Language fluency and earnings: Estimation with misclassified language indicators

We use panel data to analyze the determinants of speaking fluency and wages of immigrants. Our model takes account of two problems that may bias OLS e stimates of the impact of speaking fluency on earnings. First, subjective v ariables on an ordinal discrete scale, such as self-reported language abili ty, can suffer from misclassification errors. The model decomposes misclass ification errors into a time-persistent and a time-varying component. Secon d, the model accounts for correlated unobserved heterogeneity in language a nd earnings equation, The main finding is that these two generalizations of the standard model both lead to substantial changes in the estimated effec t of speaking fluency on earnings.