Inflation Measured Every Day Keeps Adverse Responses Away: Temporal Aggregation and Monetary Policy Transmission

Abstract

Using daily inflation data from the Billion Prices Project [Cavallo and Rigobon (2016)], we show how temporal aggregation biases estimates of monetary policy transmission. We argue that the information mismatch between private agents and the econometrician —the source of temporal aggregation bias —is equally important as the more studied mismatch between private agents and the central bank (the “Fed information effect”). We find that the adverse response of daily inflation to high-frequency monetary policy shocks is short-lived, if present at all, in impulse responses from both local projections and an unobserved components model of inflation dynamics. To reconcile how one can obtain a sizable adverse response with monthly or quarterly data when only a limited adverse response exists at a higher frequency, we appeal to a simple monetary policy model and show how temporal aggregation bias can exacerbate initial impulse response functions. Because our modeling results are generic and macroeconomic indicators are published with a lag, we argue that temporal aggregation bias will be a key feature of the nascent field of high-frequency macroeconomics.