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Predicting the Present with Google Trends

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Cited by:

  1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
  2. Victor Ginsburgh & Olivier Gergaud, 2013. "Measuring the effect of cultural events with special emphasis on music festivals," ULB Institutional Repository 2013/152437, ULB -- Universite Libre de Bruxelles.
  3. Link, Sebastian & Peichl, Andreas & Roth, Christopher & Wohlfart, Johannes, 2023. "Attention to the Macroeconomy," CEPR Discussion Papers 18699, C.E.P.R. Discussion Papers.
  4. Gutiérrez, Antonio, 2023. "La brecha de género en el emprendimiento y la cultura emprendedora: Evidencia con Google Trends [Entrepreneurship gender gap and entrepreneurial culture: Evidence from Google Trends]," MPRA Paper 115876, University Library of Munich, Germany.
  5. Baur, Dirk G. & Dimpfl, Thomas, 2016. "Googling gold and mining bad news," Resources Policy, Elsevier, vol. 50(C), pages 306-311.
  6. Monge, Manuel & Poza, Carlos & Borgia, Sofía, 2022. "A proposal of a suspicion of tax fraud indicator based on Google trends to foresee Spanish tax revenues," International Economics, Elsevier, vol. 169(C), pages 1-12.
  7. Haodong Sun & Yang Yang & Yanyan Chen & Xiaoming Liu & Jiachen Wang, 2023. "Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model," Information Technology & Tourism, Springer, vol. 25(2), pages 205-233, June.
  8. Schniederjans, Dara G. & Curado, Carla & Khalajhedayati, Mehrnaz, 2020. "Supply chain digitisation trends: An integration of knowledge management," International Journal of Production Economics, Elsevier, vol. 220(C).
  9. Keane, Michael & Neal, Timothy, 2021. "Consumer panic in the COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 220(1), pages 86-105.
  10. Chi, Tsung-Li & Liu, Hung-Tsen & Chang, Chia-Chien, 2023. "Hedging performance using google Trends–Evidence from the indian forex options market," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 107-123.
  11. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
  12. Ching Hsu & Tina Yu & Shu-Heng Chen, 2021. "Narrative economics using textual analysis of newspaper data: new insights into the U.S. Silver Purchase Act and Chinese price level in 1928–1936," Journal of Computational Social Science, Springer, vol. 4(2), pages 761-785, November.
  13. Susan Athey & Michael Luca, 2019. "Economists (and Economics) in Tech Companies," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 209-230, Winter.
  14. Johannes Bock, 2018. "Quantifying macroeconomic expectations in stock markets using Google Trends," Papers 1805.00268, arXiv.org.
  15. Livio Fenga, 2020. "Filtering and prediction of noisy and unstable signals: The case of Google Trends data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 281-295, March.
  16. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
  17. Li, Cheng & Ge, Peng & Liu, Zhusheng & Zheng, Weimin, 2020. "Forecasting tourist arrivals using denoising and potential factors," Annals of Tourism Research, Elsevier, vol. 83(C).
  18. Craig A. Depken II & E. Frank Stephenson, 2017. "Copper Theft in the United States," The American Economist, Sage Publications, vol. 62(1), pages 66-76, March.
  19. Vicki Wei Tang, 2018. "Wisdom of Crowds: Cross‐Sectional Variation in the Informativeness of Third‐Party‐Generated Product Information on Twitter," Journal of Accounting Research, Wiley Blackwell, vol. 56(3), pages 989-1034, June.
  20. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
  21. Tamgac, Unay, 2021. "Emerging market exchange rates during quantitative tapering: The effect of US and domestic news," Research in International Business and Finance, Elsevier, vol. 57(C).
  22. John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353, arXiv.org.
  23. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
  24. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
  25. Saiz, Albert & Salazar-Miranda, Arianna, 2023. "Understanding Urban Economies, Land Use, and Social Dynamics in the City: Big Data and Measurement," IZA Discussion Papers 16501, Institute of Labor Economics (IZA).
