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Nowcasting is not Just Contemporaneous Forecasting

Citations

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Cited by:

  1. POPESCU Mioara, 2015. "Construction Of Economic Indicators Using Internet Searches," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 6(1), pages 25-31.
  2. Andrea Monaco & Adamaria Perrotta & Joseph Mulligan, 2024. "Selecting sensitive web info via conditional probabilities to model economics and financial variables," Empirical Economics, Springer, vol. 66(1), pages 467-481, January.
  3. 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.
  4. Popescu Mioara, 2017. "Modelling prediction of unemployment statistics using web technologies," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 8(3), pages 55-60, December.
  5. Pablo Duarte & Bernd Süssmuth, 2018. "Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 127-141, April.
  6. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
  7. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
  8. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
  9. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
  10. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
  11. Peter A.G. van Bergeijk, 2021. "Pandemic Economics," Books, Edward Elgar Publishing, number 20401.
  12. Neil Ericsson & Erica Reisman, 2012. "Evaluating a Global Vector Autoregression for Forecasting," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 18(3), pages 247-258, August.
  13. Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
  14. Adam, Christopher & Cobham, David, 2009. "Using Real-Time Output Gaps to Examine Past and Future Policy Choices," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 98-110, October.
  15. Anh Dinh Minh Nguyen, 2017. "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series 41, Bank of Lithuania.
  16. Chauvet, Marcelle & Gabriel, Stuart & Lutz, Chandler, 2016. "Mortgage default risk: New evidence from internet search queries," Journal of Urban Economics, Elsevier, vol. 96(C), pages 91-111.
  17. David F. Hendry, 2011. "Empirical Economic Model Discovery and Theory Evaluation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(46), October.
  18. 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.
  19. 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.
  20. 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.
  21. Amstad, Marlene & Fischer, Andreas M., 2010. "Monthly pass-through ratios," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1202-1213, July.
  22. Pablo Duarte & Bernd Süssmuth, 2014. "Robust Implementation of a Parsimonious Dynamic Factor Model to Nowcast GDP," CESifo Working Paper Series 4574, CESifo.
  23. Damien Challet & Ahmed Bel Hadj Ayed, 2014. "Do Google Trend data contain more predictability than price returns?," Papers 1403.1715, arXiv.org.
  24. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
  25. Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.
  26. Ene Andreea Bianca, 2018. "Distance Education in Romanian Higher Education," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 9(1), pages 65-70, May.
  27. Maaß, Christina Heike, 2021. "Nowcast als Forecast: Neue Verfahren der BIP-Prognose in Echtzeit," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 101-127, Hamburg Institute of International Economics (HWWI).
  28. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
  29. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
  30. William Larson, 2015. "Forecasting an Aggregate in the Presence of Structural Breaks in the Disaggregates," Working Papers 2015-002, The George Washington University, The Center for Economic Research.
  31. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
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