Peanut research and poverty reduction: impacts of variety improvement to control peanut viruses in Uganda.

Ersado, L., G. Amacher, and J. Alwang. 2004. "Productivity and Land Enhancing Technologies in Northern Ethiopia: Health, Public Investments, and Sequential Adoption." American Journal of Agricultural Economics 86:321-31.

Foster, J., J. Greer, and E. Thorbecke. 1984. "A Class of Decomposable Poverty Measures." Econometrica 52:761-6.

Gibbons, R.W. 1977. "Disease, Pests and Weeds in Tropical Crops: Groundnut Rosette Virus." In J. Cranz, J. Schutter, and W. Koch, eds. Diseases of Tropical Crops. Berlin: Verlag Paul Parey, pp. 19-21.

Godtland, E.M., E. Sadoulet, A. De Janvry, R. Murgai, and O. Ortiz. 2004. "The Impact of Farmer Field Schools on Knowledge and Productivity: A Study of Potato Farmers in the Peruvian Andes." Economic Development and Cultural Change 53:63-92.

International Crop Research Institute for Semi-Arid Tropics (ICRISAT). 2005. "Management of Groundnut Rosette: Past, Present, and Future." Available at http://www.icrisat.org/ text/research/grep/homepage/grephomepage/ archives/rosette.html.

Karanja, D.D., M. Renkow, and E. Crawford. 2003. "Welfare Effects of Maize Technologies in Marginal and High Potential Regions of Kenya." Agricultural Economics 29:331-41.

Mills, B.F. 1997. "Ex-ante Agricultural Research Evaluation with Site Specific Technology Generation: The Case of Sorghum in Kenya." Agricultural Economics 16:125-38.

Morris, M.L., and RW. Heisey. 2003. "Estimating the Benefits of Plant Breeding Research: Methodical Issues and Practical Challenges." Agricultural Economics 29:241-52.

Moyo, S. 2004. "The Economic Impact of Peanut Research on the Poor: The Case of Resistance Strategies to Control Peanut Viruses in Uganda." M.S. thesis, Virginia Tech, Blacksburg.

Mutangadura, G., and G.W. Norton. 1999. "Agricultural Research Priority Setting under Multiple Objectives: An Example from Zimbabwe." Agricultural Economics 20:277-86.

Ravallion, M. 1992. "Poverty Comparisons: A Guide to Concepts and Methods." LSMS Working paper No. 88. Washington DC: The World Bank.

Renkow, M. 1993. "Differential Technology Adoption and Income Distribution in Pakistan: Implications for Research Resource Allocation." American Journal of Agricultural Economics 75:33-43.

Smith, V.H., and P.G. Pardey. 1997. "Sizing Up Social Science Research." American Journal of Agricultural Economics 79:1530-4.

Thirtle, C., L. Lin, and J. Piesse. 2003. "Impact of Research Led Agricultural Productivity Growth on Poverty Reduction in Africa, Asia and Latin America." World Development 31:1959-75.

Uganda National Household Survey 1999-2000. 2001. Uganda Bureau of Statistics, Ministry of Finance, Planning, and Economic Development, Kampala.

World Bank. 2006. Uganda Country Brief. Available at http://www.worldbank.org/ug/ ctry_brief.htm.

(1) Research leading to the Rosette-resistant varieties was supported by the Ugandan National Agricultural Research System, the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and the U.S. Agency for International Development (USAID)-funded Peanut Collaborative Research Support Program (Peanut CRSP).

(2) Consumption of peanuts is 6 kg/person/year in Uganda, compared to 14 for all sub-Sahara Africa according to FAO statistics.

(3) When [alpha] = 0, [P.sub.[alpha]] is the headcount index, or the proportion of the population that is poor. When [alpha] = 1, [P.sub.[alpha]] is the poverty gap index, a money-metric measure of depth of poverty. Depth is based on the aggregate poverty deficit of the poor relative to the poverty line. When [alpha] > 1, [P.sub.[alpha]] reflects increased sensitivity to inequality among the poor.

(4) Alternative models of adoption could be considered in our framework. For example, farmers may partially adopt the technology or, if the technology under consideration includes several components, adopt it sequentially (see Ersado, Amacher, and Alwang 2004). The researcher would need to adapt the particular adoption model to compute the expected change in income/surplus at the household level.

(5) Due to lack of consensus about an income-measured poverty line in Uganda, we used a poverty line equal to $0.75 per person per day. Although this line is low by international standards (the World Bank standard is $1 per person per day), international standards tend to refer to consumption poverty and measured consumption is usually significantly higher than income. The poverty line can be adjusted accordingly as consensus about an income poverty line is attained.

Sibusiso Moyo, George W. Norton, and Jeffrey Alwang are, respectively, former graduate research assistant, professor, and professor at Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061. Ingrid Rhinehart is research analyst, International Food Policy Research Institute, Washington DC. Michael Deom is professor at University of Georgia. Table 1. Base Poverty Indices for Peanut-Producing and All Households Poverty Peanut All Index Producers (PP) Sample (AS) Headcount 0.7084 0.7456 Depth 0.3286 0.3894 Severity 0.1896 0.2454 Source: Own computation using Uganda National Household Survey 1999-2000 (2001). Table 2. Characteristics of Adopting and Nonadopting Households

Adopters

(N = 499) Variable Description Mean SD Age of household head (years) 43.2 15.5 Number of people normally residing 6.4 3.7

in the household Income per capita (US$) 165.0 163.0 Land owned per capita (Hectares) 2.9 4.4 Number of hoes owned 4.0 2.7 Extension advice (=1 indicates household 0.6 1.4

received extension advice in 1998)

N % Male household head 87 17.4 Married household head 82 16.4 Highest level of education completed

Primary 261 52.3

Junior 20 4.0

Secondary and beyond 135 27.0 Land tenure

Freehold 302 60.5

Customary 160 32.0 Market information received in 1998 222 44.5

Nonadopters

(N = 1,560) Variable Description Mean SD Age of household head (years) 45.3 16.6 Number of people normally residing 5.5 3.3

in the household Income per capita (US$) 127.0 160.0 Land owned per capita (Hectares) 2.9 3.9 Number of hoes owned 3.1 2.1 Extension advice (=1 indicates household 0.2 0.8

received extension advice in 1998)

N % Male household head 1144 73.30 Married household head 1142 73 Highest level of education completed

Primary 844 54.10

Junior 43 2.80

Secondary and beyond 224 14.40 Land tenure

Freehold 738 47.30

Customary 745 47.80 Market information received in 1998 498 32 Source: Uganda National Household Survey 1999-2000 (2001). Exchange rate $1:UGS1900. Table 3. Summary of the Probit Results: (Dependent Variable = 1 for Adopters and 0 Otherwise)

Marginal Parameter Estimate Effect Intercept -2.9177 Male-headed household 0.3107 0.0873 Age of household head squared -0.0001 -0.0000 Married household head -0.0908 -0.0277 Completed junior level education 0.2451 0.0796 Completed secondary level education 0.2864 0.0916 Received extension advice 0.1464 0.0440 Market information received, 1998 0.1918 0.0588 Hectares of land owned 0.0306 0.0092 Freehold tenure status 0.2824 0.0845 Household size 0.0264 0.0079 Income 0.1217 0.0365 Number of hoes owned 0.2661 0.0799