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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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    References listed on IDEAS

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    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Zhenguo Lin & Eric Rosenblatt & Vincent Yao, 2009. "Spillover Effects of Foreclosures on Neighborhood Property Values," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 387-407, May.
    3. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    4. Chomsisengphet, Souphala & Kiefer, Hua & Liu, Xiaodong, 2018. "Spillover effects in home mortgage defaults: Identifying the power neighbor," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 68-82.
    5. Jose M. Berrospide & Lamont K. Black & William R. Keeton, 2016. "The Cross‐Market Spillover of Economic Shocks through Multimarket Banks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 957-988, August.
    6. Sumit Agarwal & Brent W. Ambrose & Souphala Chomsisengphet & Anthony B. Sanders, 2012. "Thy Neighbor’s Mortgage: Does Living in a Subprime Neighborhood Affect One’s Probability of Default?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40(1), pages 1-22, March.
    7. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    8. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
    9. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    10. Charles W. Calomiris & Stanley D. Longhofer & William R. Miles, 2013. "The Foreclosure–House Price Nexus: A Panel VAR Model for U.S. States, 1981–2009," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 41(4), pages 709-746, December.
    11. Zihui Yang & Yinggang Zhou, 2017. "Quantitative Easing and Volatility Spillovers Across Countries and Asset Classes," Management Science, INFORMS, vol. 63(2), pages 333-354, February.
    12. Ambrose, Brent W. & Diop, Moussa, 2014. "Spillover effects of subprime mortgage originations: The effects of single-family mortgage credit expansion on the multifamily rental market," Journal of Urban Economics, Elsevier, vol. 81(C), pages 114-135.
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    More about this item

    Keywords

    Mortgage default risk; Connectedness network; Centrality; Metropolitan statistical area; States; United States;
    All these keywords.

    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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