The four most readily available tests of autocorrelation in dynamic
models namely Durbin’s M test,
Durbin’s H test, Breusch Godfrey test
(BGF) and Ljung & Box (Q)
test are compared in terms of their power for varying sample sizes, levels of
autocorrelation and significance using Monte Carlo simulations in STATA. Power
comparison reveals that the Durbin M
test is the best option for testing the hypothesis of no autocorrelation in
dynamic models for all sample sizes. Breusch Godfrey’s test has comparable and
at times minutely better performance than Durbin’s M test however in small sample sizes, Durbin’s M test outperforms the Breusch Godfrey test in terms of power. The
Durbin H and the Ljung & Box Q
tests consistently occupy the second last and last positions respectively in
terms of power performance with maximum power gap of 63 & 60% respectively
from the best test (M test).
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | September 25, 2019 |
Submission Date | July 24, 2018 |
Published in Issue | Year 2019 Volume: 11 Issue: 2 |