2001 Fiscal Year Final Research Report Summary
Study of Economic Fluctuations Using the Method of Nonlinear Dynamics
| Project/Area Number |
11630020
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
経済理論
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| Research Institution | Waseda University |
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Principal Investigator |
INABA Toshio Waseda University, School of Education, Professor, 教育学部, 教授 (30120950)
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| Co-Investigator(Kenkyū-buntansha) |
TANAKA Hisanori Waseda University, School of Political Science and Economics, Assistant, 政治経済学部, 助手 (00339665)
WARAGAI Tomoki Waseda University, School of Education, Professor, 教育学部, 教授 (20267462)
SASAKURA Kazuyuki Waseda University, School of Political Science and Economics, Professor, 教育学部, 教授 (90235284)
MISAWA Tetsuya Nagoya City University, Faculty of Economics, Professor, 経済学部, 教授 (10190620)
MATSUMOTO Akio Chuo University, Department of Economics, Professor, 経済学部, 教授 (50149473)
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| Project Period (FY) |
1999 – 2001
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| Keywords | Business Cycle / Nonlinear Dynamics / Chaos / Noise |
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| Research Abstract |
(1) One Dimensional Models
Chaos occurs in a nonlinear cobweb model with normal demand and supply, naive expectations and adaptive production adjustment. We demonstrates the possibility that chaotic fluctuations may be preferable to a steady state for a simple macro disequilibrium model in which inventory can be chaotically fluctuated.
(2) High Dimensional Models
We investigate the global dynamics of two-dimensional Diamond-type overlapping generations model extended to allow for government intervention. We identify conditions under which transverse homoclinic points to the golden rule steady state are generated. We examine by mean of analytical method and numerical simulations the properties of three-dimensional Kaldor-type business cycle models in which a parameter is fluctuated by noise. It is shown that noise may not obscure the underling structures, but also reveal the hidden structures.
(3) New Numerical Approximation Schemes
Composition methods for autonomous stochastic differential equations (SDEs) are formulated to produce numerical approximation schemes for the equations. The new schemes are advantageous to preserve the special character of SDEs numerically and are useful for approximations of the solutions to stochastic nonlinear equations
(4) Alternative Approaches and Models
We investigate various alternative approaches and models. For example, percolation theory is employed to model stock price fluctuations.
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