Forecasting Housing Prices with Google Econometrics

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

MoreLess

Year of publication:	2015
Authors:	Kulkarni, Rajendra
Other Persons:	Haynes, Kingsley E. (contributor) ; Stough, Roger R. (contributor) ; Paelinck, Jean H. P. (contributor)
Publisher:	[2015]: [S.l.] : SSRN
Subject:	Prognoseverfahren \| Forecasting model \| Immobilienpreis \| Real estate price \| Suchmaschine \| Search engine \| Ökonometrie \| Econometrics \| Prognose \| Forecast \| Hedonischer Preisindex \| Hedonic price index \| Schätzung \| Estimation

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Extent:	1 Online-Ressource (38 p)
Series:	GMU School of Public Policy Research Paper ; No. 2009-10
Type of publication:	Book / Working Paper
Language:	English
Other identifiers:	10.2139/ssrn.1438286 [DOI]
Classification:	C10 - Econometric and Statistical Methods: General. General ; C20 - Econometric Methods: Single Equation Models. General ; C30 - Econometric Methods: Multiple/Simultaneous Equation Models. General ; C40 - Econometric and Statistical Methods: Special Topics. General ; C50 - Econometric Modeling. General
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013039407