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

Lindenfors, Patrik , Krusell, Joshua & Lindberg, Staffan I. | 2019

Social Science Quarterly, 838-856

Abstract

Objectives
This article 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.

Methods
The approach is a sorting algorithm through repeated pairwise investigations of states in a set of variables and identifying what states in the variables occur before states in all other variables. We illustrate the proposed method by analyzing a set of variables from version 7.1 of the V‐Dem data set (Coppedge et al. 2017. Varieties of Democracy (V‐Dem) Project; Pemstein et al. 2017. University of Gothenburg, Varieties of Democracy Institute: Working Paper No. 21). With a large set of indicators measured over many years, the method makes it possible to identify and compare long, complex sequences across many variables.

Results
This affords an opportunity, for example, to disentangle the sequential requisites of failing and successful sequences in democratization, or if requisites are different during different time periods.

Conclusions
For policy purposes, this is instrumental: Which components of democracy occur earlier and which later? Which components of democracy are therefore the ideal targets for democracy promotion at different stages? 

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Social Science Quarterly, 838-856

Abstract

Objectives
This article 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.

Methods
The approach is a sorting algorithm through repeated pairwise investigations of states in a set of variables and identifying what states in the variables occur before states in all other variables. We illustrate the proposed method by analyzing a set of variables from version 7.1 of the V‐Dem data set (Coppedge et al. 2017. Varieties of Democracy (V‐Dem) Project; Pemstein et al. 2017. University of Gothenburg, Varieties of Democracy Institute: Working Paper No. 21). With a large set of indicators measured over many years, the method makes it possible to identify and compare long, complex sequences across many variables.

Results
This affords an opportunity, for example, to disentangle the sequential requisites of failing and successful sequences in democratization, or if requisites are different during different time periods.

Conclusions
For policy purposes, this is instrumental: Which components of democracy occur earlier and which later? Which components of democracy are therefore the ideal targets for democracy promotion at different stages? 

Läs artikeln