Bilal Islah | Searcharxiv

arXiv2025

Keeping in Place After the Storm-Emergency Assistance and Evictions

We offer evidence that federal emergency assistance (FEMA) in the days following natural disasters mitigate evictions in comparison to similar emergency scenarios where FEMA aid is not provided. We find an approximate 10.9% increase in overall evictions after hurricane natural disaster events driven in large part by areas in close proximity of the hurricane path that do not receive FEMA rental assistance. Furthermore, we also show that FEMA aid acts as a liquidity buffer to other forms of emergency credit, specifically we find that both transactions volumes and defaults decrease during hurricane events in locations that do receive FEMA aid. This effect largely reverses in areas that do not receive FEMA aid, where the magnitude of transaction volumes drop by less and default rates remain similar relative to the baseline. Overall, this suggests that the availability of emergency liquidity during natural disaster events is indeed a binding constraint with real household financial consequences, in particular through our documented channel of evictions and in usage of high-cost credit.

econ.GN↗

arXiv2025

Bounded Foresight Equilibrium in Large Dynamic Economies with Heterogeneous Agents and Aggregate Shocks

Large dynamic economies with heterogeneous agents and aggregate shocks are central to many important applications, yet their equilibrium analysis remains computationally challenging. This is because the standard solution approach, rational expectations equilibria require agents to predict the evolution of the full cross-sectional distribution of state variables, leading to an extreme curse of dimensionality. In this paper, we introduce a novel equilibrium concept, N-Bounded Foresight Equilibrium (N-BFE), and establish its existence under mild conditions. In N-BFE, agents optimize over an infinite horizon but form expectations about key economic variables only for the next N periods. Beyond this horizon, they assume that economic variables remain constant and use a predetermined continuation value. This equilibrium notion reduces computational complexity and draws a direct parallel to lookahead policies in reinforcement learning, where agents make near-term calculations while relying on approximate valuations beyond a computationally feasible horizon. At the same time, it lowers cognitive demands on agents while better aligning with the behavioral literature by incorporating time inconsistency and limited attention, all while preserving desired forward-looking behavior and ensuring that agents still respond to policy changes. Importantly, in N-BFE equilibria, forecast errors arise endogenously. We measure the foresight errors for different foresight horizons and show that foresight significantly influences the variation in endogenous equilibrium variables, distinguishing our findings from traditional risk aversion or precautionary savings channels. This variation arises from a feedback mechanism between individual decision-making and equilibrium variables, where increased foresight induces greater non-stationarity in agents' decisions and, consequently, in economic variables.

econ.GN↗