Kizito MSU CIRAD 2010

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Kizito MSU CIRAD 2010

  1. 1. Estimating The Benefits From Improved Market Information Andrew Kizito Agricultural, Food, and, Resource Economics g , , , Michigan State University A paper prepared for the workshop on “Agricultural Market Information Systems in Africa: Renewal and Impact” Montpellier (France), 29-31 March 2010
  2. 2. Summary of presentation • Method Used To Value Information • The Price Adjustment Model • Comparative Statics • Application of the Model – Results and Sensitivity Analysis – Cost - Benefit Comparisons • Summary and Conclusion • Implications for MIS Investment
  3. 3. Method Used To Value Information Hayami and Peterson (1972): Increase in social welfare resulting from increased accuracy or reduction in sampling errors 1.Inventory Adjustment Model a) Constant production ) p 2.Production Adjustment Model a) Production adjusts Complementarities with other reforms • Potentially lead to attribution problems • Jointly measure the benefits and costs of complementary programs
  4. 4. The Price Adjustment Model • Based on the partial equilibrium model – Value information as the reduction in dead-weight loss when users with rational expectations respond to improved price forecasts from MIS. – Reduction of the cost of being off the equilibrium price and quantity
  5. 5. The Price Adjustment Model Setting and Assumptions: • MIS provides price forecasts • A closed economy with no international trade • Rational Expectations- Based on new information – Adjust Production strategies (how much to grow) – Adjust Marketing strategies (when to sell or store) • A single homogenous commodity replicated commodity, to four separate commodities sold on the market.
  6. 6. The Price Adjustment Model • Benefits in form of reduction in net social welfare loss by producers and consumers as a result of reduction in price forecasting errors. • Also known as cost of being off the equilibrium price and quantity ilib i i d tit • Estimations based on – Fo r major cereals (millet mai e sorgh m Four (millet, maize, sorghum and rice) – Account for more than 85% of cereal calories in Mali (Dembélé and Staatz., 1999).
  7. 7. The Price Adjustment Model ΔQ P Price Ed = * = elasticity of demand A S ΔP Q Pc ΔQ P Es = = elasticity of supply ΔP Q P B ˆ P C ΔP =| P − P |= e p P ˆ D ΔQ =| Q s - Q |= e p E s Q O Qs Q Q Quantity y ΔQ P ΔP2 =| Pc − P |= = e p Es P / Ed P = producer price of the commodity. Ed Q ˆ P = forecast producerprice of the commodity 1 E (L) = ΔQ(ΔP + ΔP2 ) ( Pt − Pt ) ˆ 2 ep = price forecasterror Pt 1 2 ⎛ Es2 ⎞ Q = quantityproduced E (L) = e p PQ⎜ ⎜ E + Es ⎟ ⎟ 2 ⎝ d ⎠
  8. 8. Comparative Statics-Payoffs greater where: (a)The level of uncertainty about future market price in the market is high (sampling error is large) ∂L ⎛ E s2 ⎞ = e p PQ⎜ ⎜ E + Es ⎟>0 ⎟ ∂e p ⎝ d ⎠ Large forecasts errors lead to less production Excess demand large cost of being off the equilibrium price and quantity Low forecasts errors lead to a smaller cost of being off the equilibrium
  9. 9. Comparative Statics-Payoffs greater where: (b) The own-price elasticity of demand for agricultural commodity is low (becomes less negative—i.e., less elastic). ∂L 1 2 ⎛ Es2 ⎞ = − e p PQ⎜ 2 ⎟ < 0 ⎜E ⎟ ∂Ed 2 ⎝ d⎠ When production respond to price forecasts, but consumption decisions do not, there is a misallocation of resources d t “ i t k ” i ll ti f due to “mistaken” price forecasts.
  10. 10. Comparative Statics-Payoffs greater where: (c) The own-price elasticity of supply for the agricultural commodity is high. ∂L 1 2 ⎛ 2 E s ⎞ = e p PQ⎜ ⎜ E + 1⎟ > 0 ⎟ ∂E s 2 ⎝ d ⎠ Poor price forecast induce a relatively large shift in production, implying a relatively large misallocation of resources resources. (d) The value of farm production of the crop is g high
  11. 11. Application of the Model Elasticities of demand and supply 2002 Elasticities Maize Millet ce, Paddy Sorghum Demand -1.968 -0.691 -0.767 -0.691 Supply 0.17 0.14 0.18 0.14 Production, prices and value of farm production in '000 CFA francs and USD, 2002 Crop Production and Prices Maize Millet ce, Paddy Sorghum Total Production (000' MT) 364 795 710 642 Price CFA Franc/MT 72 92 128 87 Value of Farm Production (CFAF)* 26,254 73,233 90,653 55,827 245,967 Value of Farm Production (USD)** 37,668 105,070 130,063 80,098 352,899 * V l of F Value f Farm Production i '000 CFAF P d ti in **2002 Exchange rate 1 USD=696.99 CFA; CIA World Fact Book Demand and Supply Elasticities • Rogers and Lowdermilk (1991) Camara (2004) Lo dermilk (1991), (2004), Rosegrant, et al., 2001 Value of Farm Production • quantity produced (Q) x producer prices (P) f tit d d d i from FAOSTAT
