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Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence

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Cited by:

  1. Dušan Marković & Igor Mladenović & Miloš Milovančević, 2017. "RETRACTED ARTICLE: Estimation of the most influential science and technology factors for economic growth forecasting by soft computing technique," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1133-1146, May.
  2. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022. "Nowcasting the Portuguese GDP with Monthly Data," Papers 2206.06823, arXiv.org.
  3. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
  4. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
  5. Sokolov-Mladenović, Svetlana & Milovančević, Milos & Mladenović, Igor, 2017. "Evaluation of trade influence on economic growth rate by computational intelligence approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 358-362.
  6. João B. Assunção & Pedro Afonso Fernandes, 2022. "Nowcasting GDP: An Application to Portugal," Forecasting, MDPI, vol. 4(3), pages 1-15, August.
  7. Petra Karanikić & Igor Mladenović & Svetlana Sokolov-Mladenović & Meysam Alizamir, 2017. "RETRACTED ARTICLE: Prediction of economic growth by extreme learning approach based on science and technology transfer," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1395-1401, May.
  8. Marković, Dušan & Petković, Dalibor & Nikolić, Vlastimir & Milovančević, Miloš & Petković, Biljana, 2017. "Soft computing prediction of economic growth based in science and technology factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 217-220.
  9. 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.
  10. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
  11. Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
  12. Siliverstovs, Boriss, 2017. "Dissecting models' forecasting performance," Economic Modelling, Elsevier, vol. 67(C), pages 294-299.
  13. Abdić Ademir & Resić Emina & Abdić Adem, 2020. "Modelling and forecasting GDP using factor model: An empirical study from Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 10-26, May.
  14. Abdić Ademir & Resić Emina & Abdić Adem & Rovčanin Adnan, 2020. "Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 1-14, December.
  15. Đokić, Aleksandar & Jović, Srđan, 2017. "Evaluation of agriculture and industry effect on economic health by ANFIS approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 396-399.
  16. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  17. Kordanuli, Bojana & Barjaktarović, Lidija & Jeremić, Ljiljana & Alizamir, Meysam, 2017. "Appraisal of artificial neural network for forecasting of economic parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 515-519.
  18. Eric W. K. See-To & Eric W. T. Ngai, 2018. "Customer reviews for demand distribution and sales nowcasting: a big data approach," Annals of Operations Research, Springer, vol. 270(1), pages 415-431, November.
  19. Samvel S. Lazaryan & Nikita E. German, 2018. "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 83-94, December.
  20. António Rua, 2017. "Dating the Portuguese business cycle," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  21. António Rua & Nuno Lourenço, 2022. "A circular business cycle clock for Portugal," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  22. Milačić, Ljubiša & Jović, Srđan & Vujović, Tanja & Miljković, Jovica, 2017. "Application of artificial neural network with extreme learning machine for economic growth estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 285-288.
  23. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
  24. Igor Mladenović & Miloš Milovančević & Svetlana Sokolov-Mladenović, 2017. "RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1297-1304, May.
  25. António Rua & Nuno Lourenço & Francisco Dias, 2018. "Forecasting exports with targeted predictors," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
  26. Maksimović, Goran & Jović, Srđan & Jovanović, Radomir, 2017. "Economic growth rate management by soft computing approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 520-524.
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