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.

Recent research provides evidence of important changes in the U.S. economic environment over the last 40 years. This appears to be associated with an alteration of the monetary transmission mechanism. In this paper we investigate the implications for the evolution of monetary policy effectiveness. Using an identified VAR over the pre-and post-1980 periods we first provide evidence of a reduction in the effect of monetary policy shocks in the latter period. We then present and estimate a fully specified model that replicates well the dynamic response of output, inflation, and the federal funds rate to monetary policy shocks in both periods. Using the estimated structural model, we perform counterfactual experiments to determine the source of the observed change in the monetary transmission mechanism, as well as in the economy's response to supply and demand shocks. The main finding is that monetary policy has been more stabilizing in the recent past, as a result of both the way it has responded to shocks, but also by ruling out non-fundamental fluctuations.JEL Classification: E52, E3, C32

Factors estimated from large macroeconomic panels are being used in an increasing number of applications. However, little is known about how the size and the composition of the data affect the factor estimates. In this paper, we question whether it is possible to use more series to extract the factors, and yet the resulting factors are less useful for forecasting, and the answer is yes. Such a problem tends to arise when the idiosyncratic errors are cross-correlated. It can also arise if forecasting power is provided by a factor that is dominant in a small dataset but is a dominated factor in a larger dataset. In a real time forecasting exercise, we find that factors extracted from as few as 40 pre-screened series often yield satisfactory or even better results than using all 147 series. Weighting the data by their properties when constructing the factors also lead to improved forecasts. Our simulation analysis is unique in that special attention is paid to cross-correlated idiosyncratic errors, and we also allow the factors to have stronger loadings on some groups of series than others. It thus allows us to better understand the properties of the principal components estimator in empirical applications.

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 sectorspecific shocks. The observed flexibility of disaggregated prices reflects the fact that sector-specific shocks account on average for 85 percent of their monthly fluctuations. (JEL E13, E31, E32, E52)

No abstract

Recent research provides evidence of important changes in the U.S. economic environment over the last 40 years. This appears to be associated with an alteration of the monetary transmission mechanism. In this paper we investigate the implications for the evolution of monetary policy effectiveness. Using an identified VAR over the pre-and post-1980 periods we first provide evidence of a reduction in the effect of monetary policy shocks in the latter period. We then present and estimate a fully specified model that replicates well the dynamic response of output, inflation, and the federal funds rate to monetary policy shocks in both periods. Using the estimated structural model, we perform counterfactual experiments to determine the source of the observed change in the monetary transmission mechanism, as well as in the economy's response to supply and demand shocks. The main finding is that monetary policy has been more stabilizing in the recent past, as a result of both the way it has responded to shocks, but also by ruling out non-fundamental fluctuations.JEL Classification: E52, E3, C32

We thank Mario Forni and Marco Lippi for useful comments and for sharing their computer codes for the one-sided estimation of the generalized dynamic factor model. We also thank James Stock and Mark Watson for many helpful discussions.

Despite the large amount of empirical research on monetary policy rules, there is surprisingly little consensus on the nature or even the existence of changes in the conduct of U.S. monetary policy. Three issues appear central to this disagreement: (1) the specific type of changes in the policy coefficients, (2) the treatment of heteroskedasticity, and (3) the real-time nature of the data used. This paper addresses these issues in the context of forward-looking Taylor rules with drifting coefficients. The estimation is based on real-time data and accounts for the presence of heteroskedasticity in the policy shock. The findings suggest important but gradual changes in the rule coefficients, not adequately captured by the usual split-sample estimation. In contrast to Orphanides (2002, 2003), I find that the Fed's response to the real-time forecast of inflation was weak in the second half of the 1970s, perhaps not satisfying Taylor's principle as suggested by Clarida, Gali, and Gertler (2000). However, the response to inflation was strong before 1973 and gradually regained strength from the early 1980s onward. Moreover, as in Orphanides (2003), the Fed's response to real activity fell substantially and lastingly during the 1970s.