# **1. Introduction**

The discourse on whether and how economic growth translates into poverty reduction is a topic of significant importance and enduring debate in economic development. This debate extends far beyond academic circles, touching the core of policy making. A critical challenge is the ability to offer concrete guidance on prioritizing growth-oriented policies and identifying the specific nature of growth that effectively mitigates poverty. This ongoing discourse underscores the need for rigorous analysis and evidence to inform policy choices, particularly when considering the multiple facets of poverty beyond mere income metrics to encompass a broader range of deprivations affecting individual well-being.

While a substantial body of empirical evidence exists pointing to a generally negative correlation between economic growth and poverty, it is noteworthy that the lion's share of this literature has traditionally focused on income or monetary poverty. This narrow focus on money leaves a significant gap in our understanding of the dynamics between economic growth and multidimensional poverty—a form of poverty that considers various dimensions of deprivation, including education, health, and living standards (Alkire et al., 2021). The relationship between multidimensional poverty and economic growth remains relatively underexplored, with most studies merely qualitatively tracing the trajectories of GDP growth and multidimensional poverty at the national level without engaging in formal statistical analysis (e.g., Djossou et al. (2017), Tran et al. (2015)).

A handful of studies have ventured into examining the correlation between changes in GDP and shifts in composite indices of multidimensional poverty using cross-sectional data across different time points (Alkire et al., 2017; Burchi et al., 2019; Seth & Alkire, 2021). However, rigorous assessments of the relationship between economic growth and multidimensional poverty are scarce. To our knowledge, only two attempts have been made in this direction, notably by Santos et al. (2019) and Balasubramanian et al. (2023). Both employed unbalanced panel data and a firstdifference estimator (FDE) to uncover a negative correlation, albeit focusing on different indices of multidimensional poverty and study periods.

Our paper endeavors to contribute meaningfully to this relatively uncharted but essential literature. We begin our investigation by constructing a panel dataset that integrates Multidimensional Poverty Index (MPI) data with indicators of economic growth. Following the methodological footsteps of Santos et al. (2019) and Balasubramanian et al. (2023), we employ a first-difference model to elucidate the fundamental relationship between MPI and economic growth.

We begin the analysis by exploring the fundamental relationship between the MPI and economic growth, focusing on variations across different income groups and regions. This initial analysis replicates existing findings from the literature, providing a solid foundation for our research. Building upon this, our study contributes significantly to the literature by examining the subcomponents of MPI—namely education, health, and living standards—to identify any heterogeneity within these subcomponents. Furthermore, we investigate economic growth across various dimensions and components to provide deeper insights and distinguish our work from previous studies. In the second part of our study, we analyze the effects of economic growth by 2