IDEAS home Printed from https://ideas.repec.org/a/aen/journl/ej40-si2-martinez-garcia.html
   My bibliography  Save this article

Drilling Down: The Impact of Oil Price Shocks on Housing Prices

Author

Listed:
  • Valerie Grossman, Enrique Martínez-García, Luis Bernardo Torres, and Yongzhi Sun

Abstract

This paper investigates the impact of oil price shocks on house prices in the largest urban centers in Texas. We model their dynamic relationship taking into account demand- and supply-side housing fundamentals (personal disposable income per capita, long-term interest rates and rural land prices) as well as their varying dependence on oil activity. We show the following: 1) Oil price shocks have limited pass-through to house prices?the highest pass-through is found among the most oil-dependent cities where, after 20 quarters, the cumulative response of house prices is 21 percent of the cumulative effect on oil prices. Still, among less oil-dependent urban areas, the house price response to a one standard deviation oil price shock is economically significant and comparable in magnitude to the response to a one standard deviation income shock. 2) Omitting oil prices when looking at housing markets in oil-producing areas biases empirical inferences by substantially overestimating the effect of income shocks on house prices. 3) The empirical relationship linking oil price fluctuations to house prices has remained largely stable over time, in spite of the significant changes in Texas? oil sector with the onset of the shale revolution in the 2000s.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Valerie Grossman, Enrique Martínez-García, Luis Bernardo Torres, and Yongzhi Sun, 2019. "Drilling Down: The Impact of Oil Price Shocks on Housing Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    • Handle: RePEc:aen:journl:ej40-si2-martinez-garcia
    as

    Download full text from publisher

    File URL: http://www.iaee.org/en/publications/ejarticle.aspx?id=3229
    Download Restriction: Access to full text is restricted to IAEE members and subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Clapp, John M & Rodriguez, Mauricio & Pace, R Kelley, 2001. "Residential Land Values and the Decentralization of Jobs," The Journal of Real Estate Finance and Economics, Springer, vol. 22(1), pages 43-61, January.
    3. Brantley Liddle, 2013. "The Energy, Economic Growth, Urbanization Nexus Across Development: Evidence from Heterogeneous Panel Estimates Robust to Cross-Sectional Dependence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Marius Claudy and Claus Michelsen, 2016. "Housing Market Fundamentals, Housing Quality and Energy Consumption: Evidence from Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    5. repec:aen:journl:eeep4_1_krupnick is not listed on IDEAS
    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. Ting Zhang & Dan Gerlowski & Deborah Ford, 2014. "Housing price variability: national and local impacts," Applied Economics, Taylor & Francis Journals, vol. 46(28), pages 3494-3502, October.
    8. Andrews, Donald W. K. & Lu, Biao, 2001. "Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models," Journal of Econometrics, Elsevier, vol. 101(1), pages 123-164, March.
    9. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    10. Zhongmin Wang and Alan Krupnick, 2015. "A Retrospective Review of Shale Gas Development in the United States: What Led to the Boom?," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    11. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gupta, Rangan & Sheng, Xin & van Eyden, Reneé & Wohar, Mark E., 2021. "The impact of disaggregated oil shocks on state-level real housing returns of the United States: The role of oil dependence," Finance Research Letters, Elsevier, vol. 43(C).
    2. Jin, Yi & Liu, Sinuo & Sun, Yongping & Fang, Jie, 2024. "Energy transition and housing market bubbles: Evidence from prefecture cities in China," Energy Economics, Elsevier, vol. 133(C).
    3. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2021. "House price synchronization across the US states: The role of structural oil shocks," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    4. Ekinci, Mehmet Fatih & Omay, Tolga, 2020. "Current account and credit growth: The role of household credit and financial depth," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Nguyen, Thi Thu Ha & Naeem, Muhammad Abubakr & Balli, Faruk & Balli, Hatice Ozer & Syed, Iqbal, 2021. "Information transmission between oil and housing markets," Energy Economics, Elsevier, vol. 95(C).
    6. Fennee Chong, 2023. "Housing Price and Interest Rate Hike: A Tale of Five Cities in Australia," JRFM, MDPI, vol. 16(2), pages 1-13, January.
    7. Nyakundi M. Michieka & Richard S. Gearhart & Noha A. Razek, 2024. "Oil Price Dynamics and Housing Demand in Oil Producing Counties in the U.S," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(2), pages 483-512, June.

