Publication - Working Paper
The Government of Punjab, Pakistan and DFID have launched a collaborative development programme, Punjab Economic Opportunities Programme (PEOP), for four economically marginalized districts in Southern Punjab: Bahawalpur, Bahawalnagar, Lodhran and Muzaffargarh. The PEOP will focus on the provision of marketable skills and interventions related to the livestock and dairy sector of the target areas.
This report offers baseline indicators for the PEOP programme logframe. These indicators have been developed for the two major components of the programme, skill development and livestock.
Poverty in all target districts increased between 2003/04 and 2007/08 except for Muzaffargarh where it decreased marginally. The data suggests increasing divergence in incomes. The poor in the region witnessed a decrease in their purchasing power as their real income decreased, while overall average income in the region increased. Clearly, the current economic structure of these high-poverty districts is not enabling inclusive growth outcomes to be realized.
The poor have consistently fewer assets across districts; they are less likely to own land or their own homes. The non poor have better housing, are more urban and are more likely to receive remittances from outside their locality. Across districts the poor have similar literacy rates and demographic profiles, but are less literate and younger than the non poor. There are substantial variations within the poor as well. Among the poor literacy correlates with income; it is lowest among the poorest. Unemployment indicators, remittances and nominal income all move in the expected directions as we compare different bands of poverty. Comparing genders, female headed households are less likely to own land, have fewer average numbers of animals and are more urban than non-female headed households.
Apart from reporting on available indicators, this section also identifies knowledge gaps that can be filled only by way of detailed surveys at the community level that, for instance, capture information regarding access to fodder and nutrition for animals by households.