Polytechnic University of Valencia Congress, CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics

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Forecasting Births Using Google
Francesco Billari, Francesco D'Amuri, Juri Marcucci

Last modified: 17-11-2017


Monitoring fertility change is particularly important for policy and planning purposes. New data may help us in this monitoring. We propose a new leading indicator based on Google web-searches. We then test its predictive power using US data. In a deep out-of sample comparison we show tha t popular time series specifications augmented with web-search-related data improve their forecasting performance at forecast horizons of 6 to 24 months. The superior performance of these augmented models is confirmed by formal tests of equal forecast accuracy. Moreover, our results survive a falsification test and are confirmed also when a forecast horse race is conducted using different out-of-sample tests, and at the state rather than at the federal level. Conditioning on the same information set, the forecast error of our b est model for predicting 2009 births is 35% lower than the Census bureau projections. Our findings indicate the potential use of Googe web-searches in monitoring fertility change and in informing fertility forecasts.

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