Sticky information and model uncertainty in survey data on inflation expectations

By William A. Branch. 2007

196 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7dba3339851ee946fbecc816d9f7838e19156f67

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In Economics and Econometrics

Citations in the corpus

Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts (2012, unknown): “In the same spirit, Branch (2007) compares the fit of sticky-information and model-switching characterizations of the expectations formation process while Carroll (2003) tests an epidemiological model of expectations in which information diffuses over time from professional forecasters to consumers.”
What can survey forecasts tell us about informational rigidities (2008, unknown): “Finally, following Mankiw, Reis and Wolfers (2004) and Branch (2007), we study the cross-sectional dispersion of forecasts across agents.”
Imperfect Information and Aggregate Supply (2010, unknown): “ Finally, Branch (2007) finds that the sticky information model can match many features of the distribution of inflation expectations in the Michigan survey.”
Behavioral & Experimental Macroeconomics and Policy Analysis: A Complex Systems Approach (2018, methodology): “Branch (2004, 2007) fit a heuristic switching model with amongst others a naive heuristic, and a fundamentalistic VAR heuristic to data from Michigan Survey of Consumer Attitudes an Behavior.”
A New Keynesian model with heterogeneous expectations (2009, background): “Branch (2004, 2007) finds that survey data on inflation expectations are consistent with a dynamic discrete choice between statistical predictor functions.”
Learning from Inflation Experiences (2016, background): “The literature on adaptive learning (see Bray (1982); Sargent (1993); Evans and Honkapohja (2001)) views individual agents as econometricians who make forecasts based on simple forecasting rules estimated on historical data, but there is yet little direct empirical evidence on the actual forecasting”
The Price Is Right: Updating Inflation Expectations in a Randomized Price Information Experiment (2016, background): “Furthermore, we find that some of these same demographic groups – females in 43 Since our design consists of only round of revisions, we are unable to say much about whether consumers have timedependent rules (Carroll, 2003; Branch, 2007).”
Inattentive professional forecasters (2013, unknown): “Mankiw et al. (2003) and Branch (2007) focus on the cross-section distribution of forecasts to calibrate the sticky-information attention parameter mentioned above.”
Disagreement and Biases in Inflation Expectations (2006, unknown): “This is important because we have to address the possibility that different information sets (as suggested, among others, by Mankiw and Reis 2002) or different forecasting models (as suggested, among others, by Branch (2007)) could be causing the differences among forecasters that we are observing.”
Heterogeneity, learning and information stickiness in inflation expectations (2010, background): “Branch (2004, 2007) assesses the importance of the rst two roots of heterogeneity and nds that data are consistent with both of them.”