IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp15290.html
   My bibliography  Save this paper

Optimal Travel Restrictions in Epidemics

Author

Listed:
  • Shi, Wei

    (Jinan University)

  • Qiu, Yun

    (Jinan University)

  • Yu, Pei

    (Rice University)

  • Chen, Xi

    (Yale University)

Abstract

Travel restrictions are often imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, this paper examines the optimal design of restrictions that target specific travel routes. We propose a model with trade-offs between costs of infections and costs of travel restrictions, where decisions are made with or without coordination between local jurisdictions and provide a computational feasible way to solve the optimization problem. We illustrate the model using the COVID-19 data in China. When travel restrictions target key routes, only around 5% of the possible routes need to be closed in order to have the same number of confirmed COVID-19 cases in the initial outbreaks. Uncoordinated travel restrictions ignore policy externalities and therefore are sub-optimal in comparison to coordinated restrictions.

Suggested Citation

  • Shi, Wei & Qiu, Yun & Yu, Pei & Chen, Xi, 2022. "Optimal Travel Restrictions in Epidemics," IZA Discussion Papers 15290, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp15290
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp15290.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lawrence E. Blume & William A. Brock & Steven N. Durlauf & Rajshri Jayaraman, 2015. "Linear Social Interactions Models," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 444-496.
    2. Coralio Ballester & Antoni Calvó-Armengol & Yves Zenou, 2006. "Who's Who in Networks. Wanted: The Key Player," Econometrica, Econometric Society, vol. 74(5), pages 1403-1417, September.
    3. Pablo D. Fajgelbaum & Amit Khandelwal & Wookun Kim & Cristiano Mantovani & Edouard Schaal, 2021. "Optimal Lockdown in a Commuting Network," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 503-522, December.
    4. Cohen-Cole, Ethan & Fletcher, Jason M., 2008. "Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic," Journal of Health Economics, Elsevier, vol. 27(5), pages 1382-1387, September.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    6. Liu, Xiaodong & Lee, Lung-fei, 2010. "GMM estimation of social interaction models with centrality," Journal of Econometrics, Elsevier, vol. 159(1), pages 99-115, November.
    7. Fernando E. Alvarez & David Argente & Francesco Lippi, 2020. "A Simple Planning Problem for COVID-19 Lockdown," NBER Working Papers 26981, National Bureau of Economic Research, Inc.
    8. Fang, Hanming & Wang, Long & Yang, Yang, 2020. "Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China," Journal of Public Economics, Elsevier, vol. 191(C).
    9. Wong, Grace, 2008. "Has SARS infected the property market Evidence from Hong Kong," Journal of Urban Economics, Elsevier, vol. 63(1), pages 74-95, January.
    10. David Holtz & Michael Zhao & Seth G. Benzell & Cathy Y. Cao & Mohammad Amin Rahimian & Jeremy Yang & Jennifer Allen & Avinash Collis & Alex Moehring & Tara Sowrirajan & Dipayan Ghosh & Yunhao Zhang & , 2020. "Interdependence and the cost of uncoordinated responses to COVID-19," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(33), pages 19837-19843, August.
    11. 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.
    12. Yun Qiu & Xi Chen & Wei Shi, 2020. "Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1127-1172, October.
    13. Saidi, Farzad & Alfaro, Laura & Faia, Ester & Lamersdorf, Nora, 2020. "Social Interactions in Pandemics: Fear, Altruism, and Reciprocity," CEPR Discussion Papers 14716, C.E.P.R. Discussion Papers.
    14. Lee, Lung-fei, 2007. "Identification and estimation of econometric models with group interactions, contextual factors and fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 333-374, October.
    15. Jeong, Hanbat & Lee, Lung-fei, 2020. "Spatial dynamic models with intertemporal optimization: Specification and estimation," Journal of Econometrics, Elsevier, vol. 218(1), pages 82-104.
    16. Jayson S. Jia & Xin Lu & Yun Yuan & Ge Xu & Jianmin Jia & Nicholas A. Christakis, 2020. "Population flow drives spatio-temporal distribution of COVID-19 in China," Nature, Nature, vol. 582(7812), pages 389-394, June.
    17. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Chen, Xi & Qiu, Yun & Shi, Wei & Yu, Pei, 2022. "Key links in network interactions: Assessing route-specific travel restrictions in China during the Covid-19 pandemic," China Economic Review, Elsevier, vol. 73(C).
    2. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute of Labor Economics (IZA).
    3. David E. Bloom & Michael Kuhn & Klaus Prettner, 2022. "Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses," Journal of Economic Literature, American Economic Association, vol. 60(1), pages 85-131, March.
    4. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    5. Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org, revised Jul 2019.
    6. Monte, Ferdinando, 2020. "Mobility Zones," Economics Letters, Elsevier, vol. 194(C).
    7. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    8. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    9. Bisin, Alberto & Moro, Andrea, 2022. "JUE insight: Learning epidemiology by doing: The empirical implications of a Spatial-SIR model with behavioral responses," Journal of Urban Economics, Elsevier, vol. 127(C).
    10. Rokhaya Dieye & Bernard Fortin, 2017. "Gender Peer Effects Heterogeneity in Obesity," Cahiers de recherche 1702, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    11. Chih-Sheng Hsieh & Michael D. Konig & Xiaodong Liu, 2022. "A Structural Model for the Coevolution of Networks and Behavior," The Review of Economics and Statistics, MIT Press, vol. 104(2), pages 355-367, May.
    12. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    13. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    14. Zenou, Yves & Lindquist, Matthew & Sauermann, Jan, 2015. "Network Effects on Worker Productivity," CEPR Discussion Papers 10928, C.E.P.R. Discussion Papers.
    15. Rainone, Edoardo, 2020. "The network nature of over-the-counter interest rates," Journal of Financial Markets, Elsevier, vol. 47(C).
    16. Patacchini, Eleonora & Rainone, Edoardo & Zenou, Yves, 2011. "Dynamic Aspects of Teenage Friendships and Educational Attainment," Research Papers in Economics 2011:4, Stockholm University, Department of Economics.
    17. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    18. Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    19. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Zenou, Yves & Patacchini, Eleonora & Rainone, Edoardo, 2012. "Student Networks and Long-Run Educational Outcomes: The Strength of Strong Ties," CEPR Discussion Papers 9149, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    transmission; public health; economic cost; coordination; externality; COVID-19;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:iza:izadps:dp15290. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.