Meta-Analytic Structural Equation Modeling (MASEM) is a correlation-based meta-analysis, so the type of data is a multivariate correlation effect size of the studied study. The effect size of MASEM is likely to be heterogeneous; therefore, MASEM, which exhibits heterogeneity issues, is a random-effects model. The heterogeneity problem must be overcome by choosing the best estimation method. The generalized method of moments (GMM) is an estimation method that overcomes heterogeneity problems. The estimation of the parameters of the MASEM random effects model using the GMM method fulfills the quality characteristics of the estimator being unbiased and consistent. This research brings a new approach to the estimation of MASEM parameters, whereas previous studies relied mainly on simulation-based or computational approaches to obtain MASEM estimates. The main features of this study are as follows:•This study focuses on effect sizes obtained from correlations in the ordinary structural equation model, without intermediate or moderating variables.•Variance between studies in the estimation process is addressed using lag in time series theory, which allows us to consider the main research problem, namely heterogeneity.