  26. Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
  27. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
  28. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
  29. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2024. "Lessons from nowcasting GDP across the world," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 8, pages 187-217, Edward Elgar Publishing.
  30. Mioara, POPESCU, 2015. "Construction Of Economic Indicators Using Internet Searches," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 6(1), pages 25-31.
  31. 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.
  32. Shin, Sunny Y. & McKenzie, Jordi & Crosby, Paul, 2024. "Cultural affinity and international trade in motion pictures: Empirical evidence using categorised internet search activity," Economic Modelling, Elsevier, vol. 136(C).
  33. Yu-Chih Wei & Yan-Ling Ou & Jianqiang Li & Wei-Chen Wu, 2022. "Forecasting the Potential Number of Influenza-like Illness Cases by Fusing Internet Public Opinion," Sustainability, MDPI, vol. 14(5), pages 1-24, February.
  34. Yoo, Do-il, "undated". "Vegetable Price Prediction Using Atypical Web-Search Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236211, Agricultural and Applied Economics Association.
  35. Briggs, Justin Thomas & Tabarrok, Alexander, 2014. "Firearms and suicides in US states," International Review of Law and Economics, Elsevier, vol. 37(C), pages 180-188.
  36. Junzhao Ma & Dewi Tojib & Yelena Tsarenko, 2022. "Sex Robots: Are We Ready for Them? An Exploration of the Psychological Mechanisms Underlying People’s Receptiveness of Sex Robots," Journal of Business Ethics, Springer, vol. 178(4), pages 1091-1107, July.
  37. Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
  38. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
  39. Martha Bicket & Robin Vanner, 2016. "Designing Policy Mixes for Resource Efficiency: The Role of Public Acceptability," Sustainability, MDPI, vol. 8(4), pages 1-17, April.
  40. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
  41. Thiemo Fetzer & Lukas Hensel & Johannes Hermle & Christopher Roth, 2021. "Coronavirus Perceptions and Economic Anxiety," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 968-978, December.
  42. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023. "Testing big data in a big crisis: Nowcasting under Covid-19," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.
  43. Pietro Giorgio Lovaglio & Mario Mezzanzanica & Emilio Colombo, 2020. "Comparing time series characteristics of official and web job vacancy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 85-98, February.
  44. Kim, Jooho & Bae, Juhee & Hastak, Makarand, 2018. "Emergency information diffusion on online social media during storm Cindy in U.S," International Journal of Information Management, Elsevier, vol. 40(C), pages 153-165.
  45. Ajay Agrawal & John Horton & Nicola Lacetera & Elizabeth Lyons, 2015. "Digitization and the Contract Labor Market: A Research Agenda," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 219-250, National Bureau of Economic Research, Inc.
  46. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
  47. Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers 2024-15, University of Sydney, School of Economics.
  48. Artem Meshcheryakov & Stoyu I Ivanov, 2017. "Investor's sentiment in predicting the Effective Federal Funds Rate," Economics Bulletin, AccessEcon, vol. 37(4), pages 2767-2796.
  49. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
  50. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
  51. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
  52. Hulya Bakirtas & Vildan Gulpinar Demirci, 2022. "Can Google Trends data provide information on consumer’s perception regarding hotel brands?," Information Technology & Tourism, Springer, vol. 24(1), pages 57-83, March.
  53. Cong Peng, 2019. "Does e-commerce reduce traffic congestion? Evidence from Alibaba Single Day shopping event," CEP Discussion Papers dp1646, Centre for Economic Performance, LSE.
  54. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
  55. Mikhail Stolbov & Maria Shchepeleva, 2023. "Sentiment-based indicators of real estate market stress and systemic risk: international evidence," Annals of Finance, Springer, vol. 19(3), pages 355-382, September.
  56. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2019. "Forecast density combinations with dynamic learning for large data sets in economics and finance," Working Paper 2019/7, Norges Bank.
