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Forecasting Existing Home Sales using Google Search Engine Queries

By Brian Humphrey

This paper employs OLS regressions to determine whether Google search query data improves national and local existing home sales forecasts. The local dataset features metropolitan statistical area data from Texas. Initially, the national and local regressions are estimated without macroeconomic variables. Macroeconomic variables are subsequently included in order to determine if Google search queries provide information not already present in the macroeconomic variables. The impact of the Google variables is assessed using root mean squared error, p-values, and adjusted r-squared values. Finally, the top models are compared using out-of-sample testing. Both the in-sample and out-of-sample test results suggest that Google search query data improves national and local existing home sales forecasts.

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Advisor: James Roberts

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