An Empirical Investigation Of Risk Perception, Risk Management Strategies And Poverty Among Cotton Farmers In Pakistan

Economic development and livelihoods in Pakistan are highly dependent on the agricultural sector which accounts for 21% of the country’s total Gross Domestic Product(GDP) and employs 43% of the total labor force. Since last decade, the increasing population couple with stagnant agricultural growth has caused imbalance in the supply and demand of agricultural commodities. The stagnant agricultural growth is mainly due to the continuously declining or static crop productivity which are closely relate to increase exposure to different kinds of risk including climatic risks and low adaptive capacity at farm level. In term of climatic risks, Pakistan comes in the list of top ten highly affected countries over the last decade. Farmers who are the primary stakeholder in agriculture are directly suffering from ongoing crises and risks. Farmers have to deal with numerous risks which rise from natural, economic and sociopolitical environments. Farmers need to adopt various management strategies to avoid those risks and to protect their crop production. Current agricultural policies in Pakistan do not focus much more on the aspect of farmers’ perceptions and management of risks at farm level. Further, literature on these kinds of interactions is limited in Pakistan.The presented Ph.D. research takes the case of cotton farmers and focuses on the factors motivating the farmers to adopt different management options including diversifying income source to manage different kinds of risks in crop production. Specifically the study has four research objectives first to describe and categorize the major agricultural risks, second to identify the on and off-farm risk management strategies used by the farmers, third to discern the determinants of non-farm income and fourth is the association between nonfarm income and poverty alleviation. The research is based on a household level survey conducted in 2014-15 in the Punjab province Pakistan. We interviewed about 480 farm households through well-structured questionnaire. The study uses different economic and statistical tools to explore the study objectives. The factor analysis using SPSS software was adapted to determine the major risk sources and risk management strategies at farm level. Further, we used OLS regression to determine the association among farm and farmer’s characteristics, risk source and risk management factors. Through factor analysis, we identified five major risk sources i.e. labour and market information, production, institutional, financial and Natural and five major risk management strategies at farm level i.e. capital management, credit, research and development, information management and diversification. The results of OLS regression shows that a number of farm and framer’s characteristics significantly affecting farmers perceptions of risk sources and choice of management strategies.Further, we employed ELCE method to analyze the behavior of farmers about risk and we found that in general majority of the farmers were risk averse in nature. Furthermore, Probit model was applied to determine the factors affecting the risk averse nature of the farmers and perception of four major risks i.e. flood, excessive rainfall, pest and disease and high input prices. Results of probit models explain that demographics characteristics i.e. age, education, location play significant role in determining the risk averse nature of agricultural household and perception of important risks.Further, we employed logistic regression approach to identify the determinants of offfarm income diversification by farmers in relation to perceived risks. We found that non-farm incomes does not only help farmers to avoid complete loss in case of adverse effects due to certain risk but it also provide farmers some additional income to timely buy farm inputs like seed, fertilizer and ground water. Off-farm income sources were categorized in three types according to farmer’s response such as business, services and off-farm labour. The results of logistics regression explain that characteristics like farm size, number of workers in household, dependency ratio, access to road etc. are the factors responsible for participation in each type of non-farm income sources.Poverty is also a big hindrance at farm level that limits farmer’s capacity to manage agricultural risks. Here, in order to calculate the poverty level and severity of poverty among agricultural household, we use FGT technique. A standard of $2 a day per person was considered to estimates the number of people living below the poverty line. Results show that more than half of the respondents were living under the poverty line. Further, findings of the logistic regression show that factors like education, dependency ration, having access to loan, adaptation to risk management strategies etc. affecting significantly to the poverty of the respondents in the study area.From all these findings we can conclude that to get good production in agriculture it is essential for the farmers to have sound awareness about risk sources and risk managementPOVERTY AMONG COTTON FARMERS IN PAKISTAN strategies. Government should formulate better policies and develop institutional mechanism like crop insurance system which can help to share agricultural risk. Getting higher production may have multiplier effect on the life of agricultural household. It will increase their annual income and help them to come out from poverty cycle. To increase the adoption of off-farm income sources for the farmers there should be the availability of small enterprises to attain more income. To address the poverty among respondents increase in agricultural income and non-farm income is required. This goal can be achieved by utilizing household workers in non-farm enterprises. So there is need to design appropriate policies in this aspect.