Logo
Munich Personal RePEc Archive

Artificial Intelligence, Aging, and the Macroeconomy

Wabenga Yango, James (2026): Artificial Intelligence, Aging, and the Macroeconomy.

[thumbnail of MPRA_paper_129480.pdf]
Preview
PDF
MPRA_paper_129480.pdf

Download (634kB) | Preview

Abstract

This paper develops a general-equilibrium overlapping-generations model with endogenous fertility, in which firms accumulate both physical and artificial intelligence (AI) capital, and uses it to study the macroeconomic transmission of two structural disturbances: an AI technology shock and a longevity shock. The AI shock acts as a capital-demand disturbance: it raises all rates of return, most sharply the return to AI capital, reallocates investment from physical to AI capital, and produces a frontloaded expansion of output that decays monotonically. The longevity shock acts as a saving-supply disturbance: it deepens the aggregate capital stock, compresses returns and the real interest rate, and generates hump-shaped, persistent dynamics. The two shocks move fertility in opposite directions: AI raises it modestly through an income effect, while longevity lowers it by strengthening the life-cycle saving motive and the opportunity cost of child-rearing. A forecast-error variance decomposition attributes the bulk of the volatility in most aggregate variables to the longevity shock, while the AI shock accounts for the largest share of the variance in the return to AI capital. Fertility is strongly countercyclical and almost perfectly negatively correlated with hours worked, placing the household time-allocation margin at the center of the transmission mechanism. A robustness analysis confirms that these conclusions reflect structural properties of the model: variation in the capital share and in the persistence of the AI shock leaves the signs of the wage, fertility, output, and consumption responses unchanged, and only the labor–AI elasticity of substitution can reverse them, beyond a threshold that lies well above standard empirical estimates.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.