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Measurement of competitiveness in smallholder livestock systems and emerging policy advocacy: An application to Botswana

  1. Measurement of competitiveness in smallholder livestock systems and emerging policy advocacy: An application to Botswana S. Bahta (ILRI) and P. Malope (BIDPA) Conference on Policies for Competitive Smallholder Livestock Production Gaborone, Botswana, 4-6 March 2015
  2. Structure of Presentation Introduction and objectives Methodological approach Results and discussion Conclusion and policy implications
  3. Introduction and background • Agric. Dominated by livestock production, esp. beef. • Dual production systems, with communal dominating • Productivity low esp. in the communal sector • Not clear as to whether beef production is competitive • Studies have relied on budgetary analysis and limited household data • Others have calculated comp. at macro level
  4. Objectives • Measure competitiveness of beef production using household data • Specifically the study seeks to: • Identify the determinants of profitability • Identify efficiency drivers • Measure overall profit efficiency of beef production • Come up with policy recommendations to improve profitability of beef production
  5. Competetiviness defined • Competitiveness has many definitions • Competitiveness can be measured at three levels, macro; meso and micro-levels • Study measure competitiveness at micro level • Definition at micro level relate to profitability • “the ability to sell products that meet demand requirements in terms of price, quality & quantity and at the same time ensure profits”
  6. Methodology - Study area
  7. Approach • Translog profit frontier function • Dependent variable = profit per beef equivalent • Independent variable = weighted output price, Input prices per beef equivalent (feed, veterinary and Labor), Fixed costs per beef equivalent (Fixed capital, family labor and Land) • Efficiency drivers: household characteristics (Age, Education, Gender, non-farm income, access to crop farm income) and transaction cost variables (distance to markets, access to agriculture/market information) and location variable (FMD zone)
  8. Results – Stochastic frontier estimates Variables OLS MLU Coefficient t-values Coefficient t-values Constant -34.87 -26.31 -38.12 -32.49 Ln (Average Beef cattle price) 5.01 28.23*** 5.51 34.85*** Ln (Feed) -0.15 -3.61*** -0.13 -3.11*** Ln (Veterinary) -0.12 -2.97** -0.09 -2.46** Ln (Labour.) 0.08 0.24** -0.79 -1.93** Ln (fixed capital.) -0.02 -0.64 0.02 0.53 Ln (Family labour Hours) -0.06 0.28* 0.46 1.82* Ln (Crop land area) 0.55 2.95* 0.28 1.70*
  9. Results – Efficiency drivers Variables Coefficient t-values Constant -11.86 -2.47** Age of household head -1.26 -3.44*** Education of Household head 0.043 0.14 Annual household non-farm income 0.26 2.64*** Distance market (commonly used) 0.56 2.42** Herd size 2.48 4.92*** Gender (% female farmers) -2.82 -2.43*** Information access (Yes=1, No=0) 4.15 2.80*** FMD disease zone (Yes=1, No=0) -4.56 -3.84*** Crop income (Yes=1, No=0) -2.31 -2.94***
  10. Conclusions and policy implications • Profits could be increased through reduction in inputs prices, increase in output price and access to crop land. • Presence of inefficiency in the study reminds that production models that assume absolute efficiency could lead to misleading conclusions. • The mean efficiency of 0.56 implies that there is a substantial loss of profit due to inefficiency.
  11. Conclusions and policy implications Policies to improve farm profit should be directed at • Enhancing producer prices as well as ways to reduce input prices • Improving infrastructure such as roads and collection points of livestock • Improving access to crop land and • Encouraging farmers to engage in crop farming, particularly in feed production.
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