Obtaining consistent time series from Google Trends.
Google Trends data are a popular data source for research, but raw data are frequency‐inconsistent: daily data fail to capture long‐run trends. This issue has gone unnoticed in the literature. In addition, sampling noise can be substantial. We develop a procedure (available in an R‐package), which s...
| Publicado en: | Economic Inquiry Vol. 60; no. 2; pp. 694 - 706 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Wiley-Blackwell
Apr2022
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=155474556&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 155474556 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00952583 EIQ jtl: Economic Inquiry issn: 00952583 maglogo: Y pubinfo: dt: Apr2022 vid: 60 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 155474556 10.1111/ecin.13049 ppf: 694 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P size: 4.8MB tig: atl: Obtaining consistent time series from Google Trends. aug: au: Eichenauer, Vera Z. Indergand, Ronald Martínez, Isabel Z. Sax, Christoph affil: ETH Zürich, KOF Swiss Economic Institute, Zürich, Switzerland State Secretariat for Economic Affairs SECO, Bern, Switzerland Faculty of Business and Economics, University of Basel, Basel, Switzerland Cynkra LLC, Zürich, Switzerland su: Economic indicators Business cycles Time series analysis sug: subj: Economic indicators Business cycles Time series analysis keyword: COVID‐19 forecasting Google Trends high frequency measurement COVID‐19 forecasting Google Trends high frequency measurement ab: Google Trends data are a popular data source for research, but raw data are frequency‐inconsistent: daily data fail to capture long‐run trends. This issue has gone unnoticed in the literature. In addition, sampling noise can be substantial. We develop a procedure (available in an R‐package), which solves both issues at once. We apply this procedure to construct long‐run, frequency‐consistent daily economic indices for three German‐speaking countries. The resulting indices are significantly correlated with traditional leading economic indicators while being available in real time. We discuss potential applications across disciplines and spanning well beyond business cycle analysis. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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