IDEAS home Printed from https://ideas.repec.org/p/een/camaaa/2025-45.html
   My bibliography  Save this paper

Nowcasting Transaction-Based House Price Indices Using Web-Scraped Listings and MIDAS Regression

Author

Listed:
  • Radoslaw Trojanek
  • Luke Hartigan
  • Norbert Pfeifer
  • Miriam Steurer

Abstract

Timely transaction-based residential property price indices are crucial for effective monetary and macroprudential policy, yet transaction-based data often suffer from significant reporting delays. Online property platforms, by contrast, provide list prices of properties in real-time. This paper examines whether immediately available online list prices can improve timely nowcasts of transaction price movements. Using 16 years of micro-level data from Warsaw and Poznan, we construct quality-adjusted monthly list-price and quarterly transaction-price indices using the hedonic rolling-time-dummy method. We find that list-price indices consistently lead transaction-price indices by one to two months, with the strongest relationship in Warsaw's larger, more liquid market. Building on this lead-lag relationship, we develop a Mixed Data Sampling (MIDAS) regression framework to nowcast quarterly transaction-price growth using monthly list-price data. Our preferred MIDAS specifications reduce one-quarter-ahead root mean square error by approximately 16-23 percent for Warsaw and 5-15 percent for Poznan relative to standard autoregressive benchmarks. The predictive advantage is greatest when incorporating list-price data from the first or second month of the quarter, as third-month data introduce forward-looking noise. Our results show that properly constructed list-price indices can play an important role to provide early housing market signals, potentially enhancing the timeliness of policy responses.

Suggested Citation

  • Radoslaw Trojanek & Luke Hartigan & Norbert Pfeifer & Miriam Steurer, 2025. "Nowcasting Transaction-Based House Price Indices Using Web-Scraped Listings and MIDAS Regression," CAMA Working Papers 2025-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2025-45
    as

    Download full text from publisher

    File URL: https://crawford.anu.edu.au/sites/default/files/2025-08/45_2025_Trojanek_Hartigan_Pfeifer_Steurer_1.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bajari, P. & Cen, Z. & Chernozhukov, V. & Manukonda, M. & Vijaykumar, S. & Wang, J. & Huerta, R. & Li, J. & Leng, L. & Monokroussos, G. & Wang, S., 2025. "Hedonic prices and quality adjusted price indices powered by AI," Journal of Econometrics, Elsevier, vol. 251(C).
    2. Alberto Cavallo & W. Erwin Diewert & Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2018. "Using Online Prices for Measuring Real Consumption across Countries," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 483-487, May.
    3. Elliot Anenberg & Steven Laufer, 2017. "A More Timely House Price Index," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 722-734, July.
    4. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    5. Choi, Chi-Young & Hansz, J. Andrew, 2021. "From banking integration to housing market integration - Evidence from the comovement of U.S. Metropolitan House Prices," Journal of Financial Stability, Elsevier, vol. 54(C).
    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. Hai Long Vo & Duc Hong Vo, 2023. "The purchasing power parity and exchange‐rate economics half a century on," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 446-479, April.
    2. Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
    3. Santiago E. Alvarez & Sarah M. Lein, 2020. "Tracking inflation on a daily basis," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-13, December.
    4. Apostolos Filippas & John J. Horton & Joseph M. Golden, 2019. "Reputation Inflation," NBER Working Papers 25857, National Bureau of Economic Research, Inc.
    5. Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019. "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 373-402, National Bureau of Economic Research, Inc.
    6. Ilaria Benedetti & Tiziana Laureti & Luigi Palumbo & Brandon M. Rose, 2022. "Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques," Economies, MDPI, vol. 10(4), pages 1-20, April.
    7. Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
    8. Fernando Alvarez & Francesco Lippi & Juan Passadore, 2017. "Are State- and Time-Dependent Models Really Different?," NBER Macroeconomics Annual, University of Chicago Press, vol. 31(1), pages 379-457.
    9. David O. Argente & Chang-Tai Hsieh & Munseob Lee, 2020. "Measuring the Cost of Living in Mexico and the US," NBER Working Papers 27806, National Bureau of Economic Research, Inc.
    10. Trojanek, Radoslaw & Gluszak, Michal, 2022. "Short-run impact of the Ukrainian refugee crisis on the housing market in Poland," Finance Research Letters, Elsevier, vol. 50(C).
    11. Fernando Alvarez & Francesco Lippi, 2020. "Temporary Price Changes, Inflation Regimes, and the Propagation of Monetary Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 104-152, January.
    12. Fernando Alvarez & Andrea Ferrara & Erwan Gautier & Hervé Le Bihan & Francesco Lippi, 2025. "Empirical Investigation of a Sufficient Statistic for Monetary Shocks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 92(4), pages 2165-2196.
    13. John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353, arXiv.org.
    14. Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
    15. Bajari, P. & Cen, Z. & Chernozhukov, V. & Manukonda, M. & Vijaykumar, S. & Wang, J. & Huerta, R. & Li, J. & Leng, L. & Monokroussos, G. & Wang, S., 2025. "Hedonic prices and quality adjusted price indices powered by AI," Journal of Econometrics, Elsevier, vol. 251(C).
    16. Erwan Gautier & Elvira Prades, 2025. "Monitoring food price changes in the euro area in real time - Lessons from the 2022 24 period [Suivre l’évolution des prix alimentaires dans la zone euro en temps réel – Les leçons de la période 20," Bulletin de la Banque de France, Banque de France, issue 259.
    17. Jennifer Peña & Elvira Prades, 2021. "Price setting in Chile: Micro evidence from consumer on-line prices during the social outbreak and Covid-19," Working Papers 2112, Banco de España.
    18. Giuseppe Arbia & Vincenzo Nardelli, 2024. "Using Web-Data to Estimate Spatial Regression Models," International Regional Science Review, , vol. 47(2), pages 204-226, March.
    19. Levy, Daniel & Chen, Haipeng (Allan) & Ray, Sourav & Charette, Elliot & Ling, Xiao & Zhao, Weihong & Bergen, Mark & Snir, Avichai, 2025. "Asymmetric price adjustment over the business cycle," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 0, pages 112450-1124.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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:een:camaaa:2025-45. 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: Cama Admin (email available below). General contact details of provider: https://edirc.repec.org/data/asanuau.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.