Business Cycle Modeling Between Financial Crises and Black Swans: Ornstein-Uhlenbeck Stochastic Process versus Kaldor Deterministic Chaotic Model

G. Orlando, G. Zimatore
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引用次数: 2

Abstract

Business cycles are oscillations in the economy because of recessions and expansions. In this paper we investigate the oscillation of the gross domestic product as a result of its relations with the other main macroeconomic variables such as capital, consumption, and investment. There is a long-standing debate about chaos and non-linear dynamics in economy and even the usefulness of those concepts has been questioned. Stochastic modeling has proven to be able to simulate reality fairly well. However, a stochastic behavior implies that reality is about exogenous randomness, while a chaotic behavior means that reality is deterministic and non-linearities are endogenous. Here we compare an Ornstein-Uhlenbeck stochastic process with a Kaldor-Kalecki deterministic chaotic model to understand which one fits better real data. We show that our chaotic model is able to represent reality as well as the stochastic model taken into consideration. Furthermore, our model may reproduce an extreme event (black swans).
金融危机与黑天鹅之间的商业周期建模:Ornstein-Uhlenbeck随机过程与Kaldor确定性混沌模型
商业周期是由经济衰退和扩张引起的经济波动。在本文中,我们研究了国内生产总值与其他主要宏观经济变量(如资本、消费和投资)的关系所产生的振荡。关于经济中的混沌和非线性动力学的争论由来已久,甚至这些概念的实用性也受到质疑。随机建模已被证明能够很好地模拟现实。然而,随机行为意味着现实是外生随机性,而混沌行为意味着现实是确定性的,非线性是内生的。在这里,我们将Ornstein-Uhlenbeck随机过程与Kaldor-Kalecki确定性混沌模型进行比较,以了解哪种模型更适合实际数据。结果表明,混沌模型既能反映实际情况,又能反映随机模型。此外,我们的模型可能重现一个极端事件(黑天鹅事件)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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