Description
hetwals computes the WALS estimates of a linear regression model with multiplicative heteroskedasticity, using a feasible generalized least squares (FGLS) strategy. In the first step, we estimate the parameters of the variance function from the unrestricted model using either the ML estimator or Harvey's two-step GLS estimator (Harvey 1976). In the second step, we fit a weighted WALS regression with analytic weights equal to the reciprocals of the estimated variances.
Help files
After installation, you can view the estimation options by typing in Stata
help hetwals
and the post-estimation options by typing
help hetwals postestimation
Key references (in chronological order)
Harvey, A. C. (1976). Estimating regression models with multiplicative heteroscedasticity. Econometrica, 44, 461–465.
Magnus, J. R., Wan, A. T. K., and Zhang, X. (2011). Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market. Computational Statistics & Data Analysis, 55, 1331-1341.
De Luca, G., and Magnus, J. R. (2025c). Weighted-average least squares: Beyond the simple linear regression model. The Stata Journal, 25(4), 1-40.