Measuring resilience and fatality rate during the first wave of COVID-19 pandemic in Northern Italy: a note
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Connelly, Luke B. & Birch, Stephen, 2022. "Answers in search of questions: what does the comparison of COVID19 data among regions in Northern Italy tell us?," Health Economics, Policy and Law, Cambridge University Press, vol. 17(2), pages 224-226, April.
- Durante, Ruben & Guiso, Luigi & Gulino, Giorgio, 2021.
"Asocial capital: Civic culture and social distancing during COVID-19,"
Journal of Public Economics, Elsevier, vol. 194(C).
- Ruben Durante & Luigi Guiso & Giorgio Gulino, 2020. "Asocial capital: Civic culture and social distancing during COVID-19," Economics Working Papers 1723, Department of Economics and Business, Universitat Pompeu Fabra.
- Ruben Durante & Luigi Guiso & Giorgio Gulino, 2020. "Asocial Capital: Civic Culture and Social Distancing during COVID-19," Working Papers 1181, Barcelona School of Economics.
- Durante, Ruben & Guiso, Luigi & Gulino, Giorgio, 2020. "Asocial Capital: Civic Culture and Social Distancing during COVID-19," CEPR Discussion Papers 14820, C.E.P.R. Discussion Papers.
- Ruben Durante & Luigi Guiso & Giorgio Gulino, 2020. "Asocial Capital: Civic Culture and Social Distancing during COVID-19," EIEF Working Papers Series 2012, Einaudi Institute for Economics and Finance (EIEF), revised May 2020.
- Nicola Borri & Francesco Drago & Chiara Santantonio & Francesco Sobbrio, 2021.
"The “Great Lockdown”: Inactive workers and mortality by Covid‐19,"
Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2367-2382, September.
- Nicola Borri & Francesco Drago & Chiara Santantonio & Francesco Sobbrio, 2020. "The "Great Lockdown": Inactive Workers and Mortality by Covid-19," CESifo Working Paper Series 8584, CESifo.
- Drago, Francesco & Borri, Nicola & Santantonio, Chiara & Sobbrio, Francesco, 2020. "The 'Great Lockdown': Inactive Workers and Mortality by Covid-19," CEPR Discussion Papers 15317, C.E.P.R. Discussion Papers.
- Manski, Charles F. & Molinari, Francesca, 2021.
"Estimating the COVID-19 infection rate: Anatomy of an inference problem,"
Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
- Charles F. Manski & Francesca Molinari, 2020. "Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem," NBER Working Papers 27023, National Bureau of Economic Research, Inc.
- Charles F. Manski & Francesca Molinari, 2020. "Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem," CeMMAP working papers CWP20/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Charles F. Manski & Francesca Molinari, 2020. "Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem," Papers 2004.06178, arXiv.org.
- Domenico Depalo, 2021.
"True COVID-19 mortality rates from administrative data,"
Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 253-274, January.
- Depalo, Domenico, 2020. "True Covid-19 mortality rates from administrative data," GLO Discussion Paper Series 630, Global Labor Organization (GLO).
- Hortaçsu, Ali & Liu, Jiarui & Schwieg, Timothy, 2021.
"Estimating the fraction of unreported infections in epidemics with a known epicenter: An application to COVID-19,"
Journal of Econometrics, Elsevier, vol. 220(1), pages 106-129.
- Ali Hortaçsu & Jiarui Liu & Timothy Schwieg, 2020. "Estimating the Fraction of Unreported Infections in Epidemics with a Known Epicenter: an Application to COVID-19," NBER Working Papers 27028, National Bureau of Economic Research, Inc.
- Ali Hortacsu & Jiarui Liu & Timothy Schwieg, 2020. "Estimating the Fraction of Unreported Infections in Epidemics with a Known Epicenter: an Application to COVID-19," CeMMAP working papers CWP21/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Daniel L. Millimet & Christopher F. Parmeter, 2022.
"COVID‐19 severity: A new approach to quantifying global cases and deaths,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
- Millimet, Daniel L. & Parmeter, Christopher F., 2021. "COVID-19 Severity: A New Approach to Quantifying Global Cases and Deaths," IZA Discussion Papers 14116, Institute of Labor Economics (IZA).
- Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.
