Corporate governance research is often limited in its ability to employ within-firm estimators, which address time-invariant endogeneity, when the variables of interest exhibit low time variation (for example, ownership and board independence). The problem is further exacerbated if data for multiple points in time needs to be hand-collected. We offer simulation-based methodological guidance about the statistical power of within-firm estimators in the presence of low time variation. We illustrate the usefulness of our simulation results by replicating two influential studies on ownership and board independence and extending them with a within-firm estimator. Based on widely used databases as well as a novel granular database, we document the different degrees and nature of time variation of ownership and board independence across jurisdictions and subgroups by listed status, family control and complexity of ownership structure. These differences in time variation are associated with different power properties as identified by our simulation results. Researchers can use our findings to make empirical design decisions and informed choices about frequency of sampling and/or hand collection of fewer non-consecutive time periods that ensures sufficient time variation and statistical power.
|Number of pages||60|
|Publication status||Submitted - 5 Apr 2020|
- business groups
- family firms
- cross-sectional and time-series variation
- ultimate cash flow rights