presented by Mr. Dereje Getu at the In-House Seminar organized by IFPRI - ESAO

1. IFPRI
INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
Effectiveness of Rural Income
Diversification Program
Supports in Ethiopia: A Cross
Sectional Study
Preliminary Findings
Dereje Getu and Getaw Tadesse
September 26, 2016

2. Outline
 Introduction
 Objectives and Research Questions
 Data and descriptive statistics
 Estimation approach
 Estimation results and Discussion
 Conclusion

3. Int: Why for Income Diversification
Poverty reduction in Africa is best achieved if
the burden on agriculture is somehow lifted
through diversified employment both in rural
and urban areas.
Generally, diverse livelihoods are less
vulnerable to shocks than undiversified ones
(Ellis, 2000)
Lifting the burden from agriculture
»moving up ??
»moving out ??

4. Opportunities for rural income diversification In Africa
 Expansion of rural infrastructure
» Transaction cost
» Business communication
 Education
 Economic Growth
 Agr Productivity Growth
 DD for Non agr services

5. Limiting factors for Income diversification in Africa
 Limited business literacy
 Capital or credit shortage
 Cultural resistance
 Risk aversion
 Asymmetries in output market
 Underdeveloped input supply market
 Rigid land policy

6. HABP for Income Diversification
 Launched in 2010
 Rural incomes are less diversified
 Self reliance and graduation from PSNP
 How RIDS shall be guided and targeted
 A series of Supports
Consultation
meeting
Business
Plan
Preparation
Credit
Access
Technical and
Commercial
Support

7. Objectives of the study
G O: to measure the effectiveness of HABP
program support for RIGA’s Success
 How diversified are RIG pathways?
 To what extent the program supports are
implemented?
 How the supports are perceived by the
beneficiaries?
 Which supports are effective
 Which supports for Which IGA pathways

8. Data and descriptive statistics
 Structured questionnaire
» 4 regions
» 8 Woredas
» 40 kebeles
» 600 HHs
» All HABP beneficiaries
 Multi stage Sampling
 Both descriptive and econometric analysis were
employed

9. Measuring Success / Performance in Rural IGA
• No profit
• No Sales
• Discontinued
Failed HHs
• made profit
• discontinuedRisk coping HHs
• Active
• No sale
• No profit
Struggling HHS
• Have sale
• Active
• No profit
Reviving HHs
• Have no sale
• Active
• Made Profit
Declining HHs
• Made profit
• Current saleSuccessful HHs
• Annual sales
• Profitability and
• Sustainability

10. Table 1. Diversification of RIGAs in rural Ethiopia
Rural business pathways Tigray Amhara Oromiya SNNP Total
Type of IGAs per Kebele 8.5 6.1 5 2.6 5.6
Number households per
Kebele(N)
556.5 263.6 26.4 25.4 218
Beef 0.04 0.12 0.33 0.13 0.08
Dairy 0.15 0.07 0.06 0.16 0.12
Small ruminant 0.38 0.76 0.39 - 0.49
Poultry 0.15 0.01 - - 0.10
Beekeeping 0.03 - - - 0.02
Irrigation/crop 0.11 - 0.08 0.22 0.08
Petty trade 0.12 0.04 0.14 0.12 0.10
Manufacturing 0.01 0.01 - - 0.01
Rural service 0.00 0.01 - 0.37 0.01
Resource extraction/use 0.01 - - - 0.01
On-farm 0.86 0.95 0.86 0.51 0.88
Off-farm 0.14 0.05 0.14 0.49 0.12

11. Table 2: Participation of HHs to HABP Program Support
Program supports Dairy
Farming
Small
Ruminants
Crop
Production
Beef
fattening
Off farm Total
Proportion
participated in
consultation meeting
91.18 82.11 92.68 88.37 93.02 87.96
Business plan
prepared
94.12 82.63 90.24 94.77 87.21 89.13
Proportion received
training
72.06 63.16 80.49 72.09 77.91 71.24
Proportion received
advice
91.18 85.26 90.24 85.47 86.05 86.79
Proportion took loan 98.53 100.00 100.00 100.00 100.00 99.83
Input market linkage
created by HABP
26.47 17.37 50.00 9.30 2.33 18.39
Average loan taken
(000)
5.704478 4.713889 6.552122 4.45407 5.396326 5.101
Number of HHs 68 190 82 172 86 599

