Small sample properties of the conditional least squares estimator in SETAR models
نویسنده
چکیده
This note considers the small sample performance of the conditional least squares estimator of the threshold parameters in nonlinear threshold and particularly self exciting threshold autoregressive (SETAR) models. It is shown that despite the superconsistency of the threshold parameter estimates the estimator performs poorly in samples of sizes usually encountered in macroeconomics. 2000 Elsevier Science S.A. All rights reserved.
منابع مشابه
Eco 2009/42 Department of Economics Generalized Least Squares Estimation for Cointegration Parameters under Conditional Heteroskedasticity
In the presence of generalized conditional heteroscedasticity (GARCH) in the residuals of a vector error correction model (VECM), maximum likelihood (ML) estimation of the cointegration parameters has been shown to be efficient. On the other hand, full ML estimation of VECMs with GARCH residuals is computationally difficult and may not be feasible for larger models. Moreover, ML estimation of V...
متن کاملResurrecting Weighted Least Squares
This paper shows how asymptotically valid inference in regression models based on the weighted least squares (WLS) estimator can be obtained even when the model for reweighting the data is misspecified. Like the ordinary least squares estimator, the WLS estimator can be accompanied by heterokedasticty-consistent (HC) standard errors without knowledge of the functional form of conditional hetero...
متن کامل2-step Estimation of Semiparametric Censored Regression Models
It has been shown by Powell (1986a,b) that p n-consistent estimation of the slope parameters in the linear censored regression model is possible under a conditional quantile and a conditional symmetry restriction on the error term, respectively. While the proposed estimators have desirable asymptotic properties, simulation studies have shown these estimators to exhibit a small sample bias in th...
متن کاملEffects of Outliers on the Identification and Estimation of Garch Models
This paper analyses how outliers affect the identification of conditional heteroscedasticity and the estimation of generalized autoregressive conditionally heteroscedastic (GARCH) models. First, we derive the asymptotic biases of the sample autocorrelations of squared observations generated by stationary processes and show that the properties of some conditional homoscedasticity tests can be di...
متن کاملConditional Inference for Possibly Unidenti...ed Structural Equations
The possibility that a structural equation may not be identi...ed casts doubt on the measures of estimator precision that are normally used. We argue that the observed identi...ability test statistic is directly relevant to the precision with which the structural parameters can be estimated, and hence argue that inference in such models should be conditioned on the observed value of that statis...
متن کامل