Inflation and Inflation Expectations: Supply-Side Perspectives and Heterogeneity
Paper Session
Saturday, Jan. 3, 2026 8:00 AM - 10:00 AM (EST)
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Chairs:
Karen Smith, Drew University - Rupal Kamdar, Indiana University-Bloomington
Inflation Is a Supply Phenomenon
Abstract
A sine qua non condition for inflation bursts is supply deficiency—caused either by exogenous shocks to aggregate supply (supply disruptions), or by excessive aggregate demand (supply-constrained demand booms). Aggregate demand booms, even big ones, that do not trigger supply deficiencies, are not inflationary. We survey the literature on the topic and discuss the evidence. Absent glaring macroeconomic mismanagement, we argue that viewing supply issues as the root cause for inflationary episodes provides an accurate account of when and where inflation occurs. Supply deficiencies typically lead to high, but ultimately moderate, inflation rates.Supply Chain Networks and The Macroeconomic Expectations of Firms
Abstract
We explore the role of supply chain networks in shaping macroeconomic expectations. Using a randomized control trial of over 1,000 firm-firm pairs in New Zealand that have a business relationship, we provide an information treatment to analyze both the direct effects on expectations and action of firms receiving this information and the network effect on connected firms that did not directly receive information. In a follow-up three months later, we find that the treatment significantly affects the expectations of both directly treated and connected firms. Using the variation induced by the treatment, we find that an increase in expected GDP growth increases prices and employment decisions. Moreover, an increase in expected GDP uncertainty reduces treated and connected firms’ price, investment, and employment decisions. Our empirical evidence and insights from a production network model show that communication, not only actions, drives the change in expectations and actions of connected firms. Consequently, communication between firms connected through the supply chain is a relevant transmission mechanism of shocks and aggregate uncertainty.Heterogeneous Responses to Signals and the Predictability of Forecast Errors
Abstract
Why do analysts underreact to news at the aggregate level yet overreact at the individual level? The literature explains underreaction with information frictions and overreaction with extrapolation from recent events. However, forecast revisions are weak predictors of forecast errors out-of-sample. I instead argue analysts overvalue private signals while underweighting public signals. To test this, I propose a novel method to disentangle responses to private signals from heterogeneous responses to public signals in high-frequency data. Using data from professional analysts’ expectations of US firm revenues, I find that asymmetric responses to signals uncover behavioral bias that predicts forecast errors out-of-sample.Cross-Country Inflation Expectations: Evidence of Heterogeneous and Synchronized ‘Mistakes’
Abstract
This paper evaluates the assumption of Full-Information Rational Expectations (FIRE) in the inflation predictions of professional forecasters across forty-six countries from 1990 to 2020. I argue that adopting a more international approach to modeling belief formation is critical for understanding the nature of the Expectation Formation Process (EFP) and formulating optimal monetary policy. When evaluated across countries, I document widespread heterogeneity in the magnitude and direction of FIRE violations and provide new evidence contradicting established stylized facts about the EFP. Juxtaposing this heterogeneity, I present a Bayesian Dynamic Factor Model illustrating a latent factor in cross-country forecast errors. I show that this factor, which indicates synchronization in forecaster mistakes, accounted for 15% of the variability in country-specific forecast errors during the Global Financial Crisis and up to 59% in advanced economies at the start of the COVID-19 pandemic. I add another dimension to this empirical analysis by introducing a novel real-time CPI dataset, augmenting international real-time macroeconomic data availability.Discussant(s)
Jean-Paul L'Huillier
,
Brandeis University
Karen Smith
,
Drew University
Ina Hajdini
,
Federal Reserve Bank of Cleveland
Symeon Taipliadis
,
University of Florida
Rupal Kamdar
,
Indiana University-Bloomington
JEL Classifications
- E3 - Prices, Business Fluctuations, and Cycles
- D8 - Information, Knowledge, and Uncertainty