IDEAS home Printed from https://ideas.repec.org/p/mib/wpaper/513.html
   My bibliography  Save this paper

Leaning against housing booms fueled by credit

Author

Listed:
  • Carlos Canizares Martinez

Abstract

The aim of this paper is to empirically identify the state of the US housing market and to set state-dependent policy rules to smooth the housing cycle. I do so by estimating a three states Markov-switching model of housing prices in which mortgage debt is the state-dependent variable. As a result, the housing market state might be classified as being in housing booms fueled by credit, normal or implosion times. Second, I propose a state-contingent policy rule fed with the probabilities of being in each state. I apply such rule to set a housing countercyclical capital buffer (SCCyB) and a time-varying home mortgage interest deduction rule. Finally, I show that such rules have forecasting ability to predict the charge-off rates on real estate residential loans. The significance of this study is that it informs policymakers about the state of the housing market mechanically while it also provides a simple rule that allows the implementation of state-contingent macroprudential policy. Further, the structure of such rule is general enough to be applied to other policy tools.

Suggested Citation

  • Carlos Canizares Martinez, 2023. "Leaning against housing booms fueled by credit," Working Papers 513, University of Milano-Bicocca, Department of Economics.
  • Handle: RePEc:mib:wpaper:513
    as

    Download full text from publisher

    File URL: http://repec.dems.unimib.it/repec/pdf/mibwpaper513.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Angela Maddaloni & Jose-Luis Peydro, 2011. "Bank Risk-taking, Securitization, Supervision, and Low Interest Rates: Evidence from the Euro-area and the U.S. Lending Standards," Review of Financial Studies, Society for Financial Studies, vol. 24(6), pages 2121-2165.
    2. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2011. "When credit bites back: leverage, business cycles, and crises," Working Paper Series 2011-27, Federal Reserve Bank of San Francisco.
    3. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    4. James M. Poterba, 1991. "House Price Dynamics: The Role of Tax Policy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(2), pages 143-204.
    5. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    6. repec:ucp:bkecon:9780226081946 is not listed on IDEAS
    7. Crowe, Christopher & Dell’Ariccia, Giovanni & Igan, Deniz & Rabanal, Pau, 2013. "How to deal with real estate booms: Lessons from country experiences," Journal of Financial Stability, Elsevier, vol. 9(3), pages 300-319.
    8. van Norden, Simon & Schaller, Huntley, 1993. "The Predictability of Stock Market Regime: Evidence from the Toronto Stock Exchange," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 505-510, August.
    9. Atif Mian & Amir Sufi, 2011. "House Prices, Home Equity-Based Borrowing, and the US Household Leverage Crisis," American Economic Review, American Economic Association, vol. 101(5), pages 2132-2156, August.
    10. Tirole, Jean, 1985. "Asset Bubbles and Overlapping Generations," Econometrica, Econometric Society, vol. 53(6), pages 1499-1528, November.
    11. Atif Mian & Amir Sufi, 2009. "The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1449-1496.
    12. Babić, Domagoj & Fahr, Stephan, 2019. "Shelter from the storm: recent countercyclical capital buffer (CCyB) decisions," Macroprudential Bulletin, European Central Bank, vol. 7.
    13. Bernanke, Ben & Gertler, Mark, 1989. "Agency Costs, Net Worth, and Business Fluctuations," American Economic Review, American Economic Association, vol. 79(1), pages 14-31, March.
    14. Simon van Norden & Huntley Schaller & ), 1995. "Speculative Behaviour, Regime-Switching, and Stock Market Crashes," Econometrics 9502003, University Library of Munich, Germany.
    15. John Muellbauer, 2012. "When is a Housing Market Overheated Enough to Threaten Stability?," RBA Annual Conference Volume (Discontinued), in: Alexandra Heath & Frank Packer & Callan Windsor (ed.),Property Markets and Financial Stability, Reserve Bank of Australia.
    16. Jeremy C. Stein, 2021. "Can Policy Tame the Credit Cycle?," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(1), pages 5-22, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlos Canizares Martinez, 2023. "Leaning against housing booms fueled by credit," Working and Discussion Papers WP 9/2023, Research Department, National Bank of Slovakia.
