Showing 1 - 10 of 29
least squares estimate and a second method which uses the best linear combination of the forward and backward predictors. We … derive the estimators for some simple models. We also give a method for calculatingthe exact likelihood of Gaussian linear …
Persistent link: https://www.econbiz.de/10005783581
In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models …
Persistent link: https://www.econbiz.de/10005088308
The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...
Persistent link: https://www.econbiz.de/10005022239
A unit root test is usually carried out by using the regression test introduced by Dickey and Fuller (1979). Under the null hypothesis the series should be a random walk. But a non-stationary series can usually be decomposed into a random walk and a stationary component. This is what is done in...
Persistent link: https://www.econbiz.de/10005669448
This paper considers residuals for time series regression. Despite much literature on visual diagnostics for uncorrelated data, there is little on the autocorrelated case. In order to examine various aspects of the fitted time series regression model, three residuals are considered. The fitted...
Persistent link: https://www.econbiz.de/10005581126
from the Hodrick-Prescott filter, linear detrending and first differencing. Our results indicate that the choice of an …
Persistent link: https://www.econbiz.de/10005587695
The paper contains some implications for applied econometric research. Two important ones are, first, that invertible models, such as AR or VAR models, cannot in general be used to model seasonally adjusted or detrended data. The second one is that to look at the business cycle in detrended...
Persistent link: https://www.econbiz.de/10005774245
The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...
Persistent link: https://www.econbiz.de/10005774248
Persistent link: https://www.econbiz.de/10005775748
This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We...
Persistent link: https://www.econbiz.de/10005779650