6533b831fe1ef96bd1299002

RESEARCH PRODUCT

Qualitative analysis of housing demand using Google trends data

Tiffany Hui-kuang YuMaría Rodríguez-garcíaKun-huang Huarng

subject

time series modelshousing demandEconomics and Econometricsbusiness.industryComputer scienceSèries temporals AnàlisiBig datalcsh:Regional economics. Space in economicsData sciencelcsh:HD72-88lcsh:HT388Proxy (climate)lcsh:Economic growth development planningQualitative analysisTime series models; qualitative forecasting; housing demandbusinessqualitative forecasting

description

Big data analytics often refer to the breakdown of huge amounts of data into a more readable and useful format. This study utilises Google Trends big data as a proxy for an analysis of housing demand. We employ a qualitative method (fuzzy set/Qualitative Comparative Analysis, fsQCA), instead of a quantitative method, for our estimate and forecast. The empirical results show that fsQCA successfully forecasts seasonal time series, even though the dataset is small in size. Our findings fill the gap in the qualitative and time series forecasting literature, and the forecasting procedure herein also offers a good standard for industry.

yearjournalcountryeditionlanguage
2019-06-13Economic Research-Ekonomska Istraživanja
https://doi.org/10.1080/1331677x.2018.1547205