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An endogenous gridpoint method for distributional dynamics
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DOI：10.1016/j.jmoneco.2026.103895.png)
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• We develop a novel endogenous gridpoint method (DEGM) to solve distributional dynamics in heterogeneous agent models. DEGM is a fast and accurate interpolation scheme that captures nonlinearities without requiring integration. • Compared to the standard lottery method, DEGM converges faster and achieves higher accuracy with fewer gridpoints. This improves the computational tractability of solving models with rich heterogeneity. • We show that DEGM is compatible with third-order perturbation methods and captures nonlinear distributional effects that the lottery method misses. • Applying our method to a model with capital depreciation shocks, we find that aggregate investment risk increases wealth inequality. The effect arises from nonlinear distributional dynamics that DEGM captures and standard methods miss.
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4.1
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Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models.png)
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