Residential income segregation: A behavioral model of the housing market

TL;DR

This paper introduces a spatial Agent-Based Model of the housing market to analyze how income segregation, inequality, and policies influence house prices and neighborhood composition, providing new insights into urban economic dynamics.

Contribution

It develops a novel ABM explicitly modeling buyer and seller behaviors, with analytical and simulation results linking income distribution, segregation, and policy effects.

Findings

Higher income inequality lowers overall house prices.

Demand spikes increase prices citywide.

Subsidies are more effective than taxes in promoting social mixing.

Abstract

We represent the functioning of the housing market and study the relation between income segregation, income inequality and house prices by introducing a spatial Agent-Based Model (ABM). Differently from traditional models in urban economics, we explicitly specify the behavior of buyers and sellers and the price formation mechanism. Buyers who differ by income select among heterogeneous neighborhoods using a probabilistic model of residential choice; sellers employ an aspiration level heuristic to set their reservation offer price; prices are determined through a continuous double auction. We first provide an approximate analytical solution of the ABM, shedding light on the structure of the model and on the effect of the parameters. We then simulate the ABM and find that: (i) a more unequal income distribution lowers the prices globally, but implies stronger segregation; (ii) a spike of the demand in one part of the city increases the prices all over the city; (iii) subsidies are more efficient than taxes in fostering social mixing.