Th4_How accessibility to seeds affects the potential adoption of an improved rice based technology:
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share

Th4_How accessibility to seeds affects the potential adoption of an improved rice based technology:

  • 404 views
Uploaded on

3rd Africa Rice Congress ...

3rd Africa Rice Congress
Theme 4: Rice policy for food security through smallholder and agribusiness development
Mini symposium 4: Evidence of impact and adoption of rice technologies
Author: Dibba

More in: Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
404
On Slideshare
404
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
3
Comments
0
Likes
1

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. 1 How accessibility to seeds affects the potential adoption of an improved rice based technology: The case of New Rice Varieties for Africa (NERICA) in The Gambia Varieties for Africa (NERICA) in The Gambia Lamin Dibba*, Manfred Zeller, Aliou Diagne and Thea Nielsen
  • 2. 2 Outline of the presentation 1. Introduction 2. Objective of the study 3. Methodology 4. Results and discussion 5. Conclusions 6. Acknowledgments 7. Reference
  • 3. Introduction • The per capita consumption of rice is estimated at 177kg per annum (PSU, 2011) • Of the 195,811 metric tons of rice consumed in 2011, only 51,137 metric tons was produced locally (Agricultural census, 2012) • Out of the 51,137 metric tons of rice produced locally in 2011, 23,302 metric tons were entirely attributed to NERICA cultivation (Agric census, 2012) • Past studies that assess NERICA adoption in The Gambia control only exposure or awareness (Dibba et. al., 2012; Diagne et. al., 2012) 3
  • 4. Objectives • Assess NERICA adoption by controlling for both exposure and seed access • Provide estimates of actual and potential adoption rates and their determinants of the NERICA varieties • Determine the adoption gap that arises due to lack of access to adequate supply of NERICA seeds 4
  • 5. 5 Methodology: Sampling procedure and data • Multi-stage stratified random sampling procedure to select villages and farmers across the six agricultral regions • 5 NERICA seed dessimination and non NERICA seed dessination villages randomly selected from each region • 10 rice farmers randomly selected in each village • Data collected included both agronomic and socio-economic information
  • 6. 6 Methodology: Conceptual framework • This study relies on the potential outcome framework to assess the effect of exposure and access to seeds on NERICA adoption • Every farmer has two potential or counterfactual outcomes (Y1 and Y0 ) for each treatment (Rosenbaum and Rubin, 1983) • The causal effect of each treatment (Y1 - Y0 ) • In the adoption context Y0 = 0 for any observational unit whether treated or untreated • The adoption impact for farmer i is given by Yi1 and the average impact is given by ATE = E(Y1 )
  • 7. 7 Methodology: Estimation of adoption rates • The Conditional Independence (CI) assumption (Rosenbaum and Rubin,1983): • w(s) is independent of Y1 and Y0 conditional of X • Potential adoption is independent from Zi conditional on Xi (Diagne and Demont, 2007) • Exposure or access to seed is independent of Xi conditional on Zi • Overlap for all covariates. Then ATE is semiparametrically identified by equation 1 ˆ ATE e , s 1 n n i 1 ˆ m( xi ) .......... .......... ......( 1) ˆ p ( zi )
  • 8. 8 Results and Discussion Table 1: Comparison of 2006 and 2010 survey results Variable 2006 (N=600) 2010 (N=515) Difference (T-test) Exposure to NERICA 0.47 (0.02) 0.88 (0.01) 0.41 (0.02)*** Adoption within NERICA exposed sub-population 0.85 (0.03) 0.77 (0.03) -0.08 (0.03)*** NERICA sample adoption 0.40 (0.02) 0.66 (0.02) 0.26 (0.03)*** Practice of upland rice production 0.53 (0.02) 0.78 (0.02) 0.25 (0.03)*** Practice of lowland rice production 0.80 (0.02) 0.43 (0.02) - 0.36 (0.03)*** Farmer contact with NARI 0.5 (0.01) 0.21 (0.02) 0.16 (0.02)*** Farmer contact with DAS 0.31(0.02) 0.32 (0.02) 0.01(0.03)
