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Type | Working Paper |
Scope | Discipline-based scholarship |
Title | Resurrecting weighted least squares |
Organization Unit | |
Authors |
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Language |
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Institution | University of Zurich |
Series Name | Working paper series / Department of Economics |
Number | 172 |
ISSN | 1664-7041 |
Number of Pages | 48 |
Date | 2016 |
Abstract Text | 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. |
Official URL | http://www.econ.uzh.ch/static/wp/econwp172.pdf |
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PDF File | Download from ZORA |
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Keywords | Conditional heteroskedasticity, HC standard errors, weighted least squares, ökonometrisches Modell, gewichtete Methode der kleinsten Quadrate, Heteroskedastizität |
Additional Information | Revised version |