The article discusses a method called two-pass cross-sectional regression used to estimate and test asset pricing models. The researchers propose a way to calculate standard errors that are robust to model misspecification. They also develop a test to compare the performance of different pricing models. The study shows that existing models may not perfectly reflect reality, and their new approach can improve the accuracy of estimating risk premia in asset pricing models.