We develop a novel method for the identification of monetary policy shocks. By applying natural language processing techniques to documents that Federal Reserve staff prepare in advance of policy decisions, we capture the Fed's information set. Using machine learning techniques, we then predict...

We develop a simple menu-cost model with non-constant elasticity of demand that features idiosyncratic productivity and demand shocks. The model is calibrated to match firm-level productivity and demand processes estimated from U.S. data. Despite its simplicity, the calibrated model delivers...