AAMP Training Materials

1. AAMP Training Materials Steven Haggblade (MSU) blade@msu.edu Module 1.1: Production Cost and Farm Productivity

2. Module Contents • Objectives • Background material • Exercises • Conclusions

3. Objectives • Understand what determines the price level of a good • Compute plot-level production costs and compare between farmers • Explore what affects farm productivity using estimate yield functions • Examine policy implications (for stimulating agricultural growth & government procurement pricing)

4. Background Material • Review determinants of price • What factors affect the cost of supplying maize to the market? • Why does productivity vary across farms?

5. Determinants of price

6. Determinants of price (contd.)

7. What affects the cost of supplying maize to the market? • Farm-level cost of production • Transport costs (distance to market) • Marketing costs (handling, storage, profit, risk premium)

8. Why does productivity vary… • Among farmers? • Across plots? Q: Is this a good farmer or a bad farmer?

9. Good farmer? Bad farmer?

10. Good farmer? Bad farmer?

11. Good farmer? Bad farmer?

12. Where are the good farmers and bad farmers on this supply curve?

13. Exercise 1: Compute Plot-level Cost • Open “Production Cost and Price Variability.xls” • Read the red NOTES tab to familiarize yourself with the contents of the workbook • Click on the [data1 – plots] tab and explore the data • There are 200 farmers represented • Focus on yield • Why is yield so variable?

14. Exercise 1: Compute Plot-level Cost contd. • Click on the [ex 1 – cost of production] tab • Values in yellow refer to [data1 – plot] • Values in green are results • What do you notice? • On average, do farmers have positive revenue? • What are the major costs? • Compare farm productivity between farms • Select a farmer from [data1 – plot] • Link the yellow highlighted values to a farm in [data1 – plot] • How does this compare to the mean? • Repeat for several different farms • How do they compare to each other?

15. Exercise 1: Results • Farm productivity varies greatly • Some farmers in the sample receive negative revenue from maize • Policy should focus on increasing farmer productivity • Raises farmers’ profits • Lowers consumer costs

16. Exercise 2: Cost Histogram & Supply Curve • Examine the Cost Histogram in [ex 2 – cost groups] • What do you see? • Can you make generalizations about “smallholder production costs” based on this histogram?

17. Exercise 2: Cost Histogram & Supply Curve • Next, examine columns Z, AA & AB in [data4 – cost per ton] • Copy column AB (tot_cost_ton) from [data4 – cost per ton] and paste it into [ex 2 – cost per ton] • Sort the column in ascending order (small values to large values) • Select the entire column and make a line chart • What does this chart show? • Compare with the chart in slide 11 of this presentation • If you were asked to choose a “fair maize price” based on this chart, what price would you choose?

18. Exercise 2: Results • Individual farmers’ cost of production varies greatly • Setting a price floor based on production costs has several problems • Who decides what’s “fair”? Where do you draw the line? • Set the price too high  government buys large volumes from inefficient farmers • High price risks pushing out private traders & hurting consumers • Policy that focuses on lowering farmers’ cost of production evades these problems

19. Exercise 3: Estimate Plot-level Yield Function • What are the factors affecting plot-level yield? • Seed Type (high yielding varieties vs. local) • Fertilizer application (kg/ha) • Time of planting (number of days after November 1) • Tillage system (hand hoe, conservation farming basins, plowing, ripper) • Number of years experience with conservation farming • Plot size • Gender • Yield = a + b Fert + c HYV + d Till + … • Yield is a function of Fertilizer, seed type, tillage type etc....

20. Exercise 3: Regression Equation • Open a new sheet in Excel • Use the Regression Tool to estimate the yield function • See notes in this presentation, as well as the NOTES tab in the Excel workbook for tips • Examine the coefficients • Which variables have the most impact on maize yield? • Are there any surprises? • How can this information be used in agricultural policy? • Research? • Extension?

21. Exercise 3: Interpreting Regression Coefficients

22. Exercise 3: Interpreting Regression Coefficients

23. Exercise 3: Results • High yielding seed varieties, planting basins, and fertilizer have a positive impact • Which has the biggest impact? • Which is cost effective? Look at the coefficient on fertilizer… is that a big enough increase in yield to justify the cost? • The planting date variable has a strong negative impact. • Highlights the importance of timeliness in agriculture. • What does this mean for agricultural extension?

24. Conclusions: empirical • Cost of production differs across farmers and plots • Efficient farmers produce at lowest cost

25. Conclusions: policy • Raising farm productivity  higher farmer profits and lower costs to consumers • Key public investments for lowering farmers’ cost of production • Agricultural research (breeding, agronomy) • Extension (improves agronomic and management practices) • Infrastructure improvements (lowers input cost prices) • If government sets procurement prices… • High price  large volumes procured. Purchases made from inefficient farmers • Low price  lower volumes procured. Purchases made only from efficient farmers

26. References • Chirwa, E. 2007. Sources of Technical Efficiency among Smallholder Maize Farmers in Southern Malawi. AERC Research Paper 172. Nairobi: African Economic Research Consortium.