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...

In this paper, we employ both calibration and modern (Bayesian) estimation methods to assess the role of neutral and investment-specific technology shocks in generating fluctuations in hours. Using a neoclassical stochastic growth model, we show how answers are shaped by the identification...

We develop a state-space model with a state-transition equation that takes the form of a functional vector autoregression and stacks macroeconomic aggregates and a cross-sectional density. The measurement equation captures the error in estimating log densities from repeated cross-sectional...

We propose a parsimonious framework for real rigidities, in the form of strategic complementarities, that can generate real and nominal dynamics and match key features of the data across several literatures. Existing menu-cost models featuring strategic complementarities require unrealistically...

We propose a parsimonious framework for real rigidities, in the form of strategic complementarities, that can generate real and nominal dynamics and match key features of the data across several literatures. Existing menu-cost models featuring strategic complementarities require unrealistically...

In this paper, we employ both calibration and modern (Bayesian) estimation methods to assess the role of neutral and investment-specific technology shocks in generating fluctuations in hours. Using a neoclassical stochastic growth model, we show how answers are shaped by the identification...

Dynamic stochastic general equilibrium (DSGE) models use modern macroeconomic theory to explain and predict comovements of aggregate time series over the business cycle and to perform policy analysis. We explain how to use DSGE models for all three purposes – forecasting, story-telling, and...