Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
Displaying 1 of 1 results rental market clear search
HousingABM_Japan: An Agent-Based Model of Price and Rent Amplification in the Tokyo Housing Market
Eiki Tamama | Published Sunday, September 06, 2026HousingABM_Japan is a NetLogo agent-based model of the residential market of Tokyo’s 23 wards. It evaluates whether a single parameter configuration can jointly reproduce key features of prices, rents, yields, and market turnover across distinct market regimes from 2001 to 2025, with particular attention to demand- and supply-side trend-following during the 2021–2025 price surge.
The model builds on the Bank of England housing-market lineage (Baptista et al. 2016; Carro et al. 2023) and introduces four extensions: (1) dynamic linkages between the sale and rental markets through vacancy, rents, and yields; (2) heterogeneous demand-side trend-following; (3) supply-side trend-following through construction-cost trend anchoring and a momentum-dependent dynamic premium; and (4) housing-equity borrowing that converts unrealized equity into additional borrowing capacity.
Twenty parameters are calibrated using 2001–2015 data and held fixed for post-calibration evaluation over 2016–2020 and 2021–2025, while annual exogenous inputs follow observed historical paths. The model reproduces the shift from moderate price growth to the 2021–2025 surge, as well as rent acceleration, surge-period yield compression, and persistently low market turnover, although it understates the intermediate acceleration of 2016–2020.
…