IDEAS home Printed from https://ideas.repec.org/r/tcb/cebare/v15y2015i3p15-40.html
   My bibliography  Save this item

Nowcasting the Unemployment Rate in Turkey : Let's ask Google

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. 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.
  2. Moses Tule & Taiwo Ajilore & Godday Ebuh, 2016. "A composite index of leading indicators of unemployment in Nigeria," Journal of African Business, Taylor & Francis Journals, vol. 17(1), pages 87-105, January.
  3. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
  4. Costa, Eduardo André & Silva, Maria Eduarda & Galvão, Ana Beatriz, 2024. "Real-time nowcasting the monthly unemployment rates with daily Google Trends data," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
  5. Burcu Gurcihan Yunculer & Gonul Sengul & Arzu Yavuz, 2014. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 14(1), pages 23-45.
  6. Jacques Bughin, 2015. "Google searches and twitter mood: nowcasting telecom sales performance," Netnomics, Springer, vol. 16(1), pages 87-105, August.
  7. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
  8. 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.
  9. 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).
  10. Franch, Fabio, 2021. "Political preferences nowcasting with factor analysis and internet data: The 2012 and 2016 US presidential elections," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  11. 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.
  12. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
  13. 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).
  14. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
  15. Omer ZEYBEK & Erginbay UGURLU, 2014. "Nowcasting Credit Demand in Turkey with Google Trends Data," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 1(1), pages 333-340, December.
  16. 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.
  17. Bulut Levent & Dogan Can, 2018. "Google Trends and Structural Exchange Rate Models for Turkish Lira–US Dollar Exchange Rate," Review of Middle East Economics and Finance, De Gruyter, vol. 14(2), pages 1-12, August.
  18. Per Nymand-Andersen, 2016. "Big data: the hunt for timely insights and decision certainty," IFC Working Papers 14, Bank for International Settlements.
  19. M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.
  20. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. Voraprapa Nakavachara & Nuarpear Lekfuangfu, 2017. "Predicting the Present Revisited: The Case of Thailand," PIER Discussion Papers 70, Puey Ungphakorn Institute for Economic Research.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.