(Slides)
Stylized facts on output and interest rates in the U.S. have so far proved hard to match with simple economic models of the business cycle. But model predictions hinge on the joint specification of economic structure and a set of driving processes. In a typical model economy, different shocks induce different comovements, such that the overall pattern depends as much on the specified transmission mechanisms from shocks to outcomes, as well as on the composition of these driving processes. I estimate covariances of output, nominal and real interest rate conditional on several shocks, since such evidence has mostly been lacking in previous discussions of the output-interest rate puzzle.
Conditional on shocks to neutral technology and monetary policy, the results square with simple models, like the standard RBC model or a textbook version of the New Keynesian model. In addition, news about future productivity help to explain the overall anti-cyclical behavior of the real rate. Over the Great Moderation, neutral technology shocks are more dominant in explaining comovements between output and interest rates, and the real rate is in fact pro-cyclical. During the Great Inflation, permanent shocks to inflation account for the anti-cyclical behavior of the real rate and its inverted leading indicator property.
(Slides)
In models of monetary policy, discretionary policymaking often lacks the ability to manage public beliefs, which explains the theoretical appeal of policy rules and commitment strategies. But as shown in this paper, when a policymaker possesses private information, belief management becomes an integral part of optimal discretion policies and improves their performance.
Solving for optimal policy in a simple New Keynesian model, this paper shows how discretionary losses are reduced when the policymaker has private information. Furthermore, disinflations are pursued more vigorously, when the hidden information problem is larger, even when inflation is partly backward-looking.
( Slides)
No, not really. In response to concerns about the reliability of SVARs, it has previously been proposed to combine OLS estimates of a VAR with non-parametric estimates of the spectral density. But as shown here, spectral estimators are no panacea for implementing long-run restrictions. They suffer from small sample and misspecification biases just as VARs do.
In addition, when combining VAR coefficients with non-parametric estimates of the spectral density, it is important to consistently account for information embedded in the non-parametric estimates about serial correlation in VAR residuals. This paper uses a spectral factorization to ensure a correct representation of the data's variance. But this cannot overcome the fundamental problem of having to estimate the long-run dynamics of macroeconomic data in moderately sized samples.
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