The main purpose of the SRM project is to improve the efficiency and effectiveness of social programmes so that limited programme resources primarily reach the poor (i.e. minimizing leakage to non-poor) and the poor are not excluded (i.e. minimizing under-coverage of the poor). It has been designed to become an exhaustive and centralized database of social programme beneficiaries with the following objectives:
• to better identify beneficiaries of social programmes;
• to manage social programmes in an integrated way;
• to better harmonise the criteria for the different social programmes run by different Ministries; and
• to analyse cyclical and structural poverty reduction policies.
The SRM is therefore an instrument to assist government in identifying the beneficiaries of social programmes and deciding the level of assistance for each beneficiary. It will also serve to evaluate existing social programmes and improve performance and service delivery.
Proxy Means Test allows us to estimate the income or consumption when precise measurements are unavailable or difficult to obtain mainly in countries where there is a large informal sector. In many cases it is difficult to tell how much a family earns or spends every month. Even the household members themselves might not be able to tell. However we can guess based on household characteristics. For example if we have two families same size, same district, same age but living in different houses, one house made of wood and the other made of concrete then our proxy will be “Type of Wall' and “Type of Roof". There is great variability in incomes, even between families living in houses made of wood so we should not limit ourselves to only one proxy. The PMT test uses many proxies to obtain a test that will accurately predict the income of different households.
Following the Household Budget Survey of 2006, a LCS (Living Condition Survey) was carried out to provide information on basic needs by consumption category and from this information, a method was designed to calculate monetary assessments of each of these basic needs.
The Household budget survey data was used for regressing the Living Standard variable on household characteristics easy to observe.
The Living standard predictions were calculated by defining the quantile regressions in terms of living standard levels i.e on household consumption levels representative of the poor.Precisely, the quantile regression centered in the quantile of living standard corresponding to the consumption- based Poverty Line was used.
The predicted consumption levels are multiplied by the number of adult equivalence scale and then compared against the Poverty lines of the Empowerment act (The per capita threshold table below refers) to identify the eligible poor and within these eligible households a further check is done based on their income which also include transfers, pensions etc.
In July 2010 a first PMT 1 formula was produced and it was used as from April 2012.
In 2015 a new PMT 2 formula was produced, this new PMT also included assets and it is still being used, only the CPI has been adjusted.