Google Searches as a Means of Improving the Nowcasts of Key Macroeconomic Variables
AbstractThe Google Insights data are a collection of recorded Internet searches for a huge number of the keywords, which are available since January 2004. These searches represent a kind of revealed perceptions of Internet users, which are a (possibly not entirely representative) sample of the general public. These data can be used to improve the short-term forecasts or nowcasts of various macroeconomic variables. In this paper, we compare the nowcasts of the growth rates of the real US private consumption based on both the conventional consumer confidence indicators and the Google indicators. The latter are extracted from the Google searches using the principal component analysis. It is shown that the Google indicators are especially successful at predicting private consumption in times of economic trouble, for they are 20% more accurate than the best alternative during the 2008m1-2009m5 forecast period. In addition, Google indicators are available at weekly frequency and not subject to revisions. This makes them an excellent source of information for the macroeconomic forecasting.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 946.
Length: III, 11 p.
Date of creation: 2009
Date of revision:
Google indicators; forecasting; principal components; US private consumption;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bibliothek).
If references are entirely missing, you can add them using this form.