Abstract
The Breusch-Godfrey LM test is one of the most popular tests for autocorrelation. However, it has been shown that the LM test may be erroneous when there exist heteroskedastic errors in a regression model. Recently, remedies have been proposed by Godfrey and Tremayne [9] and Shim et al. [21]. This paper suggests three wild-bootstrapped variance-ratio (WB-VR) tests for autocorrelation in the presence of heteroskedasticity. We show through a Monte Carlo simulation that our WB-VR tests have better small sample properties and are robust to the structure of heteroskedasticity.
| Original language | English |
|---|---|
| Pages (from-to) | 1531-1542 |
| Number of pages | 12 |
| Journal | Journal of Applied Statistics |
| Volume | 39 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2012 Jul 1 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
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Wild-bootstrapped variance-ratio test for autocorrelation in the presence of heteroskedasticity. / Jeong, Jinook; Kang, Byunguk.
In: Journal of Applied Statistics, Vol. 39, No. 7, 01.07.2012, p. 1531-1542.Research output: Contribution to journal › Article
TY - JOUR
T1 - Wild-bootstrapped variance-ratio test for autocorrelation in the presence of heteroskedasticity
AU - Jeong, Jinook
AU - Kang, Byunguk
PY - 2012/7/1
Y1 - 2012/7/1
N2 - The Breusch-Godfrey LM test is one of the most popular tests for autocorrelation. However, it has been shown that the LM test may be erroneous when there exist heteroskedastic errors in a regression model. Recently, remedies have been proposed by Godfrey and Tremayne [9] and Shim et al. [21]. This paper suggests three wild-bootstrapped variance-ratio (WB-VR) tests for autocorrelation in the presence of heteroskedasticity. We show through a Monte Carlo simulation that our WB-VR tests have better small sample properties and are robust to the structure of heteroskedasticity.
AB - The Breusch-Godfrey LM test is one of the most popular tests for autocorrelation. However, it has been shown that the LM test may be erroneous when there exist heteroskedastic errors in a regression model. Recently, remedies have been proposed by Godfrey and Tremayne [9] and Shim et al. [21]. This paper suggests three wild-bootstrapped variance-ratio (WB-VR) tests for autocorrelation in the presence of heteroskedasticity. We show through a Monte Carlo simulation that our WB-VR tests have better small sample properties and are robust to the structure of heteroskedasticity.
UR - http://www.scopus.com/inward/record.url?scp=84861856975&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861856975&partnerID=8YFLogxK
U2 - 10.1080/02664763.2012.658360
DO - 10.1080/02664763.2012.658360
M3 - Article
AN - SCOPUS:84861856975
VL - 39
SP - 1531
EP - 1542
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
SN - 0266-4763
IS - 7
ER -