Ali M. Oumer - ioa.uwa.edu.au · Summary. 1. Significant dynamic interrelationships between different types of sustainable agricultural technologies. 2. Input-intensive and NRM technologies

Adoption of Sustainable Agricultural Intensification Technologies in Ethiopia: Drivers and Synergies

Ali M. Oumer

UWA School of Agriculture and Environment

UWA Institute of AgriculturePostgraduate Showcase

SupervisorsAssociate Professor Michael Burton Associate Professor Atakelty HailuSenior Lecturer Amin MugeraProfessor Salvatore Di FalcoDr Menale Kassie

Data accessEIAR - Ethiopian Institute of Agricultural ResearchCIMMYT - International Maize and Wheat Improvement CentreNMA- National Meteorological Agency of Ethiopia

Acknowledgments

FundingAustralian Government through ACIAR - Australian Centre for International Agricultural Research

Project facilitationDr Chilot YirgaDebra Basanovic

Farming: >95% smallholders

Average farm size: <1 hectare

Fertilizer: low (34 kg/ha)

Land degradation, soil fertility depletiono Mono-cropping, removal of farm resources, top soil erosiono Extractive practices: soil nutrients mining

Mainly rain-fed; prone to weather variabilityo 1% of total maize area irrigated

Research context: Maize in Ethiopia

Wide yield gaps

Ethiopian maize yield (tons/ha)

Global yield gap Atlas (www.yieldgap.org)

0

2

4

6

8

10

12

14

16

On-station trials On-farm trials National average

Raise crop yields while enhancing natural resourceso Input-intensive: e.g. improved seeds, chemical fertilizerso Natural resource management: e.g. crop residues, minimum

tillage, organic manure, etc.o No consensus on most appropriate

Public debate: these two strategies often perceived as incompatible. Environmental NGOs: low external input strategies the only sustainable form of agriculture (Wainaina et al., 2016).

Solution: Sustainable Intensification

Sustainable agricultural technologies.

Research question:

What determines the adoption of sustainable agricultural technologies?

o Analyse drivers of individual technologies: interdependency between technologies overlooked

o Use different methods and data: comparisons between multiple technologies are not easily possible

o Lack of intertemporal dynamics among different types of technologies

But in practice, farmers’ technology adoptions are inherently dynamic, sequential and interdependent…

Motivation of the study

Limitations of empirical research on adoption (Doss 2006):

Doss, C. R. 2006. Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement. Agricultural Economics, 34, 207-219.

The study area and data

Sample villages from maize growing districts of Ethiopia

Multi-stage random sampling procedure

Sample size: Panel of 2031 households in 2009/2010 and 2012/2013

Household level data matched with village level climate data

Sustainable agricultural technologies

Proportion of households adopted

00.10.20.30.40.50.60.70.80.9 2009/2010 2012/2013

Dynamic multivariate probit

The empirical model

* ' ,itm itm m itmy x β ε= +

1 * 0,

0 itm

itm

if yy

otherwise>

=

Where:

i = household, t = time period=1,2

m = sustainable agricultural technology=1,2….8 in each period with a total of 16 binary choices

y* is a latent variable that captures the expected benefit from adopting a technology in each period

X is a vector of covariates (drivers)

is unobserved error term capturing unobserved effect of interrelationships

is unknown parameter

Observable unobservable

𝜺𝜺

𝛃𝛃

Significant drivers in period one

Main drivers Sustainable agricultural technologies

CF IS M SWC CR MT LR LIClimate factorsHist. Rainfall abundance + - + + + + +Hist. temperature + - +Hist. rainfall variability - + + + - +Lag rainfall variability - + + + - -Hist. temperature variability - + + -

CF=Chemical fertilizer IS=Improved seed

M=ManureSWC=Soil-water conservation

CR=Crop residueMT=Minimum tillage

LR=Legume rotation LI=Legume intercrop

Significant drivers in period one cont.…

Main drivers Sustainable agricultural technologiesCF IS M SWC CR MT LR LI

Farm characteristicsAge of farm manager - - - + -Farm size + + + + + +Infertile soils + + - -Steep fields + + + -Farm distance + - + + +Altitude + + - -






Main drivers Sustainable agricultural technologiesCF IS M SWC CR MT LR LI

Household characteristicsOff-farm income - - - - +Lack of oxen - - + +Credit use + +Institutions + + + - - +Tenure security + +Family education + + -Education of head +Family labour + - -






Main drivers Sustainable agricultural technologies

CF IS M SWC CR MT LR LIEconomic factors

Fertilizer price - - - +Seed price + + - - -

Labour price - - + + +





Temporal dynamics of adoption

Sustainable agricultural technologies Intertemporalcorrelation

Chemical fertilizer 0.52***Improved variety seed 0.22***Manure 0.18***Soil and water conservation structures 0.19***Crop residue retention 0.13***Minimum tillage 0.47***Legume rotation 0.21***Legumes intercropping 0.27***

We observe persistence in the adoption of technologies: Positive spill-over effect of time in adoption behaviour.

