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Public debt and welfare with machine learning

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  • Zhu, Jingjing
  • Huang, Tianyuan

Abstract

The issuance of public debt affects asset returns in the market, which in turn affects macroeconomic equilibrium and wealth distribution. We use a two-period overlapping generations model with idiosyncratic investment risk to solve the general equilibrium problem of public debt and welfare, using machine learning techniques to obtain stable distributions and comparative static analysis to derive four channels that affect welfare. We find that the income channel has the largest impact on welfare from changes in public debt and the investment ratio channel has the smallest impact on welfare, where the setting of the model parameters does not affect the results of the channel decomposition.

Suggested Citation

  • Zhu, Jingjing & Huang, Tianyuan, 2024. "Public debt and welfare with machine learning," Finance Research Letters, Elsevier, vol. 69(PA).
    • Handle: RePEc:eee:finlet:v:69:y:2024:i:pa:s1544612324011930
    DOI: 10.1016/j.frl.2024.106164
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    References listed on IDEAS

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