Leveraging Non-traditional Data for Macroeconomic Nowcasting: The Case of Morocco
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- D’Amuri, Francesco & Marcucci, Juri, 2017.
"The predictive power of Google searches in forecasting US unemployment,"
International Journal of Forecasting, Elsevier, vol. 33(4), pages 801-816.
- Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
- Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
- Caroline Jardet & Baptiste Meunier, 2022.
"Nowcasting world GDP growth with high‐frequency data,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
- Caroline Jardet & Baptiste Meunier, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
- Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
- Geun-Cheol Lee, 2025. "A Data-Driven Approach to Tourism Demand Forecasting: Integrating Web Search Data into a SARIMAX Model," Data, MDPI, vol. 10(5), pages 1-13, May.
- Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
- Tomas Havranek & Ayaz Zeynalov, 2021.
"Forecasting tourist arrivals: Google Trends meets mixed-frequency data,"
Tourism Economics, , vol. 27(1), pages 129-148, February.
- Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
- Laurent Ferrara & Anna Simoni, 2023.
"When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
- Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
- Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print hal-03919944, HAL.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
- Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
- Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers hal-04159714, HAL.
- Greta Polo & Yuan Gao Rollinson & Ms. Yevgeniya Korniyenko & Tongfang Yuan, 2025. "Nowcasting GCC GDP: A Machine Learning Solution for Enhanced Non-Oil GDP Prediction," IMF Working Papers 2025/268, International Monetary Fund.
- Eurydice Fotopoulou & Iyke Maduako & M. Belen Sbrancia & Prachi Srivastava, 2026. "Nowcasting Economic Growth with Machine Learning and Satellite Data," IMF Working Papers 2026/020, International Monetary Fund.
- Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
- Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024. "Reinvigorating GVA Nowcasting in the Post-pandemic Period: A Case Study for India," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(Spesial I), pages 95-130, February.
- J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012.
"Measuring Economic Growth from Outer Space,"
American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
- J. Vernon Henderson & Adam Storeygard & David N. Weil, 2009. "Measuring Economic Growth from Outer Space," NBER Working Papers 15199, National Bureau of Economic Research, Inc.
- Vernon Henderson & Adam Storeygard & David N. Weil, 2009. "Measuring Economic Growth from Outer Space," Working Papers 2009-8, Brown University, Department of Economics.
- Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
- Zheng, Tingguo & Fan, Xinyue & Jin, Wei & Fang, Kuangnan, 2024. "Words or numbers? Macroeconomic nowcasting with textual and macroeconomic data," International Journal of Forecasting, Elsevier, vol. 40(2), pages 746-761.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Marta Crispino & Vincenzo Mariani, 2025.
"A Tool to Nowcast Tourist Overnight Stays with Payment Data and Complementary Indicators,"
Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 11(1), pages 285-312, March.
- Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
- Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
- Daniel Borup & Erik Christian Montes Schütte, 2022.
"In Search of a Job: Forecasting Employment Growth Using Google Trends,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 186-200, January.
- Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
- Mr. Paul A Austin & Mr. Marco Marini & Alberto Sanchez & Chima Simpson-Bell & Jim Tebrake, 2021. "Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity," IMF Working Papers 2021/295, International Monetary Fund.
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This paper has been announced in the following NEP Reports:- NEP-ARA-2026-07-27 (MENA - Middle East and North Africa)
- NEP-BIG-2026-07-27 (Big Data)
- NEP-FOR-2026-07-27 (Forecasting)
- NEP-INV-2026-07-27 (Investment)
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