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Macroeconomic Uncertainty and Expectations: Measurement and Implications

Paper Session

Friday, Jan. 3, 2025 10:15 AM - 12:15 PM (PST)

Hilton San Francisco Union Square, Continental Ballroom 1&2
Hosted By: American Economic Association
  • Chair: Yuriy Gorodnichenko, University of California-Berkeley

Smooth Diagnostic Expectations

Francesco Bianchi
,
John Hopkins University
Cosmin Ilut
,
Duke University
Hikaru Saijo
,
University of California-Santa Cruz

Abstract

We introduce “smooth diagnosticity.” Under smooth diagnosticity, agents over-react to new information defined as the difference between the current information set and a previous information set. Since new information typically changes not just the conditional mean, but also the conditional uncertainty, changes in uncertainty surrounding current and past beliefs affect the severity of the Diagnostic Expectations (DE) distortion. Smooth DE nests the baseline DE of Bordalo et al. (2018) and implies a joint and parsimonious micro-foundation for various properties of survey data: (1) overreaction of conditional mean to news, (2) stronger over-reaction for weaker signals and longer forecast horizons, and (3) over-confidence in subjective uncertainty. We embed Smooth DE in an analytical RBC model. The model accounts for over-reaction and over-confidence in surveys, as well as three salient properties of the business cycle: (1) asymmetry, (2) countercyclical micro volatility, and (3) countercyclical macro volatility.

Business Uncertainty in Developing and Emerging Economies

Edgar Avalos
,
World Bank
Jose Maria Barrero
,
Mexico Autonomous Institute of Technology
Elwyn Davies
,
World Bank
Leonardo Iacovone
,
World Bank
Jesica Torres
,
World Bank

Abstract

We study business uncertainty under high and low volatility by surveying over 31,000 managers across 41 countries and eliciting subjective probability distributions for future own-firm sales. We measure uncertainty with the mean absolute deviation of each subjective distribution and, analogously, measure realized volatility using absolute forecast errors. We establish two new facts. (1) Subjective uncertainty and realized volatility both decline with GDP per capita. (2) Managers underestimate volatility everywhere (they are overprecise), but more so in low-volatility rich countries. Using a heterogeneous-firm dynamic model with real options, we show how our facts amplify the role of aggregate TFP in accounting for cross-country income gaps. With convex firm value and investment rules, volatility provides growth opportunities whereas overprecision improves selection and reallocation. Both therefore raise GDP per capita. But the volatility effect dominates, so we need up to 35% lower TFP in poor countries to reconcile their low income and high volatility.

The Speed of Firms’ Response to Inflation

Ivan Yotzov
,
Bank of England
Nicholas Bloom
,
Stanford University
Philip Bunn
,
Bank of England
Paul Mizen
,
King’s College London
Gregory Thwaites
,
University of Nottingham

Abstract

This paper analyses the response of firms to monthly CPI inflation releases using a large economy-wide business survey. CPI inflation perceptions respond very quickly, in a matter of hours after the release. We also find that firms’ expected own-price growth has a strong positive correlation with changes in CPI inflation, particularly for increases in inflation. This sensitivity is stronger when inflation is high. Firms are also more responsive when inflation coverage in the media is elevated and appear to have a supply-side view of the economy: higher aggregate inflation leads to lower expected sales volume growth and higher expected cost growth. Firms also seem to anticipate the monetary policy response, as positive inflation changes are associated with higher expected borrowing rates.

Causal Effects of Inflation Uncertainty on Households’ Beliefs and Actions

Olivier Coibion
,
University of Texas-Austin
Yuriy Gorodnichenko
,
University of California-Berkeley
Dimitris Georgarakos
,
European Central Bank
Geoff Kenny
,
European Central Bank

Abstract

The 2021-2023 global surge of inflation rekindled debates about the effects of inflation on the macroeconomy and specifically how households respond to inflation. A key element of these debates is how inflation expectations amplify and propagate inflationary shocks. While recent research focused on how point predictions for inflation affect beliefs and actions, there is virtually no evidence on how inflation uncertainty influences beliefs and actions. The dearth of evidence reflects a number of challenges. First, expectations are clearly endogenous and thus establishing causal links is particularly difficult. Furthermore, uncertainty is systematically related to point predictions (i.e., 1st moments) and so it is hard to disentangle uncertainty effects from level effects. Second, measurement of uncertainty in surveys is a relatively new development and hence only a handful of surveys gather this information. Third, with decades of low and stable inflation in advanced economies, there was too little variation in inflation to discern the effects of uncertainty. To address these challenges and shed new light on the matter, we implement a large-scale randomized controlled trial (RCT) in a population representative survey that focuses on identifying causal effects of inflation uncertainty. We find that inflation uncertainty strongly inhibits spending on durable goods, encourages more intensive job search, and results in portfolio reallocations towards inflation-proof assets.

Discussant(s)
Sanjay R. Singh
,
Federal Reserve Bank of San Francisco
Brent Meyer
,
Federal Reserve Bank of Atlanta
Oliver Pfäuti
,
University of Texas-Austin
Olena Kostyshyna
,
Bank of Canada
JEL Classifications
  • E3 - Prices, Business Fluctuations, and Cycles
  • E7 - Macro-Based Behavioral Economics