  57. Nian Li & Chunling Li & Runsen Yuan & Muhammad Asif Khan & Xiaoran Sun & Nosherwan Khaliq, 2021. "Investor Attention and Corporate Innovation Performance: Evidence from Web Search Volume Index of Chinese Listed Companies," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
  58. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
  59. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German car sales using Google data and multivariate models," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 97-135.
  60. Runde Fu & Xinhuan Zhang & Degang Yang & Tianyi Cai & Yufang Zhang, 2021. "The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region," IJERPH, MDPI, vol. 18(2), pages 1-20, January.
  61. Ying Liu & Yibing Chen & Sheng Wu & Geng Peng & Benfu Lv, 2015. "Composite leading search index: a preprocessing method of internet search data for stock trends prediction," Annals of Operations Research, Springer, vol. 234(1), pages 77-94, November.
  62. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
  63. 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.
  64. Binru Zhang & Yulian Pu & Yuanyuan Wang & Jueyou Li, 2019. "Forecasting Hotel Accommodation Demand Based on LSTM Model Incorporating Internet Search Index," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
  65. Yang, Yang & Fan, Yawen & Jiang, Lan & Liu, Xiaohui, 2022. "Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?," Annals of Tourism Research, Elsevier, vol. 93(C).
  66. Jina Suh & Eric Horvitz & Ryen W. White & Tim Althoff, 2022. "Disparate impacts on online information access during the Covid-19 pandemic," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  67. Ma, Junzhao & Seenivasan, Satheesh & Yan, Bingyu, 2020. "Media influences on consumption trends: Effects of the film Food, Inc. on organic food sales in the U.S," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 320-335.
  68. Georg von Graevenitz & Christian Helmers & Valentine Millot & Oliver Turnbull, 2016. "Does Online Search Predict Sales? Evidence from Big Data for Car Markets in Germany and the UK," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2016-07, Centre for Competition Policy, University of East Anglia, Norwich, UK..
  69. Karolien Lenaerts & Miroslav Beblavý & Brian Fabo, 2016. "Prospects for utilisation of non-vacancy Internet data in labour market analysis—an overview," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
  70. Axenbeck, Janna & Breithaupt, Patrick, 2019. "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers 19-063, ZEW - Leibniz Centre for European Economic Research.
  71. Yann Algan & Fabrice Murtin & Elizabeth Beasley & Kazuhito Higa & Claudia Senik, 2019. "Well-being through the lens of the internet," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-23, January.
  72. Huijian Han & Zhiming Li & Zongwei Li, 2023. "Using Machine Learning Methods to Predict Consumer Confidence from Search Engine Data," Sustainability, MDPI, vol. 15(4), pages 1-12, February.
  73. Chang, Young Bong & Kwon, YoungOk, 2018. "Ambiguities in valuing information technology firms: Do internet searches help?," Journal of Business Research, Elsevier, vol. 92(C), pages 260-269.
  74. David Lenz & Peter Winker, 2020. "Measuring the diffusion of innovations with paragraph vector topic models," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
  75. Ziru Li & Chen Liang & Yili Hong & Zhongju Zhang, 2022. "How Do On‐demand Ridesharing Services Affect Traffic Congestion? The Moderating Role of Urban Compactness," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 239-258, January.
  76. David Kreitmeir & Paul A. Raschky, 2024. "The Heterogeneous Productivity Effects of Generative AI," Papers 2403.01964, arXiv.org, revised Jun 2024.
  77. Sujin Pyo & Jaewook Lee & Mincheol Cha & Huisu Jang, 2017. "Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-17, November.
  78. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
  79. Ronald MacDonald & Xuxin Mao, "undated". "An Alternative way of predicting the putcome of the Scottish Independence Referendum: the information in the Ether," Working Papers 2015_05, Business School - Economics, University of Glasgow.
  80. Zhongchen Song & Tom Coupé, 2023. "Predicting Chinese consumption series with Baidu," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 21(3), pages 429-463, July.
