ERGM

Exponential random graph models function almost as a traditional regression model by evaluating the probability of a tie forming between two nodes.

We begin our exponential random graph models with network structural terms designed to model the underlying data generation process in the network.

Much like we divide results by wave with our descriptive results, we employ a similar approach with the exponential random graph models. Unfortunately, the first wave is too sparse for meaningful analysis with exponential random graph models, and we are thus unable to model it.

The results, with some exceptions, generally confirm our expectations via both descriptive network analysis and from a more causal standpoint via exponential random graph models. From a purely descriptive standpoint, we find that not all states participate in the education finance reform diffusion network.