Identifying at-risk populations is essential for designing effective energy poverty interventions. Using data from the HILDA Survey, a longitudinal dataset representative of the Australian population, and a multidimensional index of energy poverty, we develop a machine learning model combined...

Identifying at-risk populations is essential for designing effective energy poverty interventions. Using data from the HILDA Survey, a longitudinal dataset representative of the Australian population, and a multidimensional index of energy poverty, we develop a machine learning model combined...

The primary objective of this empirical study is to investigate the Indian equity market network by analyzing its topological properties using the disparity filtering technique, and a minimum spanning tree. It investigates the backbone structure of the reduced weighted equity network and...