IDEAS home Printed from https://ideas.repec.org/p/ems/eureri/100.html
   My bibliography  Save this paper

An Equilibrium-Correction Model for Dynamic Network Data

Author

Listed:
  • Dekker, D.J.
  • Franses, Ph.H.B.F.
  • Krackhardt, D.

Abstract

We propose a two-stage MRQAP to analyze dynamic network data, within the framework of an equilibrium-correction (EC) model. Extensive simulation results indicate practical relevance of our method and its improvement over standard OLS. An empirical illustration additionally shows that the EC model yields interpretable parameters, in contrast to an unrestricted dynamic model.

Suggested Citation

  • Dekker, D.J. & Franses, Ph.H.B.F. & Krackhardt, D., 2001. "An Equilibrium-Correction Model for Dynamic Network Data," ERIM Report Series Research in Management ERS-2001-39-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:100
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/100/erimrs20010620164657.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gerhard G. Van De Bunt & Marijtje A.J. Van Duijn & Tom A.B. Snijders, 1999. "Friendship Networks Through Time: An Actor-Oriented Dynamic Statistical Network Model," Computational and Mathematical Organization Theory, Springer, vol. 5(2), pages 167-192, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Buechel, Berno & Buskens, Vincent, 2011. "The dynamics of closeness and betweenness," Center for Mathematical Economics Working Papers 398, Center for Mathematical Economics, Bielefeld University.
    2. Aalbers, Rick & Dolfsma, Wilfred & Koppius, Otto, 2013. "Individual connectedness in innovation networks: On the role of individual motivation," Research Policy, Elsevier, vol. 42(3), pages 624-634.
    3. Dekker, D.J. & Krackhardt, D. & Franses, Ph.H.B.F., 2002. "Dynamic Effects of Trust and Cognitive Social Structures on Information Transfer Relationships," ERIM Report Series Research in Management ERS-2002-33-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    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. Joshua Lospinoso & Michael Schweinberger & Tom Snijders & Ruth Ripley, 2011. "Assessing and accounting for time heterogeneity in stochastic actor oriented models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(2), pages 147-176, July.
    2. Mark Huisman & Tom A. B. Snijders, 2003. "Statistical Analysis of Longitudinal Network Data With Changing Composition," Sociological Methods & Research, , vol. 32(2), pages 253-287, November.
    3. Maurits C. de Klepper & Giuseppe (Joe) Labianca & Ed Sleebos & Filip Agneessens, 2017. "Sociometric Status and Peer Control Attempts: A Multiple Status Hierarchies Approach," Journal of Management Studies, Wiley Blackwell, vol. 54(1), pages 1-31, January.
    4. Prasanta Bhattacharya & Tuan Q. Phan & Xue Bai & Edoardo M. Airoldi, 2019. "A Coevolution Model of Network Structure and User Behavior: The Case of Content Generation in Online Social Networks," Service Science, INFORMS, vol. 30(1), pages 117-132, March.
    5. Karen Haandrikman & Leo J. G. Wissen, 2012. "Explaining the Flight of Cupid’s Arrow: A Spatial Random Utility Model of Partner Choice," European Journal of Population, Springer;European Association for Population Studies, vol. 28(4), pages 417-439, November.
    6. Siegwart Lindenberg, 2000. "It Takes Both Trust and Lack of Mistrust: The Workings of Cooperation and Relational Signaling in Contractual Relationships," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 4(1), pages 11-33, March.
    7. Hideki Fujiyama, 2020. "Network centrality, social loops, and utility maximization," Evolutionary and Institutional Economics Review, Springer, vol. 17(1), pages 39-70, January.
    8. Buchmann, Tobias & Hain, Daniel & Kudic, Muhamed & Müller, Matthias, 2014. "Exploring the Evolution of Innovation Networks in Science-driven and Scale-intensive Industries: New Evidence from a Stochastic Actor-based Approach," IWH Discussion Papers 1/2014, Halle Institute for Economic Research (IWH).
    9. Sofia Dokuka & Diliara Valeeva, 2015. "Statistical Models for Analysis of Social Network Dynamics in Educational Studies," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 201-213.
    10. Mercken, Liesbeth & Snijders, Tom A.B. & Steglich, Christian & de Vries, Hein, 2009. "Dynamics of adolescent friendship networks and smoking behavior: Social network analyses in six European countries," Social Science & Medicine, Elsevier, vol. 69(10), pages 1506-1514, November.
    11. Pink, Sebastian & Kretschmer, David & Leszczensky, Lars, 2020. "Choice modelling in social networks using stochastic actor-oriented models," Journal of choice modelling, Elsevier, vol. 34(C).
    12. Neil Hwang & Jiarui Xu & Shirshendu Chatterjee & Sharmodeep Bhattacharyya, 2022. "The Bethe Hessian and Information Theoretic Approaches for Online Change-Point Detection in Network Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 283-320, June.
    13. Mary-Anne Holfve-Sabel, 2015. "Students’ Individual Choices of Peers to Work with During Lessons May Counteract Segregation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 577-594, June.
    14. Long, Emily & Gardani, Maria & McCann, Mark & Sweeting, Helen & Tranmer, Mark & Moore, Laurence, 2020. "Mental health disorders and adolescent peer relationships," Social Science & Medicine, Elsevier, vol. 253(C).
    15. Shahadat Uddin & Arif Khan & Liaquat Hossain & Mahendra Piraveenan & Sven Carlsson, 2015. "A topological framework to explore longitudinal social networks," Computational and Mathematical Organization Theory, Springer, vol. 21(1), pages 48-68, March.
    16. Schweinberger, Michael & Snijders, Tom A.B., 2007. "Markov models for digraph panel data: Monte Carlo-based derivative estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4465-4483, May.
    17. Devari, Aashwinikumar & Nikolaev, Alexander G. & He, Qing, 2017. "Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 105-122.

    More about this item

    Keywords

    cognitive social structures; consistent accuracy; network centrality; structural autocorrelation; two-stage equilibrium model;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:ems:eureri:100. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/erimanl.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.