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Tracking activity in real time with Google Trends
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Cited by:
- Phurichai Rungcharoenkitkul, 2021.
"Macroeconomic effects of COVID‐19: A mid‐term review,"
Pacific Economic Review, Wiley Blackwell, vol. 26(4), pages 439-458, October.
- Phurichai Rungcharoenkitkul, 2021. "Macroeconomic effects of Covid-19: a mid-term review," BIS Working Papers 959, Bank for International Settlements.
- Daniel Ollech & Deutsche Bundesbank, 2023. "Economic analysis using higher-frequency time series: challenges for seasonal adjustment," Empirical Economics, Springer, vol. 64(3), pages 1375-1398, March.
- Takashi Nakazawa, 2022. "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series 22-E-9, Bank of Japan.
- David Kohns & Arnab Bhattacharjee, 2020.
"Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model,"
Papers
2011.00938, arXiv.org, revised May 2022.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
- Marcelo C. Medeiros & Henrique F. Pires, 2021. "The Proper Use of Google Trends in Forecasting Models," Papers 2104.03065, arXiv.org, revised Apr 2021.
- Huaqing Xie & Xingcheng Xu & Fangjia Yan & Xun Qian & Yanqing Yang, 2024. "Deep Learning for Multi-Country GDP Prediction: A Study of Model Performance and Data Impact," Papers 2409.02551, arXiv.org.
- Yanqing Yang & Xingcheng Xu & Jinfeng Ge & Yan Xu, 2024. "Machine Learning for Economic Forecasting: An Application to China's GDP Growth," Papers 2407.03595, arXiv.org.
- Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
- Benmir, Ghassane & Jaccard, Ivan & Vermandel, Gauthier, 2023.
"Optimal monetary policy in an estimated SIR model,"
European Economic Review, Elsevier, vol. 156(C).
- Ghassane Benmir & Ivan Jaccard & Gauthier Vermandel, 2023. "Optimal monetary policy in an estimated SIR model," Post-Print hal-04502674, HAL.
- Benmir, Ghassane & Jaccard, Ivan & Vermandel, Gauthier, 2023. "Optimal monetary policy in an estimated SIR model," Working Paper Series 2847, European Central Bank.
- Daniel E. O'Leary, 2024. "Toward an extended framework of exhaust data for predictive analytics: An empirical approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
- Brault, Julien, 2023. "Recent trends in EU corporate demography and policy: COVID and beyond," EIF Working Paper Series 2023/90, European Investment Fund (EIF).
- Fatima-Zahra Jaouimaa & Daniel Dempsey & Suzanne Van Osch & Stephen Kinsella & Kevin Burke & Jason Wyse & James Sweeney, 2021.
"An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost,"
PLOS ONE, Public Library of Science, vol. 16(12), pages 1-25, December.
- Fatima-Zahra Jaouimaa & Daniel Dempsey & Suzanne van Osch & Stephen Kinsella & Kevin Burke & Jason Wyse & James Sweeney, 2021. "An age-structured SEIR model for COVID--19 incidence in Dublin, Ireland with framework for evaluating health intervention cost," Papers 2106.06377, arXiv.org.
- Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
- Annamaria de Crescenzio & Etienne Lepers, 2021. "Extreme capital flow episodes from the Global Financial Crisis to COVID-19: An exploration with monthly data," OECD Working Papers on International Investment 2021/05, OECD Publishing.
- Tomas Adam & Ondrej Michalek & Ales Michl & Eva Slezakova, 2021. "The Rushin Index: A Weekly Indicator of Czech Economic Activity," Working Papers 2021/4, Czech National Bank.
- Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
- Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023. "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 213-234, March.
- Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
- Alexandre Aspremont & Simon Ben Arous & Jean-Charles Bricongne & Benjamin Lietti & Baptiste Meunier, 2023.
"Satellites Turn “Concrete”: Tracking Cement with Satellite Data and Neural Networks,"
Working papers
916, Banque de France.
- d’Aspremont, Alexandre & Arous, Simon Ben & Bricongne, Jean-Charles & Lietti, Benjamin & Meunier, Baptiste, 2024. "Satellites turn “concrete”: tracking cement with satellite data and neural networks," Working Paper Series 2900, European Central Bank.
- Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
- Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2024. "Big data financial transactions and GDP nowcasting: The case of Turkey," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 227-248, March.
- Daniel E. Rigobon & Thibaut Duprey & Artur Kotlicki & Philip Schnattinger & Soheil Baharian & Thomas R. Hurd, 2022. "Business Closures and (Re)Openings in Real-Time Using Google Places: Proof of Concept," JRFM, MDPI, vol. 15(4), pages 1-10, April.
- Bhanu Pratap & Nalin Priyaranjan, 2023. "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, vol. 65(4), pages 1599-1625, October.
- Hal Varian, 2021. "Economics at Google," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 195-199, October.
- Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2021. "Big Data Information and Nowcasting: Consumption and Investment from Bank Transactions in Turkey," Papers 2107.03299, arXiv.org.
- Ten,Gi Khan & Merfeld,Joshua David & Hirfrfot,Kibrom Tafere & Newhouse,David Locke & Pape,Utz Johann, 2022. "How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19 ?," Policy Research Working Paper Series 10080, The World Bank.
- Sabyasachi Kar & Amaani Bashir & Mayank Jain, 2021. "New Approaches to Forecasting Growth and Inflation: Big Data and Machine Learning," IEG Working Papers 446, Institute of Economic Growth.
- Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
- Florian Gunsilius & David Van Dijcke, 2023. "Free Discontinuity Regression: With an Application to the Economic Effects of Internet Shutdowns," Papers 2309.14630, arXiv.org, revised Jan 2024.
- David J. Haw & Christian Morgenstern & Giovanni Forchini & Robert Johnson & Patrick Doohan & Peter C. Smith & Katharina D. Hauck, 2022. "Data needs for integrated economic-epidemiological models of pandemic mitigation policies," Papers 2209.01487, arXiv.org.
- Ollech, Daniel, 2021. "Economic analysis using higher frequency time series: Challenges for seasonal adjustment," Discussion Papers 53/2021, Deutsche Bundesbank.
- Atin Aboutorabi & Ga'etan de Rassenfosse, 2024. "Nowcasting R&D Expenditures: A Machine Learning Approach," Papers 2407.11765, arXiv.org.
- Krzysztof Drachal & Daniel González Cortés, 2022. "Estimation of Lockdowns’ Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data," IJERPH, MDPI, vol. 20(1), pages 1-24, December.
- Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
- Lolić, Ivana & Matošec, Marina & Sorić, Petar, 2024. "DIY google trends indicators in social sciences: A methodological note," Technology in Society, Elsevier, vol. 77(C).