Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity /
As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of...
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| Other Authors: | , , |
| Format: | Journal |
| Language: | English |
| Published: |
Washington, D.C. :
International Monetary Fund,
2021.
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| Series: | IMF Working Papers; Working Paper ;
No. 2021/295 |
| Subjects: | |
| Online Access: | Full text available on IMF |
| Summary: | As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators. |
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| Item Description: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Physical Description: | 1 online resource (47 pages) |
| Format: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Access: | Electronic access restricted to authorized BRAC University faculty, staff and students |