Structural vector autoregressions (VARs) are widely used to trace out the effect of monetary policy innovations on the economy.However, the sparse information sets typically used in these empirical models lead to at least two potential problems with the results.First, to the extent that central banks and the private sector have information not reflected in the VAR, the measurement of policy innovations is likely to be contaminated.A second problem is that impulse responses can be observed only for the included variables, which generally constitute only a small subset of the variables that the researcher and policymaker care about.In this paper we investigate one potential solution to this limited information problem, which combines the standard structural VAR analysis with recent developments in factor analysis for large data sets.We find that the information that our factor-augmented VAR (FAVAR) methodology exploits is indeed important to properly identify the monetary transmission mechanism.Overall, our results provide a comprehensive and coherent picture of the effect of monetary policy on the economy.

We investigate the implications of changes in the structure of the U.S. economy for monetary policy effectiveness. Estimating a vector autoregression over the pre- and post-1980 periods, we provide evidence of a reduced effect of monetary policy shocks in the latter period. We estimate a structural model that replicates well the economy's response in both periods, and perform counterfactual experiments to determine the source of the change in the monetary transmission mechanism and in the economy's volatility. We find that by responding more strongly to inflation expectations, monetary policy has stabilized the economy more effectively in the post-1980 period.

This paper shows that the recent evidence that disaggregated prices are volatile does not necessarily challenge the hypothesis of price rigidity used in a large class of macroeconomic models. We document the effect of macroeconomic and sectoral disturbances by estimating a factor-augmented vector autoregression using a large set of macroeconomic indicators and disaggregated prices. Our main finding is that disaggregated prices appear sticky in response to macroeconomic and monetary disturbances, but flexible in response to sector-specific shocks. The observed flexibility of disaggregated prices reflects the fact that sector-specific shocks account on average for 85 percent of their monthly fluctuations.