- Ichino, Andrea & Favero, Carlo A. & Rustichini, Aldo, 2020. "Restarting the economy while saving lives under Covid-19," CEPR Discussion Papers 14664, C.E.P.R. Discussion Papers.
- Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
- Garriga, Carlos & Manuelli, Rody & Sanghi, Siddhartha, 2022.
"Optimal management of an epidemic: Lockdown, vaccine and value of life,"
Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
- Carlos Garriga & Rody Manuelli & Siddhartha Sanghi, 2020. "Optimal Management of an Epidemic: Lockdown, Vaccine and Value of Life," Working Papers 2020-031, Human Capital and Economic Opportunity Working Group.
- Carlos Garriga & Rodolfo E. Manuelli & Siddhartha Sanghi, 2022. "Optimal Management of an Epidemic: Lockdown, Vaccine and Value of Life," Working Papers 2020-046, Federal Reserve Bank of St. Louis.
- Gourieroux, C. & Jasiak, J., 2023.
"Time varying Markov process with partially observed aggregate data: An application to coronavirus,"
Journal of Econometrics, Elsevier, vol. 232(1), pages 35-51.
- Christian GOURIEROUX & Joann JASIAK, 2020. "Time Varying Markov Process with Partially Observed Aggregate Data; An Application to Coronavirus," Working Papers 2020-11, Center for Research in Economics and Statistics, revised 08 May 2020.
- Fischer, Kai & Reade, J. James & Schmal, W. Benedikt, 2022. "What cannot be cured must be endured: The long-lasting effect of a COVID-19 infection on workplace productivity," Labour Economics, Elsevier, vol. 79(C).
- Cem Cakmakli & Yasin Simsek, 2020.
"Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model,"
Papers
2007.02726, arXiv.org, revised Feb 2021.
- Cem Cakmakli & Yasin Simsek, 2021. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Koç University-TUSIAD Economic Research Forum Working Papers 2013, Koc University-TUSIAD Economic Research Forum.
- Cem Cakmaklı & Yasin Simsek, 2020. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Working Paper series 20-23, Rimini Centre for Economic Analysis, revised Feb 2021.
- Kent A. Smetters, 2020. "Stay-at-home orders and second waves: a graphical exposition," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 94-103, September.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021.
"Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs,"
CESifo Working Paper Series
8977, CESifo.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 2021-09, FEDEA.
- Fernández-Villaverde, Jesús & Arias, Jonas & Rubio-RamÃrez, Juan Francisco & Shin, Minchul, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CEPR Discussion Papers 15951, C.E.P.R. Discussion Papers.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan Rubio Ramírez & Minchul Shin, 2021. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," NBER Working Papers 28617, National Bureau of Economic Research, Inc.
- Robert S. Pindyck, 2020. "COVID-19 and the Welfare Effects of Reducing Contagion," NBER Working Papers 27121, National Bureau of Economic Research, Inc.
- Facundo Piguillem & Liyan Shi, 2022.
"Optimal Covid-19 Quarantine and Testing Policies,"
The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.
- Piguillem, Facundo & Shi, Liyan, 2020. "Optimal COVID-19 Quarantine and Testing Policies," CEPR Discussion Papers 14613, C.E.P.R. Discussion Papers.
- Facundo Piguillem & Liyan Shi, 2020. "Optimal COVID-19 Quarantine and Testing Policies," EIEF Working Papers Series 2004, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2020.
- Toulis, Panos, 2021. "Estimation of Covid-19 prevalence from serology tests: A partial identification approach," Journal of Econometrics, Elsevier, vol. 220(1), pages 193-213.
- Panos Toulis, 2020. "Estimation of COVID-19 Prevalence from Serology Tests: A Partial Identification Approach," Working Papers 2020-54_Revised, Becker Friedman Institute for Research In Economics.
- Jose Olmo & Marcos Sanso‐Navarro, 2021. "Modeling the spread of COVID‐19 in New York City," Papers in Regional Science, Wiley Blackwell, vol. 100(5), pages 1209-1229, October.
- Panos Toulis, 2020. "Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach," Papers 2006.16214, arXiv.org.
- Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
- 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.
More about this item
Keywords
Resilience; Missing data; Epidemiology; Novel coronavirus; Italy; Healthcare governance;All these keywords.
JEL classification:
- I10 - Health, Education, and Welfare - - Health - - - General
- I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:esprep:231374. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.