Inference with Dependent Data in Accounting and Finance Applications

Posted: 17 May 2019

See all articles by Timothy G. Conley

Timothy G. Conley

University of Chicago - Booth School of Business

Sílvia Gonçalves

Independent

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics

Multiple version iconThere are 2 versions of this paper

Date Written: September 1, 2018

Abstract

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.

Keywords: hypothesis testing; confidence intervals; robust standard error estimation; spatial dependence; bootstrap; fixed-effects

JEL Classification: C12; C23

Suggested Citation

Conley, Timothy G. and Gonçalves, Sílvia and Hansen, Christian, Inference with Dependent Data in Accounting and Finance Applications (September 1, 2018). Journal of Accounting Research, Vol. 56, No. 4, 2018. Available at SSRN: https://ssrn.com/abstract=3374508

Timothy G. Conley

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-7281 (Phone)

Sílvia Gonçalves

Independent ( email )

No Address Available

Christian Hansen (Contact Author)

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States
773-834-1702 (Phone)

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