Understanding how the effects of conditional conservatism measurement bias vary with the research context

We re-examine previous seminal studies on conditional conservatism (CC) that apply the asymmetric timeliness (AT) measure of Basu [(1997). The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics, 24(1), 3–37. https://doi.org/10.1016/S0165-4101(97)00014-1] and compare the outcomes with those based on the modified AT (MAT) measure of Badia et al. [(2021). Debiasing the measurement of conditional conservatism. Journal of Accounting Research, 59(4), 1221–1259. https://doi.org/10.1111/1475-679X.12366] and the spread in conditional variances (SCV) measure of Dutta and Patatoukas [(2017). Identifying conditional conservatism in financial accounting data: Theory and evidence. The Accounting Review, 92(4), 191–216. https://doi.org/10.2308/accr-51640]. Our conclusions are threefold. First, all three measures yield similar inferences in interrupted time-series settings that examine the change in CC following a policy mandate. Second, the inferences drawn from the AT measure in studies that model the determinants of CC based on cross-sectional settings are more sensitive to test specifications and research designs. Third, across the three measures, MAT shows the best empirical performance in terms of aligning with existing theories while being less affected by AT bias.