IDEAS home Printed from https://ideas.repec.org/p/arz/wpaper/eres2012_174.html
   My bibliography  Save this paper

Can housing liquidity help forecast subsequent house price appreciation: Evidence from the US and the Netherlands

Author

Listed:
  • Erik Robert de Carrillo
  • William Larson

Abstract

This paper studies whether liquidity information is helpful to forecast future prices in the housing market. First, we construct a panel of indicators that measure housing conditions in the Netherlands and in one large suburban area of the Washington DC area. Besides average home prices, the indicators include (quality adjusted) mean and median time on the market, mean difference between list prices and transaction prices, share of transactions below the transaction price, among others. These statistics will be used to construct an index that measures seller's bargaining power and several indicators about housing liquidity. To estimate indicators that measure housing liquidity and sellerís bargaining power we will follow the methods proposed by Carrillo and Pope (2012) and Carrillo (forthcoming). Second, we test if the bargaining power index and the other measures of housing market conditions have any predictive power to forecast home appreciation rates. Conventional time-series models are used to explore the link between housing liquidity, sellerís bargaining power and the rate of change in home prices. This research has important implications for both the real estate industry and policy makers. Given the importance of the housing market and the availability of MLS data, the construction of such indicators on regular basis for all areas in the US, the Netherlands and other developed countries should be a relative straightforward task that could inform economic agents about market conditions. Improved forecasts and understanding of current market conditions should be of interest to home buyers and sellers (and their agents) who generally like to be informed about market conditions when setting their optimal marketing strategies and, of course lenders, the PMI industry, and even participants in the derivatives market. Information about seller's bargaining power and housing liquidity could also be relevant to investors and regulators because, it provides information about market risk and, more importantly, it could be a valuable input to predict future home prices.

Suggested Citation

  • Erik Robert de Carrillo & William Larson, 2012. "Can housing liquidity help forecast subsequent house price appreciation: Evidence from the US and the Netherlands," ERES eres2012_174, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2012_174
    as

