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Food Security Futures: some comments from
          a Brazilian perspective

                                                              Geraldo B. Martha Jr.




          Food Security Futures Conference, CGIAR-FAO, Dublin, Ireland, 10-11 April
Agricultural Productivity
Scenarios and Links to
Climate Change Models
Technology adoption vs. price effects
                                                                            Food Price Index             Meat Price Index
                                                                            Dairy Price Index
                                                                            Oils Price Index
                                                                                                         Cereals Price Index
                                                                                                         Sugar Price Index     Technology adoption versus
   Annual real food price (2002-2004=100)




                                            350,0
                                                                                                                               relative prices;
                                            300,0


                                            250,0                                                                              Relative prices versus land-
                                            200,0                                                                              competition;
                                            150,0
                                                                                                                               Relative prices versus food supply,
                                            100,0
                                                                                                                               price volatility and (exploitable)
                                             50,0
                                                                                                                               yield gaps;
                                              0,0
                                                    90

                                                         91

                                                              92

                                                                   93



                                                                           95

                                                                           96

                                                                           97

                                                                           98

                                                                           99

                                                                           00

                                                                           01

                                                                           02

                                                                           03



                                                                           05

                                                                           06

                                                                           07

                                                                           08

                                                                           09

                                                                           10

                                                                           11
                                                                           94




                                                                           04




                                                                        20
                                                19

                                                     19

                                                           19

                                                                19



                                                                        19

                                                                        19

                                                                        19

                                                                        19

                                                                        19

                                                                        20

                                                                        20

                                                                        20

                                                                        20



                                                                        20

                                                                        20

                                                                        20

                                                                        20

                                                                        20

                                                                        20
                                                                     19




                                                                        20




FAO (2011)




                                                         G.B.Martha, work in progress, data from IBGE.
Technology adoption vs. price effects




  IBGE database, Martha, Jr. (2012).
Agriculture production potential in Brazil
                                                                     2010 avg.      Top Producers    Research
                           12.000

                           10.000

                            8.000
           Yield (kg/ha)




                            6.000

                            4.000

                            2.000

                               0
                                               Rice                 Beans                 Corn              Soybean   Wheat


                                                                  2010, avg.     Top Producers   Research
                                                         350,00

 Crop-land area                                          300,00
                                                                                                                           Increase
 constant, 2010                                          250,00                                                                
                                          Million tons




 values                                                  200,00                                                         Top prod.: 36%
                                                         150,00                                                                
                                                         100,00
                                                                                                                        Research: 134%
                                                          50,00

                                                           0,00
                                                                                      R+B+C+S+W
                     Martha Jr. (2012).
Technology adoption vs. novel systems effects
Technology adoption vs. Climate Change effects

                       0-10 cm   0-30   0-50 cm




 Sousa et al., 1996.
Technology adoption vs. land-saving effects

   Stocking rate                      LWG      Productivity       Land-saving effect
             hd/ha                   (kg/hd)   (kg PV/ha/yr)   (ha spared/ha recovered)
                0,4                   100           40                    -
                0,7                   120           84                   1,1
                1,1                   135          149                   2,7
                1,6                   160          256                   5,4
G.B.Martha Jr. (work in progress).
Metrics, Prices, and Short vs. Long-term Trends




  MCT (2010).




                      Economist (2012 and 2013).
Embrapa's R&D Efforts
Agricultural R&D investiments - the case of
Brazilian Embrapa
                                                              Around 90% of the ag. research effort in
                                                              Brazil is public;

                                                              From 50% to 60% of Brazilian public
                                                              investment in agricultural R&D goes to
                                                              Embrapa;




     Martha Jr. & Lopes (2013), data from IBGE and Embrapa.
Agricultural Development
in a More Broad Context
Issues for Large-Scale Adoption of Low-
 Carbon Agricultural Technologies

1) Considering specific regional characteristics and resource endowments and
   possibilities to foster an inclusive low-carbon emission agriculture strategy:
 
 a) What is the cost of this new technology and its economic return / cash flow in
 comparison with technologies that are already in use in farms?
 b) What is the new technology’s opportunity cost considering other eligible
 agricultural activities in the region? How robust is the new technology’s comparative
 economic performance considering a range of relative prices and terms of trade?
 c) If this new technology is well implemented in farms, what is the potential to
 generate strong backward and forward linkages and thus foster virtuous cycles of
 development in rural areas?


                                                                             Martha Jr. & Vilela (2013).
Issues for Large-Scale Adoption of Low-
 Carbon Agricultural Technologies

1) Considering specific regional characteristics and resource endowments and
possibilities to foster an inclusive low-carbon emission agriculture strategy:
 
 d) What are the major changes required in infrastructure and supply chain
 arrangements relative to a business as usual scenario (and their associated
 timeline)?
 e) How dependent on (distorting vs. non-distorting) incentives is such strategy and
 for how long?

2) What is needed to better integrate poor farmers to the value of chain and to
increase their competitiveness in a low-carbon emission agriculture era? What
are the implications for their well-being and for the rural-to-urban migration
process?
                                                                             Martha Jr. & Vilela (2013).
Issues for Large-Scale Adoption of Low-
Carbon Agricultural Technologies

3) How do distortions to agricultural prices ultimately affect the adoption of
low-carbon emission technologies in the agricultural sector in developed,
developing and poor countries or in different regions inside a given country?

