Multidimensional Poverty in Malaysia : Improving Measurement and Policies in the 2020s

There are many dimensions to poverty, and research and applications of new methods for better understanding this multidimensionality have blossomed in the past 10-15 years. Malaysia established an official Multidimensional Poverty Index (MPI) in 2015 as a complement to the income-based poverty measure that has been in use since the 1970s. To date the MPI has not featured prominently in policy formulation or in public discourse, being overshadowed by other measures. Most notable among these is the "B40", an income-based measure that refers to the bottom 40 percent of the income distribution. Nevertheless, the MPI remains one of several instruments available to monitor the well-being of the population and inform policy decisions. The government of Malaysia recently revised its methodology for the income poverty line and is considering revisions to the MPI as well. The objective of this policy note is to examine possible ways to improve both the relevance of Malaysia's MPI and expand its usage in informing policies. It is one of many available indicators of progress in the people's well-being, but it is also uniquely positioned both to summarize gains across many aspects of daily life and to provide insights into specific dimensions of poverty that are progressing well or are lagging. Section 2 briefly describes some of the main concepts in multidimensional poverty and highlights recent developments in research and measurement. Section 3 offers details about the introduction and use of the MPI in Malaysia, the structure and content of the MPI, and MPI statistics. Section 4 discusses ways in which the MPI indicators could be modified to conform better to the Malaysian context, using recent household survey data to quantify the effects of those modifications. Section 5 presents several examples of the multidimensional poverty approaches in comparator countries, including regional and global peers. Section 6 illustrates some basic analytical approaches that could be used to extract more policy-relevant information from the MPI about the various dimensions of poverty. Concluding remarks are provided in section 7