Abstract #300212

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JSM 2003 Abstract #300212
Activity Number: 328
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Business & Economics Statistics Section
Abstract - #300212
Title: Effect of Non-Normality on Tests of Random Walk Models Against Regression Models
Author(s): Leslie Chandrakantha*+ and Swamy A.V.B. Paravastu and Jatinder Mehta
Companies: John Jay College/CUNY and and Temple University
Address: 445 W 59th St., New York, NY, 10019-1104,
Keywords: random walk ; hypothesis testing ; power of the test ; non-normality
Abstract:

In practice, the functional forms of regression models and the complete lists of their explanatory variables would not be known. Fortunately, this fact is not an obstacle to our success in deriving tests of random walk models against a large class of regression models assuming normally distributed error terms as Chandrakantha (1990) has shown. The powers of these tests have also been investigated by Chandrakantha. However, these tests can be misleading as almost valueless unless in most situations met in practice they are insensitive to departures from normality. We study the effect of departures from normality on these tests of hypothesis. We assume that the error term follows an exponential power distribution.

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