Computational and statistical efficiency of semiparametric gls estimators

Joel L. Horowitz, George R. Neumann

Research output: Contribution to journalArticlepeer-review

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In this note, we report a dramatic improvement in the computational efficiency of semiparametric generalized least squares(SGLS) estimation. Computation of SGLS estimates no longer presents serious problems with data sets of moderate size. We also correct a numerical error in the standard errors of the SGLS estimates reported in our recent paper in this journal (Horowitz and Neumann, 1987). The corrected standard errors of SGLS are comparable to those we reported for quantile estimates.
Original languageEnglish
Pages (from-to)223-225
JournalEconometric Reviews
StatePublished - 1989


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