Publication Type

Working Paper

Publication Date

1-2000

Abstract

We consider the problem of formulating and estimating dynamic regression models with variables observed at different frequencies. The strategy adopted is to define the dynamics of the model in terms of the highest available frequency, and to apply certain lag polynomials to transform the dynamics so that the model is expressed solely in terms of observed variables. A general solution is provided for models with monthly and quarterly observations. We also show how the methods can be extended to models with quarterly and annual observations, and models combining monthly and annual observations.

Keywords

Variables of different frequencies, dynamic regressions, temporal aggregation, systematic sampling, lag polynomials, serial correlation

Discipline

Econometrics

Research Areas

Econometrics

First Page

1

Last Page

22

Publisher

National University of Singapore, Dept of Economics, Paper No. 2000/21

City or Country

Singapore

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Included in

Econometrics Commons

Share

COinS