Abstract: This paper develops an analytical framework for heterogeneous agent models with household-level heterogeneity in labor productivity and wealth returns, accommodating both growth and business cycle dynamics. I establish the existence of moment-recursive competitive equilibrium (MRCE), where aggregate dynamics depend only on aggregate capital and wealth-idiosyncratic state covariances. The framework yields three key insights: (i) distributional covariances create state-dependent aggregate dynamics through novel channels; (ii) idiosyncratic return risks are priced via their wealth covariance; (iii) equilibrium outcomes are invariant to individual beliefs about aggregates, eliminating expectation formation concerns. This framework enables unified analysis of growth, business cycles, inequality dynamics, and their interactions.

Abstract: https://github.com/QuantEcon/kyoto_2025

Abstract: Over the past three decades China and India have experienced rapid growth and structural transformation. Underneath this similarity however is one significant difference: rural-urban wage gaps during this period declined in India, but widened in China. We formalize a two-sector-two-location model in which structural transformation and urbanization respond endogenously to productivity shocks. While the structural transformation effect widens the rural-urban wage gap, the urbanization effect reduces it. We attribute the contrasting wage gap dynamics in the two countries to the higher costs of urban relocation for workers in China.

Abstract: In the theory of dynamic programming, an optimal policy is a policy whose lifetime value dominates that of all other policies from every possible initial condition in the state space. This raises a natural question: when does optimality from a single state imply optimality from every state? Working in a general setting, we provide sufficient conditions for this property that relate to reachability and irreducibility. Our results have significant implications for modern policy-based algorithms used to solve large-scale dynamic programs. We illustrate our findings by applying them to an optimal savings problem via an algorithm that implements gradient ascent in a policy space constructed from neural networks.

要旨：This paper examines the optimal design of retirement policies that rely on private insurance markets while accounting for financial frictions within these markets. We analyze the impact of uninsurable aggregate interest rate shocks in a life-cycle model where the government screens productivity, longevity, and altruism. We show that observing retirees’ annuitization choices helps separate individual types. However, private annuity markets face supply-side inefficiencies due to interest rate risk. To improve market efficiency, the government can issue long-term bonds, supported by interest rate-contingent taxes. Therefore, full privatization can only be optimal without interest rate shocks; otherwise, Social Security remains necessary.