(with Thomas Drechsel)
Published in Journal of Monetary Economics, 2024, 148 Supplement, 103635.
We study how monetary policy affects subcomponents of the Personal Consumption Expenditures Price Index (PCEPI) using local projections. Following a monetary policy contraction, the response of aggregate PCEPI turns significantly negative after over three years. There are stark differences in the timing and magnitude of the responses across price categories, including some prices that show an initially positive response. We discuss theoretical interpretations of our findings and point to useful directions for future theoretical research. We also show how to re-aggregate our cross-sectional estimates and their standard errors, taking into account dependence between different prices using a Seemingly Unrelated Regression approach. Re-aggregation exercises show that changes in expenditure behavior have not accelerated the long-lagged response of inflation to monetary policy.

First Draft : May 2024
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MATLAB Code for Aggregation of Local Projection Estimates via SUR

We develop a novel method for the identification of monetary policy shocks. By applying natural language processing techniques to documents that Federal Reserve staff prepare in advance of policy decisions, we capture the Fed’s information set. Using machine learning techniques, we then predict changes in the target interest rate conditional on this information set and obtain a measure of monetary policy shocks as the residual. We show that the documents’ text contains essential information about the economy which is not captured by numerical forecasts that the staff include in the same documents. The dynamic responses of macro variables to our monetary policy shocks are consistent with the theoretical consensus. Shocks constructed by only controlling for the staff forecasts imply responses of macro variables at odds with theory. We directly link these differences to the information that our procedure extracts from the text over and above information captured by the forecasts.





















