Understanding Chaos as an Indicator of Economic Stability

Understanding Chaos as an Indicator of Economic Stability

Rohnn B. Sanderson
DOI: 10.4018/978-1-4666-9484-2.ch017
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With what appears to be the increasing sensitivity of economic/financial systems to various events, whether they be natural disaster, changing financial products or government policy, the need to understand how volatility has changed in modern economic systems and how to recognize when volatility will occur is a topic that is extremely important. This topic has been categorized under various topics such as: business cycles, chaos, dynamic systems, fractals, Brownian motion and super cycles just to name a few. The author believes that all of these areas need to be considered at once when analyzing dynamic phenomena which may have varying degrees of the aforementioned. This chapter will implement a Hicksian Accelerator to develop a framework for stylized facts of general dynamic macroeconomic behavior. The chapter will then implement the model and begin the process of estimating the degree of and sensitivity to volatility in a macro economy.
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The study of business cycles and cycling phenomena has a rich and varied history, from a study of them, to an attempt to understand cycles and to possibly control them. This idea has been around for a long time and if it were possible, then understanding the nature of cycles would allow them to be used as an early warning system for economies and financial markets.

For early studies, one could look at the early work of authors such as F.A Hayek (1934) who thought about capital and how it is developed and how prices coordinate economic activity. The cycling work of Nikolai Kondratiev (2014) who during the 1920's found fifty four to sixty year cycles in many economic time series. This is also conferred by Edward Dewey (1971) who found numerous cycles that exist in most phenomina. One such example is his detection of a fifty four year cycle in the European wheat price from 1513-1856. Udny Yule (1926) sought rigor in measuring time-series and showed we need to use caution in correlations in time-series.

Key Terms in this Chapter

Fractal: A natural phenomenon or a mathematical set that exhibits a repeating pattern which can be replicated at every scale.

Currency: A paper or non-metal circulating medium of exchange.

Dynamic System: A concept in mathematics where a fixed rule describes how a point in a geometric space depends on time.

Brownian Motion: A mathematical model used to describe random movements.

Accelerator: The effect of private investment and the marginal propensity to consume on the growth of the economy.

Money: A medium of exchange that has an intrinsic value on its own, other than a medium of exchange.

Chaos Theory: The study of the behavior of dynamical systems that are highly sensitive to initial conditions.

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