Quarterly Fiscal Policy Experiments with a Multiplier-Accelerator Model

Kendrick, David A.; Shoukry, George

doi:10.1007/s10614-013-9389-4

Cited by 16 publications

(44 citation statements)

References 6 publications

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“…The estimations in Kendrick (1981) experienced problems with the poor fit of some variables, and problems with coefficient signs that were opposite of theoretical expectations. The empirical results of our model show that the accelerator model achieves superior measurement and performance when constructed as a second-order difference equation system, which is consistent with the larger lag structure in Kendrick and Shoukry (2013). The fit of the model using a large data set aligns with the theoretical expectations of the consumption crowding-in effect and the investment crowding-out effect of government spending, and further establishes the accelerator model as being a fundamental tool for use in conducting policy analysis.…”

Section: Contribution To Research On Robustness and Fiscal Policysupporting

confidence: 67%

“…Our empirical analysis confirms the usefulness of the accelerator model used in Kendrick (1981) and Kendrick and Shoukry (2013). The estimations in Kendrick (1981) experienced problems with the poor fit of some variables, and problems with coefficient signs that were opposite of theoretical expectations.…”

Section: Contribution To Research On Robustness and Fiscal Policysupporting

confidence: 67%

“…The fit of the model using a large data set aligns with the theoretical expectations of the consumption crowding-in effect and the investment crowding-out effect of government spending, and further establishes the accelerator model as being a fundamental tool for use in conducting policy analysis. Kendrick and Amman (2010), and Kendrick and Shoukry (2013), demonstrate the benefits from employing a quarterly fiscal policy over an annual fiscal policy. They find that more frequent policy changes can respond more quickly to downturns, and achieve more stabilization while creating less additional public debt.…”

Section: Contribution To Research On Robustness and Fiscal Policymentioning

confidence: 99%

“…This section develops a version of the Kendrick (1981) and Kendrick and Shoukry (2013) partial-adjustment, closed-economy macroeconomic accelerator model. Let the variables be defined as follows:…”

Section: Macroeconomic Model Derivation For Deterministic and Lqg Optmentioning

confidence: 99%

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Entering H $$^{\infty }$$ ∞ -Optimal Control Robustness into a Macroeconomic LQ-Tracking Model

Hudgins

2014

Comput Econ

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This analysis explores robust designs for an applied macroeconomic discrete-time LQ tracking model with perfect state measurements. We develop a procedure that reframes the tracking problem as a regulator problem that is then used to simulate the deterministic, stochastic LQG, H-infinity, multiple-parameter minimax, and mixed stochastic/H-infinity control, for quarterly fiscal policy. We compare the results of the five different design structures within a closed-economy accelerator model using data for the United States for the period 1947-2012. When the consumption and investment tracking errors are more heavily emphasized, the H-infinity design renders the most aggressive fiscal policy, followed by the multiple-parameter minimax, mixed, LQG, and deterministic versions. When the control tracking errors are heavily weighted, the resulting fiscal policy is initially more aggressive under the multi-parameter specification than under the H-infinity and mixed designs. The results from both weighting schemes show that fiscal policy remains more aggressive under the robust designs than the deterministic model. The simulations show that the multiparameter minimax and mixed designs provide a balancing compromise between the stochastic and robust methods when the worst-case concerns can be primarily limited to a subset of the state-space.

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Section: Contribution To Research On Robustness and Fiscal Policysupporting

confidence: 67%

Section: Contribution To Research On Robustness and Fiscal Policysupporting

confidence: 67%

Section: Contribution To Research On Robustness and Fiscal Policymentioning

confidence: 99%

Section: Macroeconomic Model Derivation For Deterministic and Lqg Optmentioning

confidence: 99%

See 2 more Smart Citations

Entering H $$^{\infty }$$ ∞ -Optimal Control Robustness into a Macroeconomic LQ-Tracking Model

Hudgins

2014

Comput Econ

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“…Most importantly, the feedback methodology allows for more frequent (and, possibly, smaller) interventions by the policymaker, which are likely to result in a smoother transition path for the economy (see Kendrick and Amman 2014;Kendrick and Shoukry 2014).…”

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confidence: 99%

Feedback policy rules for government spending: an algorithmic approach

Kostarakos

Kotsios

2017

Economic Structures

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One of the most important objectives of economic policy is to ensure, via the appropriate manipulation of the available policy instruments (control variables), that the economic system tracks, as closely as possible, a desired path for the policy targets (outputs). One of the approaches that has been utilized for the design of economic policy is the feedback approach, stemming from the mathematical control theory literature. Various aspects of the feedback methodology have been utilized for the purposes of policy design for more than 50 years, starting with the use of PID controllers in the seminal paper by Phillips (1954). These aspects range from (stochastic) optimal feedback control (see, The importance of feedback rules for policy design is evident from the fact that for more than 20 years monetary policy decisions have been, to a large extent, based on the Taylor rule (see Taylor 1993); this is a linear feedback policy rule stipulating (in its simplest form) that the interest rate is set based on deviations of inflation and GDP from target levels of inflation and potential GDP, respectively. It is interesting to note here that Taylor presented a rule that had fixed settings for the parameters; in particular:among(1) r = p + 0.5y + 0.5(p − 2) + 2 AbstractWe present an algorithmic approach for the design of fiscal policy rules. In particular, using algorithmic feedback control techniques, we design linear feedback policy rules such that predetermined target levels for GDP and public debt are simultaneously, exactly tracked. We run a number of simulations in order to examine the effects of different policy response rates and the overall effectiveness of the proposed methodology.

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What is the right balance between US monetary and fiscal policy? Explorations using simulated wavelet-based optimal tracking control

Crowley

Hudgins

2017

Empir Econ

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Quarterly Fiscal Policy Experiments with a Multiplier-Accelerator Model

Cited by 16 publications

References 6 publications

Entering H $$^{\infty }$$ ∞ -Optimal Control Robustness into a Macroeconomic LQ-Tracking Model

Entering H $$^{\infty }$$ ∞ -Optimal Control Robustness into a Macroeconomic LQ-Tracking Model

Feedback policy rules for government spending: an algorithmic approach

What is the right balance between US monetary and fiscal policy? Explorations using simulated wavelet-based optimal tracking control

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