Mertens and Ravn (2013) estimate impulse response functions (IRFs) from income tax changes in a structural vector autoregression (SVAR) by using narrative accounts of tax liability changes as proxy variables. To produce confidence intervals for their IRFs, they use a residual-based wild bootstrap, which has subsequently become popular in the proxy SVAR literature. We argue that their wild bootstrap is not valid, producing confidence intervals that are much too small. Using a residual-based moving block bootstrap that is proven to be asymptotically valid, we reestimate confidence intervals for Mertens and Ravn’s (2013) IRFs and find no statistically significant effects of tax changes on output, labor, and investment. (JEL E23, E62, H24, H25, H31, H32)

This paper develops a simple estimator to identify structural shocks in vector autoregressions (VARs) by using a proxy variable that is correlated with the structural shock of interest but uncorrelated with other structural shocks. When the proxy variable is weak, modeled as local to zero, the estimator is inconsistent and converges to a distribution. This limiting distribution is characterized, and the estimator is shown to be asymptotically biased when the proxy variable is weak. The F statistic from the projection of the proxy variable onto the VAR errors can be used to test for a weak proxy variable, and the critical values for different VAR dimensions, levels of asymptotic bias, and levels of statistical signifi cance are provided. An important feature of this F statistic is that its asymptotic distribution does not depend on parameters that need to be estimated.

I show that the nature of the Federal Open Market Committee’s (FOMC’s) forward guidance language shapes the private sector’s responses to monetary policy statements. From February 2000 to June 2003, the FOMC only gave forward guidance about economic outlook risks, and a decrease in the expected federal funds rate path caused stock prices to fall, GDP growth forecasts to fall, and the unemployment rate to rise. From August 2003 to May 2006, the FOMC added forward guidance about policy inclinations, and a decrease in the expected federal funds rate path had the opposite effects. These results suggest that forward guidance that emphasizes economic outlook risks causes stronger information effects than forward guidance that emphasizes policy inclinations. (JEL D83, E52, E58, E66)

We study long-run correlations between safe real interest rates in the United States and over 30 variables that have been hypothesized to influence real rates. The list of variables is motivated by an intertermporal IS equation, by models of aggregate savings and investment, and by reduced-form studies. We use annual data, mostly from 1890 to 2016. We find that safe real interest rates are correlated as expected with demographic measures. For example, the long-run correlation with labor force hours growth is positive, which is consistent with overlapping generations models. For another example, the long-run correlation with the proportion of 40 to 64 year-olds in the population is negative. This is consistent with standard theory where middle-aged workers are high savers who drive down real interest rates. In contrast to standard theory, we do not find productivity to be positively correlated with real rates. Most other variables have a mixed relationship with the real rate, with long-run correlations that are statistically or economically large in some samples and by some measures but not in others. (JEL E21, E22, E24, E43, E52)

We study long-run correlations between safe real interest rates in the United States and over 20 variables that have been hypothesized to infl uence real rates. The list of variables is motivated by the familiar intertermporal IS equation, by models of aggregate savings and investment, and by reduced form studies. We use annual data, mostly from 1890 to 2016. We fi nd that safe real interest rates are correlated as expected with demographic measures. For example, the longrun correlation with labor force hours growth is positive, which is consistent with overlapping generations models. For another example, the long-run correlation with the proportion of 40-to 64-year-olds in the population is negative. This is consistent with standard theory where middle-aged workers are high-savers who drive down real interest rates. In contrast to standard theory, we do not fi nd productivity to be positively correlated with real rates. Most other variables have a mixed relationship with the real rate, with long-run correlations that are statistically or economically large in some samples and by some measures but not in others.