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We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a treated and a control area. This type of geographically discontinuous treatment assignment can be analyzed in a standard regression discontinuity (RD) framework if the exact geographic location of each unit in the dataset is known. Such data, however, is often unavailable due to privacy considerations or measurement limitations. In the absence of geo-referenced individual-level data, two scenarios can arise depending on what kind of geographic information is available. If researchers have information about each observation’s location within aggregate but small geographic units, a modified RD framework can be applied, where the running variable is treated as discrete instead of continuous. If researchers lack this type of information and instead only have access to the location of units within coarse aggregate geographic units that are too large to be considered in an RD framework, the available coarse geographic information can be used to create a band or buffer around the border, only including in the analysis observations that fall within this band. We characterize each scenario, and also discuss several methodological challenges that are common to all research designs based on geographically discontinuous treatment assignments. We illustrate these issues with an original geographic application that studies the effect of introducing copayments for the use of the Children’s Health Insurance Program in the United States, focusing on the border between Illinois and Wisconsin.

This chapter analyzes a geographic quasi-experiment embedded in a cluster-randomized experiment in Honduras. In the experiment, average treatment effects of conditional cash transfers on school enrollment and child labor were large – especially in the poorest experimental blocks – and could be generalized to a policy-relevant population given the original sample selection criteria. In contrast, the geographic quasi-experiment yielded point estimates that, for two of three dependent variables, were attenuated. A judicious policy analyst without access to the experimental results might have provided misleading advice based on the magnitude of point estimates. We assessed two main explanations for the difference in point estimates, related to external and internal validity.

Advocates of market-based reforms in the public sector argue that competition between providers drives up performance. But in the context of schooling, the concern is that any improvements in efficiency may come at the cost of increased stratification of schools along lines of pupil ability and attainments. In this chapter, we discuss our empirical work on competition and parental choice in English primary schools and present a methodology for identifying competition effects that exploits discontinuities in market access close to education district boundaries.

We discuss the two most popular frameworks for identification, estimation and inference in regression discontinuity (RD) designs: the continuity-based framework, where the conditional expectations of the potential outcomes are assumed to be continuous functions of the score at the cutoff, and the local randomization framework, where the treatment assignment is assumed to be as good as randomized in a neighborhood around the cutoff. Using various examples, we show that (i) assuming random assignment of the RD running variable in a neighborhood of the cutoff implies neither that the potential outcomes and the treatment are statistically independent, nor that the potential outcomes are unrelated to the running variable in this neighborhood; and (ii) assuming local independence between the potential outcomes and the treatment does not imply the exclusion restriction that the score affects the outcomes only through the treatment indicator. Our discussion highlights key distinctions between “locally randomized” RD designs and real experiments, including that statistical independence and random assignment are conceptually different in RD contexts, and that the RD treatment assignment rule places no restrictions on how the score and potential outcomes are related. Our findings imply that the methods for RD estimation, inference, and falsification used in practice will necessarily be different (both in formal properties and in interpretation) according to which of the two frameworks is invoked.

Multinational corporations (MNCs) have increasingly sourced knowledge across borders, and foreign subsidiaries operations have played a critical role in MNC international knowledge sourcing strategies. The growing responsibility of foreign subsidiaries has paralleled an interest on the geography of this phenomenon by international business and international management scholars. In this chapter, we review this research. In addition, based on recent research in economics and management drawing on economic geography and innovation studies, we highlight possible avenues of research to enrich our understanding of the geographical aspects of international knowledge sourcing. In particular, we suggest three lines of research opportunities. A first opportunity relates to the explicit consideration of distance and border effects. A further research opportunity arises from investigating the geographical distance of heterogeneous host country knowledge sources from the foreign subsidiary. A final research opportunity we discuss is about the contribution of heterogeneous host country knowledge sources to the variety of knowledge developed by the foreign subsidiary.

Alliances often turn into acquisitions (i.e., one alliance partner is acquired by the other). In these transitional governance trajectories, geography-related factors can play a crucial role. Factors like location and distance can notably influence the decision to acquire the alliance partner, as well as the performance implications of such a transition. However, existing studies on transitional governance tend to underemphasize the geographic dimension of the phenomenon. In this chapter, we take a first step toward connecting the field of transitional governance and the discipline of economic geography, which does emphasize location and distance as critical determinants of economic activities. We discuss how economic geography can inform the field of transitional governance and propose some promising avenues for future studies linking organization, place, and space in transitional governance trajectories.

This chapter aims to provide suggestive evidence on how the Lombardy region dealt with the COVID-19 pandemic in 2020 and discuss future challenges for the Lombardy healthcare system. After an introduction to the wide spread of the virus inside the region, we describe the Lombardy health system so the reader may understand the context in which the virus has taken hold so quickly. The pandemic has heavily stressed the system, mainly because Lombardy experienced an excess of hospital admissions. We have considered the increased mortality rate as a proxy of the proper managing of the COVID-19 pandemic. In addition, we describe the process of treating non-COVID patients, such as those affected by acute myocardial infarction (AMI), stroke and oncological diseases. Despite the pandemic, hospitals have been able to guarantee a high level of performance. A discussion of the future evolution of the healthcare system concludes this chapter.

In this chapter I argue that the distance research in international business studies is at a turning point, not in terms of its popularity, nor the quantity of articles published, but rather, in terms of the types of issues that are explored. Past distance research has largely been conducted at the level of the firm and/or the market – that is, linking national-level measures of distance with specific firm behaviors and outcomes. However, the seminal paper by Shenkar (2001) represents a shift in focus that is only just beginning to gain traction. This shift involves stepping back and beginning to unpack the black box we call ‘distance’ by exploring the micro-level mechanisms involved. In essence, it is about digging deeper in multiple aspects, to understand when, why and how distance matters in the international business (IB) context. These are issues that until now have typically been neglected. A metaphor borrowed from the social psychology literature, known as Coleman’s Boat, is used as a vehicle to explain the key issues involved in this shift and the opportunities for future research.