Add to ORKGShown is a new method for estimating linear models with general time-varying structures such as the State Space Model based on the idea that the models can be represented as a classical regression model. The parameters are all estimated by OLS or GLS. An application of the smoothing to a time-varying AR model is presented.
Standard solution methods for linearised models with rational expectations take the structural param...
The continued increase in availability of economic data in recent years and, more impor-tantly, the ...
We develop a flexible semi-parametric method for the introduction of time-varying parameters in a mo...
This paper shows the formal equivalence of Kalman filtering and smoothing techniques to generalized ...
The paper describes a general approach to the modelling of nonlinear and nonstationary economic syst...
Very preliminary draft: comments welcome, please do not quote without permission of authors. We prop...
This paper provides a new algorithm for estimating state space dynamic models and, as an example, it...
State space modeling provides a unified methodology for treating a wide range of problems in time se...
A multivariate, non-Bayesian, regression-based, or feasible generalized least squares (GLS)-based ap...
Abstract: Known results for the general linear mixed model and its special case, the variance compon...
Standard solution methods for linearised models with rational expectations take the structural param...
This text presents modern developments in time series analysis and focuses on their application to e...
The paper considers local linear regression of a time series model with non-stationary regressors an...
Presents the main statistical tools of econometrics, focusing specifically on modern econometric met...
When linear equality constraints are invariant through time they can be incorporated into estimation...
Standard solution methods for linearised models with rational expectations take the structural param...
The continued increase in availability of economic data in recent years and, more impor-tantly, the ...
We develop a flexible semi-parametric method for the introduction of time-varying parameters in a mo...
This paper shows the formal equivalence of Kalman filtering and smoothing techniques to generalized ...
The paper describes a general approach to the modelling of nonlinear and nonstationary economic syst...
Very preliminary draft: comments welcome, please do not quote without permission of authors. We prop...
This paper provides a new algorithm for estimating state space dynamic models and, as an example, it...
State space modeling provides a unified methodology for treating a wide range of problems in time se...
A multivariate, non-Bayesian, regression-based, or feasible generalized least squares (GLS)-based ap...
Abstract: Known results for the general linear mixed model and its special case, the variance compon...
Standard solution methods for linearised models with rational expectations take the structural param...
This text presents modern developments in time series analysis and focuses on their application to e...
The paper considers local linear regression of a time series model with non-stationary regressors an...
Presents the main statistical tools of econometrics, focusing specifically on modern econometric met...
When linear equality constraints are invariant through time they can be incorporated into estimation...
Standard solution methods for linearised models with rational expectations take the structural param...
The continued increase in availability of economic data in recent years and, more impor-tantly, the ...
We develop a flexible semi-parametric method for the introduction of time-varying parameters in a mo...