Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

Abstract

Mixed-methods designs, especially those where cases selected for small-N analysis (SNA) are nested within a large-N analysis (LNA), have become increasingly popular. Yet, since the LNA in this approach assumes that units are independently distributed, such designs are unable to account for spatial dependence, and dependence becomes a threat to inference, rather than an issue for empirical or theoretical investigation. This is unfortunate, since research in political science has recently drawn attention to diffusion and interconnectedness more broadly. In this paper we develop a framework for mixed-methods research with spatially dependent data—a framework we label “geo-nested analysis”—where insights gleaned at each step of the research process set the agenda for the next phase and where case selection for SNA is based on diagnostics of a spatial-econometric analysis. We illustrate our framework using data from a seminal study of homicides in the United States.

Incorporating Space in Multimethod Research: Combining Spatial Analysis with Case-Study Research

“…A logical next question is to identify which other third variable might be exerting a conditioning or moderating effect to produce this local variation. However, qualitative work and case knowledge can provide explanations for this variation (Harbers and Ingram 2017a; 2017b).…”

“… 3. For a more in-depth discussion of how multimethod research may be leveraged to understand the spatial process, see Harbers and Ingram 2017a and 2017b. …”

“…Indeed, while there are other benefits from this integration, this article makes a core, two-pronged point: (1) without integrating insights from spatial analysis, multimethod designs can be self-defeating because one method may undermine the logic of another; and (2) without integrating insights from multimethod research, spatial statistics and econometrics can fall short by assuming rather than demonstrating both (a) the mechanisms underlying key spatial processes and (b) the proper unit or level of analysis. Because explicit strategies for integrating spatial econometrics and qualitative methods in multimethod research are discussed elsewhere, we refer readers to those works for specific strategies (e.g., Harbers and Ingram 2015; 2017a; 2017b) and focus instead on the more general motivations for combining spatial analysis with case-study research.…”

Comparative Area Studies and the Study of the Global South

“…There is no questioning the predominance of quantitative research that eschews any mention of specificity of place or locus except when absolutely unavoidable [King 1996]. Cross-national large-N comparison and survey research addressing individual attitudes try to minimize the significance of the particular as much as possible, using geographi-cally specific nominal variables ("dummy variables") to hold place as a constant [Harbers, Ingram 2017]. Formal and game theoretical models are even more abstract, seeking essentially to make area irrelevant.…”

Identifying gatekeepers in the allocation of public funds: a spatial econometric analysis

“…To our knowledge, this approach is currently absent from the debate on distributive politics. Spatial analysis is expected to significantly contribute to political analysis, reflecting its influence in the social sciences (Beck et al, 2006;Harbers & Ingram, 2017a, 2017bIngram & Harbers, 2020). A thorough investigation must account for the relationships and influences occurring within and between territorial units.…”