Economic Recession Prediction Using Deep Neural Network

• URL: http://arxiv.org/abs/2107.10980v1
• Date: Wed, 21 Jul 2021 22:55:14 GMT
• Title: Economic Recession Prediction Using Deep Neural Network
• Authors: Zihao Wang, Kun Li, Steve Q. Xia, Hongfu Liu
• Abstract summary: We identify the deep learning methodology of Bi-LSTM with Autoencoder as the most accurate model to forecast the beginning and end of economic recessions in the U.S. We adopt commonly-available macro and market-condition features to compare the ability of different machine learning models to generate good predictions both in-sample and out-of-sample.
• Score: 26.504845007567972
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We investigate the effectiveness of different machine learning methodologies in predicting economic cycles. We identify the deep learning methodology of Bi-LSTM with Autoencoder as the most accurate model to forecast the beginning and end of economic recessions in the U.S. We adopt commonly-available macro and market-condition features to compare the ability of different machine learning models to generate good predictions both in-sample and out-of-sample. The proposed model is flexible and dynamic when both predictive variables and model coefficients vary over time. It provided good out-of-sample predictions for the past two recessions and early warning about the COVID-19 recession.

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