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Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values

Citations

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Cited by:

  1. Rickard Nyman & Sujit Kapadia & David Tuckett & David Gregory & Paul Ormerod & Robert Smith, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
  2. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
  3. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
  4. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
  5. Ksenia Yakovleva, 2018. "Text Mining-based Economic Activity Estimation," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 26-41, December.
  6. Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
  7. Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
  8. Diana Gabrielyan & Lenno Uusküla, 2022. "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 142, Faculty of Economics and Business Administration, University of Tartu (Estonia).
  9. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
  10. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
  11. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
  12. repec:spo:wpmain:info:hdl:2441/7v8fvu0bf08jcoi4epn8cutjm8 is not listed on IDEAS
  13. Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
  14. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
  15. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  16. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
  17. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," Working Papers hal-03403256, HAL.
  18. Erik Andres-Escayola & Corinna Ghirelli & Luis Molina & Javier J. Pérez & Elena Vidal, 2022. "Using newspapers for textual indicators: which and how many?," Working Papers 2235, Banco de España.
  19. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
  20. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
  21. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
  22. 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).
  23. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
  24. repec:hal:spmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS
  25. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
  26. repec:hal:spmain:info:hdl:2441/7v8fvu0bf08jcoi4epn8cutjm8 is not listed on IDEAS
  27. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
  28. repec:spo:wpmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS
  29. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
  30. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
  31. Erik Andres-Escayola & Corinna Ghirelli & Luis Molina & Javier J. Perez & Elena Vidal, 2024. "Using Newspapers for Textual Indicators: Guidance Based on Spanish- and Portuguese-Speaking Countries," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 643-692, August.
  32. Mathilde Gerardin & Martial Ranvier, 2021. "Enrichment of the Banque de France s monthly business survey: lessons from textual analysis of business leaders comments," Working papers 821, Banque de France.
  33. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.
  34. Julian Ashwin & Eleni Kalamara & Lorena Saiz, 2024. "Nowcasting Euro area GDP with news sentiment: A tale of two crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 887-905, August.
  35. Yolanda S. Stander, 2024. "A News Sentiment Index to Inform International Financial Reporting Standard 9 Impairments," JRFM, MDPI, vol. 17(7), pages 1-23, July.
  36. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
  37. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  38. Zhao, Lu-Tao & Wang, Dai-Song & Ren, Zhong-Yuan, 2024. "The impact of joint events on oil price volatility: Evidence from a dynamic graphical news analysis model," Economic Modelling, Elsevier, vol. 130(C).
  39. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
  40. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
  41. Alexander Jaax & Annabelle Mourougane & Frederic Gonzales, 2024. "Nowcasting services trade for the G7 economies," The World Economy, Wiley Blackwell, vol. 47(4), pages 1336-1386, April.
  42. Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
  43. David Ardia & Keven Bluteau, 2024. "Optimal Text-Based Time-Series Indices," Papers 2405.10449, arXiv.org.
  44. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
  45. Nyman, Rickard & Kapadia, Sujit & Tuckett, David, 2021. "News and narratives in financial systems: Exploiting big data for systemic risk assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
  46. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).
  47. Cerqueti, Roy & Ficcadenti, Valerio & Mattera, Raffaele, 2024. "Investors’ attention and network spillover for commodity market forecasting," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
  48. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
  49. Guo, Minjia & Zong, Xiangyu & Guo, Lubingzhi & Lei, Yongyu, 2024. "Does haze-related sentiment affect income inequality in China?," International Review of Economics & Finance, Elsevier, vol. 94(C).
  50. Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.
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