Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster
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DOI: 10.1016/j.eap.2020.12.013
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- Chuku, Chuku & Simpasa, Anthony & Oduor, Jacob, 2019.
"Intelligent forecasting of economic growth for developing economies,"
International Economics, Elsevier, vol. 159(C), pages 74-93.
- Chuku Chuku & Anthony Simpasa & Jacob Oduor, 2019. "Intelligent forecasting of economic growth for developing economies," International Economics, CEPII research center, issue 159, pages 74-93.
- Yoo, Sunbin & Managi, Shunsuke, 2020.
"Global mortality benefits of COVID-19 action,"
Technological Forecasting and Social Change, Elsevier, vol. 160(C).
- Yoo, Sunbin & Managi, Shusuke, 2020. "Global Mortality Benefits of COVID-19 Action," MPRA Paper 102040, University Library of Munich, Germany, revised Jul 2020.
- Marta Bańbura & Domenico Giannone & Lucrezia Reichlin, 2010.
"Large Bayesian vector auto regressions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92, January.
- Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
- Reichlin, Lucrezia & Giannone, Domenico & Banbura, Marta, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
- Marta Bañbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
- Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
- Dominique Guegan & Patrick Rakotomarolahy, 2010.
"Alternative methods for forecasting GDP,"
Documents de travail du Centre d'Economie de la Sorbonne
10065, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00505165, HAL.
- Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00511979, HAL.
- Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00511979, HAL.
- Jahn, Malte, 2020. "Artificial neural network regression models in a panel setting: Predicting economic growth," Economic Modelling, Elsevier, vol. 91(C), pages 148-154.
- Saman, Corina, 2011. "Scenarios of the Romanian GDP Evolution With Neural Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 129-140, December.
- Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69.
- Szafranek, Karol, 2019.
"Bagged neural networks for forecasting Polish (low) inflation,"
International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
- Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
- M. Ali Choudhary & Adnan Haider, 2012.
"Neural network models for inflation forecasting: an appraisal,"
Applied Economics, Taylor & Francis Journals, vol. 44(20), pages 2631-2635, July.
- M. Ali Choudhary & Adnan Haider, 2012. "Neural network models for inflation forecasting: an appraisal," Applied Economics, Taylor & Francis Journals, vol. 44(20), pages 2631-2635, July.
- Ali Choudhary & Adnan Haider, 2008. "Neural Network Models for Inflation Forecasting: An Appraisal," School of Economics Discussion Papers 0808, School of Economics, University of Surrey.
- M. Ali Choudhary, 2011. "Neural Network Models for Inflation Forecasting: An Appraisal," Post-Print hal-00704670, HAL.
- Karlsson, Martin & Nilsson, Therese & Pichler, Stefan, 2014. "The impact of the 1918 Spanish flu epidemic on economic performance in Sweden," Journal of Health Economics, Elsevier, vol. 36(C), pages 1-19.
- McAdam, Peter & McNelis, Paul, 2005.
"Forecasting inflation with thick models and neural networks,"
Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
- McAdam, Peter & McNelis, Paul, 2004. "Forecasting inflation with thick models and neural networks," Working Paper Series 352, European Central Bank.
- Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," PSE-Ecole d'économie de Paris (Postprint) halshs-00511979, HAL.
- Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
- Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00505165, HAL.
- repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
- Surender Kumar & Shunsuke Managi, 2020.
"Does Stringency of Lockdown Affect Air Quality? Evidence from Indian Cities,"
Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 481-502, October.
- Surender Kumar & Shunsuke Managi, 2020. "Does stringency of lockdown affect air quality? Evidence from Indian cities," Working papers 312, Centre for Development Economics, Delhi School of Economics.
- Kock, Anders Bredahl & Teräsvirta, Timo, 2014.
"Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
- Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
- Nakamura, Hiroki & Managi, Shunsuke, 2020. "Airport risk of importation and exportation of the COVID-19 pandemic," Transport Policy, Elsevier, vol. 96(C), pages 40-47.
- Daron Acemoglu & Victor Chernozhukov & Ivàn Werning & Michael D. Whinston, 2020. "A Multi-Risk SIR Model with Optimally Targeted Lockdown," CeMMAP working papers CWP14/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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