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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- Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
- Richard Harris & Robert Lewis, 2013. "Introduction," Planning Perspectives, Taylor & Francis Journals, vol. 28(1), pages 113-116, January.
- 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.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521747387, December.
- 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.
- 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.
- 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.
- James J. Heckman, 1977.
"Dummy Endogenous Variables in a Simultaneous Equation System,"
NBER Working Papers
0177, National Bureau of Economic Research, Inc.
- Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
- Wu, De-Min, 1973. "Alternative Tests of Independence Between Stochastic Regressors and Disturbances," Econometrica, Econometric Society, vol. 41(4), pages 733-750, 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.
- 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.
- Brock,W.A. & Durlauf,S.N., 2004. "Identification of binary choice models with social interactions," Working papers 2, Wisconsin Madison - Social Systems.
- David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
- Amos Tversky & Daniel Kahneman, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Levine's Working Paper Archive
7656, David K. Levine.
- Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
- 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).
- 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.
- Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2004.
"Social Interaction and Stock-Market Participation,"
Journal of Finance,
American Finance Association, vol. 59(1), pages 137-163, 02.
- Sunil Mani & Richard R. Nelson, 2013. "Introduction," Chapters, in: TRIPS Compliance, National Patent Regimes and Innovation, chapter 1, pages 1-15 Edward Elgar Publishing.
- D. S. Prasada Rao & Bart van Ark, 2013. "Introduction," Chapters, in: World Economic Performance, chapter 1, pages 1-6 Edward Elgar Publishing.
- 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.
- 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.
- 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 454-462, March.
- 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.
- Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
- 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.
- T. Heller & R. Huet & Bénédicte Vidaillet, 2013. "Introduction," Post-Print hal-00848256, HAL.
- Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, Oxford University Press, vol. 107(3), pages 797-817.
- 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.
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