HousingABM_Japan: An Agent-Based Model of Price and Rent Amplification in the Tokyo Housing Market (1.0.0)
HousingABM_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.
The archive contains the full NetLogo model, including all BehaviorSpace experiment definitions; a README with paper-to-code parameter mapping and reproduction instructions; and a supplementary table with the full sensitivity-analysis results. This model was developed for a manuscript submitted to New Generation Computing.
Release Notes
v1.0.0 — Initial release accompanying the manuscript submitted to New Generation Computing. Includes the full NetLogo model with all BehaviorSpace experiment definitions, README with paper-to-code parameter mapping, and full sensitivity-analysis results.
Associated Publications
HousingABM_Japan: An Agent-Based Model of Price and Rent Amplification in the Tokyo Housing Market 1.0.0
Submitted by
Eiki Tamama
Published Sep 06, 2026
Last modified Sep 06, 2026
HousingABM_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.
The archive contains the full NetLogo model, including all BehaviorSpace experiment definitions; a README with paper-to-code parameter mapping and reproduction instructions; and a supplementary table with the full sensitivity-analysis results. This model was developed for a manuscript submitted to New Generation Computing.
Release Notes
v1.0.0 — Initial release accompanying the manuscript submitted to New Generation Computing. Includes the full NetLogo model with all BehaviorSpace experiment definitions, README with paper-to-code parameter mapping, and full sensitivity-analysis results.