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When will the Covid-19 pandemic peak?

Citations

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Cited by:

  1. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
  2. Andrew Atkeson & Karen Kopecky & Tao Zha, 2020. "Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model," NBER Working Papers 27335, National Bureau of Economic Research, Inc.
  3. Medeiros, Marcelo C. & Street, Alexandre & Valladão, Davi & Vasconcelos, Gabriel & Zilberman, Eduardo, 2022. "Short-term Covid-19 forecast for latecomers," International Journal of Forecasting, Elsevier, vol. 38(2), pages 467-488.
  4. Bårdsen, Gunnar & Nymoen, Ragnar, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Memorandum 3/2023, Oslo University, Department of Economics.
  5. Shaw, Norman & Eschenbrenner, Brenda & Baier, Daniel, 2022. "Online shopping continuance after COVID-19: A comparison of Canada, Germany and the United States," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
  6. Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.
  7. Ricardo Martínez & Juan D Moreno Ternero, 2021. "Pandemic performance," ThE Papers 21/09, Department of Economic Theory and Economic History of the University of Granada..
  8. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
  9. Martínez, Ricardo & Moreno-Ternero, Juan D., 2022. "An axiomatic approach towards pandemic performance indicators," Economic Modelling, Elsevier, vol. 116(C).
  10. Andrew Atkeson, 2020. "On Using SIR Models to Model Disease Scenarios for COVID-19," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 41(01), pages 1-35, June.
  11. Rebucci, Alessandro & Chudik, Alexander & Pesaran, M. Hashem, 2020. "Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries," CEPR Discussion Papers 14646, C.E.P.R. Discussion Papers.
  12. Lee, Sokbae & Liao, Yuan & Seo, Myung Hwan & Shin, Youngki, 2021. "Sparse HP filter: Finding kinks in the COVID-19 contact rate," Journal of Econometrics, Elsevier, vol. 220(1), pages 158-180.
  13. Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2021. "Local mortality estimates during the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1189-1217, October.
  14. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
  15. Monika Małgorzata Wojcieszak-Zbierska & Anna Jęczmyk & Jan Zawadka & Jarosław Uglis, 2020. "Agritourism in the Era of the Coronavirus (COVID-19): A Rapid Assessment from Poland," Agriculture, MDPI, vol. 10(9), pages 1-19, September.
  16. Julliard, Christian & Shi, Ran & Yuan, Kathy, 2023. "The spread of COVID-19 in London: Network effects and optimal lockdowns," Journal of Econometrics, Elsevier, vol. 235(2), pages 2125-2154.
  17. David Meintrup & Martina Nowak-Machen & Stefan Borgmann, 2021. "Nine Months of COVID-19 Pandemic in Europe: A Comparative Time Series Analysis of Cases and Fatalities in 35 Countries," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
  18. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
  19. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
  20. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
  21. Ba Chu & Shafiullah Qureshi, 2020. "Predicting the COVID-19 pandemic in Canada and the US," Economics Bulletin, AccessEcon, vol. 40(3), pages 2565-2585.
  22. Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
  23. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  24. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2023. "How to go viral: A COVID-19 model with endogenously time-varying parameters," Journal of Econometrics, Elsevier, vol. 232(1), pages 70-86.
  25. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear modal regression for dependent data with application for predicting COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1424-1453, July.
  26. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2024. "Estimating the Impact of Social Distance Policy in Mitigating COVID-19 Spread with Factor-Based Imputation Approach," Papers 2405.12180, arXiv.org.
  27. Gunnar BÃ¥rdsen & Ragnar Nymoen, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Working Paper Series 19623, Department of Economics, Norwegian University of Science and Technology.
  28. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
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