TY - JOUR
T1 - Stochastic regression model with dependent disturbances
AU - Choy, Kokyo
AU - Taniguchi, Masanobu
PY - 2001/3
Y1 - 2001/3
N2 - In this paper, we consider the estimation of the coefficient of a stochastic regression model whose explanatory variables and disturbances are permitted to exhibit short-memory or long-memory dependence. Three estimators of the coefficient are proposed. A variety of their asymptotics are illuminated under various assumptions on the explanatory variables and the disturbances. Numerical studies of the theoretical results are given. They show some unexpected aspects of the asymptotics of the three estimators.
AB - In this paper, we consider the estimation of the coefficient of a stochastic regression model whose explanatory variables and disturbances are permitted to exhibit short-memory or long-memory dependence. Three estimators of the coefficient are proposed. A variety of their asymptotics are illuminated under various assumptions on the explanatory variables and the disturbances. Numerical studies of the theoretical results are given. They show some unexpected aspects of the asymptotics of the three estimators.
KW - Best linear unbiased estimator (BLUE)
KW - Least squares estimator (LSE)
KW - Long-memory process
KW - Ratio estimator (RE)
KW - Short-memory process
KW - Spectral density
KW - Stationary linear process
KW - Stochastic regression model
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U2 - 10.1111/1467-9892.00218
DO - 10.1111/1467-9892.00218
M3 - Article
AN - SCOPUS:0039296754
VL - 22
SP - 175
EP - 196
JO - Journal of Time Series Analysis
JF - Journal of Time Series Analysis
SN - 0143-9782
IS - 2
ER -