    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. Sigmund, Michael & Ferstl, Robert, 2021. "Panel vector autoregression in R with the package panelvar," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 693-720.
    2. Alfonso Mendoza-Velázquez & Luis Carlos Ortuño-Barba & Luis David Conde-Cortés, 2022. "Corporate governance and firm performance in hybrid model countries," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 21(1), pages 32-58, February.
    3. Kate Hynes & Yum K. Kwan & Anthony Foley, 2017. "Local linkages: The interdependence of foreign and domestic firms," GRU Working Paper Series GRU_2017_006, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    4. Hynes, Kate & Kwan, Yum K. & Foley, Anthony, 2020. "Local linkages: The interdependence of foreign and domestic firms in Ireland," Economic Modelling, Elsevier, vol. 85(C), pages 139-153.
    5. Al-Jahwari, Salim Ahmed Said, 2021. "Does the Twin-Deficits doctrine apply to the Gulf Cooperation Council? A dynamic panel VAR-X model approach," MPRA Paper 111232, University Library of Munich, Germany.
    6. Hertweck, Matthias & Brey, Bjoern, 2017. "The Persistent Effects of Monsoon Rainfall Shocks in India: A Nonlinear VAR Approach," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168256, Verein für Socialpolitik / German Economic Association.
    7. Odolinski, Kristofer & Wheat, Phill, 2018. "Dynamics in rail infrastructure provision: Maintenance and renewal costs in Sweden," Economics of Transportation, Elsevier, vol. 14(C), pages 21-30.
    8. Ulaşan, Bülent, 2012. "Cross-country growth empirics and model uncertainty: An overview," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-69.
    9. Raffaella Santolini, 2017. "Electoral Rules And Public Spending Composition: The Case Of Italian Regions," Contemporary Economic Policy, Western Economic Association International, vol. 35(3), pages 551-577, July.
    10. Lips, Johannes, 2018. "Debt and the Oil Industry - Analysis on the Firm and Production Level," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181504, Verein für Socialpolitik / German Economic Association.
    11. Bennett, Daniel L., 2019. "Infrastructure investments and entrepreneurial dynamism in the U.S," Journal of Business Venturing, Elsevier, vol. 34(5), pages 1-1.
    12. Ejike Udeogu & Shampa Roy-Mukherjee & Uzochukwu Amakom, 2021. "Does Increasing Product Complexity and Diversity Cause Economic Growth in the Long-Run? A GMM Panel VAR Evidence," SAGE Open, , vol. 11(3), pages 21582440211, August.
    13. repec:zbw:rwirep:0123 is not listed on IDEAS
    14. DELL'ANNO, Roberto & VILLA, Stefania, 2012. "Growth in Transition Countries: Big Bang versus Gradualism," CELPE Discussion Papers 122, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    15. Giorgio Calzolari & Laura Magazzini, 2014. "Improving GMM efficiency in dynamic models for panel data with mean stationarity," Working Papers 12/2014, University of Verona, Department of Economics.
    16. Ding, Guangyuan & Xiong, Yunbiao & Wang, Yashu, 2024. "Moderating effect of digital governance and eco-policy stringency in realizing natural resources-growth nexus: Role of financial development and FDI in G20 countries," Resources Policy, Elsevier, vol. 92(C).
    17. Shackleton, Mark & Yan, Jiali & Yao, Yaqiong, 2022. "What drives a firm's ES performance? Evidence from stock returns," Journal of Banking & Finance, Elsevier, vol. 136(C).
    18. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    19. Michael R.M. Abrigo & Inessa Love, 2016. "Estimation of Panel Vector Autoregression in Stata: a Package of Programs," Working Papers 201602, University of Hawaii at Manoa, Department of Economics.
    20. Christos Kollias & Suzanna-Maria Paleologou, 2016. "Investment, growth, and defense expenditure in the EU15: Revisiting the nexus using SIPRI’s new consistent dataset," Economics of Peace and Security Journal, EPS Publishing, vol. 11(2), pages 28-37, October.
    21. Odolinski, Kristofer & Wheat, Phillip, 2016. "Dynamics in rail infrastructure provision: maintenance and renewal costs in Sweden," Working papers in Transport Economics 2016:23, CTS - Centre for Transport Studies Stockholm (KTH and VTI), revised 11 Dec 2017.

    More about this item

    JEL classification:

    • F0 - International Economics - - General

    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:aen:journl:ej40-si2-martinez-garcia. 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: David Williams (email available below). General contact details of provider: https://edirc.repec.org/data/iaeeeea.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.