Pooling data from different sources helps to account for individual-specific hidden factors that can affect results. By using instrumental variables and characteristics of these hidden factors, researchers can test for their presence, identify all model parameters, and calculate efficient estimates. In a study using income data, researchers found that the returns to schooling were significantly higher than previously estimated using different methods.