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Cereal Production and Technical Change in Ethiopia


        Alejandro Nin-Pratt, Binxing Yu, José Funes and Sinafikeh Asrat


                                 Presented by
                 John Hoddinott on behalf of Alejandro Nin-Pratt

                   Paper prepared for the IFPRI – ESSP2 conference
                         Addis Ababa, October 22-24, 2009



                                                                     Wednesday, November 04, 2009
Introduction


• Increasing yields is critical for sustaining output growth in Ethiopian
  agriculture.

• Improved agricultural technologies are critical for yield growth

• Given this, this presentation focuses on two questions:
   – What factors assist, or inhibit , the adoption of these technologies
   – What are the consequences of their adoption for yields

• In developing this work, we draw on very rich data, the Agricultural
  Sample Survey (AgSS), nationally representative data made available to
  the research team by the Central Statistical Agency



                                     Page 2
ADOPTION




  Page 3
Trends in the use of fertilizer and improved seeds




     Area (1000 ha) sown to barley, maize, sorghum, teff and wheat




                               Page 4
Page 5
What factors are associated with the adoption of fertilizer and
                  improved seeds at the plot level?
•        Pool data across four years and use logit estimation model to plot level
         outcomes
•        Two outcomes
     –      Fertilizer is applied to this plot (=1 if yes, 0 otherwise)
     –      Fertilizer and improved seeds are applied to this plot (=1 if yes, 0 otherwise)
•        Factors
     –      Time trend (captures secular factors that affect adoption)
     –      Number of oxen available to the plot holder
     –      Suitability of the area for production of the crop grown on the plot (wereda-level
            aggregate)
     –      Population density per square kilometer (wereda-level aggregate)
     –      All-weather road density in meters per square kilometer (wereda-level aggregate)
     –      Holder used extension services
     –      Holder used credit




                                                 Page 6
Marginal effects of different variables on the probability of
                      adopting fertilizer

0.45
 0.4
                                            Year
0.35
                                            Oxen
 0.3
                                            Suitability
0.25
                                            Population density
 0.2
                                            All-weather road density
0.15
                                            Extension
 0.1
                                            Credit
0.05
                                            Improved seed
   0
-0.05   Maize       Teff      Wheat




                             Page 7
Marginal effects of different variables on the probability of
          adopting fertilizer and improved seeds

  0.2


 0.15                                      Year
                                           Oxen

  0.1                                      Suitability
                                           Population density

 0.05                                      All-weather road density
                                           Extension

   0                                       Credit
           Maize          Wheat

-0.05




                            Page 8
IMPACT




 Page 9
Average cereal yields obtained using different combination of
                        inputs (tons)

           Fertilizer & local seed             Improved seed no fertilizer
           Improved seed and fertilizer        Local seed no fertilizer
  3.0

  2.5

  2.0

  1.5

  1.0

  0.5

  0.0
           2003                2004                    2006               2007




                                     Page 10
Difference in yield obtained by holders with access to
                  extension and credit
    Disaggregated by adopters and non-adopters of modern inputs


     160
     140
     120
     100
      80
      60
      40
      20
       0
     -20
                Adopters       Non-adopters       Adopters       Non-adopters


                           Extension                        Credit

           Only differences shown in red are statistically significant



                                              Page 11
Summary
•    Based on these preliminary results:
    – Access to modern crop technologies are “tightly wedded” to access
        to extension services
    – Yield improvements are the outcome of a package deal, where the
        package includes fertilizers and seeds and extension services

• Future work;
   – Use more data rounds
   – Increase sophistication of the empirical analysis: Examine production
     frontiers, technical efficiency, changes in total factor productivity
   – “Unpack” the package nature of the drivers of yield improvements




                                   Page 12

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Cereal Production and Technical Change in Ethiopia

  • 1. Cereal Production and Technical Change in Ethiopia Alejandro Nin-Pratt, Binxing Yu, José Funes and Sinafikeh Asrat Presented by John Hoddinott on behalf of Alejandro Nin-Pratt Paper prepared for the IFPRI – ESSP2 conference Addis Ababa, October 22-24, 2009 Wednesday, November 04, 2009
  • 2. Introduction • Increasing yields is critical for sustaining output growth in Ethiopian agriculture. • Improved agricultural technologies are critical for yield growth • Given this, this presentation focuses on two questions: – What factors assist, or inhibit , the adoption of these technologies – What are the consequences of their adoption for yields • In developing this work, we draw on very rich data, the Agricultural Sample Survey (AgSS), nationally representative data made available to the research team by the Central Statistical Agency Page 2
  • 4. Trends in the use of fertilizer and improved seeds Area (1000 ha) sown to barley, maize, sorghum, teff and wheat Page 4
  • 6. What factors are associated with the adoption of fertilizer and improved seeds at the plot level? • Pool data across four years and use logit estimation model to plot level outcomes • Two outcomes – Fertilizer is applied to this plot (=1 if yes, 0 otherwise) – Fertilizer and improved seeds are applied to this plot (=1 if yes, 0 otherwise) • Factors – Time trend (captures secular factors that affect adoption) – Number of oxen available to the plot holder – Suitability of the area for production of the crop grown on the plot (wereda-level aggregate) – Population density per square kilometer (wereda-level aggregate) – All-weather road density in meters per square kilometer (wereda-level aggregate) – Holder used extension services – Holder used credit Page 6
  • 7. Marginal effects of different variables on the probability of adopting fertilizer 0.45 0.4 Year 0.35 Oxen 0.3 Suitability 0.25 Population density 0.2 All-weather road density 0.15 Extension 0.1 Credit 0.05 Improved seed 0 -0.05 Maize Teff Wheat Page 7
  • 8. Marginal effects of different variables on the probability of adopting fertilizer and improved seeds 0.2 0.15 Year Oxen 0.1 Suitability Population density 0.05 All-weather road density Extension 0 Credit Maize Wheat -0.05 Page 8
  • 10. Average cereal yields obtained using different combination of inputs (tons) Fertilizer & local seed Improved seed no fertilizer Improved seed and fertilizer Local seed no fertilizer 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2003 2004 2006 2007 Page 10
  • 11. Difference in yield obtained by holders with access to extension and credit Disaggregated by adopters and non-adopters of modern inputs 160 140 120 100 80 60 40 20 0 -20 Adopters Non-adopters Adopters Non-adopters Extension Credit Only differences shown in red are statistically significant Page 11
  • 12. Summary • Based on these preliminary results: – Access to modern crop technologies are “tightly wedded” to access to extension services – Yield improvements are the outcome of a package deal, where the package includes fertilizers and seeds and extension services • Future work; – Use more data rounds – Increase sophistication of the empirical analysis: Examine production frontiers, technical efficiency, changes in total factor productivity – “Unpack” the package nature of the drivers of yield improvements Page 12