Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jan, 1984, Volume 52, Issue 1

Nonlinear Regression with Dependent Observations<143:NRWDO>2.0.CO;2-1
p. 143-162

Halbert White, Ian Domowitz

This paper provides general conditions which ensure consistency and asymptotic normality for the nonlinear least squares estimator. These conditions apply to time-series, cross-section, panel, or experimental data for single equations as well as systems of equations. The regression errors may be serially correlated and/or heteroscedastic. For an important special case, we propose a new covariance matrix estimator which is consistent regardless of the presence of heteroscedasticity or serial correlation of unknown form. We also give some new tests for model misspecification, based on the information matrix testing principle.

Log In To View Full Content

Journal News