We establish five facts about prices in the U.S. economy: 1) The median frequency of nonsale price change is 9-12% per month, roughly half of what it is including sales. This implies an uncensored median duration of regular prices of 8-11 months. Product turnover plays an important role in truncating price spells in durable goods. The median frequency of price change for finished goods producer prices is roughly 11% per month. 2) One-third of regular price changes are price decreases. 3) The frequency of price increases covaries strongly with inflation while the frequency of price decreases and the size of price increases and price decreases do not. 4) The frequency of price change is highly seasonal: It is highest in the 1st quarter and lowest in the 4th quarter. 5) The hazard function of price changes for individual consumer and producer goods is downward sloping for the first few months and then flat (except for a large spike at 12 months in consumer services and all producer prices). These facts are based on CPI microdata and a new comprehensive data set of microdata on producer prices that we construct from raw production files underlying the PPI. We show that the 1st, 2nd and 3rd facts are consistent with a benchmark menu-cost model, while the 4th and 5th facts are not.

We present estimates of monetary non-neutrality based on evidence from high-frequency responses of real interest rates, expected inflation, and expected output growth. Our identifying assumption is that unexpected changes in interest rates in a 30-minute window surrounding scheduled Federal Reserve announcements arise from news about monetary policy. In response to an interest rate hike, nominal and real interest rates increase roughly one-for-one, several years out into the term structure, while the response of expected inflation is small. At the same time, forecasts about output growth also increase-the opposite of what standard models imply about a monetary tightening. To explain these facts, we build a model in which Fed announcements affect beliefs not only about monetary policy but also about other economic fundamentals. Our model implies that these information effects play an important role in the overall causal effect of monetary policy shocks on output.

We use rich historical data on military procurement to estimate the effects of government spending. We exploit regional variation in military buildups to estimate an “open economy relative multiplier” of approximately 1.5. We develop a framework for interpreting this estimate and relating it to estimates of the standard closed economy aggregate multiplier. The latter is highly sensitive to how strongly aggregate monetary and tax policy “leans against the wind.” Our open economy relative multiplier “differences out” these effects because monetary and tax policies are uniform across the nation. Our evidence indicates that demand shocks can have large effects on output. (JEL E12, E32, E62, F33, H56, H57, R12)

and seminar participants at various institutions for valuable comments and discussions. We thank the National Science Foundation (grant SES-1056107) for financial support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Empirical evidence suggests that as much as one-third of the U.S. business cycle is due to nominal shocks. We calibrate a multisector menu cost model using new evidence on the cross-sectional distribution of the frequency and size of price changes in the U.S. economy. We augment the model to incorporate intermediate inputs. We show that the introduction of heterogeneity in the frequency of price change triples the degree of monetary non-neutrality generated by the model. We furthermore show that the introduction of intermediate inputs raises the degree of monetary non-neutrality by another factor of three, without adversely affecting the model's ability to match the large average size of price changes. A single-sector model with a frequency of price change equal to the median, rather than the mean, generates monetary non-neutrality similar to that in our multisector model. Our multisector model with intermediate inputs generates variation in real output in response to calibrated aggregate nominal shocks that can account for roughly 23% of the U.S. business cycle.

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and seminar participants at various institutions for helpful comments and conversations. Barro would like to thank the National Science Foundation for financial support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We use rich historical data on military procurement spending across U.S. regions to estimate the effects of government spending in a monetary union. Aggregate military build-ups and draw-downs have differential effects across regions. We use this variation to estimate an "open economy relative multiplier" of approximately 1.5. We develop a framework for interpreting this estimate and relating it to estimates of the standard closed economy aggregate multiplier. The closed economy aggregate multiplier is highly sensitive to how strongly aggregate monetary and tax policy "leans against the wind." In contrast, our open economy relative multiplier "differences out" these effects because different regions in the union share a common monetary and tax policy. Our estimates provide evidence in favor of models in which demand shocks can have large effects on output.