Nowcasting Obesity in the U.S. Using Google Search Volume Data
“Googling” is now ubiquitous in our society. We typically start searching on Google before we make purchase decisions or when we have interest in certain topics. Aggregating these search data can provide us with real-time and possibly accurate information on people's behavior. In fact, Google keeps tracks of all the search queries and has accumulated a tremendous amount of information about people's interest at the society level. It currently provides search volume data of keywords for different regions and time intervals on its free and public service of Google Trends. An interesting and hot research area is how to exploit the Google Search volume data in innovative ways to benefit our society. This paper aims to reveal the connection between obesity prevalence and people’s online search behavior in the United States by combining data from Google Trends and data from Behavioral Risk Factor Surveillance System (BRFSS) which is updated by the Centers for Disease Control and Prevention (CDC) annually. We first handselected keywords that are associated to people's life style and used panel data model to study association between search pattern and obesity level. We found significant correlation power of those keywords with Body Mass Index (BMI) level and results suggest great promise of the idea of obesity monitoring through real-time Google Trends data. We believe this is an important finding and is particularly attractive for government health institutions and private businesses such as insurance companies etc.
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kahneman, Daniel & Tversky, Amos, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Econometric Society, vol. 47(2), pages 263-91, March.
- Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
- Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
- De Giorgi, Giacomo & Pellizzari, Michele & Redaelli, Silvia, 2007. "Be as Careful of the Books You Read as of the Company You Keep: Evidence on Peer Effects in Educational Choices," IZA Discussion Papers 2833, Institute for the Study of Labor (IZA).
- Bruce Sacerdote, 2000.
"Peer Effects with Random Assignment: Results for Dartmouth Roommates,"
NBER Working Papers
7469, National Bureau of Economic Research, Inc.
- Bruce Sacerdote, 2001. "Peer Effects with Random Assignment: Results for Dartmouth Roommates," The Quarterly Journal of Economics, Oxford University Press, vol. 116(2), pages 681-704.
- Richard Harris & Robert Lewis, 2013. "Introduction," Planning Perspectives, Taylor & Francis Journals, vol. 28(1), pages 113-116, January.
- Kenneth Train, 2003.
"Discrete Choice Methods with Simulation,"
Online economics textbooks,
SUNY-Oswego, Department of Economics, number emetr2.
- Esther Duflo & Emmanuel Saez, 2003. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 118(3), pages 815-842.
- David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
- Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992.
"An ordered probit analysis of transaction stock prices,"
Journal of Financial Economics,
Elsevier, vol. 31(3), pages 319-379, June.
- Hausman, J.A. & Lo, A.W. & MacKinlay, A.C., 1991. "An Ordered Probit Analysis of Transaction Stock Prices," Weiss Center Working Papers 26-91, Wharton School - Weiss Center for International Financial Research.
- Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, Archie Craig, 1955-, 1990. "An ordered probit analysis of transaction stock prices," Working papers 3234-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Jerry A. Hausman & Andrew W. Lo & A. Craig MacKinlay, 1991. "An Ordered Probit Analysis of Transaction Stock Prices," NBER Working Papers 3888, National Bureau of Economic Research, Inc.
- Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, 09.
- Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
- Brock,W.A. & Durlauf,S.N., 2004.
"Identification of binary choice models with social interactions,"
2, Wisconsin Madison - Social Systems.
- Brock, William A. & Durlauf, Steven N., 2007. "Identification of binary choice models with social interactions," Journal of Econometrics, Elsevier, vol. 140(1), pages 52-75, September.
- Wu, De-Min, 1973. "Alternative Tests of Independence Between Stochastic Regressors and Disturbances," Econometrica, Econometric Society, vol. 41(4), pages 733-50, July.
- Douglas Staiger & James H. Stock, 1997.
"Instrumental Variables Regression with Weak Instruments,"
Econometric Society, vol. 65(3), pages 557-586, May.
- Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
- Richards, Timothy J. & Patterson, Paul M., 1999. "The Economic Value Of Public Relations Expenditures: Food Safety And The Strawberry Case," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(02), December.
- Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
- Michael Luca, 2011. "Reviews, Reputation, and Revenue: The Case of Yelp.com," Harvard Business School Working Papers 12-016, Harvard Business School, revised Mar 2016.
- D. S. Prasada Rao & Bart van Ark, 2013. "Introduction," Chapters, in: World Economic Performance, chapter 1, pages 1-6 Edward Elgar Publishing.
- Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2001.
"Social Interaction and Stock-Market Participation,"
NBER Working Papers
8358, National Bureau of Economic Research, Inc.
- T. Heller & R. Huet & Bénédicte Vidaillet, 2013. "Introduction," Post-Print hal-00848256, HAL.
- Herr, Paul M & Kardes, Frank R & Kim, John, 1991. " Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective," Journal of Consumer Research, Oxford University Press, vol. 17(4), pages 454-62, March.
- Sunil Mani & Richard R. Nelson, 2013. "Introduction," Chapters, in: TRIPS Compliance, National Patent Regimes and Innovation, chapter 1, pages 1-15 Edward Elgar Publishing.
- Heckman, James J, 1978.
"Dummy Endogenous Variables in a Simultaneous Equation System,"
Econometric Society, vol. 46(4), pages 931-59, July.
- James J. Heckman, 1977. "Dummy Endogenous Variables in a Simultaneous Equation System," NBER Working Papers 0177, National Bureau of Economic Research, Inc.
- Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
- Esther Duflo & Emmanuel Saez, 2003. "The role of information and social interactions in retirement plan decisions: Evidence from a randomized experiment," Framed Field Experiments 00141, The Field Experiments Website.
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