• Medientyp: E-Book
  • Titel: Can Google Trends Actually Improve Housing Market Forecasts?
  • Beteiligte: Limnios, Christopher [VerfasserIn]; You, Hao [VerfasserIn]
  • Erschienen: [S.l.]: SSRN, 2018
  • Umfang: 1 Online-Ressource (29 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.2886705
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 11, 2018 erstellt
  • Beschreibung: We augment linear pricing models for the housing market commonly used in the literature with google trends data in order to assess whether or not crowd-sourced search query data can improve the forecasting ability of the models. We compare various performance measures of the augmented linear model's out-of-sample, one-step ahead, dynamic forecasts against a baseline version. We find that augmenting the models to take advantage of the availability of Google trend data does not improve the forecasting performance of the models
  • Zugangsstatus: Freier Zugang