• D. S. Priyarsono IPB University
  • Siti Magfirotul Laelia , Fakultas Ekonomi dan Manajemen, Institut Pertanian Bogor



Google Trends data, forecasting method, youth unemployment


Google Trends data is an unbiased sample of search data produced by the Google search machine. This data represents the number of searches for a specific keyword using the search machine.  The availability of this free of charge data creates various opportunities of utilization for forecasting economic variables.  On the other hand, data produced by standard methods (using surveys) cannot be issued very frequently because of financial constraints and the limited mobility during COVID-19 pandemic.  This article reports a methodological study on the use of Google Trends data. The objective of this study is to show that the use of Google Trends data can improve the quality of forecasting.  To achieve the objective, youth unemployment data are utilized and prepared for analysis of Autoregressive Integrated Moving Average.  The quality of forecasting utilizing additional Google Trends data is compared with that without involving Google Trends data.  It is concluded that the quality of the forecasting using the first method is better than that of the second one.  This conclusion implies that utilizing Google Trends data can potentially improve the quality of forecasting and partially solve the problem of data scarcity resulted from financial constraints and the COVID-19 pandemic.


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