  81. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
  82. Bronitsky, Georgy & Vakulenko, Elena, 2024. "Using Google Trends to forecast migration from Russia: Search query aggregation and accounting for lag structure," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 73, pages 78-101.
  83. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
  84. Marc Bourreau & François Moreau & Patrik Wikström, 2022. "Does digitization lead to the homogenization of cultural content?," Economic Inquiry, Western Economic Association International, vol. 60(1), pages 427-453, January.
  85. Ali Kabiri & Harold James & John Landon-Lane & David Tuckett & Rickard Nyman, 2020. "The Role of Sentiment in the Economy: 1920 to 1934," CESifo Working Paper Series 8336, CESifo.
  86. Janna Axenbeck & Patrick Breithaupt, 2021. "Innovation indicators based on firm websites—Which website characteristics predict firm-level innovation activity?," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-23, April.
  87. Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Seismonomics: Listening to the heartbeat of the economy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 288-309, December.
  88. Francesco Capozza & Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2021. "Studying Information Acquisition in the Field: A Practical Guide and Review," CEBI working paper series 21-15, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
  89. Lengyel, Attila, 2016. "Tourism, meditation, sustainability," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 10(1), pages 1-11, March.
  90. Branislav Saxa, 2014. "Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand," Working Papers 2014/14, Czech National Bank.
  91. Ahmed Al-Imam & Usama Khalid & Dawoude Kaouche & Nawfal Al-Hadithi, 2019. "Real-time Inferential Analytics Based on Online Databases of Trends: A Breakthrough Within the Discipline of Digital Epidemiology of Dentistry and Oral-Maxillofacial Surgery," Modern Applied Science, Canadian Center of Science and Education, vol. 13(2), pages 1-81, February.
  92. Francesco Decarolis & Maris Goldmanis & Antonio Penta, 2020. "Marketing Agencies and Collusive Bidding in Online Ad Auctions," Management Science, INFORMS, vol. 66(10), pages 4433-4454, October.
  93. Wenxing Lu & Jieyu Jin & Binyou Wang & Keqing Li & Changyong Liang & Junfeng Dong & Shuping Zhao, 2020. "Intelligence in Tourist Destinations Management: Improved Attention-based Gated Recurrent Unit Model for Accurate Tourist Flow Forecasting," Sustainability, MDPI, vol. 12(4), pages 1-20, February.
  94. Tommaso Colussi & Ingo E. Isphording & Nico Pestel, 2021. "Minority Salience and Political Extremism," American Economic Journal: Applied Economics, American Economic Association, vol. 13(3), pages 237-271, July.
  95. Fu, Hengni & Zheng, Chengsi & Yang, PingYu, 2024. "Digital inclusive finance and green transformation of manufacturing enterprises: Empirical analysis based on the dual perspectives of demand and supply," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
  96. Bae, Siye & Jo, Soojin & Shim, Myungkyu, 2023. "United States of Mind under Uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 102-127.
  97. Andreea Avramescu & Arkadiusz Wiśniowski, 2021. "Now-casting Romanian migration into the United Kingdom by using Google Search engine data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(40), pages 1219-1254.
  98. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
  99. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
  100. Atin Aboutorabi & Ga'etan de Rassenfosse, 2024. "Nowcasting R&D Expenditures: A Machine Learning Approach," Papers 2407.11765, arXiv.org.
  101. 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.
  102. Kučerová, Zuzana & Pakši, Daniel & Koňařík, Vojtěch, 2024. "Macroeconomic fundamentals and attention: What drives european consumers’ inflation expectations?," Economic Systems, Elsevier, vol. 48(1).
  103. 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.
  104. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
  105. Wohlfarth, Paul, 2018. "Measuring the impact of monetary policy attention on global asset volatility using search data," Economics Letters, Elsevier, vol. 173(C), pages 15-18.
  106. Huang, Xiankai & Zhang, Lifeng & Ding, Yusi, 2017. "The Baidu Index: Uses in predicting tourism flows –A case study of the Forbidden City," Tourism Management, Elsevier, vol. 58(C), pages 301-306.