    2. John V. Duca & Lilit Popoyan & Susan M. Wachter, 2019. "Real Estate And The Great Crisis: Lessons For Macroprudential Policy," Contemporary Economic Policy, Western Economic Association International, vol. 37(1), pages 121-137, January.
    3. Ferrero, Andrea & Harrison, Richard & Nelson, Benjamin, 2018. "House Price Dynamics, Optimal LTV Limits and the Liquidity Trap," CEPR Discussion Papers 13400, C.E.P.R. Discussion Papers.
    4. Guerrieri, V. & Uhlig, H., 2016. "Housing and Credit Markets," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1427-1496, Elsevier.
    5. Bengui, Julien & Phan, Toan, 2018. "Asset pledgeability and endogenously leveraged bubbles," Journal of Economic Theory, Elsevier, vol. 177(C), pages 280-314.
    6. Xavier Freixas, 2018. "Credit Growth, Rational Bubbles and Economic Efficiency," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(1), pages 87-104, March.
    7. D'Orazio, Paola, 2019. "Income inequality, consumer debt, and prudential regulation: An agent-based approach to study the emergence of crises and financial instability," Economic Modelling, Elsevier, vol. 82(C), pages 308-331.
    8. Paulo M.M. Rodrigues & Rita Fradique Lourenço, 2015. "House prices: bubbles, exuberance or something else? Evidence from euro area countries," Working Papers w201517, Banco de Portugal, Economics and Research Department.
    9. R. Barrell & D. Karim & C. Macchiarelli, 2020. "Towards an understanding of credit cycles: do all credit booms cause crises?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(10), pages 978-993, July.
    10. Manconi, Alberto & Braggion, Fabio & Zhu, Haikun, 2018. "Can Technology Undermine Macroprudential Regulation? Evidence from Peer-to-Peer Credit in China," CEPR Discussion Papers 12668, C.E.P.R. Discussion Papers.
    11. Tobias Adrian & Nellie Liang, 2018. "Monetary Policy, Financial Conditions, and Financial Stability," International Journal of Central Banking, International Journal of Central Banking, vol. 14(1), pages 73-131, January.
    12. Guerini, Mattia & Moneta, Alessio & Napoletano, Mauro & Roventini, Andrea, 2020. "The Janus-Faced Nature Of Debt: Results From A Data-Driven Cointegrated Svar Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 24(1), pages 24-54, January.
    13. Ozlem Akin & José Montalvo & Jaume García Villar & José-Luis Peydró & Josep Raya, 2014. "The real estate and credit bubble: evidence from Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 5(2), pages 223-243, August.
    14. Mikkel Hermansen & Oliver Röhn, 2017. "Economic resilience: The usefulness of early warning indicators in OECD countries," OECD Journal: Economic Studies, OECD Publishing, vol. 2016(1), pages 9-35.
    15. Douglas Sutherland & Peter Hoeller, 2012. "Debt and Macroeconomic Stability: An Overview of the Literature and Some Empirics," OECD Economics Department Working Papers 1006, OECD Publishing.
    16. Valentina Michelangeli & José-Luis Peydró & Enrico Sette, 2021. "Borrower versus Ban Channels in Lending: Experimental- and Administrative-Based Evidence," Working Papers 1307, Barcelona School of Economics.
    17. Simon van Norden & Huntley Schaller, 2002. "Fads or bubbles?," Empirical Economics, Springer, vol. 27(2), pages 335-362.
    18. Gabriel Jiménez & Steven Ongena & José‐Luis Peydró & Jesús Saurina, 2014. "Hazardous Times for Monetary Policy: What Do Twenty‐Three Million Bank Loans Say About the Effects of Monetary Policy on Credit Risk‐Taking?," Econometrica, Econometric Society, vol. 82(2), pages 463-505, March.
    19. Jacopo Bonchi & Francesco Simone Lucidi, 2020. "How Low Interest Rates Discern the Bubbles Nature: Leveraged vs Unleveraged Bubble," Working Papers 12/20, Sapienza University of Rome, DISS.
    20. Stockhammer, Engelbert & Wildauer, Rafael, 2018. "Expenditure Cascades, Low Interest Rates or Property Booms? Determinants of Household Debt in OECD Countries," Review of Behavioral Economics, now publishers, vol. 5(2), pages 85-121, September.

    More about this item

    Keywords

    Housing prices; non-linear modeling; Markov switching model; housing demand; household debt; macroprudential policy.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mib:wpaper:513. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Matteo Pelagatti (email available below). General contact details of provider: https://edirc.repec.org/data/dpmibit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.