Emily Schmidt and Fanaye TadesseEthiopia 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

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)

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)

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

SLWM Investments

Soil Bunds Wood check dam

Stone terraces Stone check dam

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

Sample sites

29.4

43.338

59

52.5

59.8

72.1

Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye

Share of cultivated land per householdwith steep or mixed slope

24.1

52.949.7

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

28.4 2731.6

55.6

12.1 11.5

19

Alefa Misrak Estie Gozamin Dega Damot Mene Sibu Jeldu Toko Kutaye

Experienced drought in last 5 years

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)

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

We want to compare apples with apples…

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

Assessing impact: Evaluating the impact of the SLMP

Control

End-line (t1) Baseline (t0)

Intervention

Trend

Impact (Y1- Y1*)

Y0

Y1*

Y1

ResultsModel 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 YESBaseline * survey endline NO YES

Number of observations 2118 2118Note: 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

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 ***

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 ***

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)

Thank you.