The paper by Steven Haider and Gary Solon examines the relationship between current and lifetime earnings, challenging the traditional errors-in-variables model used in economic research. Using Social Security earnings records from the Health and Retirement Study, the authors find that the association between current and lifetime earnings varies systematically over the life cycle, deviating from the textbook model. They estimate the slope coefficients in the regression of current earnings on lifetime earnings and vice versa, which are shown to be non-constant. This departure from the textbook model has implications for the accuracy of econometric analyses that use current earnings as a proxy for lifetime earnings, potentially leading to attenuation or amplification biases. The findings highlight the need for more sophisticated methods to account for measurement errors when using short-term earnings data in economic research.The paper by Steven Haider and Gary Solon examines the relationship between current and lifetime earnings, challenging the traditional errors-in-variables model used in economic research. Using Social Security earnings records from the Health and Retirement Study, the authors find that the association between current and lifetime earnings varies systematically over the life cycle, deviating from the textbook model. They estimate the slope coefficients in the regression of current earnings on lifetime earnings and vice versa, which are shown to be non-constant. This departure from the textbook model has implications for the accuracy of econometric analyses that use current earnings as a proxy for lifetime earnings, potentially leading to attenuation or amplification biases. The findings highlight the need for more sophisticated methods to account for measurement errors when using short-term earnings data in economic research.