Labour productivity in the age of AI: Insights from Panel Data
DOI:
https://doi.org/10.46661/rev.metodoscuant.econ.empresa.9623Keywords:
Artificial Intelligence, Labour Market Dynamics, Future of Work, Human CapitalAbstract
This study examines how labour productivity is affected by AI-related developments by examining a balanced panel dataset of businesses that operate in three different areas between 2014 and 2023. The study uses pooled OLS, Fixed Effects (FE), and Random Effects (RE) models to assess the effects of important factors such as AI-related and non-AI patents, R&D investment, labour input, and company turnover on labour productivity, the dependent variable. According to the findings, AI-related patents have a notable positive impact on labour productivity, supporting earlier studies on technology-driven productivity improvements and highlighting the critical significance of AI innovation. Labour input, on the other hand, has a negative correlation with productivity, indicating either inefficiencies in managing larger workforces or diminishing returns to scale. It's interesting to note that employee turnover and productivity are positively correlated, which could be a result of workforce optimisation or the introduction of new perspectives and abilities. In comparison to pooled OLS, the FE model, which takes firm-specific heterogeneity into account, explains around 45.7% of the productivity variance. Diagnostic tests verify the models' resilience, and their validity is improved by autocorrelation and heteroscedasticity corrections. These findings warn against inefficient labour use while highlighting the value of AI and R&D expenditures in boosting productivity. This study advances our knowledge of the dynamics of productivity, labour management, and innovation and guides company executives and policymakers as they navigate the AI-driven economy.
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