Artificial Regressions

Russell Davidson, James MacKinnon and J.G.

G.R.E.Q.A.M. from Universite Aix-Marseille III

Abstract: Associated with every popular nonlinear estimationmethod is at least ont "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 paremeter 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.

Keywords: REGRESSION ANALYSIS; ESTIMATION OF PARAMETERS; ECONOMETRIC MODELS (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 22 pages
Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (21)

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Related works:
Working Paper: Artificial Regressions (2001)
Working Paper: Artificial Regressions (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:fth:aixmeq:99a04

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