Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand

Branislav Saxa

Working Papers from Czech National Bank, Research and Statistics Department

Abstract: This paper examines the usefulness of Google Trends data for forecasting mortgage lending in the Czech Republic. While the official monthly statistics on mortgage lending come with a publication lag of one month, the data on how often people search for mortgage-related terms on the internet are available without any lag on a weekly basis. Growth in searches for mortgages and growth in mortgages actually provided are strongly correlated. The lag between these two growth rates is two months. Evaluation of out-of-sample forecasts shows that internet search data improve mortgage lending predictions significantly. In addition to forecasting performance evaluation, an experimental indicator of restrictively tight mortgage credit standards and conditions is proposed. Nowadays many countries run bank lending surveys to monitor the tightness of bank lending standards and conditions. The proposed indicator represents a complementary tool to such a survey.

Keywords: Credit demand; credit standards and conditions; credit supply; forecast evaluation; forecasting; Google econometrics; Internet search data; mortgage; smoothing (search for similar items in EconPapers)
JEL-codes: C22 C82 E27 E51 (search for similar items in EconPapers)
Date: 2014-12
New Economics Papers: this item is included in nep-ban, nep-for, nep-ict, nep-mac, nep-tra and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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