Mintewab Biodiversity And Productivity1

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  • 1. Mintewab Bezabih, Salvatore Di Falco & Mahmud Yesuf
  • 2. Background
    • Maintaining diverse plant varieties on farmers’ fields is increasingly regarded as an efficient way of conservation of plant genetic resources.
    • Whether in-situ conservation could be pursued as a fruitful strategy of keeping important germplasms alive is dependent on whether it generates farm level benefits that are internalized by farmers.
    • Does crop diversity generate enough farm-level benefits to justify sufficient insitu conservation?
  • 3. Ecological and experimental agricultural studies
    • Biodiversity is an important component of ecological systems (e.g., Heal, 2000;Lenné and Wood, 1999).
    • Plant biomass is an increasing function of diversity (Lehman and Tilman, 2000).
    • Its loss can have adverse effects on the functioning of these systems (e.g., Loreau and Hector, 2001)
    • Higher diversity systems give greater yields than lower ones (Tilman et al ., 2005).
    • The productivity benefit of diversity is higher when environmental (weather factors) are taken into account (e.g. Norberg et al., 2001).
  • 4. Previous economic studies
    • The impact of biodiversity on productivity are generally positive (low).
    • Methods
      • Aggregate panel data analysis (e.g. Smale et al. 1998; Widawsky and Rozelle, 2001)
      • Farm level analysis using cross section data (e.g. Di Falco et al, 2007)
  • 5. Gaps
    • aggregate panel data analysis: the scale of these analyses does not allow controlling for farm agro-ecological characteristics and implicitly assumes that the underlying theoretical model can be scaled up at a macro level.
      • farm level analysis using cross section data : This approach has the obvious shortcoming of neglecting dynamics.
      • The impact of weather related factors in the productive role of biodiversity is not taken into account.
  • 6. Contribution
    • In light of the findings and the methods of previous similar assesments, the major contribution of the paper is:
    • Explit incorporation of the role of weather (rainfall) on the decision to maintain diversity.
    • Panel plot level production data
      • Provides: multi-crop observation for household and and across years, and addresses the issue of heterogeneity.
    • weather data (over time) matching the villages
      • Responsiveness to actual weather
  • 7. Data
    • Survey data:
      • Data are taken from three rounds of survey conducted in 2000, 2002 and 2005, involving approximately 1500 households in two districts of the Amhara National Regional State of Ethiopia.
    • Weather data
      • Seven-year monthly rainfall data from the Ethiopian Meteorological Authority.
  • 8. Estimation method
    • We frame our analysis of impact of crop biodiversity on farm household productivity under the standard theory of portfolio choice.
    • The problem facing a representative risk averse farm household is to
    • 1)Determine a production function that includes diversity
    • 2) chose an optimal level of crop diversity to maximize her expected utility from final wealth at the end of the production period, given the production function and her land, labor and other resource constraints.
  • 9. Estimation method (contd.)
  • 10. Estimation method (contd.)
    • As diversity is measured as count index, a Poisson estimation is used in the diversity regression.
    • To estimate the productivity model, we employed a pseudo-fixed effect model.
      • A standard fixed effect model has an obvious advantage over random effect and other linear models : controlling unobserved heterogeneity.
      • However, standard fixed effect models rely on data transformation that removes the individual effect.
      • Pseudo-fixed effect model ( which is run as a random effect model but at the same enables controlling for unobserved heterogenity by including mean values of time varying explanatory variables) -Mundlak’s approach ( Wooldridge 2002).
  • 11. Determinants of productivity
  • 12. Determinants of diversity (poisson estmation
  • 13.
    • The results are very similar to those we have estimating the two equations simultaneously.
  • 14. 3SLS estmation: Determinants of productivity Variables Coeffs Std errors P value Fertility -113.4782 90.06769 0.208 Flat slope -29.00117 98.00596 0.767 Labour 42.59281 69.36276 0.539 Labour ^2 9.801794 4.131985 0.018 Land 616.3177 73.68763 0.000 Land^2 -41.1687 4.401167 0.000 Oxen 47.67628 17.43194 0.006 Oxen^2 -.0621838 .0224521 0.006 Fertilizer .7430171 .1993151 0.000 Fertilizer^2 -.0000508 .0000156 0.001 Manure .0037627 .0205699 0.855 Rainfall 3.433479 1.650406 0.037 Improved seeds .3050942 .2880149 0.289 Crop Biodiversity 1175.067 472.5374 0.013 Biodiversity*Rainfall -.9440316 .3937311 0.017 Constant -3737.004 1923.756 0.052
  • 15. 3SLS estmation: determinants of diversity Variables Coeffs Std errors P value Fertility -.0266876 .1016266 0.793 Flat slope -.0840308 .1100031 0.445 Labour -.0437355 .0525935 0.406 Landsize .243942 .0543871 0.000 Oxen .0025103 .0016516 0.129 Fertilizer -6.46e-06 .0000789 0.935 Manure .0000786 .0000226 0.001 Rainfall .0018248 .0002119 0.000 Improved seeds -.0003128 .000324 0.334 Lagged rainfall -.0006388 .0002104 0.002 Gender -.4186447 .1079681 0.000 Training -.2318708 .1042899 0.026 Tenure security -.1000302 .0378401 0.008 Constant 2.399388 .3703267 0.000
  • 16. Conclusions
    • The main focus of the study has been assessing whether whether biodiversity is beneficial at a farm level.
    • The findings of the study are:
      • Diversity contributes to increased their productivity, esp when wheather is not favorable.
  • 17. Conclusions (contd.)
    • The huge agro-biodiversity resource Ethiopia has can be tapped and used towards improving the dismal performance of the country’s agricultural productivity performance.
    • At the same time, in-situ conservation could be promoted.