论文标题
关于神经和生产网络的等效性
On the Equivalence of Neural and Production Networks
论文作者
论文摘要
本文确定了Cobb-Douglas代理商和人工神经网络的经济网络之间的数学等效性。它探讨了在一般条件下这种等价的两个含义。首先，新兴的文献已经确定网络传播可以将微观经济的扰动转化为巨大的总冲击。神经网络等效性扩大了这种现象的大小和复杂性。其次，如果经济代理商在对当地条件的最佳响应中调整其生产和实用性功能，则市场定价是一个足够且强大的渠道，可以提供信息反馈，从而导致宏观学习。
This paper identifies the mathematical equivalence between economic networks of Cobb-Douglas agents and Artificial Neural Networks. It explores two implications of this equivalence under general conditions. First, a burgeoning literature has established that network propagation can transform microeconomic perturbations into large aggregate shocks. Neural network equivalence amplifies the magnitude and complexity of this phenomenon. Second, if economic agents adjust their production and utility functions in optimal response to local conditions, market pricing is a sufficient and robust channel for information feedback leading to macro learning.
