IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i6p957-d773206.html
   My bibliography  Save this article

Research on the Graphical Model Structure Characteristic of Strong Exogeneity Based on Twin Network Method and Its Application in Causal Inference

Author

Listed:
  • Rui Luo

    (Key Lab of Interior Layout optimization and Security, Chengdu Normal University, Chengdu 611130, China)

  • Lijia Sun

    (School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Yin Kuang

    (Key Lab of Interior Layout optimization and Security, Chengdu Normal University, Chengdu 611130, China)

  • Ping Deng

    (Key Lab of Information Coding and Transmission, Southwest Jiaotong University, Chengdu 611756, China)

  • Mengna Lu

    (School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China)

Abstract

Strong exogeneity is an important assumption in the study of causal inference, but it is difficult to identify according to its definition. The twin network method provides a graphical model tool for analyzing the variable relationship, involving the actual world and the hypothetical world, which facilitates the investigating of strong exogeneity. In this paper, the graphical model structure characteristic of strong exogeneity is investigated based on the twin network method. Compared with other derivation methods of graphical diagnosis, the method based on the twin network is more concise, clearer, and easier to understand. Under the condition of strong exogeneity, it is easy to estimate the probability of causation based on observational data. As an example, the application of graphical model structure characteristic of strong exogeneity in causal inference in the context of lung cancer simple sets (LUCAS) is illustrated.

Suggested Citation

  • Rui Luo & Lijia Sun & Yin Kuang & Ping Deng & Mengna Lu, 2022. "Research on the Graphical Model Structure Characteristic of Strong Exogeneity Based on Twin Network Method and Its Application in Causal Inference," Mathematics, MDPI, vol. 10(6), pages 1-13, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:6:p:957-:d:773206
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/6/957/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/6/957/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jason J. Sauppe & Sheldon H. Jacobson, 2017. "The role of covariate balance in observational studies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(4), pages 323-344, June.
    2. Dmitry Nazarov, 2020. "Causality: Intelligent Valuation Models in the Digital Economy," Mathematics, MDPI, vol. 8(12), pages 1-16, December.
    3. Roya Ghafele & Benjamin Gibert, 2014. "A Counterfactual Impact Analysis of Fair Use Policy on Copyright Related Industries in Singapore," Laws, MDPI, vol. 3(2), pages 1-26, June.
    4. Chiara Criscuolo & Ralf Martin & Henry G. Overman & John Van Reenen, 2019. "Some Causal Effects of an Industrial Policy," American Economic Review, American Economic Association, vol. 109(1), pages 48-85, January.
    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. Magnus Henrekson & Anders Kärnä & Tino Sanandaji, 2022. "Schumpeterian entrepreneurship: coveted by policymakers but impervious to top-down policymaking," Journal of Evolutionary Economics, Springer, vol. 32(3), pages 867-890, July.
    2. Gibbons, Stephen & Overman, Henry & Sarvimäki, Matti, 2021. "The local economic impacts of regeneration projects: Evidence from UK's single regeneration budget," Journal of Urban Economics, Elsevier, vol. 122(C).
    3. Giovanni Dosi & Andrea Roventini & Emmanuele Russo, 2020. "Public Policies And The Art Of Catching Up," Working Papers hal-03242369, HAL.
    4. Zheng, Guo & Barbieri, Elisa & Di Tommaso, Marco R. & Zhang, Lei, 2016. "Development zones and local economic growth: zooming in on the Chinese case," China Economic Review, Elsevier, vol. 38(C), pages 238-249.
    5. Jingyi Tian & Jun Nagayasu, 2023. "Financial Systemic Risk behind Artificial Intelligence:Evidence from China," TUPD Discussion Papers 44, Graduate School of Economics and Management, Tohoku University.
    6. Freedman, Matthew & Khanna, Shantanu & Neumark, David, 2023. "Combining rules and discretion in economic development policy: Evidence on the impacts of the California Competes Tax Credit," Journal of Public Economics, Elsevier, vol. 217(C).
    7. Giovanni Dosi & Andrea Roventini & Emanuele Russo, 2021. "Public policies and the art of catching up: matching the historical evidence with a multicountry agent-based model [Catching up, forging ahead, and falling behind]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(4), pages 1011-1036.
    8. Bart Cockx & Sam Desiere, 2023. "Labour costs and the decision to hire the first employee," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1071, Ghent University, Faculty of Economics and Business Administration.
    9. Stjepan Srhoj & Bruno Škrinjarić & Sonja Radas & Janette Walde, 2022. "Small matching grants for women entrepreneurs: lessons from the past recession," Small Business Economics, Springer, vol. 59(1), pages 117-142, June.
    10. Srhoj, Stjepan & Walde, Janette, 2020. "Getting ready for EU Single Market: The effect of export-oriented grant schemes on firm performance," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 279-293.
    11. Simone Chinetti, 2023. "Investment Subsidies Effectiveness: Evidence from a Regional Program," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(2), pages 723-759, July.
    12. Klaus Gründler & Philipp Heil & Niklas Potrafke & Timo Wochner, 2023. "The US-Inflation Reduction Act: Global Assessments of Economic Experts," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 138.
    13. Zewdie Habte Shikur, 2020. "Industrial policy measure and economic structure in Ethiopia: the case of Oromia region," International Journal of Economic Policy Studies, Springer, vol. 14(1), pages 255-274, February.
    14. Andrea Ascani & Simona Iammarino, 2018. "Multinational enterprises, service outsourcing and regional structural change," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 42(6), pages 1585-1611.
    15. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    16. Marco Di Cataldo, 2016. "Gaining and losing EU Objective 1 funds: Regional development in Britain and the prospect of Brexit," LEQS – LSE 'Europe in Question' Discussion Paper Series 120, European Institute, LSE.
    17. Segundo Camino‐Mogro, 2023. "Tax incentives, private investment and employment: Evidence from an Ecuadorian reform," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(7), pages 2129-2156, October.
    18. Jindamas Sutthichaimethee & Kuskana Kubaha, 2018. "The Relationship of Causal Factors Affecting the Future Equilibrium Change of Total Final Energy Consumption in Thailand’s Construction Sector under a Sustainable Development Goal: Enriching the SE-VA," Resources, MDPI, vol. 8(1), pages 1-18, December.
    19. Stjepan Srhoj & Michael Lapinski & Janette Walde, 2019. "Size matters? Impact evaluation of business development grants on SME performance," Working Papers 2019-14, Faculty of Economics and Statistics, Universität Innsbruck.
    20. Gonzalo Nunez-Chaim & Henry G. Overman & Capucine Riom, 2024. "Does subsidising business advice improve firm performance? Evidence from a large RCT," CEP Discussion Papers dp1977, Centre for Economic Performance, LSE.

    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:gam:jmathe:v:10:y:2022:i:6:p:957-:d:773206. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.