Accuracy, Speed and Robustness of Policy Function Iteration

Richter, Alexander W.; Throckmorton, Nathaniel A.; Walker, Todd B.

doi:10.1007/s10614-013-9399-2

Cited by 74 publications

(50 citation statements)

References 34 publications

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“…Therefore, the possibility of hitting the zero lower bound in the future a¤ects potentially the equilibrium outcome in times of unconstrained monetary policy. We use time iteration (Coleman 1990 andJudd 1998) with piecewise linear interpolation of policy functions as in Richter et al (2014). 10 Expectations are calculated using numerical integration based on Gauss-Hermite quadrature.…”

Section: A Non-linear Solution Methodsmentioning

confidence: 99%

“…We solve the model with time iterations and linear interpolation as in Richter et al (2014). Expectations are evaluated with Gauss-Hermite Quadrature.…”

Section: Model Solution and Calibration Of Parametersmentioning

confidence: 99%

“…De…ne a discretized state grid [ d t ; d t ] and integration nodesd = [ d t ; d t ].2. Guess the policy functionsg( d t ).10 This approach can handle the non-linearities associated with zero lower bound Richter et al (2014). demonstrate that linear interpolation outperforms Chebyshev interpolation, which is a popular alternative, for models with zero lower bound.…”

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confidence: 99%

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Hitting the Elusive Inflation Target

Bianchi

Melosi

Rottner

2019

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Since the 2001 recession, average core in ‡ation has been below the Federal Reserve's 2% target. This de ‡ationary bias is a predictable consequence of a low nominal interest rates environment in which the central bank follows a symmetric strategy to stabilize in ‡ation. The de ‡ationary bias increases if macroeconomic uncertainty rises or the natural real interest rate falls. An asymmetric rule according to which the central bank responds less aggressively to above-target in ‡ation corrects the bias and allows in ‡ation to converge to the central bank's target. We show that adopting this asymmetric rule improves welfare and reduces the risk of self-ful…lling de ‡ationary spirals. This approach does not entail any history dependence in setting the policy rate or any commitment to overshoot in ‡ation after periods in which the lower bound constraint was binding.JEL Codes: E31, E52, E62, E63, D83 Keywords: De ‡ationary bias, asymmetric rules, opportunistic re ‡ation, welfare, natural rate, zero lower bound, disanchoring of in ‡ation expectations, in ‡ation targeting, liquidity traps, macroeconomic uncertainty.Emails:

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Section: A Non-linear Solution Methodsmentioning

confidence: 99%

“…We solve the model with time iterations and linear interpolation as in Richter et al (2014). Expectations are evaluated with Gauss-Hermite Quadrature.…”

Section: Model Solution and Calibration Of Parametersmentioning

confidence: 99%

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confidence: 99%

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Hitting the Elusive Inflation Target

Bianchi

Melosi

Rottner

2019

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“…Richter et al . () briefly review the theory of this kind of operator applied to DSGE models and related studies.…”

Section: Solution Methods For Nonlinear Dynamic Stochastic General Eqmentioning

confidence: 99%

Review of Solution and Estimation Methods for Nonlinear Dynamic Stochastic General Equilibrium Models with the Zero Lower Bound

Hirose

Sunakawa

2019

Jpn Econ Rev

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We review solution and estimation methods for nonlinear dynamic stochastic general equilibrium models and their application, with a special focus on the zero lower bound on the nominal interest rate. In a fully nonlinear setting, both the solution and estimation methods involve iterative procedures, and their computational expense grows rapidly with an increase in the dimensionality of state variables and parameters. We describe how the procedures deal with the dimensionality problem.

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“…This solution technique discretizes the state space and iteratively solves for updated policy functions that satisfy equilibrium until a specified tolerance criterion is reached. For additional information and examples of how the algorithm is applied to conventional real business cycle and new Keynesian models see Richter et al (2011). The third row shows workers' responses to their income losses.…”

Section: B Computational Methodologymentioning

confidence: 99%