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System Dynamics and Its Contribution to Economics and Economic Modeling

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Book cover Complex Systems in Finance and Econometrics

Article Outline

Glossary

Definition of the Subject

Introduction

Types of Dynamic Simulation

Translating Existing Economic Models into a System Dynamics Format

Improving Existing Economic Models with System Dynamics

Creating Economic Dynamics Models from Scratch

Model Validity

Controversies

Future Directions

Bibliography

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Abbreviations

Stock:

Stocks, which are sometimes referred to as “levels” or “states”, accumulate (i. e., sum up) the information or material that flows into and out of them. Stocks are thus responsible for decoupling flows, creating delays, preserving system memory, and altering the time shape of flows.

Flow:

Flows of information or material enter and exit a system's stocks and, in so doing, create a system's dynamics. Stated differently, the net flow into or out of a stock is the stock's rate of change. When human decision making is represented in a system dynamics model, it appears in the system's flow equations. Mathematically, a system's flow equations are ordinary differential equations and their format determines whether or not a system is linear or nonlinear.

Feedback:

Feedback is the transmission and return of information about the amount of information or material that has accumulated in a system's stocks. When the return of this information reinforces a system's behavior, the loop is said to be positive. Positive loops are responsible for the exponential growth of a system over time. Negative feedback loops represent goal seeking behavior in complex systems. When a negative loop detects a gap between the amount of information or material in a system's stock and the desired amount of information or material, it initiates corrective action. If this corrective action is not significantly delayed, the system will smoothly adjust to its goal. If the corrective action is delayed, however, the system can overshoot or undershoot its goal and the system can oscillate.

Full information maximum likelihood with opti mal filtering:

FIMLOF is a sophisticated technique for estimating the parameters of a system dynamics model, while simultaneously fitting its output to numerical data. Its intellectual origins can be traced to control engineering and the work of Fred Schwepe. David Peterson pioneered a method for adapting FIMLOF for use in system dynamics modeling.

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Author information

Authors and Affiliations

  1. Worcester Polytechnic Institute, Worcester, USA

    Michael J. Radzicki

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Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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Radzicki, M.J. (2009). System Dynamics and Its Contribution to Economics and Economic Modeling. In: Meyers, R. (eds) Complex Systems in Finance and Econometrics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7701-4_39

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  • DOI: https://doi.org/10.1007/978-1-4419-7701-4_39

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-7700-7

  • Online ISBN: 978-1-4419-7701-4

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