Measurement of competitiveness in smallholder livestock systems and emerging policy advocacy: an...

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

Policies for Competetitive Smallholder Livestock Production

4-6 March 2015

S. Bahta and P. Malope

Structure of Presentation

Introduction and objectives

Methodological approach

Results and discussion

Conclusion and policy implications

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

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

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”

Methodology - Study area

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)

Results – Stochastic frontier estimates

Variables

OLS MLU

Coefficient t-values Coefficient t-values

Constant -34.87 -26.31 -38.12 -32.49Ln (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 0.53Ln (Family labour

Hours) -0.06 0.28* 0.46 1.82*Ln (Crop land

area) 0.55 2.95* 0.28 1.70*

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***

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.

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.

THANK YOU