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Adoption, Yields, Profits, Efficiency, Employment

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Adoption, Yields, Profits, Efficiency, Employment

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  1. Eight Years of GM Adoption by Smallholders in KwaZulu NatalMarnus Gouse and Johann KirstenDepartment of Agricultural Economics, Extension and Rural Development, University of PretoriaJenifer PiesseDepartment of Management, King’s College London and University of StellenboschColin ThirtleCentre for Environmental Policy, Imperial College London, University of Pretoriaand University of Stellenbosch16th ICABR ConferenceRavello 13-27 June 2008

  2. Adoption, Yields, Profits, Efficiency, Employment Results for 8 years show the rapid changes & transition Single area or year results do not persist To advise policy we need to see how new seeds use develops as farmer’s learn and adapt Herbicide tolerant is winning out and reduces employment by over 50% - private benefit but social cost? Need to know the output change

  3. Percentage of total South African maize area using GM This shows 70% is GM and Bt is the favourite with about 45%. But this is 96% commercial farmers. Smallholders grow 16.2% of the acreage and produce only 4.2% of the output. How different are they from commercial farmers?

  4. Number of surveys in Hlabisa and maize plots used in analysis 58 58 65 16

  5. Yields of conventional, Bt and HT maize, 8 seasons 2001/02 - 2009/10

  6. Yield comparison for Conventional, Bt, HT and BR maize (kg grain / hectare)

  7. Seed types with highest profit or lowest loss for the four seasons

  8. Data - Variables District – Hlabisa (Simdlangentsha – Dumbe 2006-7) • Output – kgs of maize • Land – hectares • Family Labour • Hired Labour • Seed cost • Fertilizer cost • Herbicide cost • Land preparation dummy • Area/farmer/soil quality dummy

  9. Stochastic Frontier • The general form of the production frontier is • The Vi’s are independently and identically distributed random error terms and uncorrelated with the regressors, and the Ui’s are non-negative random variables associated with the technical inefficiency of the firm.

  10. Hypothesis Tests

  11. Frontier Model - Elasticities

  12. Ranking of Seed Varieties by District and Method, 2006/7

  13. Land preparation method indication by Hlabisa farmers

  14. Family labour per hectare by seed type (7 hour man-days)

  15. Conclusions • First 2 years–Bt looked fine–then more arid, no gain • 2006 HT stops erosion, high yields, 10% less work • By 2009, HT & BR are adopted, but 50% less work • Change prep & planting methods–learning by doing • Like tractors in Asia in 1960s? Not in KZN perhaps • Need to know the substitution & output effects of TC • If land is not the constraint output could double and employment increase – if not employment falls hard • Small samples give any answer you want as they vary so much over time and space. • How many areas and years for sound policy advice? • So commercial maize is Bt – smallholders is HT – why?

  16. DfID study - BIASES, ENDOWMENTS & IMPACTS • The distributional impact of biased technological change depends both on the factor saving (or using) biases and the factor endowments in the economy. • If a labour saving technology is introduced in a land scarce/labour abundant economy labour incomes will fall and poverty will increase. • But labour for planting is the constraint in much of SSA. Economic development with unlimited supplies of land – Bent Hansen • If land is poor but plentiful, planting area and output could double and labour demand for all other tasks increase substantially. Can we guess for Malawi?

  17. Rockefeller supported studies of Bt maize amongst smallholders 2001/02 – relatively high stalk borer infestation 32% 2002/03 – lower pressure = 16% in KZN (Hlabisa and Simdlangentsha) 2003/04 – no borers = found no benefit

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