Forecasting Spanish unemployment with Google Trends and dimension reduction techniques
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DOI: 10.1007/s13209-021-00231-x
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Citations
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Cited by:
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- Nirmalya Thakur & Shuqi Cui & Kesha A. Patel & Isabella Hall & Yuvraj Nihal Duggal, 2023. "A Large-Scale Dataset of Search Interests Related to Disease X Originating from Different Geographic Regions," Data, MDPI, vol. 8(11), pages 1-24, October.
- Simionescu, Mihaela & Cifuentes-Faura, Javier, 2022. "Can unemployment forecasts based on Google Trends help government design better policies? An investigation based on Spain and Portugal," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 1-21.
- Rodrigo Mulero & Alfredo Garcia-Hiernaux, 2023. "Forecasting unemployment with Google Trends: age, gender and digital divide," Empirical Economics, Springer, vol. 65(2), pages 587-605, August.
- Nakamura, Nobuyuki & Suzuki, Aya, 2021. "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, vol. 76(C).
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More about this item
Keywords
Unemployment; Forecasting; Google Trends; Dimensionality reduction; RMSE;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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