LEAST ABSOLUTE DEVIATION ESTIMATION FOR UNIT ROOT PROCESSES WITH GARCH ERRORS
Keyword(s):
This paper considers a local least absolute deviation estimation for unit root processes with generalized autoregressive conditional heteroskedastic (GARCH) errors and derives its asymptotic properties under only finite second-order moment for both errors and innovations. When the innovations are symmetrically distributed, the asymptotic distribution of the estimated unit root is shown to be a functional of a bivariate Brownian motion, and then two unit root tests are derived. The simulation results demonstrate that the tests outperform those based on the Gaussian quasi maximum likelihood estimators with heavy-tailed innovations and those based on the simple least absolute deviation estimators.
Keyword(s):
2014 ◽
Vol 94
◽
pp. 69-76
◽
2018 ◽
Vol 49
(4)
◽
pp. 809-826
1993 ◽
Vol 67
(2)
◽
pp. 272-277
◽
2018 ◽
Vol 11
(3)
◽
pp. 47
◽