At the present time, there exists an important and growing econometric literature that deals with the application of multivariate-ARCH models to a variety of economic and financial data. However, the properties of the estimation procedures that are used have not yet been fully explored. This...

Newey and Smith [Newey, W.K., Smith, R.J., 2004. Higher order properties of GMM and empirical likelihood estimators. Econometrica 72, 219-255] analyzed the second order biases of GMM and GEL estimators under independence. Anatolyev [Anatolyev, S., 2005. GMM, GEL, serial correlation, and...

Kinal (1980) showed that k-class estimators for which k  1 possess all necessary higher moments. A bias approximation to order T- 2 is derived for the general k-class estimator extending the earlier result for 2SLS of Mikhail (1972) thus improving our knowledge of a potentially...

The small sample bias of the least-squares coefficient estimator is examined in the dynamic multiple linear regression model with normally distributed whitenoise disturbances and an arbitrary number of regressors which are all exogenous except for the one-period lagged-dependent variable. We...

This discussion paper led to a publication in <A href="http://onlinelibrary.wiley.com/doi/10.1111/j.1368-423X.2005.00156.x/abstract;jsessionid=146255EE7C2E41B3C91E06CCA08C53C7.d01t01?systemMessage=Wiley+Online+Library+will+be+disrupted+on+25+August+from+13%3A00-15%3A00+BST+%2808%3A00-10%3A00+EDT%29+for+essential+maintenance">'The Econometrics Journal'</A>.<P>Asymptotic expansions are employed in a dynamic regression model with a unit root inorder to find approximations for the bias, the variance and for the mean squared error of theleast-squares estimator of all coefficients....</p></a>

In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. Using expansion techniques an approximation is obtained to the bias in variance estimation yielding a bias corrected variance estimator. This is achieved for both the...

An approximation to order T−2 is obtained for the bias of the full vector of least-squares estimates obtained from a sample of size T in general stable but not necessarily stationary ARX(1) models with normal disturbances. This yields generalizations, allowing for various forms of initial...

In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. From expansions of the coefficient variance and its estimator we obtain an approximation to the bias in variance es- timation and a bias corrected variance estimator, for...

In the classical regression model with fixed regressors the statistic S 2 , i.e. the sum of squared residuals (SSR) divided by the number of degrees of freedom, is an unbiased estimator of the variance of the disturbances. If the model is dynamic and contains lagged-dependent explanatory...

Asymptotic expansions are employed in a dynamic regression model with a unit root in order to find approximations for the bias, the variance and for the mean squared error of the least-squares estimator of all coefficients. It is found that in this particular context such expansions exist only...