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- W2346188678 abstract "We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting." @default.
- W2346188678 created "2016-06-24" @default.
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- W2346188678 date "2016-05-04" @default.
- W2346188678 modified "2023-10-16" @default.
- W2346188678 title "Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data" @default.
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- W2346188678 doi "https://doi.org/10.1080/10548408.2016.1170651" @default.
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