Is the Taylor rule optimal? Evaluation using a wavelet-based control model

Crowley, Patrick M.; Hudgins, David

doi:10.1080/13504851.2020.1730752

Cited by 10 publications

(8 citation statements)

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“…This section applies the resilient and minimax control methods using the large-scale WBC model in Crowley and Hudgins ( 2021a , 2021b ). This discrete WBC model extracts embedded cycles from time series data by decomposing the value of a variable x at time instant k , x k , using Mallat’s pyramid algorithm and multiresolutional analysis, as where the d j,k terms are wavelet detail “crystals”, j = 1,…, J ; S J,k is a trend component, called the wavelet “smooth”, and J denotes the frequency bands (number of scales).…”

Section: Application and Simulationsmentioning

confidence: 99%

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Resilient Control for Macroeconomic Models

Hudgins

Crowley

2022

Comput Econ

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This paper derives a macroeconomic resilient control framework that provides the optimal feedback fiscal and monetary policy responses in response to a potentially large negative external incident. We simulate the model for the U.S. under the conditions that prevailed throughout the 2020 economic crisis that occurred due to the government lockdown that was caused by the coronavirus pandemic. We develop a discrete-time soft-constrained linear-quadratic dynamic game under a worst-case design with multiple disturbances. Within this context, we introduce a resilience feedback response and compare the case where the policymakers counter in response the external incident with the case when they do not counter. This framework is especially applicable to large-scale macroeconomic tracking control models and wavelet-based control models when formulating the magnitudes of the policy changes necessary for the unemployment rate and national output variables to maintain acceptable tracking errors in the periods following a major disruption. Our policy recommendations include the maintenance of “rainy day” funds at appropriate levels of government to mitigate the effects of large adverse events.

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Section: Application and Simulationsmentioning

confidence: 99%

“…( 22 ), real money growth is a function of a constant, lagged real money growth, the real interest rate, and the national output gap. As in Crowley and Hudgins ( 2019 , 2021a ), this equation expresses the adjustments of money demand and supply to maintain equilibrium in the asset market. The estimates for Eqs.…”

Section: Application and Simulationsmentioning

confidence: 99%

Resilient Control for Macroeconomic Models

Hudgins

Crowley

2022

Comput Econ

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“…También en forma reciente se ha propuesto el uso del análisis wavelet como una herramienta para extraer las componente de tendencia y ciclotendencia del producto y con esto estimar el OG (Barrales & von Arnim, 2017;Crowley & Hudgins, 2021;Mitra, Maheswari, & Mitra, 2011;Sun & Li, 2022;Tiwari et al, 2019). Esta herramienta es relativamente nueva en el ámbito de las series temporales (Percival & Walden, 2000) y de uso reciente en el área de la economía (Percival & Walden, 2000;Ramsey, 2002) El análisis wavelet es una herramienta que se puede usar para analizar series temporales en donde no es necesario el uso de supuestos respecto del comportamiento y dinámica de la serie a ser analizada.…”

Section: Output Gap: Revisión De La Literaturaunclassified

Estimación de la brecha del producto: una revisión de desarrollos recientes y aplicación

Colther¹

2022

RVG

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Este trabajo tiene por objetivo revisar dos nuevas herramientas que pueden ser utilizadas para obtener el output gap a través de desagregar la componente ciclo-tendencia del PIB. Se han evaluado el filtro de Hamilton (2018) y la transformada wavelet, comparando sus resultados respecto de los métodos tradicionales utilizados para estimar el output gap. Para este ejercicio se han aplicado los diferentes métodos a una serie simulada y luego una aplicación empírica al caso de Estados Unidos en el período 1957-2021. De las principales conclusiones de este trabajo, se puede mencionar las importantes diferencias en cuanto a las componentes cíclicas que se puede obtener por los diferentes métodos, que llama a la precaución por parte de los analistas en cuanto a considerar sólo un determinado método y el riesgo de cometer importantes errores de estimación. El análisis wavelet muestra gran versatilidad en cuanto a desagregar una serie temporal en componentes que pueden ser de gran utilidad para estudiar el output gap y otras componentes de interés, por lo que se recomienda profundizar en su uso en el ámbito del análisis macroeconómico.

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“…The base case, case (1), is a jointly optimal simulation with standard weightings on all macroeconomic variables. Crowley and Hudgins (2021a) found that this jointly optimal case could deliver superior results in terms of macroeconomic performance to a Taylor rule under the 2018 initial conditions that we use here, so it is clear that a non‐time‐varying rule such as the Taylor rule would be inferior to either an inflation target or an economic growth target (or presumably a combination of both) given the correct weighting and the fact that neither of these cases targets an interest rate. So in essence, in 2018, our simulations suggest that adopting the interest rate as an intermediate policy instrument would not have been the most effective way to achieve the policy goals of the Fed.…”

Section: Simulation Analysismentioning

confidence: 99%

“…The first open-economy wavelet-based control models were developed as partial accelerator models byCrowley and Hudgins (2018a) andHudgins and Crowley (2019), which analyzed various policy simulations using South African data as a developing country example Crowley and Hudgins (2021a). then examined the performance of the Taylor rule within the context of WBC model, and this was extended further byCrowley and Hudgins (2021b) by the incorporation of unemployment into the framework using Okun's Law.…”

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Monetary policy objectives and economic outcomes: What can we learn from a wavelet‐based optimal control approach?

Crowley

Hudgins

2021

The Manchester School

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It has recently been widely recognized that monetary policy objectives change through time as our understanding of monetary policy and its impact on the macroeconomy evolves. In recent years there has been an extensive review of the framework for monetary policy at major central banks around the world, given the practical problems that have been encountered with inflation targets. This paper is a contribution to this debate, in that the aim of this paper is to evaluate the consequences of adopting different monetary policy objectives in the U.S. macroeconomic policy setting. To accomplish this, we first decompose U.S. macroeconomic data using a time‐frequency domain technique, namely discrete wavelet analysis. We then model the behavior of the U.S. economy over each wavelet frequency range and use our estimated parameters to construct a tracking model. To illustrate the usefulness of this approach, we simulate jointly optimal fiscal and monetary policy with different short‐term monetary targets: an inflation target, a money growth target, an interest rate target, and a real economic growth target. The results show that the most effective monetary policy targets to achieve economic growth are either inflation targets or economic growth targets.

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Is the Taylor rule optimal? Evaluation using a wavelet-based control model

Cited by 10 publications

References 10 publications

Resilient Control for Macroeconomic Models

Resilient Control for Macroeconomic Models

Estimación de la brecha del producto: una revisión de desarrollos recientes y aplicación

Monetary policy objectives and economic outcomes: What can we learn from a wavelet‐based optimal control approach?

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