How Do Expectations about the Macroeconomy Affect Personal Expectations and Behavior?
By Christopher Roth, Johannes Wohlfart. Review of Economics and Statistics, 2020
189 citations recorded by the source corpus.
Abstract Using a representative online panel from the United States, we examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior. To exogenously vary respondents' expectations, we provide them with different professional forecasts about the likelihood of a recession. Respondents update their macroeconomic outlook in response to the forecasts, extrapolate to expectations about their personal economic circumstances, and adjust their consumption plans and stock purchases. Extrapolation to expectations about personal unemployment is driven by individuals with higher exposure to macroeconomic risk, consistent with macroeconomic models of imperfect information in which people are inattentive but understand how the economy works.
Subfields: Accounting, Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/0298244a32ad94b4dd4d1d8e906c0d965635d06e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Ingar K. Haaland
- Johannes Wohlfart
- Christopher Roth
- Y. Gorodnichenko
- Olivier Coibion
- Dimitris Georgarakos
- Michael Weber
In Economics and Econometrics
- Michael Weber
- Olivier Coibion
- Y. Gorodnichenko
- Johannes Wohlfart
- Christopher Roth
- Ingar K. Haaland
- Dimitris Georgarakos
- G. Kenny
Citations in the corpus
- The Effect of Macroeconomic Uncertainty on Household Spending (2021, background): “Roth and Wohlfart (2020), for example, use information treatments about the economic outlook to study how households’ expectations about future growth affect their consumption plans.”
- Designing Information Provision Experiments (2020, methodology): “As such, eliciting posteriors is less strictly needed than in designs where respondents receive a potentially noisy signal about a variable (e.g., Roth and Wohlfart, 2020), where posteriors are used to assess how informative respondents find the provided signal.”