Artificial regressions

Arbeitspapier

Associated with every popular nonlinear estimation method is at least one 'artificial' linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses, and computing parameter estimates. Several existing artificial regressions are discussed and are shown to satisfy the defining conditions, and a new artificial regression for regression models with heteroskedasticity of unknown form is introduced.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Queen's Economics Department Working Paper ; No. 1038

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Statistical Simulation Methods: General
• Thema: artificial regression ; LM test ; specification test ; Gauss-Newton regression ; one-step estimation ; OPG regression ; double-length regression ; binary response model

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Davidson, Russell ; MacKinnon, James
• Ereignis: Veröffentlichung
• (wer): Queen's University, Department of Economics
• (wo): Kingston (Ontario)
• (wann): 2001

Weitere Informationen

• Handle: http://hdl.handle.net/10419/67825
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