IDEAS home Printed from https://ideas.repec.org/a/eee/chieco/v73y2022ics1043951x2200058x.html
   My bibliography  Save this article

Key links in network interactions: Assessing route-specific travel restrictions in China during the Covid-19 pandemic

Author

Listed:
  • Chen, Xi
  • Qiu, Yun
  • Shi, Wei
  • Yu, Pei

Abstract

We consider a model of network interactions where the outcome of a unit depends on the outcomes of the connected units. We determine the key network link, i.e., the network link whose removal results in the largest reduction in the aggregate outcomes, and examine a measure that quantifies the contribution of a network link to the aggregate outcomes. We provide an example examining the spread of Covid-19 in China. Travel restrictions were imposed to limit the spread of infectious diseases. As uniform restrictions can be inefficient and incur unnecessarily high costs, we examine the design of restrictions that target specific travel routes. Our approach may be generalized to multiple countries to guide policies during epidemics ranging from ex ante route-specific travel restrictions to ex post health measures based on travel histories, and from the initial travel restrictions to the phased reopening.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chieco:v:73:y:2022:i:c:s1043951x2200058x
    DOI: 10.1016/j.chieco.2022.101800
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1043951X2200058X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chieco.2022.101800?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
    4. 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.
    5. Angelo Mele, 2017. "A Structural Model of Dense Network Formation," Econometrica, Econometric Society, vol. 85, pages 825-850, May.
    6. 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.
    7. Jeffrey Brinkman & Kyle Mangum, 2020. "The Geography of Travel Behavior in the Early Phase of the COVID-19 Pandemic," Working Papers 20-38, Federal Reserve Bank of Philadelphia.
    8. Fernando Alvarez & David Argente, 2020. "A Simple Planning Problem for COVID-19 Lockdown," Working Papers 2020-34, Becker Friedman Institute for Research In Economics.
    9. 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.
    10. Peter T. Leeson & Louis Rouanet, 2021. "Externality and COVID‐19," Southern Economic Journal, John Wiley & Sons, vol. 87(4), pages 1107-1118, April.
    11. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    12. Duan, Hongbo & Bao, Qin & Tian, Kailan & Wang, Shouyang & Yang, Cuihong & Cai, Zongwu, 2021. "The hit of the novel coronavirus outbreak to China's economy," China Economic Review, Elsevier, vol. 67(C).
    13. 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.
    14. Lung-Fei Lee & Xiaodong Liu & Eleonora Patacchini & Yves Zenou, 2021. "Who is the Key Player? A Network Analysis of Juvenile Delinquency," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 849-857, July.
    15. 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).
    16. 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.
    17. Coralio Ballester & Antoni Calvó-Armengol & Yves Zenou, 2010. "Delinquent Networks," Journal of the European Economic Association, MIT Press, vol. 8(1), pages 34-61, March.
    18. Deng, Liuchun & Sun, Yufeng, 2017. "Criminal network formation and optimal detection policy: The role of cascade of detection," Journal of Economic Behavior & Organization, Elsevier, vol. 141(C), pages 43-63.
    19. Dai, Ruochen & Feng, Hao & Hu, Junpeng & Jin, Quan & Li, Huiwen & Wang, Ranran & Wang, Ruixin & Xu, Lihe & Zhang, Xiaobo, 2021. "The impact of COVID-19 on small and medium-sized enterprises (SMEs): Evidence from two-wave phone surveys in China," China Economic Review, Elsevier, vol. 67(C).
    20. Margherita Comola & Silvia Prina, 2021. "Treatment Effect Accounting for Network Changes," The Review of Economics and Statistics, MIT Press, vol. 103(3), pages 597-604, July.
    21. Charles F. Manski, 2004. "Statistical Treatment Rules for Heterogeneous Populations," Econometrica, Econometric Society, vol. 72(4), pages 1221-1246, July.
    22. Clark, Andrew E. & Nong, Huifu & Zhu, Hongjia & Zhu, Rong, 2021. "Compensating for academic loss: Online learning and student performance during the COVID-19 pandemic," China Economic Review, Elsevier, vol. 68(C).
    23. Meng, Dawen & Sun, Lei & Tian, Guoqiang, 2022. "Dynamic mechanism design on social networks," Games and Economic Behavior, Elsevier, vol. 131(C), pages 84-120.
    24. 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.
    25. 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.
    26. Fowler, J.H. & Christakis, N.A., 2008. "Estimating peer effects on health in social networks: A response to Cohen-Cole and Fletcher; and Trogdon, Nonnemaker, and Pais," Journal of Health Economics, Elsevier, vol. 27(5), pages 1400-1405, September.
    27. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    28. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    29. Patacchini, Eleonora & Rainone, Edoardo & Zenou, Yves, 2017. "Heterogeneous peer effects in education," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 190-227.
    30. 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.
    31. 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.
    32. Yang Sun & Wei Zhao & Junjie Zhou, 2021. "Structural Interventions in Networks," Papers 2101.12420, arXiv.org, revised Feb 2021.
    33. 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.
    34. Brinkman, Jeffrey & Mangum, Kyle, 2022. "JUE Insight: The Geography of Travel Behavior in the Early Phase of the COVID-19 Pandemic," Journal of Urban Economics, Elsevier, vol. 127(C).
    35. 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. Shi, Wei & Qiu, Yun & Yu, Pei & Chen, Xi, 2022. "Optimal Travel Restrictions in Epidemics," IZA Discussion Papers 15290, Institute of Labor Economics (IZA).
    2. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    3. 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.
    4. Zenou, Yves & Lindquist, Matthew & Sauermann, Jan, 2015. "Network Effects on Worker Productivity," CEPR Discussion Papers 10928, C.E.P.R. Discussion Papers.
    5. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute of Labor Economics (IZA).
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    11. 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.
    12. Ushchev, Philip & Zenou, Yves, 2020. "Social norms in networks," Journal of Economic Theory, Elsevier, vol. 185(C).
    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. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.
    15. Chih‐Sheng Hsieh & Xu Lin, 2021. "Social interactions and social preferences in social networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 165-189, March.
    16. 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.
    17. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    18. 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.
    19. Cui Zhang & Dandan Zhang, 2023. "Spatial Interactions and the Spread of COVID-19: A Network Perspective," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 383-405, June.
    20. Horrace, William & Jung, Hyunseok & Presler, Jonathan & Schwartz, Amy Ellen, 2021. "What Makes a Classmate a Peer? Examining which peers matter in NYC elementary schools," Working Papers 21-4, Sinquefield Center for Applied Economic Research, Saint Louis University, revised 17 Jan 2022.

    More about this item

    Keywords

    Network interactions; Key network links; Covid-19; Transmission;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare

    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:eee:chieco:v:73:y:2022:i:c:s1043951x2200058x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/chieco .

    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.