Obtaining consistent time series from Google Trends
谷歌趋势原始数据存在频率不一致和采样噪声问题，本文开发了一个R包程序同时解决这两个问题，并构建了三个德语国家的长期日度经济指数，该指数与传统先行指标显著相关且可实时获取。
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.