Taylor Projection: A New Solution Method to Dynamic General Equilibrium Models

Levintal, Oren

doi:10.2139/ssrn.2728858

Cited by 13 publications

(54 citation statements)

References 27 publications

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“…Taylor projection is a new method recently proposed by Levintal (2016). We discuss the three methods briefly in the next pages.…”

Section: Solution Methodsmentioning

confidence: 99%

“…Obtaining perturbation solutions is easy for low orders, but the problem becomes cumbersome at high orders, especially for large models. In this paper, we use the perturbation algorithm presented in Levintal (2015), which allows to solve models with non-Gaussian shocks up to the fifth order.…”

Section: Perturbationmentioning

confidence: 99%

“…Taylor projection is a new type of projection method proposed by Levintal (2016). As with standard projection methods, the goal is to find Θ for which the residual function R (x, Θ), defined by equation (22), is approximately zero over a certain domain of the state space that is of interest.…”

Section: Taylor Projectionmentioning

confidence: 99%

“…However, Isoré and Szczerbowicz (2013) only undertake firstand second-order perturbations and Andreasen (2012) and Isoré and Szczerbowicz (2015) a third-order perturbation. We will argue below that there are reasons to be cautious about the properties of these perturbation solutions (see also Levintal, 2015). Perturbations are inherently local solution methods and rare disasters often trigger equilibrium dynamics that travel far away from the approximation point of the perturbation.…”

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confidence: 99%

“…This method, recently proposed by Levintal (2016), is a hybrid of Taylor-based perturbations and projections (and hence its name). Like standard projection methods, Taylor projection starts from a residual function created by plugging the unknown decision rules of the agents into the equilibrium conditions of the model and searching for coefficients that make that residual function as close to zero as possible.…”

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confidence: 99%

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Solution Methods for Models with Rare Disasters

Fernández-Villaverde

Levintal

2016

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This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with rare disasters along the line of those proposed by Rietz (1988), Barro (2006}, Gabaix (2012), and Gourio (2012. DSGE models with rare disasters require solution methods that can handle the large non-linearities triggered by low-probability, high-impact events with sufficient accuracy and speed. We solve a standard New Keynesian model with Epstein-Zin preferences and time-varying disaster risk with perturbation, Taylor projection, and Smolyak collocation. Our main finding is that Taylor projection delivers the best accuracy/speed tradeoff among the tested solutions. We also document that even third-order perturbations may generate solutions that suffer from accuracy problems and that Smolyak collocation can be costly in terms of run time and memory requirements.

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“…Taylor projection is a new method recently proposed by Levintal (2016). We discuss the three methods briefly in the next pages.…”

Section: Solution Methodsmentioning

confidence: 99%

Section: Perturbationmentioning

confidence: 99%

Section: Taylor Projectionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Solution Methods for Models with Rare Disasters

Fernández-Villaverde

Levintal

2016

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Solution and Estimation Methods for DSGE Models

Fernández-Villaverde

Ramírez

Schorfheide

2016

Handbook of Macroeconomics

158

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provided excellent research assistance. We thank our discussant Serguei Maliar, the editors John Taylor and Harald Uhlig, John Cochrane, and the participants at the Handbook Conference hosted by the Hoover Institution for helpful comments and suggestions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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Rare Disasters, the Natural Interest Rate and Monetary Policy*

Cantelmo

2022

Oxf Bull Econ Stat

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This paper evaluates the impact of rare disasters on the natural interest rate and macroeconomic conditions by simulating a nonlinear New-Keynesian model. The model is calibrated using data on natural disasters in OECD countries. From an ex-ante perspective, disaster risk behaves as a negative demand shock and lowers the natural rate and inflation, even if disasters hit only the supply side of the economy. These effects become larger and nonlinear if extreme natural disasters become more frequent, a scenario compatible with climate change projections. From an ex-post perspective, a disaster realization leads to temporarily higher natural rate and inflation if supply-side effects prevail. If agents' risk aversion increases temporarily, disasters may generate larger demand effects and lead to a lower natural rate and inflation. If supply-side effects dominate, the central bank could mitigate output losses at the cost of temporarily higher inflation in the short run. Conversely, under strict inflation targeting, inflation is stabilized at the cost of larger output losses.

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Taylor Projection: A New Solution Method to Dynamic General Equilibrium Models

Cited by 13 publications

References 27 publications

Solution Methods for Models with Rare Disasters

Solution Methods for Models with Rare Disasters

Solution and Estimation Methods for DSGE Models

Rare Disasters, the Natural Interest Rate and Monetary Policy*

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