Brent H. Meyer, Nicholas B. Parker, and Xuguang Simon Sheng
Working Paper 2021-12a
March 2021 (Revised December 2021)
Abstract: We propose a proxy for the inflation expectations of firms based on aggregating own-firm probabilistic unit cost expectations. Unlike other surveys of firms or households that elicit "aggregate" expectations, we focus on idiosyncratic costs that firms are well aware of, plan for, and matter for price setting. We document five key findings. first, in aggregate, firms' unit cost expectations significantly outperform households' inflation expectations and are at least as accurate as the expectations of professional forecasters in out-of-sample forecasting exercises. Second, once aggregated, firms' unit cost realizations closely comove with US inflation statistics. Third, using a novel, flexible technique to parametrically estimate firms' unit cost uncertainty, we find that up until early 2020, the evolution of firms' views was similar to other survey and market-based measures of inflation uncertainty. Fourth, using special questions, we find evidence that information treatments about aggregate inflation and policymakers' forecasts do little to alter firms' unit cost expectations. And, last, we show that unit costs at the firm level are an important determinant of their own price setting behavior.
JEL classification: E6, E31, E52, L2
Key words: bimodality, inflation expectations, probability distributions, randomized controlled trials, uncertainty, unit cost
https://doi.org/10.29338/wp2021-12a
First draft: March 17, 2021. The authors give special thanks to Brian Prescott for excellent research assistance. The authors also thank the Federal Reserve Bank of Atlanta for its ongoing support of the Economic Survey Research Center (ESRC) and the Business Inflation Expectations (BIE) survey. They remain heavily indebted to Mike Bryan for founding the BIE. They thank Jose Maria Barrero (discussant), Carola Binder (discussant), Ewa Stanisawska (discussant), Bernie Andrade, Wojtek Charemza, Oli Coibion, Jon Willis, and participants at the Philadelphia Fed Conference on "Real-Time Data Analysis, Methods, and Applications," the 21st IWH-CIREQ-GW Macroeconometric Workshop, the 23rd Federal Forecasters Conference, the ESCoE Conference on Economic Measurement, the 41st International Symposium on Forecasting, the IAAE 2021 Annual Conference, the CEBRA 2021 Annual Conference, the 35th CIRET Conference, and seminars at George Washington University, Renmin University of China, and the University College Dublin for helpful comments. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the Federal Reserve Bank of Atlanta of the Federal Reserve System. All results have been reviewed to ensure that no confidential information was disclosed.
Please address questions regarding content to Brent H. Meyer, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309.
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