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Loss aversion in aggregate macroeconomic time series

机译:总体宏观经济时间序列中的损失规避

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Prospect theory has been the focus of increasing attention in many fields of economics. However, it has scarcely been addressed in macroeconomic growth models--neither on theoretical nor on empirical grounds. In this paper we use prospect theory in astochastic optimal growth model. Thereafter, the focus lies on linking the Euler equation obtained from a prospect theory growth model of this kind to real macroeconomic data. We will use generalized method of moments (GMM) estimation to test the implications of such a non-linear prospect utility Euler equation. Our results indicate that loss aversion can be traced in aggregate macroeconomic time series.
机译:前景理论已成为许多经济学领域日益关注的焦点。但是,无论是从理论还是从经验的角度来看,宏观经济增长模型都几乎没有解决这一问题。在本文中,我们将前景理论用于随机最优增长模型。此后,重点在于将从这种前景理论增长模型获得的欧拉方程与真实的宏观经济数据联系起来。我们将使用广义矩估计(GMM)来测试这种非线性前景效用欧拉方程的含义。我们的结果表明,可以在总的宏观经济时间序列中追踪损失的厌恶情绪。

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