Narrow Your Choices

Refine By Countries

Refine By Series

Refine By Language

Refine By Date

—

Refine By IMF Taxonomy

Refine By JEL Taxonomy

Refine by LOC Taxonomy

Refine By THEMA Taxonomy

  • Print
  • Save

Business and Economics > Information Management

You are looking at 1 - 1 of 1 items for :

  • Type: Journal Issue x
  • Manufacturing industries x
Clear All Modify Search
Cover IMF Working Papers
Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity
Mr. Paul A Austin
,
Mr. Marco Marini
,
Alberto Sanchez
,
Chima Simpson-Bell
, and
James Tebrake
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.
Keywords:
Reopening; COVID-19; High-Frequency Data; Business Register.; Google Trends data; Google data; high-frequency data; high frequency indicator; reopening Indicator; APIs; Big data; Manufacturing; Africa; Global