1. Determinants of Changing Behaviors of NERICA Adoption: An Analysis of Panel Data from Uganda Yoko Kijima (University of Tsukuba) Keijiro Otsuka (FASID) Dick Sserunkuuma (Makerere University) Workshop on African Green Revolution Tokyo December 7, 2008 1

2. 2 Motivation and Background There is need for enhancing crop yield and food production in SSA for alleviating widespread poverty and food insecurity in SSA Rice in Uganda: –Rice is one of the high value crops and consumption has been increasing in Uganda –Except very limited areas, most of the farmers had never grown rice before NERICA –Seed distribution program: Seed (+ Training)

3. 3 Motivation and Background NERICA 1 Survey (2004)  Data was collected soon after NERCIA seed dissemination program initiated by Vice President of Uganda  Sample: 10 NERICA growing areas in Central and Western regions (29 LC1s), 250 NERICA and 150 non-NERICA households in 2004 (stratified random sampling) Poverty alleviation in Uganda using NERICA –Kijima, Sserunkuuma, and Otsuka (2006): NERICA yield is more than twice as high as upland rice yield in SSA. –Kijima, Otsuka and Sserunkuuma (2008): Simulation analysis suggests that introduction of NERICA increases in per capita income by 12% and decreases in poverty head count ratio by 5 percentage points, without deteriorating income distribution

4. 4 Motivation and Background NERICA 2 Survey  Total sample size becomes 347 households  Attrition due to moving-out from sample areas, dissolution of households, no contact during the data collection period  Four types of farmers: (1) non-adopters, (2) dropouts (adoption only in 2004), (3) continuous adopters, and (4) late adopters (adoption only in 2006). Adoption pattern: Panel data in 2004 and 2006: –50% of NERICA adopter in 2004 abandoned it in 2006 –20% of non-adopter in 2004 adopted NERICA in 2006 Is NERICA really profitable? Is the profitability of NERICA sustainable?

5. 5 Other Observations Changes in markets between 2004 and 2006 –Market of rice milling service have developed (Fig. 1) –The use of self-produced seeds by farmers became common –NERICA yield among continuous adopter is higher than dropout and late adopter Source: Alphonse et al. (2008)

6. Table 1a. Sample Household Characteristics in 2004 Non- adopter Dropout Continuous adopter Late adopter Number of households 94129 99 25 Rice experience (years) 0.071.49 1.88 0.50 Household head’s age 48.748.2 43.9 49.4 HH head’s years of schooling 4.97.0 7.7 4.5 Number of male age 15-59 1.431.80 1.81 0.99 Number of female age 15-59 1.501.96 1.68 1.34 Female headed household 0.330.10 0.08 0.30 Bakiga tribe 0.000.08 0.09 0.20 Per capita land owned (ha) 0.240.38 0.47 0.38 Land (owned + mailo) (ha) 2.564.52 4.23 2.53 Land cultivated (ha) 0.921.19 1.30 0.78 Household asset (USD) 160.2149.4 171.9 53.7 Value of livestock (USD) 306.9370.5 389.7 79.5 6

7. Table 1b. Sample Community Characteristics Non- adopter Dropout Continuous adopter Late adopter Availability of seed program 04 0.190.37 0.34 0.17 Availability of seed program 06 0.110.20 0.29 0.24 Distance to rice miller 04 (km) 19.015.4 26.9 28.9 Distance to rice miller 06 (km) 14.111.1 6.2 5.5 Traveling time to town (hour) 0.420.62 0.77 0.66 Area size per HH (mile 2 ) 0.02 Relative price of maize to rice 0.390.51 0.47 0.45 Rainfall 04 (mm, crop. season) 368.5424.0 429.6 393.0 Rainfall 06 (mm, crop. season) 446.2435.8 432.0 450.2 Average rainfall (01-06) 409.4435.5 441.3 421.6 C.V. of rainfall (01-06) 0.200.17 0.15 0.17 7

8. Summary of Descriptive Table 1 Early adopters are more educated, have more adult members, and more assets than the other groups There are no differences in household characteristics between dropouts and continuous adopters In 2004, seed distribution program seems enhance NERICA adoption, while availability of the program declined in 2006, except late adopters Access to rice miller improved in 2006, especially in areas with continuous and late adopters Rainfall variation is higher in areas with non-adopter

9. Table 2a. Sample NERICA Plot Characteristics 2004 2006 Drop out Continuou s adopter Late adopter Yield (ton per ha) 2.012.972.541.49 Seed source (%) Self-produced seed 5.27.741.55.8 Purchased seed from neighbor 3.811.712.046.5 Program seeds (NGO, VP) 53.842.915.010.2 Other (purchased, contract farming) 37.237.731.537.5 Yield (ton per ha) by seed source Self-produced seed 0.993.412.061.15 Purchased seed from neighbor 1.352.722.971.17 Program seeds (NGO, VP) 1.762.962.953.46 Other (purchased, contract farming) 2.492.992.751.39 Plot size (ha) 0.420.380.470.24

10. Table 2b. Sample NERICA Plot Characteristics 2004 2006 Drop out Continuou s adopter Late adopter % plots in low lying location 11.814.121.721.8 Yield in low lying location 2.042.832.091.22 Yield not in low lying location 2.013.002.671.56 % late planting 8.52.811.16.1 Yield in late planting plot 2.203.052.561.43 Yield not in late planting plot 0.680.632.442.31 % plot with zero yields 4.40.46.924.9

