IDEAS home Printed from https://ideas.repec.org/p/zbw/irtgdp/2019001.html
   My bibliography  Save this paper

Cooling Measures and Housing Wealth: Evidence from Singapore

Author

Listed:
  • Härdle, Wolfgang Karl
  • Schulz, Rainer
  • Xie, Taojun

Abstract

Excessive house price growth was at the heart of the financial crisis in 2007/08. Since then, many countries have added cooling measures to their regulatory frameworks. It has been found that these measures can indeed control price growth, but no one has examined whether this has adverse consequences for the housing wealth distribution. We examine this for Singapore, which started in 2009 to target price growth over ten rounds in total. We find that welfare from housing wealth in the last round might not be higher than before 2009. This depends on the deflator used to convert nominal into real prices. Irrespective of the deflator, we can reject that welfare increased monotonically over the different rounds.

Suggested Citation

  • Härdle, Wolfgang Karl & Schulz, Rainer & Xie, Taojun, 2019. "Cooling Measures and Housing Wealth: Evidence from Singapore," IRTG 1792 Discussion Papers 2019-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Handle: RePEc:zbw:irtgdp:2019001
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/230777/1/irtg1792dp2019-001.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 735-765.
    2. Kuttner, Kenneth N. & Shim, Ilhyock, 2016. "Can non-interest rate policies stabilize housing markets? Evidence from a panel of 57 economies," Journal of Financial Stability, Elsevier, vol. 26(C), pages 31-44.
    3. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    4. A. Atkinson, 2008. "More on the measurement of inequality," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(3), pages 277-283, September.
    5. Anthony F. Shorrocks & James E. Foster, 1987. "Transfer Sensitive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 54(3), pages 485-497.
    6. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    7. Markus K. Brunnermeier, 2009. "Deciphering the Liquidity and Credit Crunch 2007-2008," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 77-100, Winter.
    8. Cerutti, Eugenio & Claessens, Stijn & Laeven, Luc, 2017. "The use and effectiveness of macroprudential policies: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 203-224.
    9. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    10. Gabriele Galati & Richhild Moessner, 2013. "Macroprudential Policy – A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 27(5), pages 846-878, December.
    11. Samuel G. Hanson & Anil K. Kashyap & Jeremy C. Stein, 2011. "A Macroprudential Approach to Financial Regulation," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 3-28, Winter.
    12. Bawa, Vijay S., 1975. "Optimal rules for ordering uncertain prospects," Journal of Financial Economics, Elsevier, vol. 2(1), pages 95-121, March.
    13. Frank A. Cowell, 2008. "Income Distribution and Inequality," Chapters, in: John B. Davis & Wilfred Dolfsma (ed.), The Elgar Companion to Social Economics, chapter 13, Edward Elgar Publishing.
    14. Zhang, Longmei & Zoli, Edda, 2016. "Leaning against the wind: Macroprudential policy in Asia," Journal of Asian Economics, Elsevier, vol. 42(C), pages 33-52.
    15. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    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. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    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. Wolfgang Karl Hardle & Rainer Schulz & Taojun Sie, 2021. "Cooling Measures and Housing Wealth: Evidence from Singapore," Papers 2108.11915, arXiv.org.
    2. Aaberge, Rolf & Havnes, Tarjei & Mogstad, Magne, 2013. "A Theory for Ranking Distribution Functions," IZA Discussion Papers 7738, Institute of Labor Economics (IZA).
    3. Rolf Aaberge & Tarjei Havnes & Magne Mogstad, 2021. "Ranking intersecting distribution functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 639-662, September.
    4. Nitzan Tzur-Ilan, 2019. "Macroprudential Policy: Implementation, Effects, And Lessons," Israel Economic Review, Bank of Israel, vol. 17(1), pages 39-71.
    5. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    6. Charles Beach, 2023. "Quantile Tool Box Measures for Empirical Analysis and for Testing Distributional Comparisons in Direct Distribution-Free Fashion," Working Paper 1508, Economics Department, Queen's University.
    7. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Wang, 2002. "Consistent testing for stochastic dominance: a subsampling approach," CeMMAP working papers 03/02, Institute for Fiscal Studies.
    8. Maasoumi, Esfandiar & Almas Heshmati, 2003. "Evaluating Dominance Ranking of PSID Incomes by various Household Attributes," Departmental Working Papers 0509, Southern Methodist University, Department of Economics.
    9. Raymond H. Chan & Ephraim Clark & Xu Guo & Wing-Keung Wong, 2020. "New development on the third-order stochastic dominance for risk-averse and risk-seeking investors with application in risk management," Risk Management, Palgrave Macmillan, vol. 22(2), pages 108-132, June.
    10. Roxana Chiriac & Valeri Voev, 2011. "Modelling and forecasting multivariate realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 922-947, September.
    11. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2020. "Bayesian assessment of Lorenz and stochastic dominance," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 767-799, May.
    12. Christophe André, 2016. "Household debt in OECD countries: stylised facts and policy issues," Chapters from NBP Conference Publications, in: Hanna Augustyniak & Jacek Łaszek & Krzysztof Olszewski & Joanna Waszczuk (ed.), Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis - 2015 edition, chapter 2, pages v1, 33-85, Narodowy Bank Polski.
    13. David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.
    14. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    15. Duc Khuong Nguyen & Nikolas Topaloglou & Thomas Walther, 2020. "Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach," Working Papers 2020-009, Department of Research, Ipag Business School.
    16. Neanidis, Kyriakos C., 2019. "Volatile capital flows and economic growth: The role of banking supervision," Journal of Financial Stability, Elsevier, vol. 40(C), pages 77-93.
    17. Halbleib Roxana & Voev Valeri, 2011. "Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 134-152, February.
    18. Stanga, Irina & Vlahu, Razvan & de Haan, Jakob, 2020. "Mortgage arrears, regulation and institutions: Cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 118(C).
    19. Carpantier, Jean-Francois & Olivera, Javier & Van Kerm, Philippe, 2018. "Macroprudential policy and household wealth inequality," Journal of International Money and Finance, Elsevier, vol. 85(C), pages 262-277.
    20. Falter, Alexander, 2019. "Macro to the rescue? An analysis of macroprudential instruments to regulate housing credit," Discussion Papers 25/2019, Deutsche Bundesbank.

    More about this item

    Keywords

    house price distribution; stochastic dominance tests;

    JEL classification:

    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    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:zbw:irtgdp:2019001. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/wfhubde.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.