Asymptotic Variance Approximations for Invariant Estimators in Uncertain Asset-Pricing Models

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Title: Asymptotic Variance Approximations for Invariant Estimators in Uncertain Asset-Pricing Models
Authors: Robotti, C
Gospodinov, N
Kan, R
Item Type: Journal Article
Abstract: This paper derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously-updated GMM estimators in models that may not satisfy the fundamental assetpricing restrictions in population. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. While the results for the maximum likelihood estimator are only applicable to linear asset-pricing models, the asymptotic distribution of the continuously-updated GMM estimator is derived for general, possibly nonlinear, models. The large corrections in the asymptotic variances, that arise from explicitly incorporating model misspecification in the analysis, are illustrated using simulations and an empirical application.
Date of Acceptance: 18-Feb-2016
URI: http://hdl.handle.net/10044/1/29570
ISSN: 1532-4168
Publisher: Taylor & Francis
Journal / Book Title: Econometric Reviews
Keywords: Asset pricing
Model misspecification
Continuously-updated GMM
Maximum likelihood
Asymptotic approximation
Misspecification-robust tests
Econometrics
1403 Econometrics
Publication Status: Accepted
Appears in Collections:Imperial College Business School



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