Empirical evidence that cultural traits are often nonrandomly distributed because of the individual or combined effects of common history, diffusion, borrowing, and/or other types of cultural transmission processes has been accumulating for decades. Because many cultural traits have recently been shown to be influenced by more than one transmission process, it has become a methodological priority in comparative research to develop statistical methods that can simultaneously incorporate multiple transmission processes. This article proposes a multiple network autocorrelation effects model and associated two-stage least squares (2SLS) estimation procedures. The network autocorrelation effects model offers an alternative interpretation of how cultural trait transmission processes operate than does the network autocorrelation disturbances model. Conceptual differences between the two classes of models suggest that the network effects specification will be more generally applicable in comparative studies. An empirical example demonstrates the substantive value of the multiple network autocorrelation effects model and the widely available 2SLS estimation procedures.
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