LEAST SQUARES ESTIMATION FOR NONLINEAR REGRESSION MODELS WITH HETEROSCEDASTICITY. (11th December 2021)
- Record Type:
- Journal Article
- Title:
- LEAST SQUARES ESTIMATION FOR NONLINEAR REGRESSION MODELS WITH HETEROSCEDASTICITY. (11th December 2021)
- Main Title:
- LEAST SQUARES ESTIMATION FOR NONLINEAR REGRESSION MODELS WITH HETEROSCEDASTICITY
- Authors:
- Wang, Qiying
- Abstract:
- Abstract : This paper develops an asymptotic theory of nonlinear least squares estimation by establishing a new framework that can be easily applied to various nonlinear regression models with heteroscedasticity. As an illustration, we explore an application of the framework to nonlinear regression models with nonstationarity and heteroscedasticity. In addition to these main results, this paper provides a maximum inequality for a class of martingales, which is of interest in its own right.
- Is Part Of:
- Econometric theory. Volume 37:Number 6(2021)
- Journal:
- Econometric theory
- Issue:
- Volume 37:Number 6(2021)
- Issue Display:
- Volume 37, Issue 6 (2021)
- Year:
- 2021
- Volume:
- 37
- Issue:
- 6
- Issue Sort Value:
- 2021-0037-0006-0000
- Page Start:
- 1267
- Page End:
- 1289
- Publication Date:
- 2021-12-11
- Subjects:
- Econometrics -- Periodicals
330.01519505 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=ECT ↗
- DOI:
- 10.1017/S0266466620000493 ↗
- Languages:
- English
- ISSNs:
- 0266-4666
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital Store
- Ingest File:
- 20043.xml