IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v163y2018icp130-135.html
   My bibliography  Save this article

Space matters: Understanding the real effects of macroeconomic variations in cross-country housing price movements

Author

Listed:
  • Duan, Kun
  • Mishra, Tapas
  • Parhi, Mamata

Abstract

Changes in macroeconomic conditions can significantly determine directions and magnitudes of cross-country housing price movements. We demonstrate that such effects are consistently over-estimated when ‘spatial frictions’ are merely assumed, but are not explicitly modeled in the empirical framework. The extent of over-estimation bias has significant policy implications.

Suggested Citation

  • Duan, Kun & Mishra, Tapas & Parhi, Mamata, 2018. "Space matters: Understanding the real effects of macroeconomic variations in cross-country housing price movements," Economics Letters, Elsevier, vol. 163(C), pages 130-135.
    • Handle: RePEc:eee:ecolet:v:163:y:2018:i:c:p:130-135
    DOI: 10.1016/j.econlet.2017.11.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517304883
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2017.11.035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Cesa-Bianchi, Ambrogio, 2013. "Housing cycles and macroeconomic fluctuations: A global perspective," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 215-238.
    2. Tao, Ji & Yu, Jihai, 2012. "The spatial time lag in panel data models," Economics Letters, Elsevier, vol. 117(3), pages 544-547.
    3. Moro, Alessio & Nuño, Galo, 2012. "Does total-factor productivity drive housing prices? A growth-accounting exercise for four countries," Economics Letters, Elsevier, vol. 115(2), pages 221-224.
    4. Philip Arestis & Ana Rosa Gonzalez‐Martinez, 2016. "House Prices and Current Account Imbalances in OECD Countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 58-74, January.
    5. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    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. Klarl, Torben, 2018. "Housing is local: Applying a dynamic unobserved factor model for the Dutch housing market," Economics Letters, Elsevier, vol. 170(C), pages 79-84.
    2. Khamis Hamed Al-Yahyaee & Walid Mensi & Hee-Un Ko & Massimiliano Caporin & Sang Hoon Kang, 2021. "Is the Korean housing market following Gangnam style?," Empirical Economics, Springer, vol. 61(4), pages 2041-2072, October.

    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. Kun Duan & Tapas Mishra & Mamata Parhi & Simon Wolfe, 2019. "How Effective are Policy Interventions in a Spatially-Embedded International Real Estate Market?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 596-637, May.
    2. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    3. Carmelo Algeri & Antonio F. Forgione & Carlo Migliardo, 2022. "Do spatial dependence and market power matter in the diversification of cooperative banks?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    4. Han, Xiaoyi & Hsieh, Chih-Sheng & Lee, Lung-fei, 2017. "Estimation and model selection of higher-order spatial autoregressive model: An efficient Bayesian approach," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 97-120.
    5. Asgharian, Hossein & Hess, Wolfgang & Liu, Lu, 2013. "A spatial analysis of international stock market linkages," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4738-4754.
    6. Couaillier, Cyril & Scalone, Valerio, 2024. "Risk-to buffer: setting cyclical and structural banks capital requirements through stress test," Working Paper Series 2966, European Central Bank.
    7. Philip Arestis Author-Email: pa267@cam.ac.uk & Ana Rosa Gonzalez-Martinez, 2017. "Housing Market in Israel: Is there a Bubble?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 64(1), pages 1-16, December.
    8. Luping Shi & Zhongyao Cai & Xuhui Ding & Rong Di & Qianqian Xiao, 2020. "What Factors Affect the Level of Green Urbanization in the Yellow River Basin in the Context of New-Type Urbanization?," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    9. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    10. Francesc Amat & Pablo Beramendi & Miriam Hortas-Rico & Vicente Rios, 2020. "How inequality shapes political participation: The role of spatial patterns of political competition," Working Papers. Collection B: Regional and sectoral economics 2002, Universidade de Vigo, GEN - Governance and Economics research Network.
    11. Dees, Stéphane, 2016. "Credit, asset prices and business cycles at the global level," Economic Modelling, Elsevier, vol. 54(C), pages 139-152.
    12. Montmartin, Benjamin & Herrera, Marcos & Massard, Nadine, 2018. "The impact of the French policy mix on business R&D: How geography matters," Research Policy, Elsevier, vol. 47(10), pages 2010-2027.
    13. Atems, Bebonchu, 2015. "Another look at tax policy and state economic growth: The long-run and short-run of it," Economics Letters, Elsevier, vol. 127(C), pages 64-67.
    14. Cesa-Bianchi, Ambrogio & Eguren Martin, Fernando & Thwaites, Gregory, 2019. "Foreign booms, domestic busts: The global dimension of banking crises," Journal of Financial Intermediation, Elsevier, vol. 37(C), pages 58-74.
    15. Manea, Roxana Elena & Piraino, Patrizio & Viarengo, Martina, 2023. "Crime, inequality and subsidized housing: Evidence from South Africa," World Development, Elsevier, vol. 168(C).
    16. Shahnazi, Rouhollah & Dehghan Shabani, Zahra, 2020. "Do renewable energy production spillovers matter in the EU?," Renewable Energy, Elsevier, vol. 150(C), pages 786-796.
    17. Julián Ramajo & Alejandro Ricci-Risquete & Lourdes Jerez & Geoffrey J. D. Hewings, 2020. "Impacts of Neighbors on Local Tax Rates: A Space–Time Dynamic Panel Data Analysis," International Regional Science Review, , vol. 43(1-2), pages 105-127, January.
    18. Dreger, Christian & Zhang, Yanqun, 2014. "Does the economic integration of China affect growth and inflation in industrial countries?," Economic Modelling, Elsevier, vol. 38(C), pages 184-189.
    19. Hideaki Hirata & M. Ayhan Kose & Christopher Otrok & Marco E Terrones, 2013. "Global House Price Fluctuations: Synchronization and Determinants," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 9(1), pages 119-166.
    20. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).

    More about this item

    Keywords

    Macroeconomic adjustments; Spatial frictions; International housing market; Estimation bias; Spatial panel data;
    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
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    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:eee:ecolet:v:163:y:2018:i:c:p:130-135. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.