  • 9. 9 Results and Discussion Table 2: Actual adoption of NERICA varieties in 2010 Description Regions WCR LRR Total CRS NBR CRN URR Total number of farmers 89 85 89 92 78 82 515 Proportion of farmers exposed to 99 95 62 100 86 89 88 84 93 38 80 71 68 72 2008 54 69 20 67 31 56 50 2009 65 79 29 67 59 72 61 2010 76 88 35 72 62 65 66 NERICAs in 2010 (%) Proportion of exposed farmers who had access to NERICA seeds in 2010 (%) Proportion of farmers who adopted at least one NERICA (%)
  • 10. 10 Results and Discussion Table 3: ATE semi-parametric estimation of potential adoption rates ATE exposure ATE access to model seeds model Adoption gap due to lack of seeds NERICA population adoption rate (ATE) 0.76 (0.29)*** 0.92(0.09)*** 16% Adoption rate within the NERICA-exposed and 0.76 (0.34)** 0.92(0.11)*** 16% 0.73 (0.11)*** 0.89(0.05)*** 16% 0.66(0.28)*** 0.66(0.08)*** -0.10 (0.02)*** -0.26(0.01)*** 0.01 (0.05) -0.01 (0.03) seed accessed subpopulation (ATE1) Adoption within the NERICA non exposed and seed accessed subpopulation (ATE0) Joint exposure and adoption (JEA) Adoption gap of NERICA (GAP) Expected population selection bias when using the within NERICA – exposed and seed accessed sub-sample estimate (PSB)
  • 11. 11 Results and Discussion Table 4: Factors affecting exposure, access to seeds and adoption Age Years of experience in upland farming Formal education Household size Off-farm labor Woman Member of association Log of rice area in 2006 Farmer contact with extension Access to credit Farmer contact with NARI Practice of upland farming Practice of lowland farming West coast region NERICA introduction village Coefficients of Exposure -0.01 (0.007) 0.01 (0.009) Coefficient of Coefficient of Access to seeds Adoption -0.01* (0.005) -0.01 (0.006) 0.02***(0.006) 0.017** (0.008) 0.49 (0.507) 0.069** (0.030) -1.705*** (0.491) -1.017***(0.476) -0.059 (0.261) -0.233** (0.118) 0.54** (0.246) -0.017 (0.250) 0.02 (0.242) 0.02 (0.016) -0.67* (0.364) 0.03 (0.523) -0.28 (0.182) -0.09 (0.077) 0.59*** (0.154) 0.30* (0.169) 0.43*** (0.169) 1.60***(0.226) -0.07 (0.222) 1.22*** (0.46) 0.22 (0.209) 0.73*** (0.161) 0.06 (0.148) 0.32 (0.208) 0.28**(0.141) 0.16 (0.312) -0.02 (0.019) 0.449 (0.738) 0.31 (0.289) -0.28 (0.212) 0.00 (0.089) 0.494***(0.175) 0.45**(0.217)
  • 12. Conclusion • If every rice farmer is aware of the NERICA varieties 16% will not be able to adopt due to insufficient supply of seeds • For successful dissemination and adoption of NERICA concerted efforts should be made to increase farmer contact with extension • Future studies should focus on measuring the intensity of NERICA adoption 12
  • 13. Acknowledgment • Global Rice Science Program • Africa Rice Center • University of Hohenheim 13
  • 14. 14 Thank you! 14
  • 15. References • Agricultural census. 2012: Technical report of the agricultural census of The Gambia • Diagne A, Glover S, Groom B and Phillips J. 2012. “Africa’s Green Revolution? The determinants of the adoption of NERICAs in West Africa” SOAS Department of Economics Working Paper Series, No. 174, SOAS, University of London • Diagne A and Demont M. 2007. Taking a New look at Empirical Models of Adoption: Average Treatment Effect estimation of Adoption rate and its Determinants. Agricultural Economics, Vol 37 (2007). 30p. • Dibba L, Diagne A, Fialor SC and Nimoh F (2012). Diffusion and Adoption of New Rice Varieties for Africa (NERICA) in the Gambia. African Crop Science Journal, Vol. 20, No. 1, pp. 141 – 153 • Planning Service Unit. 2011. Rice fact book. Unpublished technical report • Rosenbaum PR and Rubin DR.1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects,” Bometrika 70, 41-55. 15