Democratic development: a comprehensive concept of comparative assessment
Purpose – Existing attempts to assess national development and processes of democratization suffer from conceptual and measurement challenges. This paper proposes a comprehensive concept of democratic development and develops a more inclusive concept of democracy to provide a common set of categories to evaluate its depth and quality. Design/methodology/approach – In order to measure the depth and health of democracy, democratic development incorporates four categories of human progress, each measured by multiple variables. The four categories deemed important for human progress are general development, democratic health, democratic inclusiveness, and human capital. Components of democratic development incorporate existing measures of political and economic development to create a comprehensive and accessible measure of democratic development. Findings – The comparative tables based on multiple goals of development clearly reveal that neither the GDP index nor the HDI are adequate measures of development. Democratic development can be more fully captured by four perspectives: development, democratic inclusiveness, democratic health, and human capital, providing a framework to measure progress in reform, democracy, and development, from public agencies up to the national level. This concept incorporates aspects and orientations of the capabilities approach to create a concept that is amenable to use as a self-assessment tool and as a basis for comparison of development, broadly conceived. Practical implications – This inclusive concept is particularly well suited for analyzing citizen satisfaction and democratic stability. Originality/value – Rather than focusing on singular measures, the approach presented here offers a balanced set of measures aimed at providing a comprehensive view of the gamut of democratic and economic development processes relative to existing models that is more appropriate for self-assessment/planning purposes than traditional measures, which may be more appropriate for statistical modeling purposes.
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Volume (Year): 33 (2006)
Issue (Month): 1 (January)
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