We measure soft information contained in the congressional testimonies of U.S. Federal Reserve Chairs and analyze its effect on financial markets. Our measures of Fed Chairs' emotions expressed in words, voice and facial expressions are created using machine learning. Increases in the Chair's...

Estimation and inference for weighted nonlinear least squares regressions are examined for the case in which the regressors are stochastic, rather than fixed, and where erros may be both heteroscedastic and serially correlated. The usual least squares parameter covarience matrix estimator may be...