12. Table 3 : Participants perception to the relevance of HABP program supports
Program supports
perception
Dairy
Farming
Small
Ruminant
s
Crop
Productio
n
Beef
fattening
Off farm Total
Proportion responded
the plan as relevant
90.63 94.90 94.59 96.00 95.09 94.56
Percentage responded
training as relevant
100.00 95.83 98.48 95.97 94.03 96.48
Percentage responded
advice as relevant
98.39 96.91 97.30 98.64 98.65 97.88
Proportion responded
the loan as sufficient
58.21 65.26 40.24 29.65 43.02 47.57
Number of HHs 68 190 82 172 86 599

13. Table 4: Performance of IGAs
Income generation
pathways
Average
size of
investment
in 000
Proportion
households
generated
profit
Average
total
profit
Average
rate of
return
Averag
e per
capita
sales
% of
functiona
l IGAs
Dairy 8639 73.53 5097 .732 .672 39.71
Small ruminant 6493 86.84 5376 1.03 .739 40.00
Crop Production 11103 90.24 17639 2.616 2.021 71.95
Beef Fattening 7424 75.58 5180 .930 .889 34.88
Off-farm 8469 89.53 6035 .987 2.171 74.42
Total 7921 82.94 7052 1.178 1.156 47.83

14. Table 5: Over all Performance of IGA
Performing IGA Freq Percent
Successful 262 43.74
Un successful IGAs 337 56.26

15. Estimation approach
 We have employed different regression models
» Simple linear regression
» Robust regression (rreg)
» LPM
 Functionality, percapita sales, rate of return and
performance of IGA across each IGA
 Functionality, per capita sales, rate of return and
performance of IGA for off farm and on farm
comparison
Functionality, percapita sales, rate of return and
performance of IGA of the full model
» Panel Data

16. Cot’d
 Program Support Variables
» Participation to Consultation Meeting
» Business Plan preparation
» Access to Credit
» IGA training
» Input market linkage
» IGA advice
 Controlled variables
» Social Capital
» Human Capital
» Market and Infrastructure access

17. Estimation Result 1: Small Ruminants
VARIABLES Fun_
Probit
Sales_
OLS
Sales_Robu
st Reg
Sales_
Tobit
RR_
OLS
RR_Robu
st Reg
RR_
Tobit
Perfo_
Probit
Consmeeting 0.160 0.432** 0.274** 0.699* 0.177 0.0330 0.161 0.162
(0.353) (0.200) (0.106) (0.386) (0.192) (0.168) (0.307) (0.359)
Business_Plan 0.573 -0.118 0.174 0.146 0.228 0.116 0.214 0.503
(0.367) (0.388) (0.108) (0.411) (0.189) (0.170) (0.315) (0.366)
IGA_training 0.488* 0.154 0.0581 0.126 -
0.00438
0.157 -0.0832 0.353
(0.273) (0.166) (0.0869) (0.321) (0.276) (0.138) (0.255) (0.273)
IGA_adivice 0.00540 0.735 0.175 0.971** 0.180 0.0552 0.246 0.102
(0.352) (0.666) (0.113) (0.415) (0.189) (0.177) (0.330) (0.363)
Input market
linkage
0.403 0.0046
8
0.0838 0.124 0.308 0.510*** 0.406 0.505*
(0.286) (0.184) (0.0908) (0.316) (0.236) (0.144) (0.261) (0.283)
lnCredit_amout -0.411* -0.254 -0.00944 -0.287 -0.256 -0.0718 -0.215 -0.344
(0.237) (0.191) (0.0667) (0.241) (0.174) (0.106) (0.193) (0.229)
Observations 188 189 188 189 189 189 189 188
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

