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Modeling, Identification and Control
Article . 1998 . Peer-reviewed
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Modeling, Identification and Control
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The Macroeconomy as a Network of Money-Flow Transfer Functions

The macroeconomy as a network of money-flow transfer functions
Authors: Trond Andresen;

The Macroeconomy as a Network of Money-Flow Transfer Functions

Abstract

Summary: An introduction on A. W. Phillips ``hydraulic'' macroeconomic models is given. His (and others economists') notion that a macroeconomy may reasonably be considered to have dynamics corresponding to a first-order time lag transfer function, is justified in this paper by aggregation of individual micro agents. In connection with this economic application, we derive and discuss a theorem and some rules for general networks of time lagged blocks. Finally, Monte Carlo simulations of networks of micro agents are undertaken, supporting the validity of the first-order time lag aggregate model.

Keywords

Economic growth models, Electronic computers. Computer science, network, Macroeconomics, QA75.5-76.95, block diagram, first-order time lag transfer function, time lag

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
Published in a Diamond OA journal