Note(s): Table 6, Panel A, show the results of estimation of Equation (1) using OLS regressions with DisclosureTimeliness as the dependent variable. Panel B shows the results of estimation of Equation (1) with an alternative dependent variable, DisclosureJumpQuarter, using a negative binomial regression due to the dependent variable taking the discrete values from 1 to 5. Each specification includes SIC 2-digit industry fixed effects. Columns 1 and 3 in each panel include the separate variables meant to proxy for the complexity in the firms’ implementation process (NumBusSegs, Warranty, MultipleElementArrangement, Rebate and SalesVolatility). Columns 2 and 4 include the fitted values of a principal component analysis of these five variables plus ASC606ImpactMagnitude to reduce the noise of these multiple variables and construct one, less noisy variable, ComplexityPCA. In columns 1 and 2, the independent variable of interest is the Negative606Impact indicator variable and its interaction with the absolute value of the effect on net income, ASC606ImpactMagnitude. In columns 3 and 4, those two variables are replaced by the quintile-ranked variable for the ASC 606 effect on net income (Quintile606Impact). Variables are defined in Appendix A. Robust t-statistics are in parenthesis, with statistical significance denoted as ***p < 0.01, **p < 0.05, *p < 0.1