Forecasting Housing Prices with Google Econometrics

38 Pages Posted: 25 Jul 2009 Last revised: 25 May 2015

See all articles by Rajendra Kulkarni

Rajendra Kulkarni

Schar School of Policy & Government

Kingsley E. Haynes

Schar School of Policy and Government, George Mason University

Roger R. Stough

George Mason University - School of Policy, Government, and International Affairs

Jean H. P. Paelinck

Erasmus University Rotterdam (EUR) - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Abstract

In this research note we report on our current efforts on developing a leading indicator of housing prices that could be used to forecast housing prices. Specifically we use Google search index at city level to predict Case-Shiller index. The methodology is based on Granger causality where we carry out two way regressions with lagged variables and joint F-tests to determine the direction of causality.

Keywords: Case-Shiller Index, Granger Causality, Google econometrics, HPI, Search engine

JEL Classification: C10, C20, C30, C40, C50

Suggested Citation

Kulkarni, Rajendra and Haynes, Kingsley E. and Stough, Roger R. and Paelinck, Jean H. P., Forecasting Housing Prices with Google Econometrics. GMU School of Public Policy Research Paper No. 2009-10. Available at SSRN: https://ssrn.com/abstract=1438286 or http://dx.doi.org/10.2139/ssrn.1438286

Rajendra Kulkarni (Contact Author)

Schar School of Policy & Government ( email )

Founders Hall
3351 Fairfax Dr.
Arlington, VA 22201
United States

Kingsley E. Haynes

Schar School of Policy and Government, George Mason University ( email )

Founders Hall
3351 Fairfax Dr.
Arlington, VA 22201
United States

Roger R. Stough

George Mason University - School of Policy, Government, and International Affairs ( email )

Founders Hall
3351 Fairfax Dr.
Arlington, VA 22201
United States
703-993-2268 (Phone)
703-993-5027 (Fax)

Jean H. P. Paelinck

Erasmus University Rotterdam (EUR) - Department of Economics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
0031-10-4081490 (Phone)
0031-10-4528341 (Fax)

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

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