4) How can a widespread adoption of low carbon emission technologies in
agriculture eventually affect the volatility of food supply and prices, and what
are their regional welfare impacts? How factors of production in the economy
will adjust to such a stimulus?




                                                                       Martha Jr. & Vilela (2013).
Embrapa's Strategic Intelligence System

"Targeting possible futures, their challenges, solutions and
    opportunities for the technological development of
                   Brazilian Agriculture"
Thank You !


     The solely form of forecasting the future
     is to build it      (Antonio Delfim Netto, May 2012)

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Geraldo Martha Presentation at the Food Security Futures I Conference

  • 1. Food Security Futures: some comments from a Brazilian perspective Geraldo B. Martha Jr. Food Security Futures Conference, CGIAR-FAO, Dublin, Ireland, 10-11 April
  • 2. Agricultural Productivity Scenarios and Links to Climate Change Models
  • 3. Technology adoption vs. price effects Food Price Index Meat Price Index Dairy Price Index Oils Price Index Cereals Price Index Sugar Price Index Technology adoption versus Annual real food price (2002-2004=100) 350,0 relative prices; 300,0 250,0 Relative prices versus land- 200,0 competition; 150,0 Relative prices versus food supply, 100,0 price volatility and (exploitable) 50,0 yield gaps; 0,0 90 91 92 93 95 96 97 98 99 00 01 02 03 05 06 07 08 09 10 11 94 04 20 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 19 20 FAO (2011) G.B.Martha, work in progress, data from IBGE.
  • 4. Technology adoption vs. price effects IBGE database, Martha, Jr. (2012).
  • 5. Agriculture production potential in Brazil 2010 avg. Top Producers Research 12.000 10.000 8.000 Yield (kg/ha) 6.000 4.000 2.000 0 Rice Beans Corn Soybean Wheat 2010, avg. Top Producers Research 350,00 Crop-land area 300,00 Increase constant, 2010 250,00 Million tons values 200,00 Top prod.: 36% 150,00 100,00 Research: 134% 50,00 0,00 R+B+C+S+W Martha Jr. (2012).
  • 6. Technology adoption vs. novel systems effects
  • 7. Technology adoption vs. Climate Change effects 0-10 cm 0-30 0-50 cm Sousa et al., 1996.
  • 8. Technology adoption vs. land-saving effects Stocking rate LWG Productivity Land-saving effect hd/ha (kg/hd) (kg PV/ha/yr) (ha spared/ha recovered) 0,4 100 40 - 0,7 120 84 1,1 1,1 135 149 2,7 1,6 160 256 5,4 G.B.Martha Jr. (work in progress).
  • 9. Metrics, Prices, and Short vs. Long-term Trends MCT (2010). Economist (2012 and 2013).
  • 11. Agricultural R&D investiments - the case of Brazilian Embrapa Around 90% of the ag. research effort in Brazil is public; From 50% to 60% of Brazilian public investment in agricultural R&D goes to Embrapa; Martha Jr. & Lopes (2013), data from IBGE and Embrapa.
  • 12. Agricultural Development in a More Broad Context
  • 13. Issues for Large-Scale Adoption of Low- Carbon Agricultural Technologies 1) Considering specific regional characteristics and resource endowments and possibilities to foster an inclusive low-carbon emission agriculture strategy: a) What is the cost of this new technology and its economic return / cash flow in comparison with technologies that are already in use in farms? b) What is the new technology’s opportunity cost considering other eligible agricultural activities in the region? How robust is the new technology’s comparative economic performance considering a range of relative prices and terms of trade? c) If this new technology is well implemented in farms, what is the potential to generate strong backward and forward linkages and thus foster virtuous cycles of development in rural areas? Martha Jr. & Vilela (2013).
  • 14. Issues for Large-Scale Adoption of Low- Carbon Agricultural Technologies 1) Considering specific regional characteristics and resource endowments and possibilities to foster an inclusive low-carbon emission agriculture strategy: d) What are the major changes required in infrastructure and supply chain arrangements relative to a business as usual scenario (and their associated timeline)? e) How dependent on (distorting vs. non-distorting) incentives is such strategy and for how long? 2) What is needed to better integrate poor farmers to the value of chain and to increase their competitiveness in a low-carbon emission agriculture era? What are the implications for their well-being and for the rural-to-urban migration process? Martha Jr. & Vilela (2013).
  • 15. Issues for Large-Scale Adoption of Low- Carbon Agricultural Technologies 3) How do distortions to agricultural prices ultimately affect the adoption of low-carbon emission technologies in the agricultural sector in developed, developing and poor countries or in different regions inside a given country? 4) How can a widespread adoption of low carbon emission technologies in agriculture eventually affect the volatility of food supply and prices, and what are their regional welfare impacts? How factors of production in the economy will adjust to such a stimulus? Martha Jr. & Vilela (2013).
  • 16. Embrapa's Strategic Intelligence System "Targeting possible futures, their challenges, solutions and opportunities for the technological development of Brazilian Agriculture"
  • 17. Thank You ! The solely form of forecasting the future is to build it (Antonio Delfim Netto, May 2012)