Poverty Monitoring, Measurement and Analysis (PMMA)

Developing and applying concepts, techniques and tools to monitor, measure and analyse welfare, equity and other related issues in a multidimensional setting, using primarily household survey data.

Through the PMMA research program, PEP contributes to build local capacities in microeconomic measurement and analysis in developing countries.

PEP research projects supported under the PMMA program usually aim to provide a fuller characterization of the nature, distribution, causes and consequences of poverty in beneficiary countries.

Local researchers are enabled to use complex measurement techniques to build comprehensive "profiles" of the state of welfare or development amongst certain populations, which are then used to inform policy decisions in their home countries.

A multidimensional approach

To this day, a great majority of poverty analyses in developing countries is still based on a unidimensional monetary approach. PMMA research promotes a new, multidimensional perspective on welfare issues, providing comprehensive profiles and evidence to assist in designing and targeting policy interventions for effective improvement of socioeconomic well-being.

Poverty is indeed a multidimensional phenomenon, and the poor are generally deprived in more than one dimensions of wellfare: health, income, education, sanitation, housing, security, etc. all of which must be taken into account in poverty and development policy decisions.

Using a combination of cutting-edge methofologies and analytical techniques, the outcomes of PMMA research provide reliable evidence to assist policymakers in facing challenges such as:

  • How should national priorities for public and government spending be defined?
  • Which dimensions of welfare are most important and should be prioritized?
  • Which populations (region, age group, sex, education, etc.) should be targeted and how?

PMMA research

PMMA provides support, training, mentoring and a variety of resources (e.g. documentation, software tools, concept development, etc.) for developing country researchers to rely on to strenghten their capacities in microeconomic measurement and analysis.

In addition, through the global infrastructure of PEP, the PMMA program also encourages comparative analyses between researchers from around the world, and especially in developing countries of Africa, Asia and Latin America, to compare methods, tools, findings and experience. 


The PEP PMMA research program has yielded major contributions to the field, with the development of two world-renowned software tools for distributive analysis, used and valued worldwide throughout the international development research community

PMMA resaerch puts most emphasis on the use of existing nation-wide micro-based data; collection of new data is usually not carried out. Teams generally adopt or develop common methodologies, often involving micro-econometrics, to ensure that training and technical support/partnership are provided efficiently at the network level. The PMMA program strives for good comparative international research, but retains a focus on national results and impact.

In many cases, international donor institutions and development partners have taken advantage of PEP's expertise in developing capacities and methods for the analysis of the patterns, determinants, incidence and drivers of inequities in developing countries, to commission special initiatives, such as:

Generally speaking, however, the themes of interest of PEP projects supported under the PMMA program are broad and evolving with developments in the scientific literature. They are also flexibly adapted to the heterogeneous needs of policymaking in the diverse socioeconomic environments that PEP covers.

Some examples of PMMA research focuses are:

  • Multidimensional poverty analysis
  • Public spending and its impact on poverty and equity
  • Growth and poverty dynamics
  • Policy impact analysis
  • Intra-household allocation of well-being
More on..

Multidimensional poverty analysisPublic spending and its impact on poverty and equity

This has scored particularly well in the context of several national Poverty Reduction Strategy Paper (PRSP) exercises in Africa. In 2007, in order to contribute to improve the understanding of the impact of public spending on poverty and equity, the PEP PMMA research program has broadened its methodological approach to incorporate intra-household allocation of well-being and poverty dynamics.

Growth and Poverty Dynamics

This theme includes:

  • Comparing poverty across time and space, using statistically and normatively reliable methods;
  • Analyzing the impact of demographic and socio-economic transformations (such as emigration, urbanization, environmental changes, changes in family sizes and composition, changes in human capital, changes in trade and openness) on poverty and inequality;
  • Analyzing the impact of growth and redistribution on the evolution of poverty, and in particular, the heterogeneity of that impact;
  • Analyzing the impact of growth in factor incomes on poverty alleviation;
  • Analyzing the pro-poorness of growth and policy;
  • Using panel data to look at individual and household poverty dynamics;
  • Analyzing social protection, security, risk management, and vulnerability;
  • Studying poverty duration, transient vs. permanent poverty.

Policy impact analysis

Policy Impact Evaluation Research Initiative (PIERI), funded by AusAID in 2007.

Intra-household allocation of well-being


The above-mentioned list of themes of PMMA research is not exhaustive. PMMA has supported a number of projects on gender analysis and child well-being, as well as using micro-simulation techniques and experimental data analysis.

The PMMA team has also led a number of special programs, such as the PEP-OPHI Human Development and Capabilities Initiative, and collaborated in initiatives supported under the MPIA program, to assist in the use of micro-simulation techniques.

In all cases, PMMA research work emphasizes the importance of reliability and robustness in drawing out ethical and statistical conclusions.


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