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

Plos One, Forthcoming

50 Pages Posted: 15 Oct 2014 Last revised: 21 Nov 2014

See all articles by Dean Fantazzini

Dean Fantazzini

Moscow School of Economics, Moscow State University; National Research University Higher School of Economics

Date Written: November 4, 2014

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, Google Trends

JEL Classification: C22, C53, E27, H53, I32, Q18, R23

Suggested Citation

Fantazzini, Dean, Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data (November 4, 2014). Plos One, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2509932

Dean Fantazzini (Contact Author)

Moscow School of Economics, Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia
+7 495 5105256 (Phone)
+7 495 5105267 (Fax)

HOME PAGE: https://sites.google.com/site/deanfantazzini/

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

HOME PAGE: http://www.hse.ru/org/persons/11532644

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