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arXiv · 2305.09783

Deep Learning for Solving and Estimating Dynamic Macro-Finance Models

Benjamin Fan·Edward Qiao·Anran Jiao·Zhouzhou Gu·Wenhao Li·Lu Lu
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Abstract

We develop a methodology that utilizes deep learning to simultaneously solve and estimate canonical continuous-time general equilibrium models in financial economics. We illustrate our method in two examples: (1) industrial dynamics of firms and (2) macroeconomic models with financial frictions. Through these applications, we illustrate the advantages of our method: generality, simultaneous solution and estimation, leveraging the state-of-art machine-learning techniques, and handling large state space. The method is versatile and can be applied to a vast variety of problems.

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Benjamin Fan, Edward Qiao, Anran Jiao, Zhouzhou Gu, Wenhao Li, Lu Lu. 2023-05-05. Deep Learning for Solving and Estimating Dynamic Macro-Finance Models. https://arxiv.org/abs/2305.09783

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