This paper shows that we can use social media data to improve the accuracy of GDP estimates at the country level for developing countries. I use all publicly available image tweets from 2012 and 2013 to estimate GDP at the country level for developing countries. First, I find that one can explain 76% of the cross-country variation in GDP with the volume of tweets sent from each country. I then show that the residuals on these Twitter-GDP estimates are significantly larger for countries with allegedly poor data quality. I then use Nigeria as a case study to show that this method delivers much more timely and accurate estimates than those presented by official statistic agencies.
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