Download IMAGINE methodology Reidsma

IMAGINE: methodology
Pytrik Reidsma
Kick-off meeting, 10-12 March 2015, Wageningen
Research questions
 What is a scientifically sound and applicable generic
framework linking agronomic, socio-economic,
institutional, infrastructural and policy factors, explaining
maize yield gaps in SSA?
 What are the main biophysical and farm and crop
management factors that help to explain yield gaps in
the case study countries?
 What are the main infrastructural, institutional,
socio-economic and policy factors that explain farm
and crop management and consequently yield gaps?
 Which policies and farm management options are
key for increasing yield performance in SSA?
Three stages
1. Benchmark: Calculate potential, highest farmer’s, technical efficient and
economic ceiling yields at the national and regional level
● crop growth and economic production models
● combined with actual yield data from surveys to compute the various
yield gaps
2. Explain, country-level: Analyse variations in the observed yield gaps in
space and relate them to plot-level, farm-level and context determining
factors
● econometric techniques
● decisions taken at the farm-household level
● embedded in a wider socio-economic and biophysical context
3. Explain, local: Deepen the analyses of stage 1 and 2
● local case studies at the village level
● to allow identification of farm and management innovations and policy
interventions.
Benchmarks & yield gaps
Yield
levels
Waterlimited
Gap 1
Highest farmer’s
yield
Gap 2
Economic ceiling
yield
Gap 3
Actual farmer yield
Modelled Farm and plot level observations
Production level (y)
YW
YEE
YHF
YTEx
Input level (x)
4
Methodological framework
 Frontier analysis
● efficiency gap
● resource gap
● economic efficiency
 Crop modelling
● technology gap
● biophysical ranges
● explain (climate,
soil, cultivar, timing)
5
Production level (y)
Interaction between inputs
YHF
YHF
P resource
yield gap
YFARM1
Input level (N)
P resource
yield gap
YFARM1
Input level (P)
 Only considering N: efficiency gap
 Considering N & P: resource gap of P
6
Frontier analysis: resource & efficiency gap
 Production function includes inputs & outputs (maize yield)
 Inputs:
● Traditional economic: land, labour & capital
● Proposal: growth-defining & -limiting
= factors directly required for plant growth
7
Explaining yield gaps: methods
technical inefficiency
 Along with frontier analysis:
field management
● 2nd stage multiple regression
● if inputs are growth-defining & -limiting farm, village, region
● time, space & from of inputs (~ efficiency)
● farm characteristics, socio-economic &
institutional conditions
 Crop modelling
● biophysical ranges input-output relationships
● explanation by climate, soil, sowing date, nutrients
● interviews, workshops
Production level (y)
 Participatory
Yw
Technology
YHF
yield gap
8
Input level (x)
Explaining yield gaps: data
Biophysical conditions
Distance to market
Input & output prices
Market information
Extension service – info
Subsidy programs
Insurance programs
Credit programs
Temperature
Radiation
Elevation
Slope
Rainfall + distribution
Length growing season
Farm
Plot
Age of field
Soil NPK
Soil water
Soil type
EC
pH
OM
Pest infestation
Disease infestation
...
Farm(er) characteristics
Farm area
Labour availability
Capital availability
Age
Gender
Education
HH size
Number of plots
Off-farm income
Farm labour / ha
Hired labour / ha
Field management
NKP application
Manure application
Biocide application
Irrigation
Sowing density
NPK timing
Biocide timing
Irrigation timing
Sowing date
Land preparation
Weeding
Crop residue management
Rotations
Intercropping
Tree cover
Erosion control
Yield
Village
Socio-economic conditions
9
Challenges: methods 1
 Frontier analysis
● Method: SFA or DEA
● Functional form: Cobb-Douglas, translog, quadratic,
...
● Inputs included: l,l,c / growt-defining & -limiting
K-limiting
● Outputs: only maize (more outputs possible)
 2nd stage multiple regression
● Influences efficiency levels
● Different types
 Resource gap
● Not standard output; compare TE with different
inputs
10
Challenges: methods 2
 Technology gap
● Large difference Yw and Yhf
 Explain
Production level (y)
● Can be resource or efficiency gap
● Not explained by frontier analysis
● Include high yielding regions & farms!
● Crop modelling: micro-climate, soil, NPK, sowing date
● Experiments: difference with Yhf?
Y
● Data regions similar AEZ
w
Technology
yield gap
YHF
Input level (x)
11
Challenges: data 1
 Country-level
● Ethiopia: LSMS-ISA
● Ghana: ISSER
 Additional data sources:
● Relevance of locations, type of data, collaboration?
 Local analysis:
Region2
Region1
village1
type1
village2
type2
type3
farm1 farm2 farm3
village3
type4
village1
type1
village2
type2
type3
farm1 farm2 farm3
village3
type4
12
Challenges: data 2
 Sample
● 2 regions * 3 villages * 4 farm types * 3 farms
= 72 farms per country
● size: needed <-> possible
 Criteria
● Region/village: AEZ, market access, soil fertility
● Farm types: resource endowment
 Timing of surveys: start summer 2015
 Set-up of surveys
 Responsabilities
13
Time for
discussion
?
14