We introduce a numerical algorithm for solving dynamic economic models that merges stochastic simulation and projection approaches: we use simulation to approximate the ergodic measure of the solution, we cover the support of the constructed ergodic measure with a fixed grid, and we use...

We survey and synthesize models of network formation based on random graphs and stochastic processes. We organize the material according to whether the population is treated as fixed or dynamic. We pay particular attention to the effects of homophilous linking on network structure. Finally, we...

We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is "long-run integration," whereby the composition of types in sufficiently old nodes'...

We develop a modelling framework for estimating and predicting weighted network data. The edge weights in weighted networks often arise from aggregating some individual relationships between the nodes. Motivated by this, we introduce a modelling framework for weighted networks based on the...

We present a new approach to the study of networks where the formation of links is driven by unilateral initiative of nodes. First, we propose a mathematical description of the extreme introvert and extrovert model (XIE), a dynamic network model in which the number of links fluctuates over time...

We present an analytical solution for the connectivity of a network model with a "non-simultaneous" linking scheme. Despite its simplicity, this model exhibits node-space correlations in the link distribution, and anomalous fluctuations behavior of the time series of the connectivity variable,...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...