Amati V Schönenberger F Snijders TAB 2019 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. https://sonar.ch/global/documents/288794 eng info:eu-repo/semantics/altIdentifier/doi/10.1007/s11336-019-09676-3 info:eu-repo/semantics/altIdentifier/pmid/31309405 Psychometrika. - 2019 behaviour generalized method of moments networks panel data stochastic actor-oriented model stochastic approximation Algorithms Computer Simulation Humans Stochastic Processes Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models. http://purl.org/coar/resource_type/c_6501