Sequential Requisites Analysis: A New Method for Analyzing Sequential Relationships in Ordinal Data

Abstract

This paper presents a new method inspired by evolutionary biology for analyzing longer sequences of requisites for the emergence of particular outcome variables across numerous combinations of ordinal variables in social science analysis. The approach involves repeated pairwise investigations of states in a set of variables and identifying what states in the variables that occur before states in all other variables. We illustrate the proposed method by analyzing a set of variables from version 6 of the V-Dem dataset (Coppedge et al. 2015a, b). With a large set of indicators measured over many years, the method makes it possible to explore long, complex sequences across many variables in quantitative datasets. This affords an opportunity, for example, to disentangle the sequential requisites of failing and successful sequences in democratization. For policy purposes this is instrumental: Which components of democracy are most exogenous and least endogenous and therefore the ideal targets for democracy promotion at different stages?