Date of Award

Fall 2019

Degree Type

Open Access Dissertation

Degree Name

Political Science, PhD

Program

School of Social Science, Politics, and Evaluation

Concentration

Computational Mathematics and Numerical Analysis

Advisor/Supervisor/Committee Chair

Mark Abdollahian

Dissertation or Thesis Committee Member

Zining Yang

Dissertation or Thesis Committee Member

Yi Feng

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2019 Faizan Khan

Abstract

This dissertation presents an agent-based model (ABM) to model systemic risk in the housing and financial markets from 1986 to 2017 and provides a unique approach to simulating the financial market along with demonstrating the phenomenon of emergence resulting from the interconnected-behavior of consumers, banks and the Federal Reserve. Consumers can buy or rent properties, and these agents own characteristics such as income and may be employed or unemployed. Banks own balance sheets to monitor their assets and liabilities and participate in the interbank lending market with one another. This tool can model the complexities within the United States’ housing market, conduct stress tests as interest rates fluctuate, and explore characteristics from the landmark financial crisis and epidemic of foreclosures. The blend of available financial products to consumers (i.e., ARM versus Fixed-Rate) certainly influences demand to purchase properties given that ARM products are more affordable than fixed-rate products; however, these specific products may increase the risk of “underwater” mortgages. The market value of a property is heavily influenced by the value of a neighboring property; therefore, individuals are able to gauge the probable value of a property that has not been developed yet. The blend of available financial products to consumers (i.e., ARM versus Fixed-Rate) certainly influences demand within the housing market given that ARM products are more affordable than fixed-rate products. Overall, these concepts are important as the understanding of the impact from increases in foreclosed properties, changes in rates, available financial products, and more can help policymakers and financial institutions understand and model the non-linear complexities within the housing market.

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