Which economist's work informs methodology for studying AI's economic effects?

• A. Peter McCrory
• B. Maxim Massenkoff
• C. Saffron Huang
• D. Nicholas Carlini

Answer: (A)

Measuring AI's economic effects relies on a toolkit from economics that links technology adoption to productivity, wages, employment, and prices, and it requires careful empirical methods to identify causal impacts. The best answer points to the economist whose work is known for developing and applying these kinds of methodologies to technology-driven change, providing frameworks for growth accounting, causal analysis, and technology diffusion that are essential for studying AI’s impact. Peter McCrory’s research embodies this approach, offering guidance on study design, data choice, and interpretation of results in the AI context. The other names are not recognized for making these methodological contributions to analyzing AI's economic effects, so they don’t provide the same relevant framework.