Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data

Dean Fantazziini
Authors registered in the RePEc Author Service: Dean Fantazzini

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Food Stamps; Supplemental Nutrition Assistance Program; Google; Forecasting; Global Financial Crisis; Great Recession. (search for similar items in EconPapers)
JEL-codes: C22 C53 E27 H53 I32 Q18 R23 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Journal Article: Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:59696

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