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AAMP Training Materials

AAMP Training Materials. Steven Haggblade ( MSU ) blade@msu.edu. Module 1.4: Options for Raising Productivity Among Resource-Poor Farmers. Outline. Objectives Profile of cotton farm households in Zambia Sources of CF productivity gains Linear programming (LP) optimization methods

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AAMP Training Materials

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  1. AAMP Training Materials Steven Haggblade (MSU) blade@msu.edu Module 1.4: Options for Raising Productivity Among Resource-Poor Farmers

  2. Outline • Objectives • Profile of cotton farm households in Zambia • Sources of CF productivity gains • Linear programming (LP) optimization methods • LP Exercises & Discussion • References

  3. Asset-poor farm households • How can a farmer with low assets increase productivity? • This man has a farm, his own labor, and a hand hoe – the most basic technology.

  4. Asset-poor farm households • The average farm household has land, family labor, and several hand hoes • Can their technology be improved to boost farm productivity?

  5. Asset-poor farm households • The families in the previous slides have little money, do not use herbicides, and are unlikely to have access to animal traction • What the families do have is labor • So, if families can increase labor productivity, they can increase farm productivity too • The following discussion focuses on cotton farmers in Zambia, examining the productivity differences between available technology packages and feasible alternatives for households of different asset holdings.

  6. Objectives • Evaluate the impact of Conservation Farming (CF) on asset-poor households compared to conventional tillage • Analyze the impact of different productive technologies • With and without oxen • With and without cash • With and without herbicides

  7. Outline • Objectives • Profile of cotton farm households in Zambia • Sources of CF productivity gains • Linear programming (LP) optimization methods • LP Exercises & Discussion • References

  8. Zambian Cotton Farmers

  9. Farm size distribution in AEZ 2a

  10. Asset holdings

  11. Outline • Objectives • Profile of cotton farm households in Zambia • Sources of CF productivity gains • Linear programming (LP) optimization methods • LP Exercises & Discussion • References

  12. Sources of CF Productivity Gains • Minimum tillage • Dry season land preparation • Early planting • Crop residue retention & water harvesting • Precision layout and input application

  13. Sources of CF Productivity Gains • Minimum tillage requires 75% lower energy

  14. Conventional Hand Hoe • Using a hand hoe requires a lot of energy. Every centimeter of land must be turned manually.

  15. Hand Hoe Conservation Farming • In Conservation Farming, only about 15% of the surface area is disturbed in preparing planting basins. Moving less dirt requires less energy and labor.

  16. Conventional Ox Plowing • Conventional plowing inverts all of the soil in the field. For this, the soil must be relatively soft and moist. In clay soils, the trowel-like action of the plow builds up an impermeable plow-pans after years of repeated plowing.

  17. Conservation Farming with Ripper • The CF Ripper can be used before the rains come. It is a minimum tillage method that breaks the hardpan, leaves the rest of the topsoil unturned, and needs less energy.

  18. Sources of CF Productivity Gains • Minimum tillage requires 75% lower energy • Dry season land prep  overcome peak season labour bottlenecks  increased area cultivable with fixed household labour

  19. Dry Season Land Preparation Source: Haggblade and Tembo (2003).

  20. Sources of CF Productivity Gains • Minimum tillage requires 75% lower energy • Dry season land prep  overcome peak season labour bottlenecks  increased area cultivable with fixed household labour • Early planting  1-2% yield increase per day

  21. Gains from Early Planting Sources: Arlussa (1997), Birgess (2009), Haggblade and Tembo (2003), Barratt et al. (2006), Nyagumbo (2007).

  22. Sources of CF Productivity Gains • Minimum tillage requires 75% lower energy • Dry season land prep  overcome peak season labour bottlenecks  increased area cultivable with fixed household labour • Early planting  1-2% yield increase per day • Crop residue  Soil Organic Matter (SOM) buildup  improved moisture retention  higher yields

  23. Dry Season Land Preparation M V P F E R T I L I Z E R Source: Marenya and Barrett (2009)

  24. Water Harvesting, CF Basins Water harvesting boosts the amount of water concen- trated around the crop roots. Useful in semi-arid zones.

  25. Water Harvesting, Rip Lines Water harvesting boosts the amount of water concen- trated around the crop roots. Useful in semi-arid zones.

  26. Sources of Maize Yield Gains Under CF Source: Haggblade and Tembo (2003).

  27. Outline • Objectives • Profile of cotton farm households in Zambia • Sources of CF productivity gains • Linear programming (LP) optimization methods • LP Exercises & Discussion • References

  28. Method: Linear Programming (LP) Model • Maximize Crop Income = • Revenue (∑Pi*Qi)- cost (∑ Pn*Qn) • Subject to household asset constraints • Seasonal labour availability • Animal traction (ANTRAC) • Cash • Land

  29. What Crops to Include?

  30. Alternate Technologies

  31. Seasonal Labour Constraints

  32. Outline • Objectives • Profile of cotton farm households in Zambia • Sources of CF productivity gains • Linear programming (LP) optimization methods • LP Exercises & Discussion • References

  33. Exercise 1 – Baseline Scenario (Setup) • Examine [LP – baseline] sheet in Excel file • Rows 01 – 25 are raw data (do not alter these). • Rows 25 – 45 will change during the exercises. • Rows 50 – 99 are where results are pasted for comparison • Only yellow cells should be changed • Green cells display results

  34. Exercise 1 – Baseline Scenario 0a. Actual Base Case • Before using Excel’s LP model to find the profit maximizing land allocation, first determine farmers’ actual land allocation • Change land allocation choice variables (yellow: line 30) • Input base values (set cells E30:G30 = line E25:G25) • Copy results to section 0.a. (row 53:65) • Copy the entire block of values in yellow and green • When pasting, use “paste values”

  35. Exercise 1 – Baseline Scenario 0b. Low Technology, Profit Maximization • Open LP optimization: Go to Data tab / Solver* • Set objective (H31) • By changing variable cells (E30:G30) • Subject to these constraints • Available technologies (E30:G30 >= 0) • Land holdings (H30 <= D30) • Seasonal labor (H39:42 <= D39:42) * If you don’t find the Solver add-in on the Data Tab, you may need to install it: Options/Add-Ins/Analysis Toolpak/Solver.

