IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v84y2019i4d10.1007_s11336-019-09676-3.html
   My bibliography  Save this article

Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models

Author

Listed:
  • Viviana Amati

    (ETH Zurich)

  • Felix Schönenberger

    (ETH Zurich)

  • Tom A. B. Snijders

    (University of Groningen
    University of Oxford
    University of Oxford)

Abstract

Stochastic actor-oriented models (SAOMs) can be used to analyse dynamic network data, collected by observing a network and a behaviour in a panel design. The parameters of SAOMs are usually estimated by the method of moments (MoM) implemented by a stochastic approximation algorithm, where statistics defining the moment conditions correspond in a natural way to the parameters. Here, we propose to apply the generalized method of moments (GMoM), using more statistics than parameters. We concentrate on statistics depending jointly on the network and the behaviour, because of the importance of their interdependence, and propose to add contemporaneous statistics to the usual cross-lagged statistics. We describe the stochastic algorithm developed to approximate the GMoM solution. A small simulation study supports the greater statistical efficiency of the GMoM estimator compared to the MoM.

Suggested Citation

  • Viviana Amati & Felix Schönenberger & Tom A. B. Snijders, 2019. "Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1068-1096, December.
    • Handle: RePEc:spr:psycho:v:84:y:2019:i:4:d:10.1007_s11336-019-09676-3
    DOI: 10.1007/s11336-019-09676-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11336-019-09676-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11336-019-09676-3?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 search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    4. Whitney K. Newey & Frank Windmeijer, 2009. "Generalized Method of Moments With Many Weak Moment Conditions," Econometrica, Econometric Society, vol. 77(3), pages 687-719, May.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. Breusch, Trevor & Qian, Hailong & Schmidt, Peter & Wyhowski, Donald, 1999. "Redundancy of moment conditions," Journal of Econometrics, Elsevier, vol. 91(1), pages 89-111, July.
    7. Mathis Schulte & N. Andrew Cohen & Katherine J. Klein, 2012. "The Coevolution of Network Ties and Perceptions of Team Psychological Safety," Organization Science, INFORMS, vol. 23(2), pages 564-581, April.
    8. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1997. "Estimation of stochastic volatility models with diagnostics," Journal of Econometrics, Elsevier, vol. 81(1), pages 159-192, November.
    9. Snijders, Tom A.B. & Lomi, Alessandro, 2019. "Beyond homophily: Incorporating actor variables in statistical network models," Network Science, Cambridge University Press, vol. 7(1), pages 1-19, March.
    10. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-1286, September.
    11. Kenneth Bollen & Stanislav Kolenikov & Shawn Bauldry, 2014. "Model-Implied Instrumental Variable—Generalized Method of Moments (MIIV-GMM) Estimators for Latent Variable Models," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 20-50, January.
    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. Colin Gallagher & Dean Lusher & Johan Koskinen & Bopha Roden & Peng Wang & Aaron Gosling & Anastasios Polyzos & Martina Stenzel & Sarah Hegarty & Thomas Spurling & Gregory Simpson, 2023. "Network patterns of university-industry collaboration: A case study of the chemical sciences in Australia," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4559-4588, August.
    2. Hu, Zhibin & Wu, Guangdong & Han, Yilong & Niu, Yanliang, 2023. "Unraveling the dynamic changes of high-speed rail network with urban development: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    3. Tom A.B. Snijders & Malick Faye & Julien Brailly, 2020. "Network dynamics with a nested node set: Sociability in seven villages in Senegal," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 300-323, August.

    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. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    2. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    3. Stanislav Anatolyev, 2007. "Optimal Instruments In Time Series: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 143-173, February.
    4. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    5. Alastair R. Hall & Fernanda P. M. Peixe, 2003. "A Consistent Method for the Selection of Relevant Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 269-287, January.
    6. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 799-906, Elsevier.
    7. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    8. Mardi Dungey & Vitali Alexeev & Jing Tian & Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91, pages 1-24, June.
    9. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    10. Bansal, Ravi & Kiku, Dana & Yaron, Amir, 2016. "Risks for the long run: Estimation with time aggregation," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 52-69.
    11. Smoluk, H. J. & Neveu, Raymond P., 2002. "Consumption and asset prices: An analysis across income groups," Review of Financial Economics, Elsevier, vol. 11(1), pages 47-62.
    12. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
    13. Hansen, Lars Peter & Heaton, John & Luttmer, Erzo G J, 1995. "Econometric Evaluation of Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 237-274.
    14. Botzen, W.J. Wouter & Marey, Philip S., 2010. "Did the ECB respond to the stock market before the crisis?," Journal of Policy Modeling, Elsevier, vol. 32(3), pages 303-322, May.
    15. Kris Jacobs, 2001. "Estimating Nonseparable Preference Specifications for Asset Market Participants," CIRANO Working Papers 2001s-12, CIRANO.
    16. Mittelhammer, Ron C. & Judge, George, 2011. "A family of empirical likelihood functions and estimators for the binary response model," Journal of Econometrics, Elsevier, vol. 164(2), pages 207-217, October.
    17. Matthijs Lof, 2014. "GMM Estimation with Non-causal Instruments under Rational Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 279-286, April.
    18. Flood, Robert P & Hodrick, Robert J, 1986. "Asset Price Volatility, Bubbles, and Process Switching," Journal of Finance, American Finance Association, vol. 41(4), pages 831-842, September.
    19. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Pagano, Patrizio, 2004. "Habit persistence and the marginal propensity to consume in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 18(3), pages 316-329, September.

    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:spr:psycho:v:84:y:2019:i:4:d:10.1007_s11336-019-09676-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.