This paper aims to unpack the nexus of development and demography controlling for three important variables to represent the meaning of development, that is, poverty rate, unemployment rate and human development index (HDI). Demographic variables are proxied with total fertility rate (TFR) and net migration rate (NMR).
This research applies cluster analysis at the provincial level using INDO-DAPOER and 2015 Intercensal Population Survey data sets.
Demographic and development status of Indonesian provinces can be classified into four clusters, and members of these clusters are mostly dissimilar with those of previous groupings on demographic dividends (Adioetomo, 2018). With only less than 50% matching rate, the author argues that there is no simple linear relationship between demographic and development variables.
The most recent data set on Population Census Year 2020 has not been made available at the time of the writing. Also sometimes known as unsupervised classification, cluster analysis is about finding groups in a set of objects characterised only by certain measurements; therefore, findings of this study need to be positioned solely within the context of development and demography.
Taxonomy in this study offers a more nuanced and contextual understanding of the diverse challenges at the local and regional levels. Recommendations from this study lead to asymmetrical design in development policies and budget proportions at local levels.
It is expected that the findings are relevant to the input of policymaking process within the sphere of development and demography, especially for countries with significant size of populations and grappling with development issues.
To the author’s understanding, this paper is the first to discuss the impact of “demographic dividend” to economic development in Indonesia using the approach of cluster analysis. The expected contribution of this work is twofold: Firstly, the author would like to ignite a discourse on the nexus of development and demography using the most recent data set and cutting-edge method. Secondly, the findings are relevant to the input of policymaking process within the sphere of development and demography, especially for countries with significant size of populations and grappling with development issues.