  12. 12. Welfare Loss & Benefits of Improved Information Social loss corresponding to percentage of • For sorghum, if the price forecasting error in Million Dollars, 2002 forecast error is 40%, Maize Millet Rice Sorghum Total 40% 0.56 1.42 2.31 1.08 5.36 society losses $1.08M. 35% 0.43 0 43 1.08 1 08 1.77 1 77 0.83 0 83 4.11 4 11 30% 0.31 0.80 1.30 0.61 3.02 25% 0.22 0.55 0.90 0.42 2.09 • If error is reduced to 20% 0.14 0.35 0.58 0.27 1.34 35%, society looses 15% 0.08 0.20 0.33 0.15 0.75 $0.83M 10% 0.03 0 03 0.09 0 09 0.14 0 14 0.07 0 07 0.34 0 34 5% 0.01 0.02 0.04 0.02 0.08 0% - - - - - Marginal social returns from reduction of price g p forecasting error in Million Dollars, 2002 • For Rice, reducing the 40% to 35% Maize 0.13 Millet 0.33 Rice Sorghum 0.54 0.25 Total 1.26 price forecast error from 35% to 30% 0.11 0.29 0.47 0.22 1.09 40% to 35% would save 30% to 25% 0.10 0.24 0.40 0.19 0.92 $0.54M of social welfare, 25% to 20% 0.08 0.20 0.33 0.15 0.75 while reducing the 20% to 15% 0.06 0.15 0.25 0.12 0.59 forecast error from 15% 15% to 10% 0.04 0.11 0.18 0.08 0.42 10% to 5% 0.03 0.07 0.11 0.05 0.25 to 10% would save 5% to 0% 0.01 0.02 0.04 0.02 0.08 $0.08M dollars worth in 2002 Exchange rate 1 USD=696.99 CFA; CIA World Fact Book social welfare. i l lf
  13. 13. Sensitivity Analysis: Effect of Changes in Price Forecast Errors Fig 2A. Social welfare loss corresponding to 6,000,000 percentage of forecasting error in 2002 • Total loss in social welfare from 5,000,000 a 40% forecast error is $5.4M 4,000,000 4 000 000 per year Social loss in USD 3,000,000 • Total loss in social welfare from 2,000,000 a 10% forecast error is $.34M 1,000,000 per year. year 0 0% 5% 10% 15% 20% 25% 30% 35% 40% Price forecast error Maize Millet Rice Sorghum Total Fig 2B. Marginal social returns from reduction 1,400,000 of price forecasting errors, 2002 • Reducing the error from 40% to 1,200,000 35% saves $1.2M per year Marginal soc benefits 1,000,000 800,000 • Reducing the error from 10% to cial 600,000 400,000 5% to saves $ $0.25M per year 200,000 0 • Higher losses when there is uncertainty regarding future Change in price forecast error prices Maize Millet Rice, Paddy Sorghum Total
  14. 14. Sensitivity Analysis: Effect of Increase in Elasticity of Demand Fig 3A. Effect of an increase in elasticity of 6,000,000 demand to loss in social welfare • Total loss in social welfare from 5,000,000 a 40% forecast error is $5.4M per year Social loss in USD D 4,000,000 4 000 000 3,000,000 • When the elasticity of demand is 2,000,000 increased by 50%, total loss in 1,000,000 welfare reduces to $5.1 million, representing only a 6% 0 0% 10% 20% Price forecast error 30% 40% reduction. 0% increase 25% 50% 75% 100% Fig 3B. Effect of an increase in elasticity of demand to marginal benefits from improved • Marginal Benefits from 1,400,000 1,200,000 price forecasts improved information less ocial benefits 1,000,000 variable due to changes in 800,000 elasticities of demand 600,000 600 000 Marginal so 400,000 200,000 0 Change in price forecast error 0% increase 25% 50% 75% 100%
  15. 15. Sensitivity Analysis: Effect of Decrease in Elasticity of Supply Fig 4A. Effect of a decrease in elasticity of supply to 6,000,000 loss in social welfare • Total loss in social welfare from a 40% forecast error 5,000,000 is $5.4M per year 4,000,000 4 000 000 Social loss in USD 3,000,000 • When the elasticity of 2,000,000 supply is reduced by 50%, total loss in welfare 1,000,000 reduces to $2 5M $2.5M, 0 0% 10% forecast20% Price error 30% 40% representing a 54% 0% Decrease 25% 50% 75% 100% reduction. Fig 4B. Effect of decrease in elasticity of supply to marginal benefits from improved price forecasts 1,400,000 1,200,000 • Marginal Benefits from Marginal social benefits 1,000,000 800,000 improved information 600,000 more variable due to 400,000 200,000 changes in elasticities 0 of supply Change i price forecast error Ch in i f t 0% Decrease 25% 50% 75% 100%
  16. 16. Cost - Benefit comparisons Cost / year Country Activity in USD Source Kenya ** y Dissemination only y 120,000(Shepherd, 2001) ( p ) Dissemination / Uganda language 20,000(Shepherd, 2001) Uganda* Full operation costs 30,000(Muganga, et al. 2000) Tanzania Dissemination only 10,000(Shepherd, 2001) Mali** Full operation costs 350,000(Staatz, 2006) • *Decentralized/Localized MIS covering 3 districts • ** National MIS (Covers many commodities and Markets) • Benefit from reducing price forecast errors with in a 10% to 15% range ( g ($.42 million) are larger than the ) g costs ($.35 million) of running the service.
  17. 17. Summary and Conclusions Better returns if improved market information is targeted to farmers and traders when: 1. The level of uncertainty about future market price in the market is high. 2. 2 The o n price elasticit of demand for own-price elasticity agricultural commodity is low. 3. 3 The own-price elasticity of supply for the own price agricultural commodity is high. 4. The value of farm production of the crop is p p high.
  18. 18. Implications for MIS investments • Decentralized or localized MIS: Collection, analysis and dissemination of market information on few crops in a given agro- i f ti f i i ecological, market or administrative area or region. • Targeted Crop-specific MIS: Collection, g p p , analysis and dissemination in areas where the value of agricultural production of the selected crops is high and responds to market information signals.

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