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Spillover of mortgage default risks in the United States: Evidence from metropolitan statistical areas and states

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  • Ji, Qiang
  • Gupta, Rangan
  • Bekun, Festus Victor
  • Balcilar, Mehmet

Abstract

This paper offers a new perspective to the analysis of spillover transmission in the housing market, specifically dealing with mortgage default risks. To do this, the recently developed generalized forecast error variance decomposition (FEVD) methodology proposed by Diebold and Yilmaz (2014) is utilized to investigate the degree of interconnectedness of mortgage default risks in metropolitan statistical areas (MSAs) and states of the U.S. The empirical findings, based on a real-time mortgage default risks index, reveal complex interconnectedness across twenty MSAs and forty-three states. Our study finds that Chicago, New York, and Los Angeles are net transmitters of spillover effects to other regions in the housing market investigated. This study also corroborates with the central place theory (CPT), as Washington DC serves as a key player in the housing market among the MSA's. Amongst the states, Minnesota, followed by Arizona, Pennsylvania, New York and New Hampshire, are found to be the main source of mortgage default risks spillovers. Implications of our results are discussed.

Suggested Citation

  • Ji, Qiang & Gupta, Rangan & Bekun, Festus Victor & Balcilar, Mehmet, 2019. "Spillover of mortgage default risks in the United States: Evidence from metropolitan statistical areas and states," The Journal of Economic Asymmetries, Elsevier, vol. 19(C), pages 1-1.
    • Handle: RePEc:eee:joecas:v:19:y:2019:i:c:8
    DOI: 10.1016/j.jeca.2019.e00114
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    Cited by:

    1. Duc Hong Vo, 2025. "Long-term effects of institutional quality on financial inclusion in Asia–Pacific countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-26, December.
    2. Chenjun Zhang & Hailiang Huang & Changfeng Shi & Jingru Xu & Yung-ho Chiu, 2024. "Spatial pattern and driving factors for interprovincial water use in China: Based on SNA and LMDI," Energy & Environment, , vol. 35(4), pages 2198-2227, June.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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