Okun’s law revisited in the time–frequency domain: introducing unemployment into a wavelet-based control model

Crowley, Patrick M.; Hudgins, David

doi:10.1007/s00181-020-01980-7

Cited by 6 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( 20 ). Using the method and estimates from Crowley and Hudgins ( 2021b ), unemployment is determined by Okun’s Law (OL) where the unemployment rate adjusts to the momentum in national output. Then, using Eq.…”

Section: Application and Simulationsmentioning

confidence: 99%

“…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%

“…There are penalty weights on the money growth, inflation, and national output tracking errors, so the central bank can choose to focus on monetary, economic growth, or inflation targets by selecting a large value for the penalty weight on any given objective. Crowley and Hudgins ( 2021b ) found that fiscal policy was more aggressive when economic growth was relatively prioritized, whereas monetary policy was relatively more aggressive when the inflation rate was emphasized.…”

Section: Application and Simulationsmentioning

confidence: 99%

See 2 more Smart Citations

Resilient Control for Macroeconomic Models

Hudgins

Crowley

2022

Comput Econ

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Application and Simulationsmentioning

confidence: 99%

Section: Application and Simulationsmentioning

confidence: 99%

Section: Application and Simulationsmentioning

confidence: 99%

See 1 more Smart Citation

Resilient Control for Macroeconomic Models

Hudgins

Crowley

2022

Comput Econ

Self Cite

View full text Add to dashboard Cite

show abstract

“…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.…”

mentioning

confidence: 99%

“…Crowley and Hudgins (2021b) found that including unemployment in the model dampened the thrust of monetary policy. That is, the introduction of unemployment as a variable is likely to result in less expansionary monetary policy in a low unemployment environment, but will also result in less contractionary monetary policy in a high unemployment environment.…”

mentioning

confidence: 99%

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

Crowley

Hudgins

2021

The Manchester School

Self Cite

View full text Add to dashboard Cite

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.

show abstract