Standard error: use of standard errors in a regression to correct for serial correlation

(Sample Case)
An analyst observes that two reputable statistical analysis firms estimate betas for a company A stock at 0.85 and 1.10. He concluded that the differences between his beta estimate and the published estimates resulted from his use of standard errors to correct for serial correlation; the other firms did not make a similar adjustment.


False
Using adjusted standard errors will change the t-statistics and potentially the statistical significance, but not the beta estimate itself.