Estimation of SUR Model with Non-nested Missing Observations

Hae-Shin Hwang and Craig Schulman

Annals of Economics and Statistics, 1996, issue 44, 219-240

Abstract: This paper considers alternative two-step estimators and their small sample properties for the seemingly unrelated regression (SUR) model with non-nested missing observations. A Monte Carlo experiment indicates that alternative estimators have more profound differences in their efficiency, compared to the case of nested missing observations. In particular, the two-step application of the Hartley-Hocking maximum likelihood estimator can realize a significant gain in efficiency. There are substantial losses in efficiency when only the subset of data that has complete observations is used in estimation.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:1996:i:44:p:219-240

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