Nowcasting Tourist Arrivals to Prague: Google Econometrics

Zeynalov, Ayaz (2014): Nowcasting Tourist Arrivals to Prague: Google Econometrics.

Abstract

It is expected that what people are searching for today is predictive of what they have done recently or will do in the near future. This research will analyze the eligibility of Google search data to nowcast tourist arrivals to Prague. The present research will report whether Google data is potentially useful in nowcasting or short-term forecasting using by Support Vector Regressions (SVRs), which maps data to a higher dimensional space and employs a kernel function.

• Item Type: MPRA Paper
• Language: English
• Keywords: Google trends, nowcasting, tourism forecasting
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications; L - Industrial Organization > L8 - Industry Studies: Services > L83 - Sports ; Gambling ; Restaurants ; Recreation ; Tourism

References

Concha Artola and Enrique Galn. Tracking the future on the web: construction of leading indicators using internet searches. Banco de Espania Occasional Papers 1203, Banco de Espania, April 2012.

Nikolaos Askitas and Klaus F. Zimmermann. Google Econometrics and Unemployment Forecasting. Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, 55(2):107-120, 2009.

George Athanasopoulos, Rob J. Hyndman, Haiyan Song, and Doris C. Wu. The tourism forecasting competition. International Journal of Forecasting, 27(3):822-844, July 2011.

Yan Carriere-Swallow and Felipe Labbe. Nowcasting with Google Trends in an Emerging Market. Journal of Forecasting, 32(4):289-298, 07 2013.

Hyunyoung Choi and Hal Varian. Predicting the Present with Google Trends. The Economic Record, 88(1):2-9, 06 2012.

Michael S. Drake, Darren T. Roulstone, and Jacob R. Thornock. Investor Information Demand: Evidence from Google Searches Around Earnings Announcements. Journal of Accounting Research, 50(4):1001-1040, 09 2012.

Vanja Dukic, Hedibert F. Lopes, and Nicholas G. Polson. Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model. Journal of the American Statistical Association, 107(500):1410-1426, December 2012.

Dean Fantazzini and Nikita Fomichev. Forecasting the real price of oil using online search data. International Journal of Computational Economics and Econometrics, 4(1/2): 4-31, 2014.

Y. Fondeur and F. Karam. Can Google data help predict French youth unemployment? Economic Modelling, 30(C):117-125, 2013.

S. Goel, J. Hofman, S. Lehaie, D. M. Pennock, and D. J. Watts. Predicting consumer behavior with Web search. Proceedings of the National Academy of Sciences of the United States of America, 7:1748617490, 2010.

Pilar Gonzalez and Paz Moral. An analysis of the international tourism demand in Spain. International Journal of Forecasting, 11(2):233-251, June 1995.

Wei-Chiang Hong. Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm. Energy, 36(9):5568-5578, 2011.

Ladislav Kristoufek. Can Google Trends search queries contribute to risk diversification? Papers 1310.1444, arXiv.org, October 2013.

Haiyan Song, Gang Li, Stephen F. Witt, and George Athanasopoulos. Forecasting tourist arrivals using time-varying parameter structural time series models. International Journal of Forecasting, 27(3):855-869, 2011.

Simeon Vosen and Torsten Schmidt. Forecasting private consumption: survey based indicators vs. Google trends. Journal of Forecasting, 30(6):565-578, September 2011.