During this era, applied econometrics crystallized around explicit handling of specification errors, selection bias, and unobserved heterogeneity, paired with rigorous inference. Researchers integrated cross-sectional and time-series data to estimate behavioral functions and to identify effects under varying assumptions, while embracing model diagnostics to guard against misspecification. The period also saw the rise of resampling and efficient estimation techniques to assess predictive accuracy and robustness.