Transcript Cheteni_P - Energy Postgraduate Conference

Barriers and incentives to widespread adoption of bio fuels crops by
smallholder farmers in SA: A case of Nkonkobe Municipality
Priviledge
Cheteni
Master in Agriculture
Economics
University of Fort Hare
Energy Postgraduate Conference 2013
Outline
Introduction
Problem
Research questions and hypothesis
Literature review
Methodology
Conclusion
Introduction
 Subsistence farming is a backbone of agricultural production in
SA.
 Subsistence agriculture accounts for about 3% of South African
GDP and the broader agri industrial sector contributes about
12% of GDP (Nedbank,2012).
 Small scale farmers productivity reduced by structural changes
and policies (Palmer & Ainsle, 2012)
 Lack of access of new agriculture technology identified as a
factor (Von Braun, 2007).
 Improved agriculture technology stressed in key planning
documents as a means of creating jobs, reducing inequality
and increasing economic growth in rural disadvantage areas
previous oppressed by apartheid (Integrated Development
Programme, 2000).
Problem
 Eastern Cape region is dry and not good for commercial crop
farming (Musemwa et al, 2008)
 In Nkonkobe Municipality rainfall is uneven distributed ranging from
400 mm to 1200mm (Shackleton & Shackleton,2006) making the
place not ideal for rain fed crops.
 Smallholder farmers face challenges like low productivity and
access to markets. As a result, smallholder agriculture remains low
in productivity (DBSA,2010)
•
Few small scale farmers have adopted biofuels for production
(Funke et al,2007).
 This study would investigate factors influencing adoption of
biofuels in Nkonkobe Municipality
Objectives
 The main objective of the study is to identify factors
affecting/influencing adoption of biofuel crops by small holder
farmers in Nkonkobe Municipality.
Other objectives
 To investigate if farmers are aware of bio fuels crops in
Nkonkobe Municipality.
 To estimate determinants of farmers potential to adopt bio fuels
crops in Nkonkobe.
 To develop a list of incentives that may motivate farmers to
produce biofuels.
Hypothesis
 Farmers are aware of biofuels crops in Nkonkobe Municipality.
 Social, economic and farming factors influence farmers to
adopt biofuels crops.
 Monetary incentives access to market and government
subsidies motivate farmers to adopt bio fuels crop
Research Questions
 Are farmers aware of bio fuels crops?
 What are the determinants of farmers potential to adopt bio
fuels crops?
 What incentives motivate farmers to produce biofuels crop.
Literature Review
 Ajewole (2010) measuring the response to adoption of fertiliser
used a tobit model.
 Uaine (2009) used a probit model to measure
technology adoption in Mozambique.
agriculture
 Stan and William (2003) employed the Heckman’s two-step
procedure to analyze the factors affecting awareness and
adoption of new agricultural technologies in USA.
 The first stage was the analysis of factors affecting the
awareness of new agricultural technologies and the second
stage is adoption of the new agricultural technologies
Methodology
 The study will be done in Nkonkobe Municipality in these
areas; Upper Ncera, Lower Ncera, Krwakrwa and Kayelitsha
 A stratified random sampling method will be used to select
farmers into two groups
 Questionnaires will be used to gather data.
 Primary and secondary data that would be collected includes
social economic factors such age, education , name etc, farm
specific such as number crops grown, Economic such as
income ,farm investments.
Description of respondent
type
Number to be sampled
Small-scale farmers utilising 59
land
Small Scale farmers not
utilising land
59
Total
118
Econometric model
 Adoption of biofuels involves a two stage process; first farmers
awareness of the existing bio fuels crops and second deciding
whether to adopt or not.
 The study will use a Heckman model as it gives consistent
and efficient estimates for parameters in the model (Statacorp,
2003
Model
 y*1=𝒃𝒐+𝒃𝟏∗age+𝒃𝟐∗householdsize+𝒃𝟑∗gender+𝒃𝟒∗agric
member+𝒃𝟓∗education+𝒃𝟔∗extension+𝒃𝟕∗awareness+𝒃𝟖
∗knowledge+𝒃_𝟗∗income…….(1) Selection Model
 y*2=𝒃𝒐+𝒃𝟏∗age+𝒃𝟐∗household+𝒃𝟑∗gender+𝒃𝟒∗agricmember+
𝒃𝟓∗education+𝒃𝟔∗ extension+𝒃𝟕∗ farmsize+𝒃𝟖∗knowledge+𝒃𝟗
∗income…………………………………………….(2) outcome model
 Data from the questionnaire would be anlysed using SPSS.
The end