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Can Google data help predict French youth unemployment?

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Cited by:

  1. 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.
  2. 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.
  3. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
  4. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
  5. Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
  6. Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading the Newspapers," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 17-33.
  7. 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.
  8. 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.
  9. Gupta, Kartick & Banerjee, Rajabrata, 2019. "Does OPEC news sentiment influence stock returns of energy firms in the United States?," Energy Economics, Elsevier, vol. 77(C), pages 34-45.
  10. Branislav Saxa, 2014. "Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand," Working Papers 2014/14, Czech National Bank.
  11. 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.
  12. Necmettin Alpay Koçak, 2020. "The Role of Ecb Speeches in Nowcasting German Gdp," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2020(2), pages 05-20.
  13. Marcos González-Fernández & Carmen González-Velasco, 2019. "An approach to predict Spanish mortgage market activity using Google data," Economics and Business Letters, Oviedo University Press, vol. 8(4), pages 209-214.
  14. 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.
  15. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
  16. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
  17. González-Fernández, Marcos & González-Velasco, Carmen, 2018. "Can Google econometrics predict unemployment? Evidence from Spain," Economics Letters, Elsevier, vol. 170(C), pages 42-45.
  18. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
  19. 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.
  20. 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.
  21. Jakub Szymkowiak & Lechosław Kuczyński, 2015. "Avoiding predators in a fluctuating environment: responses of the wood warbler to pulsed resources," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(2), pages 601-608.
  22. 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.
  23. Botezat, Alina, 2017. "Austerity plan announcements and the impact on the employees’ wellbeing," Journal of Economic Psychology, Elsevier, vol. 63(C), pages 1-16.
  24. Tomas Havranek & Ayaz Zeynalov, 2021. "Forecasting tourist arrivals: Google Trends meets mixed-frequency data," Tourism Economics, , vol. 27(1), pages 129-148, February.
  25. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
  26. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
  27. Mahalia Jackman & Simon Naitram, 2015. "Research Note: Nowcasting Tourist Arrivals in Barbados – Just Google it!," Tourism Economics, , vol. 21(6), pages 1309-1313, December.
  28. Jaroslav Pavlicek & Ladislav Kristoufek, 2015. "Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-11, May.
  29. Juan Camilo Anzoátegui-Zapata & Juan Camilo Galvis-Ciro, 2020. "Disagreements in Consumer Inflation Expectations: Empirical Evidence for a Latin American Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 99-122, November.
  30. Afkhami, Mohamad & Ghoddusi, Hamed & Rafizadeh, Nima, 2021. "Google Search Explains Your Gasoline Consumption!," Energy Economics, Elsevier, vol. 99(C).
  31. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
  32. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
  33. Gulsah Senturk, 2022. "Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 229-244, July.
  34. Alberto Urtasun & Mara Gil & Javier J. Perez, 2017. "Nowcasting private consumption: traditional indicators, uncertainty measures, and the role of internet search query data," EcoMod2017 10745, EcoMod.
  35. 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.
  36. Mihaela Simionescu & Dalia Streimikiene & Wadim Strielkowski, 2020. "What Does Google Trends Tell Us about the Impact of Brexit on the Unemployment Rate in the UK?," Sustainability, MDPI, vol. 12(3), pages 1-10, January.
  37. Ladislav Kristoufek, 2013. "Can Google Trends search queries contribute to risk diversification?," Papers 1310.1444, arXiv.org.
  38. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
  39. van der Wielen, Wouter & Barrios, Salvador, 2021. "Economic sentiment during the COVID pandemic: Evidence from search behaviour in the EU," Journal of Economics and Business, Elsevier, vol. 115(C).
  40. Voraprapa Nakavachara & Nuarpear Lekfuangfu, 2017. "Predicting the Present Revisited: The Case of Thailand," PIER Discussion Papers 70, Puey Ungphakorn Institute for Economic Research.
  41. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022. "Does online salience predict charitable giving? Evidence from SMS text donations," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 134-149.
  42. Ronald MacDonald & Xuxin Mao, 2015. "An Alternative way of Predicting the Outcome of the Scottish Independence Referendum: The Information in the Ether," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-69, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  43. Liwen Ling & Dabin Zhang & Shanying Chen & Amin W. Mugera, 2020. "Can online search data improve the forecast accuracy of pork price in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 671-686, July.
  44. 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.
  45. KOCAK, Necmettin Alpay, 2021. "The Impacts Of Speeches On Nowcasting Gdp: A Case Study On Euro Area Markets," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 25(1), pages 6-29, March.
  46. Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
  47. Palma Lampreia Dos Santos, Maria José, 2018. "Nowcasting and forecasting aquaponics by Google Trends in European countries," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 178-185.
  48. 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.
  49. 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.
  50. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
  51. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
  52. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
  53. Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020. "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers) 583, Bank of Italy, Economic Research and International Relations Area.
  54. María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  55. Anastasiou, Dimitrios & Bragoudakis, Zacharias & Giannoulakis, Stelios, 2021. "Perceived vs actual financial crisis and bank credit standards: Is there any indication of self-fulfilling prophecy?," Research in International Business and Finance, Elsevier, vol. 58(C).
  56. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "A sentiment index to measure sovereign risk using Google data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 406-418.
  57. 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).
  58. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
  59. Park, Sungjun & Kim, Jinsoo, 2018. "The effect of interest in renewable energy on US household electricity consumption: An analysis using Google Trends data," Renewable Energy, Elsevier, vol. 127(C), pages 1004-1010.
  60. Böhme, Marcus H. & Gröger, André & Stöhr, Tobias, 2020. "Searching for a better life: Predicting international migration with online search keywords," Journal of Development Economics, Elsevier, vol. 142(C).
  61. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," Working Papers 2020-04, Joint Research Centre, European Commission.
  62. 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).
  63. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "An alternative approach to predicting bank credit risk in Europe with Google data," Finance Research Letters, Elsevier, vol. 35(C).
  64. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.
  65. Nuno Barreira & Pedro Godinho & Paulo Melo, 2013. "Nowcasting unemployment rate and new car sales in south-western Europe with Google Trends," Netnomics, Springer, vol. 14(3), pages 129-165, November.
  66. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
  67. Zeynalov, Ayaz, 2014. "Nowcasting Tourist Arrivals to Prague: Google Econometrics," MPRA Paper 60945, University Library of Munich, Germany.
  68. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
  69. 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.
  70. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
  71. Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
  72. Dimitrios Anastasiou & Konstantinos Drakos, 2021. "Nowcasting the Greek (semi‐) deposit run: Hidden uncertainty about the future currency in a Google search," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1133-1150, January.
  73. Naccarato, Alessia & Falorsi, Stefano & Loriga, Silvia & Pierini, Andrea, 2018. "Combining official and Google Trends data to forecast the Italian youth unemployment rate," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 114-122.
  74. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
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