Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
AI and Coder Employment: Compiling the Evidence. |
| Συγγραφείς: |
Crane, Leland D.1, Soto, Paul E.1 |
| Πηγή: |
Working Papers: U.S. Federal Reserve Board's Finance & Economic Discussion Series. Mar2026, Preceding p1-56. 57p. |
| Θεματικοί όροι: |
*Computer programmers, *Computer programming, *Economic shock, *Labor market, ChatGPT, Language models |
| Περίληψη: |
We evaluate whether LLMs have had any discernible impact on the aggregate labor market so far. We focus on occupations that are computer programming-intensive, motivated by data showing that coding is one of the most LLM-exposed tasks. Linking O*NET to CPS we find that aggregate employment of coders has decelerated sharply since the introduction of ChatGPT. Using a novel control variable for industry-level shocks we show that the deceleration is not attributable to the exposure of coders to slowing industries, suggesting instead that coders experienced an occupation-specific shock around the introduction of ChatGPT. Coder employment has continued to grow in recent years, though much more slowly than it did pre-2022. We validate the industry-level control variable by examining historical examples of occupations that experienced either occupation-specific or industry-level shocks. We also provide statistics on the agreement rates between different measures of AI exposure. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Business Source Index |