11. Summary of Descriptive Table 2 The average yield for continuous adopters are higher than that of dropouts and of late adopters 25% of the late adopters failed crop totally (zero yields) Type of seeds used changed from program seeds to self-produced and seeds from neighbors Yield of self-produced seeds tends to be lower Among continuous adopters, yield of self-produced seeds is lower than that of the other type of seeds Other management issues between continuous and late adopters: low lying areas and timing of planting – no significant difference

12. Purposes of Estimation Model Why did so many early adopters become dropouts? What are the underlying factors for the superior performance of the continuous adopters? How can we increase NERICA yields? *Focus: effects of rainfall, availability of seed program, access to rice millers, and availability of seeds on adoption and yields

13. Estimation Model Changing behavior of adoption decision Multinomial logit model of 4 adopter types: Non-adopter, dropout, continuous adopter, late adopter Yield function Cross section data (regress 2004 and 2006 separately) Controlling for selection bias of adopting rice Possibility of endogeneity of seed type used: 2 specifications – (a) availability of seed program, (b) set of seed types dummies

14. Table 3. Determinants of NERICA Adoption (Multinomial Logit Model, Marginal Effects) Community characteristicsDropout Continuou s adopter Late adopter Non- adopter Average rainfall (01-06) -0.000 0.001-0.000 C.V. of rainfall (01-06) 0.421+ -0.131 -0.655**0.365 Availability of seed program 04 0.096+ 0.082* -0.122+-0.056 Availability of seed program 06 0.017 -0.021 0.077-0.073 Relative price of maize to rice 04 0.042 -0.042 0.143+-0.142 Community area size per HH 04 -3.286* -2.112+ -1.5616.959** Distance to rice miller 04 (km) -0.002* -0.000 0.006**-0.004 Distance to rice miller 06 (km) -0.001 -0.003* -0.006**0.007** Traveling time to town 04 (hour) 0.165* 0.145** -0.201*-0.109 14

15. Table 3. Determinants of NERICA Adoption, cont (Multinomial Logit Model, Marginal Effects) Household characteristicsDropout Continuous adopter Late adopter Non- adopter Rice cultivation experience 0.063* 0.039* 0.006+-0.163** Household head’s age 0.021 0.005 -0.069**0.043 HH head’s years of schooling 0.023 0.002 0.007-0.032 Number of male age 15-59 -0.075+ -0.024 0.0220.078 Number of female age 15-59 0.116 0.034 0.367-0.517* Female headed household 0.001 -0.001 0.000-0.000 Bakiga tribe 0.005 0.008* 0.007-0.020** Per capita land (ha) -0.001 0.002 0.034-0.037 Household asset (USD) 0.009 0.005 -0.0340.021 Value of livestock (USD) 0.010 0.016 -0.155*0.130 Constant -0.256* -0.102 -0.292+0.650** 15

16. 16 Summary of Regression Results NERICA adoption Rainfall variation: Dropout: higher variation (mis-targeting of the program) Later adopter: smaller variation (suitable) Availability of seed program: Increase adoption in 2004 No effect on adoption in 2006 - probably due to the self- production of seeds and trade among farmers. Improved access to rice millers increases adoption

17. Table 4. Determinants of NERICA Yield (with selection correction term) 2004 200620042006 (1) (2)(3)(4) Availability of seed program -0.3470.378** Seed source dummies Seed from neighbor -0.2940.051 Program seed -0.6141.140** Purchased from seed company -0.670-0.219 Rainfall (cropping season) -0.0000.003** 0.002** Distance to rice miller (km) 0.010-0.023*0.008*-0.024* Traveling time to town 0.1600.1720.2920.450* 17

18. Table 4. Determinants of NERICA Yield, cont. 2004 200620042006 (1) (2)(3)(4) Rice cultivation experience 0.073*0.124**0.0310.128** Number of male age 15-59 0.217+0.064-0.176**0.137+ Number of female age 15-59 0.162-0.114-0.024-0.165* Female headed household -0.106-0.216-0.341-0.131 Bakiga tibe -1.529**-0.328+0.159-0.586** Household head age -0.032**-0.021**-0.026**-0.012** HH head’s education 0.045-0.034+0.024-0.026 Per capita land (ha) -0.1200.2430.253*0.253+ Household asset # 0.0820.495-0.2420.577* Value of livestock # -0.2650.365*-0.291*0.280 Constant 2.843**1.745**2.386**1.095* 18 # Unit is thousand USD

19. 19 Summary of Regression Results NERICA yield Quality of self-produced seeds seems to be deteriorated over time: –Availability of seed program and use of program seed (treated seeds) increase yield only in 2006 Rainfall increases yield Rice cultivation experience increases yields Shortened distance to rice millers increases yield in 2006

20. 20 Conclusions Adoption process is dynamic, involving dropout We observed strong indications of the failure of extension (provision of inappropriate or insufficient information on seed production and crop management, mis-targeting of seed distribution program areas, etc.) –Strong need for capacity building of extension workers Markets have developed responding to demand for market services. Such development promoted adoption and yield growth. –Support for further development of markets will contribute to the efficiency of rice production.