Pakistan's population, estimated around 149 million, is growing at the rate of 2.1 per cent per year. Nearly 67.5 per cent of country's population is living in rural areas. In Pakistan, poverty has been higher in rural areas (38.65 percent) than urban areas .i.e. 22.44 percent. Poverty has many faces, such as hunger, lack of shelter etc. Technically poverty is "the inability to retain a minimal standard of living, measured in terms of basic consumption needs or some income required for satisfying them (World Bank, 2003). Most often, poverty is a situation from which people want to escape.
In Pakistan more than 45 percent people generate their income from agriculture sector and 86 percent of them are small farmers. Small farmer is operating less than 12.5 acres 0 f irrigated I and 0 r less than 25 acres 0 f un-irrigated I and (Agricultural Census, 2000). Thus, there is a dire need to raise agricultural productivity; as previously productivity is the most efficient means of alleviating poverty and protecting the environment.
The objectives of the study were to study current poverty profile, the factors responsible for small farmer's poverty to identify various indigenous knowledge based options and combination of farm enterprises to empower the small farmers. I n all 300 small farmers, 100 from each district i.e. Faisalabad, Jhang and TT Singh were selected. In order to derive the net income of the small farmers, farm budgets for crops and livestock were estimated. The allocative efficiency of the critical inputs and comparative advantage of the major crops were estimated. The Linear Programming Technique was. used to estimate optimal allocation of resources for maximizing the farm income.
The survey results revealed that the small farmers had 149 percent, 148 percent 159 percent cropping intensities in the three districts Faisalabad, Jhang and T.T. Singh respectively. However, wheat in all the districts was occupying the major portion of the cropped area. The allocative efficiency depicted misallocation of the critical inputs. The production elasticities of seed, water and fertilizer showed the scarcity of these The Policy Analysis Matrix (PAM) for rice at the export parity prices demonstrated clear cut comparative advantage of raising this crop. Sugarcane had comparative advantage in Faisalabad division on import parity prices and can be grown an import substitution crop. The PAM for cotton showed comparative advantage in Faisalabad division and can very well compete in the International market. The DRC ratio for wheat indicated that crop had comparative advantage on import parity prices in Faisalabad division.
Poverty estimation through different techniques showed that corresponding poverty gap a cross districts was 6 5 percent, 5 3 percent, and 5 7 percent in Faisalabad, Jhang and TT Singh. The low farm productivity, bigger family size, high dependency 'ratio, low education of the head and lack of infrastructure were the major determinants of poverty for small farmers. In order to enhance the productivity and income of the small farmers, In all 32 LP models with different scenarios were developed. The productivity enhancement was simulated through the optimal allocation of labor, irrigation water, fertilizer (Nitrogen (N) and Phosphorus (P), concentrate in case of livestock and addition of high value crops like hybrid tomato and cut flower. All scenarios showed increase in farm income to a large extent and thus help reduce the poverty of small farmers. The optimization models indicated that the small farmers should exploit the intensive margins of N. P and water through rational use to increase small farmers’ income. On the basis of farmers indigenous knowledge and perceptions, it was concluded that adulteration free " and timely supply of phosphoric fertilizer, enhancement of irrigational water and off farm employment were the pre-requisite for the reduction of poverty of small farmers.