Abstract
The power of the conventional Houck’s model of asymmetry is examined via parametric bootstrap simulation. The results of the bootstrap simulations indicate that the Houck’s model has low power in rejecting the null of symmetric adjustment. The power of the test depends on the bootstrap sample size, level of asymmetry and the amount of noise in the data generating process used in an application. With a small bootstrap sample and large noise level, the Houck’s model display low power in rejecting the null hypothesis of symmetry.
Highlights
Houck (1977) proposes a methodology to investigate asymmetric adjustment in economic relationship using conventional statistical testing procedure
The results of the bootstrap simulations indicate that rejection frequencies increase with increases in bootstrap sample size, increases in the difference between the asymmetric adjustment speeds and decreases in the amount of noise in the true data generating process used in the application
The bootstrap sample sizes, difference between the asymmetric adjustment parameters and the amount of noise in the data generating process are influential in the power of the test for asymmetry
Summary
Houck (1977) proposes a methodology to investigate asymmetric adjustment in economic relationship using conventional statistical testing procedure This involves specifying asymmetries to affect the direct impact of price increases and decreases. Regardless of the robustness of bootstrap methods and its advantages over the Monte Carlo methods, little work has been done to investigate the power of the Houck’s model in rejecting the null hypothesis of symmetric adjustments using bootstrap technique. The purpose of this paper is to investigate by use of bootstrap methods, the possibility that failure to reject the null hypothesis of symmetry in the Houck’s model is due to low power of the conventional tests.
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