Seemingly unrelated nonlinear regressions

Research output: Contribution to journalArticle

129 Citations (Scopus)

Abstract

The article considers the estimation of the parameters of a set of nonlinear regression equations when the responses are contemporaneously but not serially correlated. Conditions are set forth such that the estimator obtained is strongly consistent, asymptotically normally distributed, and asymptotically more efficient than the single-equation least squares estimator. The methods presented allow estimation of the parameters subject to nonlinear restrictions across equations. The article includes a discussion of methods to perform the computations and a Monte Carlo simulation.

Original languageEnglish (US)
Pages (from-to)35-50
Number of pages16
JournalJournal of Econometrics
Volume3
Issue number1
DOIs
StatePublished - Jan 1 1975

Fingerprint

Seemingly Unrelated Regression
Nonlinear Regression
Least Squares Estimator
Monte Carlo Simulation
Restriction
Estimator
Nonlinear regression
Equations
Monte Carlo simulation
Least squares estimator

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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title = "Seemingly unrelated nonlinear regressions",
abstract = "The article considers the estimation of the parameters of a set of nonlinear regression equations when the responses are contemporaneously but not serially correlated. Conditions are set forth such that the estimator obtained is strongly consistent, asymptotically normally distributed, and asymptotically more efficient than the single-equation least squares estimator. The methods presented allow estimation of the parameters subject to nonlinear restrictions across equations. The article includes a discussion of methods to perform the computations and a Monte Carlo simulation.",
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Seemingly unrelated nonlinear regressions. / Gallant, Andrew Ronald.

In: Journal of Econometrics, Vol. 3, No. 1, 01.01.1975, p. 35-50.

Research output: Contribution to journalArticle

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