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Obtaining consistent time series from Google Trends

Vera Z. Eichenauer, Ronald Indergand, Isabel Martínez and Christoph Sax

Economic Inquiry, 2022, vol. 60, issue 2, 694-705

Abstract: 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.

Date: 2022
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