  107. Yann Algan & Elizabeth Beasley & Florian Guyot & Kazuhito Higad & Fabrice Murtin & Claudia Senik, 2015. "Big Data Measures of Well-Being: Evidence from a Google Well-Being Index in the US," PSE Working Papers hal-03429943, HAL.
  108. Emanuele Ciani & Adeline Delavande & Ben Etheridge & Marco Francesconi, 2023. "Policy Uncertainty and Information Flows: Evidence from Pension Reform Expectations," The Economic Journal, Royal Economic Society, vol. 133(649), pages 98-129.
  109. Saakshi & Sohini Sahu & Siddhartha Chattopadhyay, 2020. "Epidemiology of inflation expectations and internet search: an analysis for India," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 649-671, July.
  110. Mingyang Zhang & Heyan Xu & Ning Ma & Xinglin Pan, 2022. "Intelligent Vehicle Sales Prediction Based on Online Public Opinion and Online Search Index," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
  111. Wei, Xiahai & Li, Jianan & Liu, Hongyou & Wan, Jiangtao, 2023. "Temperature and outdoor productivity: Evidence from professional soccer players," Journal of Asian Economics, Elsevier, vol. 87(C).
  112. Katerina Volchek & Anyu Liu & Haiyan Song & Dimitrios Buhalis, 2019. "Forecasting tourist arrivals at attractions: Search engine empowered methodologies," Tourism Economics, , vol. 25(3), pages 425-447, May.
  113. Coupé, Tom, 2018. "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-8.
  114. Kristina Gligorić & Arnaud Chiolero & Emre Kıcıman & Ryen W. White & Robert West, 2022. "Population-scale dietary interests during the COVID-19 pandemic," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  115. Ahmed Al-Imam, 2017. "Retrospective Analyses of High-risk NPS: Integrative Analyses of PubMed, Drug Fora, and the Surface Web," Global Journal of Health Science, Canadian Center of Science and Education, vol. 9(11), pages 1-40, November.
  116. Chen, Shiyi & Jiang, Lingduo & Liu, Wanlin & Song, Hong, 2022. "Fireworks regulation, air pollution, and public health: Evidence from China," Regional Science and Urban Economics, Elsevier, vol. 92(C).
  117. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2021. "Online Salience and Charitable Giving : Evidence from SMS Donations," The Warwick Economics Research Paper Series (TWERPS) 1325, University of Warwick, Department of Economics.
  118. Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
  119. Takehito Utsuro & Chen Zhao & Linghan Xu & Jiaqi Li & Yasuhide Kawada, 2017. "An Empirical Analysis on Comparing Market Share with Concerns on Companies Measured Through Search Engine Suggests," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(1), pages 3-19, March.
  120. Kyle Barron & Edward Kung & Davide Proserpio, 2021. "The Effect of Home-Sharing on House Prices and Rents: Evidence from Airbnb," Marketing Science, INFORMS, vol. 40(1), pages 23-47, January.
  121. Grzegorz Michal Bulczak, 2021. "Use of Google Trends to Predict the Real Estate Market: Evidence from the United Kingdom," International Real Estate Review, Global Social Science Institute, vol. 24(4), pages 613-631.
  122. Hal Varian, 2021. "Economics at Google," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 195-199, October.
  123. Ashish Agarwal & Alvin Chung Man Leung & Prabhudev Konana & Alok Kumar, 2017. "Cosearch Attention and Stock Return Predictability in Supply Chains," Information Systems Research, INFORMS, vol. 28(2), pages 265-288, June.
  124. Maksim Malyy & Zeljko Tekic & Tatiana Podladchikova, 2021. "The value of big data for analyzing growth dynamics of technology based new ventures," Papers 2104.03053, arXiv.org.
  125. James T. E. Chapman & Ajit Desai, 2023. "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, vol. 5(4), pages 1-32, November.
  126. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
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