Global Business Networks
71 Pages Posted: 3 Apr 2023 Last revised: 6 May 2024
There are 2 versions of this paper
Global Business Networks
Global Business Networks
Date Written: March 21, 2023
Abstract
We leverage the capabilities of GPT-3 to generate historical business descriptions for over 63,000 global firms. Utilizing these descriptions and advanced embedding models from OpenAI, we construct time-varying business networks that represent business links across the globe. We showcase the performance of these networks by studying the lead-lag effect for global stocks and predicting target firms in M&A deals. We demonstrate how masking firm-specific details can mitigate look-ahead bias concerns that may arise from the use of embedding models with a recent knowledge cutoff, and how to differentiate between competitor, supplier, and customer links by fine-tuning an open-source language model.
Keywords: Business Network, Textual Analysis, Natural Language Processing, GPT-3, Large Language Models
JEL Classification: G11, G14
Suggested Citation: Suggested Citation