Dec 29, 2006.
Majority
of the elasticity have no changes except on IVAN elasticity and US gas ratio. US gas
ratio has slightly affected by the hurricane , this can be seen in week 301. It
was notable that the Ivan data has remarkable change in terms of time series
under weeks 241 to 271 and 301. This
implies that there is a small probability of risk for the investors to invest in the
gasoline stock market.
The
Gulf gas ratio has slightly affected by the hurricane, this can be seen in
weeks 291 to 320. It shows that the Ivan data has remarkable change in terms of
time series under weeks 233 to 262 and 291 to 320. This reveals that there is a
slight effect on time series and Gulf
gas, in term of the Hurricane Katrina
and Ivan TSP_Sample_econometric_1 informational data under Jan 7, 2000 to Dec
29, 2006. This factor has slight effect on the economic process of the country.
This leads the other businessmen to transfer for another countries or ship for
another business.
The
Analysis of Variance was used to determine if there is no significant effect on
crude ratio and US gas ratio, Gulf gas ratio, Cap ratio, stocks ratio ,Hurricane
Katrina and Ivan TSP_Sample_econometric_1informational data. The result of the
“Analysis of Variance” (ANOVA) shows that the value of compute F is greater
than the tabulated F under US
gasoline price. The computed value of F is 51.989 while the tabulated F is
2.21. This implies that there is a significant effect on Gulf Coast
gasoline stock price in the existence of Katrina and Ivan Hurricanes because
null hypothesis is rejected. And the result of the “Analysis of Variance”
(ANOVA) of Gulf Coast gasoline also shows that the value
of compute F is greater than the tabulated F . The computed value of F is
50.156 while the tabulated F is 2.21. This implies that there is a significant
effect on US
gasoline stock price in the existence of Katrina and Ivan Hurricanes because
null hypothesis is rejected.
The
Regression results are as follows: the unbiased estimator of the variance of
the error in the multiple regression model is equal to .001. There is small value
of MSE so the estimator is a good fit of the regression. Standard error of
estimate is equal to 0.03145. Multiple coefficient of determination is .420 and
an adjusted multiple coefficient of determination is equal to .412 showed that the
data produced a good predictions.
The
unbiased estimator of the variance of the error in the multiple regression
model is equal to 0.001. There is a small value of MSE so the estimator of
elasticity is a good fit of the regression. Standard error of estimate is equal
to 0.3169. Multiple coefficient of determination is 0.411 and adjusted multiple
coefficient of determination is equal to .403 showed that the data produced a
good predictions.
Summary
of the two multiple regression, the two findings reveals that the variables
present in this study were good predictors of the gasoline stock price. This
implies that even though there is a hurricane in the said countries the value
of elasticity will remain controlled.
The
researcher discovered that there if there is a significant effect on crude
ratio and US gas ratio, Gulf gas ratio, Cap ratio, stocks ratio, Hurricane
Katrina and Ivan TSP_Sample_econometric_1 informational data under Jan 7, 2000
to Dec 29, 2006.
This
means that other variables can affect the flaws of the gasoline stock price.
The researcher suggested the additional parameters for the greater accuracy of
the model.