The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Joakim Westerlund. Photo.

Joakim Westerlund

Professor, Programme director – Master of Data Analytics and Business Economics

Joakim Westerlund. Photo.

On CCE estimation of factor-augmented models when regressors are not linear in the factors

Author

  • Ignace De Vos
  • Joakim Westerlund

Summary, in English

In empirical research it is often of interest to include non-linear functions of the explanatory variables, such as squares or interactions, in the specification. A popular technique to estimate such models in the presence of common factors is the Common Correlated Effects (CCE) methodology. However, this approach assumes that the regressors are linear in the factors, which is not the case if variables enter non-linearly. In this note we show how CCE should be implemented when some regressors violate the linear factor model assumption.

Department/s

  • Department of Economics

Publishing year

2019-05

Language

English

Pages

5-7

Publication/Series

Economics Letters

Volume

178

Document type

Journal article

Publisher

Elsevier

Topic

  • Economics
  • Probability Theory and Statistics

Keywords

  • CCE
  • Non-linear regressors
  • Factor-augmented regression models

Status

Published

ISBN/ISSN/Other

  • ISSN: 0165-1765