Predicting Housing Prices with Google Searches in Finland

Joona Widgrén

No 63, ETLA Reports from The Research Institute of the Finnish Economy

Abstract: Abstract This report examines whether Google search queries can be used to predict the present and the near future house prices in Finland. Compared to a simple benchmark model, Google searches improve the prediction of the present house price index by 7.5 % measured by mean absolute error. In addition, search queries improve the forecast of near future house prices. Predicting the present and near future house prices is relevant information to many agents, such as realtors and political decision makers.

Keywords: Google Trends; Internet; Nowcasting; Forecasting; Housing market; Time series (search for similar items in EconPapers)
JEL-codes: C1 C22 C43 C53 C82 E27 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2016-12-14
New Economics Papers: this item is included in nep-cmp, nep-mac and nep-ure
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