Significant correlations in period two

CF IS M SWC CR MT LR LICF 1

IS 0.67 1

M -0.09 1

SWC 0.28 0.14 1

CR -0.11 -0.09 0.08 1

MT -0.28 -0.33 -0.09 1

LR 1

LI 0.16 0.17 0.16 1





Summary

1. Significant dynamic interrelationships between different types of sustainable agricultural technologies.

2. Input-intensive and NRM technologies are compatible, contrary to the literature.

3. Drivers of adoption differ between technologies; reflect observed dynamic interdependencies [synergistic patterns]

4. Positive spill-over effect of time on adoption: enhance widespread use of the technologies if farmers get persistent and appropriate incentives.

Policy implications

Policies could promote a combination (packages) of input-intensive and NRM technologies that could lead to beneficial synergies.

The individual technology promotion approach may not work in every context as African agroecosystems are diverse and complex.

Understanding the drivers and synergies of dynamic adoption would be the best way forward.

Further research

If farmers realize the benefits of NRM technologies, why are then low adoption rates?

Could farmers get benefits for their ecosystem services beyond the farm?

What roles could sustainable agricultural technologies play in offsetting production risks and food insecurity?

Backup slides, error correlation matrix and adoption drivers with significance values

Significant correlations in period one

CF CR M IS MT LR SWC LICF 1

CR -0.10 1

M -0.12 1

IS 0.45 -0.19 -0.13 1

MT -0.41 -0.33 1

LR 0.22 0.17 1

SWC 0.12 0.10 1

LI 0.11 -0.34 0.22 0.12 1

CF=Chemical fertilizer CR=Crop residues

M=ManureIS=Improved seed

MT=Minimum tillage LR=Legume rotation

SWC=Soil-water controlLI=Legume intercrop

Results…interrelationships-period one


CR -0.10** 1

M -0.12*** 1

IS 0.45*** -0.19*** -0.13*** 1

MT -0.41*** -0.33*** 1

LR 0.22*** 0.17*** 1

SWC 0.12*** 0.10** 1

LI 0.11** -0.34*** 0.22*** 0.12** 1




SWC=Soil-water conserveLI=Legume intercrop

Results…interrelationships-period two


CR 1

M -0.09** -0.09** 1

IS 0.67*** -0.11** 1

MT -0.28*** -0.09* -0.33*** 1

LR 1

SWC 0.28*** 0.08* 0.14*** 1

LI 0.16*** 0.16*** 0.17*** 1






Results…temporal dynamics

2009/2010 [Period one]CF CR M IS MT LR SWC LI

2012

/201

3 [P

erio

d tw

o]

CF 0.52*** 0.13*** -0.14*** 0.08* 0.19***

CR -0.17*** 0.13*** -0.10** 0.09*

M -0.08** 0.18*** -0.16*** 0.07*

IS 0.34*** -0.12*** 0.22*** -0.22*** 0.19***

MT -0.19*** -0.15** 0.47*** 0.14**

LR 0.16** 0.13** 0.21***

SWC 0.15*** 0.09** 0.19*** 0.09*

LI 0.16*** -0.18*** 0.11** 0.17*** 0.27***




Results…key drivers-period one

Main drivers Sustainable agricultural intensification technologiesCF CR M IS MT LR SWC LI

Climate factorsH. rainfall 0.04*** 0.05*** 0.04*** -0.05*** 0.08*** -0.1*** 0.06***H. temperature 0.06*** 0.06*** -0.04**H. rainfall variability

6.3*** -3.5* 6.2** -6.0** 9.0*** 6.7**

Lagged rainfall variability

-1.6*** -1.3*** 0.8*** 0.8*** 1.0*** -3.4***

H. temperature variability

-6.4*** 3.3* 11.0*** -7.3***

Farm characteristicsFarm size 0.16*** 0.09** 0.10** 0.14*** 0.08* 0.09*Soil fertility 0.21*** -0.15** -0.13** 0.28***Slope of field 0.19*** 0.21*** -0.3*** 0.36***

Farm distance 0.07** 0.07** -0.2*** 0.08** 0.07**Altitude 0.10*** 0.05*** -0.18*** -0.03*

Results…key drivers-period one cont.…

Main drivers Sustainable agricultural intensification technologiesCF CR M IS MT LR SWC LI

Household characteristicsOff-farm income -0.35*** -0.32*** -0.24** 0.46*** -0.31**Lack of oxen -0.24** -0.27*** 0.50*** 0.27**Credit use 0.19** 0.20**

Institutions 0.09*** -0.11*** 0.06*** -0.06** 0.05* 0.11***

Tenure security 0.31*** 0.27**

Family education 0.05** -0.05** 0.12***Education level of head

0.04***

Economic factorsFertilizer price -0.07** 0.10*** -0.15*** -0.08**

Seed price 0.09*** 0.08*** -0.05*** -0.04*** -0.05***Labour price -0.04*** 0.04*** -0.03*** 0.021** 0.04***

Sustainable agricultural technologies

00.10.20.30.40.50.60.70.80.9 2009/2010 2012/2013

Proportion of households adopted

Thank you very much for your attention!

[email protected]

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Ali M. Oumer - ioa.uwa.edu.au · Summary. 1. Significant dynamic interrelationships between different types of sustainable agricultural technologies. 2. Input-intensive and NRM technologies