Efficient Perturbation Methods for Solving Regime-Switching DSGE Models

Maih, Junior

doi:10.2139/ssrn.2602453

Cited by 56 publications

(74 citation statements)

References 52 publications

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“…upon exit from the ZLB) adheres to the same Taylor-type policy rule (Equation 5.1), and that agents form their expectations accordingly. 3 2 We use the RISE toolbox to implement this exercise, see Maih [112]. 44 uncertainty bands in normal times (i.e.…”

Section: Allowing For Time-varying Volatilitymentioning

confidence: 99%

Challenges for Central Banks’ Macro Models

Lindé

Smets

Wouters

2016

Handbook of Macroeconomics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The Working Paper series presents reports on matters in the sphere of activities of the Riksbank that are considered to be of interest to a wider public. Terms of use: Documents inThe papers are to be regarded as reports on ongoing studies and the authors will be pleased to receive comments.The opinions expressed in this article are the sole responsibility of the author(s) and should not be interpreted as reflecting the views of Sveriges Riksbank. Challenges for Central Banks'Macro Models AbstractIn this paper we discuss a number of challenges for structural macroeconomic models in the light of the Great Recession and its aftermath. It shows that a benchmark DSGE model that shares many features with models currently used by central banks and large international institutions has di¢ culty explaining both the depth and the slow recovery of the Great Recession. In order to better account for these observations, the paper analyses three extensions of the benchmark model. First, we estimate the model allowing explicitly for the zero lower bound constraint on nominal interest rates. Second, we introduce time-variation in the volatility of the exogenous disturbances to account for the non-Gaussian nature of some of the shocks. Third and …nally, we extend the model with a …nancial accelerator and allow for time-variation in the endogenous propagation of …nancial shocks. All three extensions require that we go beyond the linear Gaussian assumptions that are standard in most policy models. We conclude that these extensions go some way in accounting for features of the Great Recession and its aftermath, but they do not su¢ ce to address some of the major policy challenges associated with the use of non-standard monetary policy and macroprudential policies. JEL Classi…cation: E52, E58

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Section: Allowing For Time-varying Volatilitymentioning

confidence: 99%

Challenges for Central Banks’ Macro Models

Lindé

Smets

Wouters

2016

Handbook of Macroeconomics

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“…In general an analytical/closed-form solution to this problem does not exist in which case we resort to finding an approximate solution. Following Maih (2015) and Foerster et al (2014) we solve the model using perturbation methods. Perturbation methods are reasonably accurate, computationally more e cient than competing methods and less prone to the curse of dimensionality.…”

Section: Generic Model and Perturbation Solutionmentioning

confidence: 99%

“…We find this solution using the e cient solution method of Maih (2015) available as part of 7 the RISE toolbox. …”

Section: Generic Model and Perturbation Solutionmentioning

confidence: 99%

“…Because it is unrelated, it will have its own distribution independently of other parts of the system. Under the anticipated shocks approach the policy functions are explicitly expressed in terms of leads of future shocks as opposed to lags in the news shocks approach (Maih, 2015). 2 Binning & Maih (2016a) describe sign reversals as ... a phenomenon that occurs when anticipated monetary policy shocks are used to enforce the lower bound constraint.…”

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confidence: 99%

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Modelling Occasionally Binding Constraints Using Regime-Switching

Binning¹,

Maih²

2017

SSRN Journal

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Occasionally binding constraints are part of the economic landscape: for instance recent experience with the global financial crisis has highlighted the gravity of the lower bound constraint on interest rates; mortgagors are subject to more stringent borrowing conditions when credit growth has been excessive or there is a downturn in the economy. In this paper we take four common examples of occasionally binding constraints in economics and demonstrate how to use regime-switching to incorporate them into DSGE models. In particular we investigate the zero lower bound constraint on interest rates, occasionally binding collateral constraints, downward nominal wage rigidities and irreversible investment. We compare our approach against some well-known methods for solving occasionally-binding constraints. We demonstrate the versatility of our regime-switching approach by combining multiple occasionally binding constraints to a model solved using higher-order perturbation methods, a feat that is di cult to achieve using alternative methodologies.

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“…Other features of the data like nonlinearities and asymmetries in the business cycle (Kim & Nelson, 2001), crises (Foerster, 2011), occasionally binding constraints (Aruoba & Schorfheide, 2013), heteroscedasticity (Liu & Mumtaz, 2011), changes in behavioral parameters (Melino & Yang, 2003), and the possibility of recurrent regimes (Sims & Zha, 2006) can all be recast and interpreted in terms of a regime switching framework. Recent advances in perturbation solution methods by Foerster et al (2014) and Maih (2015) provide tools for finding nonlinear solutions to nonlinear regime switching models with rational expectations.…”

Section: Introductionmentioning

confidence: 99%

Sigma Point Filters for Dynamic Nonlinear Regime Switching Models

Binning¹,

Maih²

2015

SSRN Journal

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In this paper we take three well known Sigma Point Filters, namely the Unscented Kalman Filter, the Divided Difference Filter, and the Cubature Kalman Filter, and extend them to allow for a very general class of dynamic nonlinear regime switching models. Using both a Monte Carlo study and real data, we investigate the properties of our proposed filters by using a regime switching DSGE model solved using nonlinear methods. We find that the proposed filters perform well. They are both fast and reasonably accurate, and as a result they will provide practitioners with a convenient alternative to Sequential Monte Carlo methods. We also investigate the concept of observability and its implications in the context of the nonlinear filters developed and propose some heuristics. Finally, we provide in the RISE toolbox, the codes implementing these three novel filters.

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Efficient Perturbation Methods for Solving Regime-Switching DSGE Models

Cited by 56 publications

References 52 publications

Challenges for Central Banks’ Macro Models

Challenges for Central Banks’ Macro Models

Modelling Occasionally Binding Constraints Using Regime-Switching

Sigma Point Filters for Dynamic Nonlinear Regime Switching Models

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