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Cited by 356

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

An Asymptotic Theory for Estimating Beta‐Pricing Models Using Cross‐Sectional Regression

Jagannathan, Ravi, Wang, Zhenyu·1998·The Journal of Finance
DOI 10.1111/0022-1082.00053
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Abstract

Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two‐stage cross‐sectional regression method shows that the standard errors produced by the Fama–MacBeth procedure do not necessarily overstate the precision of the risk premium estimates. When factors are misspecified, estimators for risk premiums can be biased, and the t‐value of a premium may converge to infinity in probability even when the true premium is zero. However, when a beta‐pricing model is misspecified, the t‐values for firm characteristics generally converge to infinity in probability, which supports the use of firm characteristics in cross‐sectional regressions for detecting model misspecification.

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Metadata

Authors
Jagannathan, R., & Wang, Z.
Venue
The Journal of Finance
Publisher
Wiley
Published
1998-08
Volume
53
Issue
4
Pages
1285-1309
ISSN
  • 0022-1082 (ISSN-L)
  • 1540-6261
DOI
10.1111/0022-1082.00053
OpenAlex
W2088603504
Cited by
356
References
2
FWCI
14.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An Asymptotic Theory for Estimating Beta‐Pricing Models Using Cross‐Sectional Regression. https://app.cochat.ai/papers/10.1111/0022-1082.00053
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Jagannathan, R., & Wang, Z. (1998). An Asymptotic Theory for Estimating Beta‐Pricing Models Using Cross‐Sectional Regression. The Journal of Finance. https://doi.org/10.1111/0022-1082.00053

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