Oil Breaks and Price Trends

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Major Contribution to the Literature:

The paper organized by the author has an in-depth relationship with other literature works on the subject of Oil Breaks and Price Trends. Firstly, it has used the Kejriwal and Perron’s sequential procedure to determine the multiple structure changes in real oil prices. However, the author avoided the circular testing problem. In fact the Kejriwal and Peron model allows the repeated use and selection of a number of breaks in the trend and in the level of a univariate time series without any prior knowledge as to whether the noise component is stationary or not.

Thus, the author, in order to officially deal with the circular testing problem ,used the stability tests suggested by Vogelsang and Harvey. Apart from these academicians, Perron and Yabu developed an alternative test with higher power and less size distortions. They used a super efficient estimate of the sum of the auto-regressive parameters and the break date is unkown. The model works by improving the finite sample properties where a bias corrected version of the OLS estimate is used. Thus, based on Perron and Yabu and the other testing strategies of Bai and Perron, Kejriwal and Perron during 2010 a sequential procedure to test the null hypothesis to test the null hypothesis of l changes against the alternative hypothesis of (l+1) changes.

The second contribution by this work is that the author performed a diagnostic check through a regression analysis in order to detect the significance and magnitude of the potential breaks detected. Also by incorporating the information found on structural changes, the literature methodology undertakes the unit root tests to check for stationirity. The literature is also well recommended as ...

... middle of paper ...

...0) (0.00) (0.10)

 0.79 0.02 0.08

(0.00) (0.82) (0.86)

 -151.7 109.6 109.9

(0.01) (0.00) (0.00)

 1.00 0.67 0.96

(0.00) (0.00) (0.00)

 0.08 0.32 0.45

(0.00) (0.00) (0.00)

t -0.06 -0.01

(0.00) (0.00)

t2 0.00002 0.00003

(0.00) (0.00)

AIC 5.540 4.074 4.637 4.230

BSC 5.613 4.162 4.731 4.315

p-values are shown in parenthesis below the coefficient

TABLE 4. TIMELINE BREAKS

Variable Coefficients Level Slope

Initial 51.9 51.9 0

Jan 1878 -30.0 21.9

Jan 1895 15.3 37.2

Jan 1913 14.5 51.7

Apr 1921 -9.82 41.88 -0.01

Mar 1930 -6.81 35.07

Aug 1946 -8.46 26.61

Feb 1974 32.8 59.41

Jul 1979 51.4 110.81 -071

Feb 1986 -20.7 90.11 0.23

Feb 1991 -7.81 82.3 -0.05

Jul 1998 -14.5 67.8 0.56

Nov 2008 -40.7 27.1 1.58

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