<ul><li>The accuracy of coefficient estimates in regression is assessed by considering their variability, which is captured through standard errors and the covariance matrix.</li><li>The standard error is the standard deviation of the coefficient estimates obtained from different datasets, indicating the uncertainty around the estimated coefficients.</li><li>The unbiased nature of OLS coefficient estimates means that, on average, the estimates from different datasets will converge towards the true population parameter.</li><li>Confidence intervals are used to determine the range within which we can be a certain level of confidence (e.g., 95%) that the true coefficient value lies.</li></ul>

Assessing the Accuracy of Coefficient Estimates

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