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Stochastic Regression Model with Dependent Disturbances
Author(s) -
Choy Kokyo,
Taniguchi Masanobu
Publication year - 2001
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00218
Subject(s) - mathematics , estimator , econometrics , regression , linear regression , regression analysis , long memory , statistics , volatility (finance)
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.