The Sustainable Land Management Program in the Ethiopian highlands: An evaluation of its impact on crop production

1. Emily Schmidt and Fanaye Tadesse
Ethiopia Strategy Support Program (IFPRI)
ILRI Campus: 2-20-2017
The Sustainable Land Management
Program in the Ethiopian highlands: An
evaluation of its impact on crop production

2. Ethiopian Agriculture
• Agriculture remains a cornerstone of Ethiopian
economy:
• 2/5 of GDP in 2012/13
• 3/4 of total employment in 2012/13
• Approximately 86% of population live in rural areas (CSA, 2009)

3. Land degradation in Ethiopia
• Land degradation and poverty continue to challenge sustainable agricultural
development opportunities in Ethiopia
• High population pressure in rural highlands, high dependence on rain-fed
agriculture, mixed crop / livestock livelihood practices.
• Loss of agricultural production due to land degradation ranges from 2 to 5 percent
of agricultural GDP per year (Yesuf et al., 2005; Sonneveld 2002; World Bank, 2013)
• Maintenance of Sustainable Land Management structures is largely absent over the
medium to long term (Shiferaw and Holden, 1998; Benin, 2006; Tadesse and Belay,
2004; Anley et al., 2007; Moges and Holder, 2007; WFP, 2005)

8. Policies for addressing SLM strategies
• Previous 5 year plan (PASDEP): series of land and watershed management activities with
the goal of augmenting agricultural production.
• Recent 5 year plan (GTP): government outlines the need to promote and invest in SLM
taking into account varying agro-ecological zones (GTP, 2011).
• Sustainable Land Management Program (SLMP) in collaboration with MoA and other
donors
• Targets 937 kebeles (177 critical watersheds) in 209 woredas in 6 regions
• Scale up and increase adoption of appropriate SLM technologies tested for specific agro-ecological
conditions in the program kebeles
• 4 components:
• Construct watershed and land management structures to stabilize soils
• Improve water retention and support efficient tillage practices
• Build capacity of service providers and rural households in implementation of SLM practices
• Enhance land tenure security of smallholder farmers

9. SLWM Investments
Soil Bunds Wood check dam
Stone terraces Stone check dam

10. Impact evaluation of SLM program
• Ethiopia watersheds panel survey collected in 2010 and 2014 (IFPRI)
• Baseline
• 9 woredas (1810 HHs) within the Blue Nile Basin
• Stratification: 3 kebeles per woreda (SLMP woredas)
• Planned SLM program
• No formal past program
• Round 2
• 1748 of baseline households were re-interviewed in 2014,
• Attrition rate of 3.4 percent over 4 years, or 0.85 percent per year
• 2 of the sample woredas did not receive an SLMP – excluded in analysis
• Finally, 1,352 households comprise the panel SLMP analysis sample

11. Sample sites

12. 29.4
43.3
38
59
52.5
59.8
72.1
Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye
Share of cultivated land per household
with steep or mixed slope

13. 24.1
52.9
49.7
52.5
10.1
29.2
37.4
Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye
Experienced flood or too much water in last 5 years

14. 28.4 27
31.6
55.6
12.1 11.5
19
Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye
Experienced drought in last 5 years

15. 8,761
5,434
8,984
4,337
5,994
7,713
5,792
Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye
Value of total crop production in Birr (2009 prices)

16. Challenges to evaluating the Sustainable Land
Management Program (SLMP)
• Targeted to provide assistance to communities struggling with soil
and water conservation (non-random program placement)
• Differences across woredas (i.e. cropping patterns, biophysical
endowments and experiencing shocks)
• SLMP rolled out in different woredas at different times.
• Amhara region began initial SLM activities in 2009
• Primarily stakeholder meetings and initial planning in April – June, 2009
• Oromiya region started in 2012

17. We want to compare apples with apples…

18. Comparing apples: Evaluating the impact of the SLMP
• Households categorized as treated and control: based on kebeles that
received an SLMP program or not.
• Takes into account household and community level interventions
• Create 3 respective groups to take into account differences in program
roll-out
• Group 1: Households with 0 exposure to the SLMP (control)
• Group 2: Households received program in 2009
• Group 3: Households received program in 2012
• Propensity score matching takes into account other potential
determinants of value of crop production: household and land
characteristics, shocks, input use

19. Assessing impact: Evaluating the impact of the SLMP
Control
End-line (t1)Baseline(t0)
Intervention
Trend
Impact (Y1- Y1*)
Y0
Y1
*
Y1

20. Results
Model 1 Model 2
2009 program group*year 2014 0.118 0.105
(0.079) (0.095)
2012 program group*year 2014 -0.024 -0.162
(0.168) (0.178)
Baseline covariates YES YES
Baseline * survey endline NO YES
Number of observations 2118 2118
Note: Figures in parentheses are robust standard errors;
***Significant at 1% level; **Significant at 5% level; *Significant at 10% level.
• Regardless of the amount of time in an SLMP (1 or 4 years), treatment
households do not have any statistically significant increases in value of
total crop production in 2013 compared to control households.
• We find similar results at plot-level analysis

21. However…
Households in Treated Kebeles Households in Control Kebeles
Baseline Endline T-test Baseline Endline T-test
Value of total crop production
(2009 prices)
5,727 7,150 *** 6,319 7,649 ***
Cereal 4,658 5,707 *** 5,178 5,804 *
Root crops 595 1,133 *** 778 1,946 ***
• the overall change in agricultural productivity across survey sights suggests a
promising trend between survey years.
• total value of production increased by 25 and 21 percent in households located in
treatment and control kebeles, respectively.
Yield (kg/hectare)
Cereal 1,383 1,437 1,251 1,443 ***
Root crops 4,601 7,956 *** 5,503 7,514 **
Input use
Fertilizer use 80.2 86.4 *** 72.0 85.8 ***
Improved seed 29.7 58.1 *** 20.6 52.1 ***

22. SLM investments have increased across all kebeles
Households in Treated Kebeles (share) Households in Control Kebeles (share)
Baseline Endline T-test Baseline Endline T-test
SLM structure 72.9 80.4 SLM structure 64.4 71.8
Irrigation 1.2 1.9 Irrigation 1 1
Stone terrace 23 32.6 *** Stone terrace 22.9 29.4 ***
Soil bund 45.9 52 *** Soil bund 21.3 43 ***
Check dam 0.1 2.2 *** Check dam 0.3 1.5 ***
Trenches 0.9 8.2 *** Trenches 0.1 10.3 ***
Trees planted 0.7 6.6 *** Trees planted 0.9 3.8 ***
Others 4.9 12 *** Others 2.1 8 ***

23. Conclusion
• Panel household survey data analysis suggest that improvements in agricultural
productivity via investments in SLM structures may only be achievable through
longer term maintenance and program participation.
• Although analysis does not suggest significant increases in value of production due
to SLM program, it does suggest that increases in productivity and input use, and
SLM investments are occurring throughout the study sites
• Previous baseline study suggests that significant increases are achievable after 7
years of investment maintenance (Schmidt and Tadesse, 2014)
• Market modeling exercise suggests that pairing SLM investments with increased
access to fertilizer may provide the needed incentives for producers to maintain
structures. (Schmidt et al., 2015)

24. Thank you.