An Agent-Based Model of the Housing Market Bubble in Metropolitan Washington D.C.

27 Pages Posted: 13 Feb 2024

See all articles by Robert Axtell

Robert Axtell

George Mason University - Department of Computational Social Science; George Mason University - Department of Economics; Santa Fe Institute - Economics

J. Doyne Farmer

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School; Santa Fe Institute

John Geanakoplos

Yale University; Santa Fe Institute

Peter Howitt

Brown University

Ernesto Carrella

Independent

Benjamin Conlee

Independent

Jon Goldstein

Independent

Matthew Hendrey

Independent

Philip Kalikman

Sy Syms School of Business, Yeshiva University

David Masad

Independent

Nathan Palmer

Board of Governors of the Federal Reserve System

Chun-Yi Yang

Independent

Date Written: May 25, 2014

Abstract

Several independent datasets concerning household behavior in the Washington, D.C. metropolitan area are combined to create an agent-based model of the recent housing market bubble and its aftermath. Comprehensive data on housing stock attributes, primarily from local government sources, are used as input to the model, as are administratively-complete data on household characteristics. Data covering all real estate transactions over the period 1997-2009 are used as targets for model output, including inventory levels and average days-on-market in addition to price statistics. Finally, a very large sample of mortgage service data (80-90 percent coverage of metro D.C.) serve as both input to the model (e.g., mortgage types, interest rates obtained) as well as target output (e.g., refinancing rates, foreclosure levels). The model consists of a large number of heterogeneous households who make rent or buy decisions, are matched to homes and commonly seek mortgages with which to purchase homes. These households have homogeneous rules of behavior but heterogeneous realized behavior since decisions depend on local household characteristics (e.g., size, composition, financials). This is a so-called agent-based computational model since each household and the banks originating mortgages are software agents while each home and each mortgage are soft- ware objects. The model is capable of running at full-scale with the metropolitan D.C. housing market, over 2 million households. Overall, we find that certain empirically- grounded household decision rules are capable of generating a home price bubble much like what was observed during this time period. The model does not get the absolute bubble level and the timing of its bursting exactly right but does a good job on certain market ’internals’ such as real estate sales, inventories and market tightness. Not in the model at present are fine-grained aspect of household decision-making (e.g., moving in advance of schools starting) and thus the model lacks certain well-known temporal phenomena like seasonality. Also, while the home purchase market is deeply represented in the model, few details of the rental market are present, a further weakness. These limitations and parameter sensitivities are described. Despite these flaws, we use the calibrated model to perform a few policy experiments. Our preliminary findings are that tighter interest rate policies would have done little to attenuate the price bubble, while limiting household leverage would have had a larger effect.

Keywords: Housing markets, agent-based modeling, financial bubbles

JEL Classification: G1, G5

Suggested Citation

Axtell, Robert and Farmer, J. Doyne and Geanakoplos, John D and Howitt, Peter and Carrella, Ernesto and Conlee, Benjamin and Goldstein, Jon and Hendrey, Matthew and Kalikman, Philip and Masad, David and Palmer, Nathan and Yang, Chun-Yi, An Agent-Based Model of the Housing Market Bubble in Metropolitan Washington D.C. (May 25, 2014). Available at SSRN: https://ssrn.com/abstract=4710928 or http://dx.doi.org/10.2139/ssrn.4710928

Robert Axtell

George Mason University - Department of Computational Social Science ( email )

4400 University Drive
375 Research Hall
Fairfax, VA 22030
United States

George Mason University - Department of Economics ( email )

4400 University Drive
Fairfax, VA 22030
United States

Santa Fe Institute - Economics ( email )

1399 Hyde Park Rd
Santa Fe, NM 87501
United States

J. Doyne Farmer (Contact Author)

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School ( email )

Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

HOME PAGE: http://www.inet.ox.ac.uk/people/view/4

Santa Fe Institute ( email )

1399 Hyde Park Road
Santa Fe, NM 87501
United States
505-984-8800 (Phone)
505-982-0565 (Fax)

HOME PAGE: http://www.santafe.edu/~jdf/

John D Geanakoplos

Yale University ( email )

30 Hillhouse Avenue
New Haven, CT 06511
United States
203-432-3397 (Phone)

HOME PAGE: http://https://economics.yale.edu/people/faculty/john-geanakoplos

Santa Fe Institute ( email )

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Peter Howitt

Brown University

Box 1860
Providence, RI 02912
United States

Ernesto Carrella

Independent

Benjamin Conlee

Independent ( email )

Jon Goldstein

Independent

Matthew Hendrey

Independent

Philip Kalikman

Sy Syms School of Business, Yeshiva University

United States

HOME PAGE: http://https://kalikman.com

David Masad

Independent

Nathan Palmer

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Chun-Yi Yang

Independent ( email )

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