• The first volume that brings together the work of scholars pioneering digital approaches to the Republic of Letters
• Innovative applications of social network analysis and digital methods to provide new perspectives on the Republic of Letters
• Exciting new perspectives on the European networks that made up the Republic of Letters
• A volume that elegantly combines traditional humanistic inquiry with innovative digital methods, to offer fresh perspectives on some of the most important issues in eighteenth-century studies
• This volume provides exemplary models of how social network analysis (SNA) can be adapted for historical research

This review evaluates the use of spatial models for the analysis of policymaking. First, we examine spatial theory and its applications in a variety ofinstitutional settings. We discuss how the preferences of the actors involvedin political processes, the steps in those processes, and the locations of thereversion policies affect the policies that emerge from the processes. To illustrate this and analyze how the rights of political actors determine the extentof policy reform and the occurrence of gridlock, we use a spatial model ofEuropean Union (EU) policy making. We apply the model to major EU reforms in two resource policy areas: the Common Agricultural Policy reformsof the past two decades and the recent reforms of the Emissions TradingSystem.

A growing number of countries have established programs to attract immigrants who can contribute to their economy. Research suggests that an immigrant's initial arrival location plays a key role in shaping their economic success. Yet immigrants currently lack access to personalized information that would help them identify optimal destinations. Instead, they often rely on availability heuristics, which can lead to the selection of sub-optimal landing locations, lower earnings, elevated outmigration rates, and concentration in the most well-known locations. To address this issue and counteract the effects of cognitive biases and limited information, we propose a data-driven decision helper that draws on behavioral insights, administrative data, and machine learning methods to inform immigrants' location decisions. The decision helper provides personalized location recommendations that reflect immigrants' preferences as well as data-driven predictions of the locations where they maximize their expected earnings given their profile. We illustrate the potential impact of our approach using backtests conducted with administrative data that links landing data of recent economic immigrants from Canada's Express Entry system with their earnings retrieved from tax records. Simulations across various scenarios suggest that providing location recommendations to incoming economic immigrants can increase their initial earnings and lead to a mild shift away from the most populous landing destinations. Our approach can be implemented within existing institutional structures at minimal cost, and offers governments an opportunity to harness their administrative data to improve outcomes for economic immigrants.

This paper empirically examines recently declassified tariff bargaining data from the GATT/WTO. Focusing on the Torquay Round (1950–1951), we document stylized facts about these interconnected high-stakes international negotiations that suggest a lack of strategic behavior among the participating governments and an important multilateral element to the bilateral bargains. We suggest that these features can be understood as emerging from a tariff bargaining forum that emphasizes the GATT pillars of MFN and multilateral reciprocity, and we offer evidence that the relaxation of strict bilateral reciprocity facilitated by the GATT multilateral bargaining forum was important to the success of the GATT approach.