Learning Production Process Heterogeneity Across Industries: Implications of Deep Learning for Corporate M&A Decisions
General Economics
2023-01-24 v1 Economics
Abstract
Using deep learning techniques, we introduce a novel measure for production process heterogeneity across industries. For each pair of industries during 1990-2021, we estimate the functional distance between two industries' production processes via deep neural network. Our estimates uncover the underlying factors and weights reflected in the multi-stage production decision tree in each industry. We find that the greater the functional distance between two industries' production processes, the lower are the number of M&As, deal completion rates, announcement returns, and post-M&A survival likelihood. Our results highlight the importance of structural heterogeneity in production technology to firms' business integration decisions.
Keywords
Cite
@article{arxiv.2301.08847,
title = {Learning Production Process Heterogeneity Across Industries: Implications of Deep Learning for Corporate M&A Decisions},
author = {Jongsub Lee and Hayong Yun},
journal= {arXiv preprint arXiv:2301.08847},
year = {2023}
}