OPTGAME3: A Dynamic Game Solver and an Economic Example

Blueschke, Dmitri; Neck, Reinhard; Behrens, Doris A.

doi:10.1007/978-3-319-02690-9_2

Cited by 17 publications

(19 citation statements)

References 12 publications

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“…Equations (1), (2) and (5) define a nonlinear dynamic tracking game problem, which can be solved for different solution concepts. In order to solve this game we use the OPTGAME algorithm as described in [14]. The OPTGAME3 algorithm allows us to find approximate solutions for nonlinear-quadratic dynamic tracking games.…”

Section: Description Of the Dynamic Game Problemmentioning

confidence: 99%

“…The dynamic system, which constrains the choices of the decision makers, is given in state-space form by the MUMOD2 model as presented in equations (6) to (14). Equations (15), (16) and the dynamic system (6)-(14) define a nonlinear dynamic tracking game problem which can be solved for different solution concepts.…”

Section: The Mumod2 Modelmentioning

confidence: 99%

“…Equations (15), (16) and the dynamic system (6)-(14) define a nonlinear dynamic tracking game problem which can be solved for different solution concepts. Using the OPTGAME3 algorithm (see [14]) we are able to solve this dynamic tracking game and to analyze the effects of different shocks acting on the system. In this study we consider demand-side shocks in the goods markets as represented by the variables zd it .…”

Section: The Mumod2 Modelmentioning

confidence: 99%

See 2 more Smart Citations

Game of Thrones: Accommodating Monetary Policies in a Monetary Union

Blueschke¹,

Neck²

2018

Preprint

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In this paper we present an application of the dynamic tracking games framework to a monetary union. We use a small stylized nonlinear three-country macroeconomic model of a monetary union to analyse the interactions between fiscal (governments) and monetary (common central bank) policy makers, assuming different objective functions of these decision makers. Using the OPTGAME algorithm we calculate solutions for several games: a noncooperative solution where each government and the central bank play against each other (a feedback Nash equilibrium solution), a fully cooperative solution with all players following a joint course of action (a Pareto optimal solution), and three solutions where various coalitions (subsets of the players) play against coalitions of the other players in a noncooperative way. It turns out that the fully cooperative solution yields the best results, the noncooperative solution fares worst, and the coalition games lie in between, with a broad coalition of the fiscally more responsible countries and the central bank against the less thrifty country coming closest to the Pareto optimum.

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Section: Description Of the Dynamic Game Problemmentioning

confidence: 99%

Section: The Mumod2 Modelmentioning

confidence: 99%

Section: The Mumod2 Modelmentioning

confidence: 99%

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Game of Thrones: Accommodating Monetary Policies in a Monetary Union

Blueschke¹,

Neck²

2018

Preprint

Self Cite

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“…Using the OPTGAME algorithm (see Blueschke et al 2013) we are able to solve the stated dynamic tracking game problem. That means, we try to find N trajectories of control variables u i t , i D 1; : : : ; N, which minimize the postulated objective functions subject to the dynamic system.…”

Section: Nonlinear Dynamic Tracking Gamesmentioning

confidence: 99%

Dynamic Approaches to Global Economic Challenges

Bednar–Friedl¹,

Kleinert²

2016

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“…Equations (15), (16) and the dynamic system (6)- (14) define a nonlinear dynamic tracking game problem which can be solved for different solution concepts. Using the OPTGAME3 algorithm (see Blueschke et al 2013) we solve this dynamic tracking game numerically and analyze the effects of different shocks acting on the system. In this study we consider demand-side shocks in the goods markets as represented by the variables (Table 5) zd it .…”

Section: The Mumod1 Modelmentioning

confidence: 99%

United we stand: on the macroeconomics of a Fiscal union

Neck

Blueschke

2016

Empirica

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In this paper, we apply dynamic tracking games to macroeconomic policy making in a monetary union. We use a small stylized nonlinear two-country macroeconomic model of a monetary union for analyzing the interactions between two fiscal (governments: ''core'' and ''periphery'') and one monetary (central bank) policy makers, assuming different objective functions of these decision makers. Using the OPTGAME algorithm, we calculate numerical solutions for cooperative (Pareto optimal) and non-cooperative games (feedback Nash). We show how the policy makers react to adverse demand shocks. We investigate the consequences of three scenarios: decentralized fiscal policies controlled by independent governments (the present situation), centralized fiscal policy (a fiscal union) with an independent central bank (pure fiscal union), and a fully centralized monetary and fiscal union. For the latter two scenarios, we demonstrate the importance of different assumptions about the joint objective function corresponding to different weights for the two governments in the design of the common fiscal policy. We show that a fiscal union with weights corresponding to the number of states in each of the blocs gives better results than non-cooperative policy making. When one bloc dominates the fiscal union, decentralized policies yield lower overall losses than the pure fiscal union and the monetary and fiscal union.

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OPTGAME3: A Dynamic Game Solver and an Economic Example

Cited by 17 publications

References 12 publications

Game of Thrones: Accommodating Monetary Policies in a Monetary Union

Game of Thrones: Accommodating Monetary Policies in a Monetary Union

Dynamic Approaches to Global Economic Challenges

United we stand: on the macroeconomics of a Fiscal union

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