While several models for analysing longitudinal network data have been proposed, their main differences, especially regarding the treatment of time, have not been discussed extensively in the literature. However, differences in treatment of time strongly impact the conclusions that can be drawn from data. In this article we compare auto-regressive network models using the example of TERGMs -an extensions of ERGMs -and process-based models using SAOMs as an example. We conclude that the basic TERGM, in contrast to the ERGM, has no consistent micro-level interpretation, and thus only allows interpretation on the level of the network. Further, parameters in the TERGM are strongly dependent on the interval length between two time-points. Neither limitations is true for processbased network models such as the SAOM. Finally, both compared models perform poorly in out-of-sample prediction compared to trivial predictive models.

Important questions in the social sciences are concerned with the circumstances under which individuals, organizations or states mutually agree to form social network ties. Examples of such coordination ties are found in such diverse domains as scientific collaboration, international treaties, or romantic relationships and marriage. This paper introduces Dynamic Network Actor Models (DyNAM) for the statistical analysis of coordination networks through time. The strength of the models is that they explicitly address five aspects about coordination networks that empirical researchers will typically want to take into account. First, that observations are dependent, second, that ties reflect the opportunities and preferences of both actors involved, third, that the creation of coordination ties is a two-sided process, fourth, that data might be available in a time-stamped format, and fifth, that processes typically differ between tie creation and dissolution (signed processes), between shorter and longer time windows (windowed processes), and between initial and repeated creation of ties (weighted processes). Two empirical case studies demonstrate the potential impact of DyNAM models: One is concerned with the formation of romantic relationships in a high school over 18 months, one investigates the formation of international fisheries treaties

Initiated in 2002, the International Environmental Agreements Data Base (IEADB) catalogs the texts, memberships, and design features of over 3,000 multilateral and bilateral environmental agreements. Using IEADB data, we create a comprehensive review of the evolution of international environmental law, including how the number, subjects, and state memberships in IEAs have changed over time. By providing IEA texts, the IEADB helps scholars identify and systematically code IEA design features. We review scholarship derived from the IEADB on international environmental governance, including insights into IEA membership, formation, and design as well as the deeper structure of international environmental law. We note the IEADB’s value as a teaching tool to promote undergraduate and graduate teaching and research. The IEADB’s structure and content opens up both broad research realms and specific research questions, and facilitates the ability of scholars to use the IEADB to answer those questions of greatest interest to them.

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