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- W1539739189 abstract "This paper shows how asymptotically valid inference in regression models based on the weighted least squares (WLS) estimator can be obtained even when the model for reweighting the data is misspecified. Like the ordinary least squares estimator, the WLS estimator can be accompanied by heterokedasticty-consistent (HC) standard errors without knowledge of the functional form of conditional heteroskedasticity. First, we provide rigorous proofs under reasonable assumptions; second, we provide numerical support in favor of this approach. Indeed, a Monte Carly study demonstrates attractive finite-sample properties compared to the status quo, both in terms of estimation and making inference." @default.
- W1539739189 created "2016-06-24" @default.
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- W1539739189 date "2016-01-01" @default.
- W1539739189 modified "2023-09-23" @default.
- W1539739189 title "Resurrecting Weighted Least Squares" @default.
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- W1539739189 doi "https://doi.org/10.2139/ssrn.2491081" @default.
- W1539739189 hasPublicationYear "2016" @default.
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