Two-way cluster-robust standard errors A methodological note on what has been done and what has not been done in accounting and finance research CQU.pdf (577.53 kB)
Two-way cluster-robust standard errors: A methodological note on what has been done and what has not been done in accounting and finance research
There is a widely application of panel data estimation in accounting and finance research. The approach is well accepted because the pooled panel data provide a rich information as compared to either cross-sections or time series data structure. However, within panel data structure variables of interest are often cross-sectionally and serially correlated and as a result OLS standard errors would be biased when panel data are used in the regression analysis. Several techniques for example firm dummy variables, one-way cluster-robust standard errors, Fama-MacBeth procedure, and Newey-West procedure are documented as a solution in analyzing panel data. These techniques to some extent correct either cross-sectional correlation or serial correlation, none is designed to deal with correlations in two dimensions (across firms and across time). With panel data structure correlations are more likely to appear in two dimensions with both firm effects and time effects, this study suggests that two-way cluster-robust standard errors approach can correct both cross-sectional correlation and serial correlation and therefore should be considered as a better alternative in handling panel data. Nonetheless, two-way cluster-robust standard errors approach could be biased when applying to a finite sample, this study uses a real data set and constructs an empirical application of the estimation procedures of two-way cluster-robust regression estimation with and without finite-sample adjustment and the results show that finite-sample adjusted estimates is superior than unadjusted asymptotic estimates
History
Volume
8Issue
9Start Page
1639End Page
1655Number of Pages
17eISSN
2162-2086ISSN
2162-2078Publisher
Scientific Research Publishing, Inc,Publisher DOI
Additional Rights
CC BY 4.0Peer Reviewed
- Yes
Open Access
- Yes
Acceptance Date
2018-06-12External Author Affiliations
Minghsin University of Science and Technology, Chinese Culture University, Taiwan;Era Eligible
- Yes