  36. Exercise 1 – Baseline Scenario 0c. Low Technology, “Safety First” • Set objective (H31) • By changing variable cells (E30:G30) • Subject to these constraints • Available technologies (E30:G30 >= 0) • Land holdings (H30 <= D30) • Seasonal labor (H39:42 <= D39:42) • Safety first (H37:38 >= D37:38) * If you don’t find the Solver add-in on the Data Tab, you may need to install it: Options/Add-Ins/Analysis Toolpak/Solver.

  37. LP Results – Baseline Scenario

  38. Discussion questions: Baseline Scenario • Why don’t farmers maximize income? • Why do they adopt the safety-first rule?

  39. Exercise 2 – Conventional Tillage • 1a. Cash constraint, Safety First • Household can use only low-input technologies & must adopt Safety First risk aversion • 1b. No cash constraint, Safety First • Can use all conventional technologies, but must adopt Safety First • 1c. No cash constraint, plow rental possible • Includes all conventional technologies plus ANTRAC >= 0 • 1d. No cash constraint, household owns cattle • All conventional technologies are available in this scenario

  40. Exercise 2 – Conventional Tillage 1a. Cash Constrained, Hand Hoe, Safety First • Open [LP Conventional tillage] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to the constraints • Available technologies (E30, O30, Q30 >= 0; all others == 0) • Land holdings (X30 <= D30) • Seasonal labor (X39-42 <= D39-42) • Safety first (X37-38 >= D37-38)

  41. Exercise 2 – Conventional Tillage 1b. No Cash Constraint, Hand Hoe, Safety First • Open [LP Conventional tillage] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to constraints • Available tech: E30, F30, O30, P30, Q30 >= 0 (all else == 0) • Land holdings (same as before) • Seasonal labor (same as before) • Safety first (same as before)

  42. Exercise 2 – Conventional Tillage 1c. Cash Available, ANTRAC Rental OK, Safety First • Open [LP Conventional tillage] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to constraints • Available tech: E30, F30, L30, M30, O30, P30, Q30, V30 >= 0 (all else == 0) • Land holdings (same as before) • Seasonal labor (same as before) • Safety first (same as before)

  43. Exercise 2 – Conventional Tillage 1d. Cash Available, ANTRAC Ownership OK, Safety First • Open [LP Conventional tillage] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to constraints • Available tech: E30, F30, L30, M30, N30, O30, P30, Q30, V30, W30 >= 0 (all else == 0) • Land holdings (same as before) • Seasonal labor (same as before) • Safety first (same as before)

  44. LP Results – Conventional Tillage

  45. Discussion questions: Conventional Tillage • 1b. Why do farmers switch to M2? • 1b. Why do cash costs increase? • 1c. What major changes result when animal traction becomes available? • 1.c. Why do cash costs increase? • 1.d. What is the most important consequence when farmers own draft oxen?

  46. Exercise 3 – Conservation Farming • 2a. Cash constraint, Safety First • Household can use only low-input Conservation Farming technologies & must adopt Safety First strategy • 2b. No cash constraint, Safety First • Can use all CF technologies, but must adopt Safety First • 2c. No cash constraint, CF ripper rental possible • Includes all CF technologies plus animal traction, Safety First • 2d. No cash constraint, herbicides available • All CF technologies are available, plus herbicides, Safety First

  47. Exercise 3 – Conservation Farming 2a. No Cash + Low Input + Safety First • Open [LP conservation farming] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to the constraints • Available technologies (E30, G30, O30, Q30, R30 >= 0; all others == 0) • Land holdings (X30 <= D30) • Seasonal labor (X39-42 <= D39-42) • Safety first (X37-38 >= D37-38)

  48. Exercise 3 – Conservation Farming 2b. Cash Available + High-Input CF + Safety First • Open [LP conservation farming] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to the constraints • Available technologies (E30, F30, G30, H30, O30, P30, Q30, R30 >= 0; all others == 0) • Land holdings (X30 <= D30) • Seasonal labor (X39-42 <= D39-42) • Safety first (X37-38 >= D37-38)

  49. Exercise 3 – Conservation Farming 2c. Cash + High-Input+ Ripper + Safety First • Open [LP conservation farming] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to the constraints • Available technologies (E30, F30, G30, H30, K30, L30, M30, O30, P30, Q30, R30, U30, V30>= 0; all others == 0) • Land holdings (X30 <= D30) • Seasonal labor (X39-42 <= D39-42) • Safety first (X37-38 >= D37-38)

  50. Exercise 3 – Conservation Farming 2d. Cash + High-Input+ Ripper + Herbicide + Safety First • Open [LP conservation farming] worksheet • Open Solver and input the following • Set objective (X31) • By changing variable cells (E30:W30) • Subject to the constraints • Available tech (E30, F30, G30, H30, I30, J30, K30, L30, M30, O30, P30, Q30, R30, S30, T30, U30, V30>= 0; all others == 0) • Land holdings (X30 <= D30) • Seasonal labor (X39-42 <= D39-42) • Safety first (X37-38 >= D37-38)

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