    Download full text from publisher

    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2012-174
    Download Restriction: no
    File URL: https://eres.architexturez.net/system/files/pdf/eres2012_174.content.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muellbauer, John & Murphy, Anthony, 1997. "Booms and Busts in the UK Housing Market," Economic Journal, Royal Economic Society, vol. 107(445), pages 1701-1727, November.
    2. Robert Novy‐Marx, 2009. "Hot and Cold Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(1), pages 1-22, March.
    3. David Genesove & Christopher Mayer, 2001. "Loss Aversion and Seller Behavior: Evidence from the Housing Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(4), pages 1233-1260.
    4. Carrillo, Paul E. & Pope, Jaren C., 2012. "Are homes hot or cold potatoes? The distribution of marketing time in the housing market," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 189-197.
    5. François Ortalo-Magné & Sven Rady, 2006. "Housing Market Dynamics: On the Contribution of Income Shocks and Credit Constraints ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(2), pages 459-485.
    6. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    7. Krainer, John, 2001. "A Theory of Liquidity in Residential Real Estate Markets," Journal of Urban Economics, Elsevier, vol. 49(1), pages 32-53, January.
    8. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    9. Case, Karl E & Shiller, Robert J, 1989. "The Efficiency of the Market for Single-Family Homes," American Economic Review, American Economic Association, vol. 79(1), pages 125-137, March.
    10. Ortalo-Magne, Francois & Rady, Sven, 1999. "Boom in, bust out: Young households and the housing price cycle," European Economic Review, Elsevier, vol. 43(4-6), pages 755-766, April.
    11. Paul E. Carrillo, 2013. "To Sell or Not to Sell: Measuring the Heat of the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 41(2), pages 310-346, June.
    12. Malpezzi, Stephen, 1999. "A Simple Error Correction Model of House Prices," Journal of Housing Economics, Elsevier, vol. 8(1), pages 27-62, March.
    13. Jeremy C. Stein, 1995. "Prices and Trading Volume in the Housing Market: A Model with Down-Payment Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 379-406.
    14. Karl E. Case & Robert J. Shiller, 1990. "Forecasting Prices and Excess Returns in the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 18(3), pages 253-273, September.
    15. Engelhardt, Gary V., 2003. "Nominal loss aversion, housing equity constraints, and household mobility: evidence from the United States," Journal of Urban Economics, Elsevier, vol. 53(1), pages 171-195, January.
    16. James A. Berkovec & John L. Goodman, 1996. "Turnover as a Measure of Demand for Existing Homes," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 24(4), pages 421-440, December.
    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. Paul E. Carrillo & Erik Robert De Wit & William D. Larson, 2012. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the U.S. and the Netherlands," Working Papers 2012-11, The George Washington University, Institute for International Economic Policy.
    2. Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
    3. François Ortalo-Magné & Sven Rady, 2006. "Housing Market Dynamics: On the Contribution of Income Shocks and Credit Constraints ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(2), pages 459-485.
    4. de Wit, Erik R. & Englund, Peter & Francke, Marc K., 2013. "Price and transaction volume in the Dutch housing market," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 220-241.
    5. Oikarinen, Elias, 2012. "Empirical evidence on the reaction speeds of housing prices and sales to demand shocks," Journal of Housing Economics, Elsevier, vol. 21(1), pages 41-54.
    6. Andrew Benito, 2006. "How does the down-payment constraint affect the UK housing market?," Bank of England working papers 294, Bank of England.
    7. Martijn I. Dröes & Marc K. Francke, 2018. "What Causes the Positive Price-Turnover Correlation in European Housing Markets?," The Journal of Real Estate Finance and Economics, Springer, vol. 57(4), pages 618-646, November.
    8. Damianov, Damian S & Escobari, Diego, 2015. "Long-Run Equilibrium Shift and Short-Run Dynamics of U.S. Home Price Tiers during the Housing Bubble," MPRA Paper 65765, University Library of Munich, Germany.
    9. L. Rachel Ngai & Silvana Tenreyro, 2014. "Hot and Cold Seasons in the Housing Market," American Economic Review, American Economic Association, vol. 104(12), pages 3991-4026, December.
    10. Suarez, Javier & Ceron, Jose A., 2006. "Hot and Cold Housing Markets: International Evidence," CEPR Discussion Papers 5411, C.E.P.R. Discussion Papers.
    11. Elliot Anenberg & Patrick Bayer, 2020. "Endogenous Sources Of Volatility In Housing Markets: The Joint Buyer–Seller Problem," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1195-1228, August.
    12. Gan, Li & Wang, Pengfei & Zhang, Qinghua, 2018. "Market thickness and the impact of unemployment on housing market outcomes," Journal of Monetary Economics, Elsevier, vol. 98(C), pages 27-49.
    13. Jim Clayton & Norman Miller & Liang Peng, 2010. "Price-volume Correlation in the Housing Market: Causality and Co-movements," The Journal of Real Estate Finance and Economics, Springer, vol. 40(1), pages 14-40, January.
    14. Carozzi, Felipe, 2015. "Credit constraints and the composition of housing sales. Farewell to first-time buyers?," LSE Research Online Documents on Economics 65016, London School of Economics and Political Science, LSE Library.
    15. Yong Tu & Seow Ong & Ying Han, 2009. "Turnovers and Housing Price Dynamics: Evidence from Singapore Condominium Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 254-274, April.
    16. Vílchez, Diego, 2015. "Evaluando las Dinámicas de Precios en el Sector Inmobiliario: Evidencia para Perú," Working Papers 2015-013, Banco Central de Reserva del Perú.
    17. Aaron Hedlund, 2014. "Illiquidity and its Discontents: Trading Delays and Foreclosures in the Housing Market," Working Papers 1417, Department of Economics, University of Missouri.
    18. Robert Edelstein & Wenlan Qian, 2014. "Short-Term Buyers and Housing Market Dynamics," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 654-689, November.
    19. Eric Smith, 2020. "High and Low Activity Spells in Housing Markets," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 36, pages 1-28, April.
    20. Elliot Anenberg, 2012. "Information frictions and housing market dynamics," Finance and Economics Discussion Series 2012-48, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

    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:arz:wpaper:eres2012_174. 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: Architexturez Imprints (email available below). General contact details of provider: https://edirc.repec.org/data/eressea.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.