Learning About Monetary Policy Rules When Long-Horizon Expectations Matter

By Bruce Preston. 2003

306 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a93fcc0c3d7f2f742671f1f8c69e3ae6f8dbc860

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Citations in the corpus

Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models (pp. 65-101) (2012, background): “In this context, it would be very interesting to test whether Preston's in nite-horizon learning approach (2005) can resolve this trade-off more ef ciently by using the restrictions from the budget constraints in the forecasts.”
Expectations, Learning and Business Cycle Fluctuations (2011, unknown): “Preston (2005) shows that this decision rule leads to suboptimal decisions – see also Marcet and Sargent (1989).21 All remaining model equations are unchanged as they do not directly depend on the specification of beliefs.”
Anchored Inflation Expectations (2020, unknown): “9See Preston (2005) and Eusepi and Preston (2018b) for discussions of optimal price setting under arbitrary beliefs.”
Optimal Monetary Policy When Agents are Learning (2010, unknown): “rt = rrt + δ π at + δ cg x bt + δ cg g gt + δ cg u ut (37) where: c x = c π −β κ d x = d π −1 κ δ π = 1− σ c π −β κ δ x = σ δ g = σ δ u = −σ d π −1 κ”
The science of monetary policy: an imperfect knowledge perspective (2018, unknown): “This is not the case for decision rules adopted under the Euler 16Evans, Honkapohja and Mitra (2013), Preston (2005) and Eusepi and Preston (2011a) discuss more broadly the relative merits and limits of these two approaches.”
Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve (2014, background): “…consistent with the above microeconomic foundations that constitute the standard New Keynesian modeling framework (a similar argument is given by Preston 2005).4 This will be the case, for instance, if firms’ expectations are not based on the same information set or if they are not perfectly…”
Liquidity traps, learning and stagnation ☆ (2008, unknown): “An alternative approach, stressed in Preston (2005) , retains adaptive learning, but asks agents each to forecast infinitely far into the future and to re-solve their dynamic optimization problem each period.”
Adaptive learning, forecast-based instrument rules and monetary policy (2006, methodology): “14 As underscored by Preston (2003), when the microfoundations underpinning this model are solved under the non-rational expectations assumption, the predicted aggregate dynamics depend on long-horizon forecasts of ination, output and the nominal interest rate into the indenite future. It is the p”
Learning and Macroeconomics (2009, methodology): “We call this approach, presented for the New Keynesian model in Preston (2005), infinite-horizon (IH) learning, and we describe it for the current context.”