Sectoral heterogeneity matters for monetary policy. Using CPI microdata, we estimate for 227 products a time-varying menu-cost model to investigate the quantitative relevance of this heterogeneity. We find a substantial degree of cross-sectoral heterogeneity in all structural parameters. Heterogeneity in the Calvo component of the pricing friction is, however, the main source of heterogeneity in price rigidity. Cross-sectoral heterogeneity amplifies the output effect of a monetary shock by a factor of about 2.5, compared to a single-sector model estimated with mean moments. Heterogeneity in the Calvo parameter plays a key role in this amplification.

We prove that the ratio of kurtosis to the frequency of price changes is a sufficient statistic for the real effects of monetary shocks, measured by the cumulated output response following the shock. The sufficient statistic result holds in a large class of models which includes Taylor (1980); Calvo (1983); Reis (2006 ); Golosov and Lucas (2007 ); Nakamura and Steinsson (2010); Midrigan (2011); and Alvarez and Lippi (2014). Several models in this class are able to account for the positive excess kurtosis of the size distribution of price changes that appears in the data. We review empirical measures of kurtosis and frequency and conclude that a model that successfully matches the microevidence on kurtosis and frequency produces real effects that are about four times larger than in the Golosov-Lucas model, and about 30 percent below those of the Calvo model. We discuss the robustness of our results to changes in the setup, including small inflation and leptokurtic cost shocks. (JEL, E23, E31)

We propose a new measure of underlying inflation that informs, in real time, about asymmetric risks on the outlook of inflationary pressures. The asymmetries are generated through nonlinearities induced by economic activity. The new indicator is based on a multivariate regime-switching framework jointly estimated on disaggregated sub-components of the euro area HICP and has several additional advantages. First, it is able to swiftly infer abrupt changes in underlying inflation. Second, it helps to timely track turning points in underlying inflation. Third, the proposed indicator also has a satisfactory performance with respect to various criteria relevant for inflation monitoring.

In a broad class of sticky-price models, the non-neutrality of nominal shocks is captured by a simple sufficient statistic: the ratio of the kurtosis of the price change distribution over the frequency of price changes. We test the sufficient statistic proposition using data for a large sample of products representative of the French economy. We first extend the theory to allow for empirically relevant monetary shocks with a transitory predictable component. We then use the microdata to measure kurtosis and frequency for about 120 producer price indices industries and 220 consumer price indices categories. We use a Factor-Augmented Vector Autoregressive (FAVAR) model to measure the industries’ response to monetary shocks, under alternative identification schemes. The estimated degree of non-neutrality correlates with the kurtosis and the frequency consistently with the predictions of the theory. Several robustness checks are discussed.