Artificial Intelligence Technology, Task Attribute and Occupational Substitutable Risk: Empirical Evidence from the Micro-level

Authors

  • Li Hung Wang National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
  • Shi Ming Hu National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
  • Zi Quan Dong Pohang University of Science and Technology, Pohang, South Korea

DOI:

https://doi.org/10.53935/jomw.v2023i1.232

Keywords:

Artificial Intelligence, Labor Market, Technological Unemployment, Firm Performance, Productivity Growth

Abstract

Artificial intelligence (AI) technology has recently emerged as a new general-purpose technology (GPT). However, its effects on firm productivity, employment, and workforce composition remain unclear. This study analyzes a micro-level panel dataset of Taiwanese electronics firms listed on the Taiwan Stock Exchange (TSE) and the Over-the-Counter (OTC) market from 2002 to 2018. Using a keyword-matching method, the research identifies AI-related patent classifications and patents that capture AI innovations. These patents are matched with listed electronics firms to create a comprehensive panel dataset. Empirical results show that AI technology is significantly and positively associated with firm productivity. The study employs various techniques of the generalized method of moments (GMM) for dynamic panel data modeling to address endogeneity, yielding consistent findings. The analysis offers valuable insights for R&D and labor policy development. Additionally, the study discusses how these measures can assist researchers and policymakers in understanding AI's impact on markets.

Published

2023-01-02

Issue

Vol. 2023 No. 1 (2023)

Section

Articles