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Economic Analysis of the Digital Economy$
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Avi Goldfarb, Shane M. Greenstein, and Catherine E. Tucker

Print publication date: 2015

Print ISBN-13: 9780226206844

Published to Chicago Scholarship Online: September 2015

DOI: 10.7208/chicago/9780226206981.001.0001

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The Future of Prediction

The Future of Prediction

How Google Searches Foreshadow Housing Prices and Sales

Chapter:
(p.89) 3 The Future of Prediction
Source:
Economic Analysis of the Digital Economy
Author(s):

Lynn Wu

Erik Brynjolfsson

Publisher:
University of Chicago Press
DOI:10.7208/chicago/9780226206981.003.0003

We demonstrate how data from search engines such as Google provide an accurate but simple way to predict future business activities. Applying our methodology to predict housing market trends, we find that a housing search index is strongly predictive of future housing market sales and prices. For state-level predictions in the United States, the use of search data produces out-of-sample predictions with a smaller mean absolute error than the baseline model that uses conventional data but lacks search data. Furthermore, we find that our simple model of using search frequencies beat the predictions published by experts from the National Association of Realtors by 23.6% for future US home sales. We also demonstrate how these data can be used in other markets, such as home appliance sales. This type of “nanoeconomic” data can transform prediction in numerous markets, thereby improving business and consumer decision-making.

Keywords:   online search, prediction, housing prices, real estate, Google trends

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