Konferenzbeitrag
Artificial Intelligence, Income Distribution and Economic Growth
The economic impact of Artificial Intelligence (AI) is studied using a (semi) endogenous growth model with two novel features. First, the task approach from labor economics is reformulated and integrated into a growth model. Second, the standard represen- tative household assumption is rejected, so that aggregate demand restrictions can be introduced. With these novel features it is shown that (i) AI automation can decrease the share of labor income no matter the size of the elasticity of substitution between AI and labor, and (ii) when this elasticity is high, AI will unambiguously reduce aggre- gate demand and slow down GDP growth, even in the face of the positive technology shock that AI entails. If the elasticity of substitution is low, then GDP, productivity and wage growth may however still slow down, because the economy will then fail to benefit from the supply-side driven capacity expansion potential that AI can deliver. The model can thus explain why advanced countries tend to experience, despite much AI hype, the simultaneous existence of rather high employment with stagnating wages, productivity, and GDP.
- Sprache
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Englisch
- Erschienen in
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Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2020: Gender Economics
Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
Technological Change: Choices and Consequences; Diffusion Processes
Human Capital; Skills; Occupational Choice; Labor Productivity
Macroeconomics: Consumption; Saving; Wealth
Aggregate Factor Income Distribution
artificial intelligence
productivity
labor demand
income distribution
growth theory
Naude, Wim
- Handle
- Letzte Aktualisierung
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20.09.2024, 08:21 MESZ
Datenpartner
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Objekttyp
- Konferenzbeitrag
Beteiligte
- Gries, Thomas
- Naude, Wim
- ZBW - Leibniz Information Centre for Economics
Entstanden
- 2020