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Nowcasting and forecasting the monthly food stamps data in the US using online search data.

Fantazzini D - PLoS ONE (2014)

Bottom Line: We propose the use of Google online search data for nowcasting and forecasting the number of food stamps recipients.We perform a large out-of-sample forecasting exercise with almost 3000 competing models with forecast horizons up to 2 years ahead, and we show that models including Google search data statistically outperform the competing models at all considered horizons.These results hold also with several robustness checks, considering alternative keywords, a falsification test, different out-of-samples, directional accuracy and forecasts at the state-level.

View Article: PubMed Central - PubMed

Affiliation: Moscow School of Economics, Moscow State University, Moscow, Russia.

ABSTRACT
We propose the use of Google online search data for nowcasting and forecasting the number of food stamps recipients. We perform a large out-of-sample forecasting exercise with almost 3000 competing models with forecast horizons up to 2 years ahead, and we show that models including Google search data statistically outperform the competing models at all considered horizons. These results hold also with several robustness checks, considering alternative keywords, a falsification test, different out-of-samples, directional accuracy and forecasts at the state-level.

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Related in: MedlinePlus

Bloomberg story-count for “food stamps” worldwide (left plot); Google standardized volume of news related to “food stamps” worldwide (right plot).Google data are registered trademarks of Google Inc., used with permission.
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pone-0111894-g001: Bloomberg story-count for “food stamps” worldwide (left plot); Google standardized volume of news related to “food stamps” worldwide (right plot).Google data are registered trademarks of Google Inc., used with permission.

Mentions: The Supplemental Nutrition Assistance Program (SNAP), which was known as the Food Stamp Program until it was renamed in the 2008 US farm bill, is a federal aid program designed to give low- and no-income people living in the US a means to buy food. Since 2011, more than 40 million Americans have received this kind of aid. The number of monthly food stamps recipients has become increasingly scrutinized worldwide as an important indicator of the US economy: see Figure 1 which reports the monthly (absolute) number of news related to food stamps in Bloomberg since 2000, and the monthly (standardized) number of news in Google since 2006 worldwide.


Nowcasting and forecasting the monthly food stamps data in the US using online search data.

Fantazzini D - PLoS ONE (2014)

Bloomberg story-count for “food stamps” worldwide (left plot); Google standardized volume of news related to “food stamps” worldwide (right plot).Google data are registered trademarks of Google Inc., used with permission.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4219814&req=5

pone-0111894-g001: Bloomberg story-count for “food stamps” worldwide (left plot); Google standardized volume of news related to “food stamps” worldwide (right plot).Google data are registered trademarks of Google Inc., used with permission.
Mentions: The Supplemental Nutrition Assistance Program (SNAP), which was known as the Food Stamp Program until it was renamed in the 2008 US farm bill, is a federal aid program designed to give low- and no-income people living in the US a means to buy food. Since 2011, more than 40 million Americans have received this kind of aid. The number of monthly food stamps recipients has become increasingly scrutinized worldwide as an important indicator of the US economy: see Figure 1 which reports the monthly (absolute) number of news related to food stamps in Bloomberg since 2000, and the monthly (standardized) number of news in Google since 2006 worldwide.

Bottom Line: We propose the use of Google online search data for nowcasting and forecasting the number of food stamps recipients.We perform a large out-of-sample forecasting exercise with almost 3000 competing models with forecast horizons up to 2 years ahead, and we show that models including Google search data statistically outperform the competing models at all considered horizons.These results hold also with several robustness checks, considering alternative keywords, a falsification test, different out-of-samples, directional accuracy and forecasts at the state-level.

View Article: PubMed Central - PubMed

Affiliation: Moscow School of Economics, Moscow State University, Moscow, Russia.

ABSTRACT
We propose the use of Google online search data for nowcasting and forecasting the number of food stamps recipients. We perform a large out-of-sample forecasting exercise with almost 3000 competing models with forecast horizons up to 2 years ahead, and we show that models including Google search data statistically outperform the competing models at all considered horizons. These results hold also with several robustness checks, considering alternative keywords, a falsification test, different out-of-samples, directional accuracy and forecasts at the state-level.

Show MeSH
Related in: MedlinePlus