THE T HEORY O F R ATIONALLY H ETEROGENEOUS EXPECTATIONS: E VIDENCE F ROM S URVEY D ATA ON I NFLATION E XPECTATIONS*

By William A. Branch. 2004

462 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/26ac408c818ae6c5299c4e14fb40f96820316cf1

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In Economics and Econometrics

Citations in the corpus

Learning from Inflation Experiences (2016, background): “Branch (2004), Branch (2007), and Pfajfar and Santoro (2010) estimate from survey data how individuals choose among competing forecasting models.”
Evolution of Forecast Disagreement in a Bayesian Learning Model (2008, background): “Notable works in this area go back to Cyert and DeGroot (1974), Townsend (1983), Haltiwanger and Waldman (1985) and Bray and Savin (1986). These papers all allow for heterogeneity in priors and with Bayesian learning, the heterogeneity disappears in the limit.”
Individual Expectations and Aggregate Macro Behavior (2011, methodology): “New Keynesian model developed by Branch and McGough (2009), which is described by the following equations:”
A New Keynesian model with heterogeneous expectations (2009, background): “…is a surprisingly diverse set of policy advice: some advocate simple, implementable policy rules (McCallum and Nelson, 1999; Schmitt-Grohe and Uribe, 2005); optimal state-contingent monetary policy (Giannoni and Woodford, 2002; Woodford, 2003; Benigno and Woodford, 2005); or, inflation…”
Learning and Macroeconomics (2009, methodology): “The dynamic selector framework is extended by Branch and Evans (2006) and Branch and Evans (2007) to incorporate stochastic features and econometric learning. Based on the assumption that agent employ parsimonious models, Branch and Evans study the implications of agents choosing between equally cos”
Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd, Elsevier, Amsterdam 2006, pp.1109-1186 (2005, background): “Branch (2004) uses survey data on inflation expectations of households to estimate a version of the dynamic HAM of Brock and Hommes (1997), with naive expectations, adaptive expectations and a VAR-forecasting rule.”
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.”
Sticky information and model uncertainty in survey data on inflation expectations (2007, background): “Great Inflation and Great Moderation) and to keep the comparison sharp with our earlier work.(5) This paper characterizes expectations of future inflation(6) and the sample consists of 93142 observations covering 187 time periods.”
Dynamic predictor selection in a new Keynesian model with heterogeneous expectations (2010, methodology): “In particular, if, for a given n, (6) is determinate then (5) is dynamically unstable; on the other hand if, for a given n, (6) is order two indeterminate then (5) is dynamically stable.”
The science of monetary policy: an imperfect knowledge perspective (2018, unknown): “A few papers have investigated the consequences of heterogeneous private beliefs for monetary policy at a theoretical level Branch (2004), Branch and McGough (2009, 2010, 2011).”
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.”
Inflation Dynamics: The Role of Expectations (2010, unknown): “(2003), Branch (2004).”