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The literature documenting a wide range of network or peer effects has blossomed in the past decade and have appeared in most major economics journals, using a variety of methods and identification strategies. Reviewing the empirics of those papers suggests a few broad classes of econometric models. The first and canonical model is the “linear-in-means,” which grows from Manski’s seminal work. More recently, it has shown that network asymmetry conditions (known as “peers-of-peers” instrument approach) can be used to instrument the endogeneity inherently present in the linear-in-means model. Moving to more recent empirical practice reveals novel and creative instrumentation strategies exploring particular empirical settings. The network identification strategies can also be combined with traditional differences-and-differences, event-study, and regression discontinuity designs. For example, under certain conditions, one can explore the variation that stems from the differential comparison of the evolution over time of well-connected versus less-well-connected individuals; or explore the variation in the network structure induced by a discontinuous change in the network. Randomized, controlled studies had substantial importance in revealing network effects in the past literature using standard methods; and, more recently, in understanding the extent to which networks can themselves be endogenous to the provision of the treatment itself. This, in turn, will present future challenges for the econometrics of networks and the identification or evaluation of treatment effects under a causal framework with endogenous interference.

International trade involves the movement of goods across borders, while immigration pertains to the movement of people across national boundaries. These two phenomena are strongly correlated. To some extent, the similarity between barriers to trade and migration explains this correlation, with distance being a crucial factor in both trade and migration. Geographically closer countries tend to engage in both trade and migration because of closer cultural connections. Immigration is itself also an important determinant of trade flows. Migrant networks play a vital role in reducing trade barriers by improving information sharing and facilitating business connections. This, in turn, leads to an increase in both exports and imports between countries. As trade increasingly relies on efficient firm and supplier matching, particularly within global supply chains, the influence of migrant networks becomes more significant. Finally, immigration also drives demand for goods and services from migrants’ home countries. Migrants often maintain strong ties to their home countries and prefer consuming products and services from those regions. This preference fosters increased bilateral trade flows between the home country and the country of immigration. In summary, international trade and immigration are closely linked, and understanding the interplay between international trade and immigration is crucial for comprehending the dynamics of the global economy.