Dairy enterprise and whole farm performance in mixed farming systems: Punjab, Pakistan Sosheel Godfrey PhD Student Supervisors: Karl Behrendt, Tom.

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Presentation transcript:

Dairy enterprise and whole farm performance in mixed farming systems: Punjab, Pakistan Sosheel Godfrey PhD Student Supervisors: Karl Behrendt, Tom Nordblom, Peter Wynn

Research Objective Identifying policies that improve the livelihoods of farmers while meeting changing consumer demands within developing countries that maintain traditional value chains for agricultural products. This will be achieved by applying value chain analysis to study the domestic and traditional milk value chains in Pakistan. A case study approach will be used to address the national challenges of low profitability and limited marketing opportunities for small dairy farmers at one end, and unsatisfied consumers at the other end.

Research Questions Is milk production a profitable and reliable source of income for dairy farmers? Can a value chain approach address issues of milk production profitability for farmers as well as address the increasing demands for nutritional and affordable milk for consumers? Can value chain mapping aid analysis assist in addressing some of the policy and regulatory issues of public concern?

Why Dairy? Research Question 44% of country’s labour associated with agriculture 40 million rural population depend on livestock for their livelihood Major product of livestock is milk whose market value exceeds the combined value of major cash crops Thus important to understand the economics of dairy i.e. is milk production profitable?

Importance of Agriculture Pakistan: Population 173million GDP $164B Agriculture as % of GDP 21% (more than half is livestock) Agriculture Value Added $32B Australia: Population 22million $1,040B 2.5% $23B

Pakistan: 2nd for buffalo milk & 14th for cow milk production Dairy Herd Size Average per lactation Production Billion Litres Production Value Buffalo 29m (2006) 2,060 litres 21 $8.1B Cow 27m (2006) 927 litres 11.5 $3.5B Australia: 18th for cow milk production 1.6m (2009) 5,445 litres 9 $2.9B

Mixed farming system where crops and livestock compete for limited land Major winter crops and fodders are wheat, berseem, lucerne and oats In summer these include rice, sugarcane, cotton, maize, millet and sorghum

Dairy stall fed with green fodders grown at farm, supplemented with roughages (wheat or rice straw) from crop residues. Concentrates, cotton seed cake and wheat bran are dietary supplements

Punjab, Pakistan 97 115 INDIA

Okara in central Punjab, is between the rivers of Ravi and Sutlej with an agriculture-based economy. It is rich in livestock such as Sahiwal cattle and Nili-Ravi water buffalo breeds

Bhakkar Western Punjab is on the left bank of mighty river Indus Bhakkar Western Punjab is on the left bank of mighty river Indus. The western part is well cultivated with land irrigated from wells as well as Thal irrigation canal

22.99 (2.59) 21.14 (3.01) 24.13(19.19) 19.67(20.05) Okara Bhakkar 115 Mean physical and economic attributes for farms in Okara and Bhakkar districts of Punjab, Pakistan. Standard deviations (SD) in parentheses. Measure Okara Bhakkar Total sample size (n) 115 97 Total land (Acres) 9.04(7.08) 9.47(9.00) Herd size (hd) 10.93(5.16) 10.50(5.58) Milking cows and buffaloes (hd) 3.71(1.92) 3.77(2.23) Total milk production (kg) 3,238(1,846) 3,288(2,604) Milk prices (Rs./kg) 22.99 (2.59) 21.14 (3.01) Milk average variable cost Rs/kg) 24.13(19.19) 19.67(20.05)

Cumulative Distribution Function (CDF) for Milk Average Variable Cost (Rs/kg)  40 % farmers in Okara and 30% in Bhakkar had average variable costs (Rs/kg) higher than farm gate milk prices of Rs. 23 and Rs 21 per kg respectively and were thus making losses. Cumulative Probability Milk Average Variable Cost (Rs/kg)

Relationship between Milk Production (kg) and Average Variable Cost (Rs/kg) Milk average variable costs per kg had an inverse relationship with production Average Variable Cost (Rs/kg) Milk Production (kg)

Relationship between Milk Production (kg) and Average Variable Cost (Rs/kg) for both districts 31.16 18.62 13.85 26.25 14.35 9.59 Average Variable Cost (Rs/kg) Milk Production (kg)

Okara -Cumulative Distribution Function (CDF) for Milk, Livestock Activity and whole farm gross margins (Rs) Okara 40% farms made losses from milk 50% from livestock activity Whole farm gross margin though are positive for 90% farms Cumulative Probability Gross Margin (Rs)

Bhakkar- Cumulative Distribution Function (CDF) for Milk, Livestock Activity and whole farm gross margins (Rs) 30% farms made losses from milk 50% from livestock activity. Whole farm gross margin was positive for 80% farms Bhakkar Cumulative Probability Gross Margin (Rs)

Cumulative Distribution Function (CDF) for Operating Profit 80% and 70% sample farms in Okara and Bhakkar respectively had positive operating profits, after removing labour cost from whole farm gross margin estimates Cumulative Probability Rupees

Cumulative Distribution Function (CDF) for Net Profits 70% and 90% sample farms though in Okara and Bhakkar showed losses when finance costs were included to get Net profit Cumulative Probability Rupees

Conclusion Overall losses from livestock enterprises are possibly due to low productivity and directly related to nutrition and management practices. Our study confirms this premise of the ACIAR project. Actual cost of capital, in particular to the small dairy holder, may be much higher than the assumed (9%), as they borrow from traditional money lenders.

Questions Does integrated mixed farming limit farmers from capitalising on advantages of becoming specialized producers? Are the better production efficiencies we found with larger numbers of milking animals also associated with greater milk marketing efficiencies?

Acknowledgements This project is funded by the Australian Centre for International Agricultural Research (ACIAR) as part of the Agricultural Sector Linkages Program (ASLP). The collection of data by David McGill, Hassan Warriach and ASLP dairy project colleagues is acknowledged. David McGill is also thanked for his help in extracting the survey data.