18. Estimation Result 2: Crop Production/ irrigation
VARIABLES Fun_
Probit
Sales_
OLS
Sales_Robust
Reg
sales_
Tobit
RR_O
LS
RR_Robus
t Reg
RR_
Tobit
Perfo_
Probit
Consmeeting -1.717 -0.681 -1.595 1.102 -0.495 1.375 -2.138**
(2.343) (0.652) (1.843) (1.910) (0.744) (2.119) (0.953)
Business_Plan 0.343 -0.823 -0.851 -0.874 0.184 -0.806 -0.673 -0.706
(0.559) (1.070) (0.591) (1.731) (1.407) (0.674) (1.934) (0.589)
IGA_training 0.709 0.497 0.430 1.952 -1.020 0.218 -0.366 1.667***
(0.501) (0.962) (0.416) (1.287) (1.182) (0.475) (1.382) (0.513)
IGA_adivice -0.790 0.808 1.016* 2.574 0.803 1.834*** 1.606 0.133
(0.733) (1.369) (0.589) (1.819) (1.470) (0.671) (1.998) (0.698)
Input_market
linkage
0.357 0.405 0.275 0.478 0.0632 -0.324 0.159 0.572
(0.462) (0.969) (0.343) (0.977) (1.125) (0.391) (1.116) (0.460)
lnCredit_amout 0.459 -2.48** -0.621** -2.51*** -1.252 -0.786** -1.201 0.632
(0.427) (1.033) (0.289) (0.798) (0.762) (0.329) (0.928) (0.409)
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

19. Estimation Result 3: Beef fattening
VARIABLES Fun_
Probit
Sales_
OLS
Sales_Robust
Reg
Sales_
Tobit
RR_
OLS
RR_Robus
t Reg
RR_
Tobit
Perfo_
Probit
Consmeeting -1.717 -0.681 -1.595 1.102 -0.495 1.375 -2.138**
(2.343) (0.652) (1.843) (1.910) (0.744) (2.119) (0.953)
Business_Plan 0.343 -0.823 -0.851 -0.874 0.184 -0.806 -0.673 -0.706
(0.559) (1.070) (0.591) (1.731) (1.407) (0.674) (1.934) (0.589)
IGA_training 0.709 0.497 0.430 1.952 -1.020 0.218 -0.366 1.667***
(0.501) (0.962) (0.416) (1.287) (1.182) (0.475) (1.382) (0.513)
IGA_adivice -0.790 0.808 1.016* 2.574 0.803 1.834*** 1.606 0.133
(0.733) (1.369) (0.589) (1.819) (1.470) (0.671) (1.998) (0.698)
Input_market
linkage
0.357 0.405 0.275 0.478 0.0632 -0.324 0.159 0.572
(0.462) (0.969) (0.343) (0.977) (1.125) (0.391) (1.116) (0.460)
lnCredit_amout 0.459 -2.48** -0.621** -2.507*** -1.252 -0.786** -1.201 0.632
(0.427) (1.033) (0.289) (0.798) (0.762) (0.329) (0.928) (0.409)
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

20. Estimation Result 4: Off farm
VARIABLES Fun_
Probit
Sales_
OLS
Sales_Robust
Reg
sales_
Tobit
RR_
OLS
RR_Robust
Reg
RR_
Tobit
Perfo_
Probit
Consmeeting -1.855* -11.2** 0.874 -12.16*** -2.00** -0.453* -2.2*** -2.083**
(1.090) (4.853) (0.530) (2.537) (0.865) (0.269) (0.553) (0.973)
Business_Plan 0.475 -2.774 0.617 -2.283 0.259 0.540** 0.508 -0.0743
(0.623) (2.216) (0.431) (2.259) (0.464) (0.222) (0.476) (0.605)
IGA_training 1.685*** -0.132 0.0808 0.205 -0.443 -0.256 -0.502 0.953*
(0.588) (1.584) (0.340) (1.739) (0.468) (0.180) (0.366) (0.506)
IGA_adivice -1.194* -1.337 -0.782* -1.597 -0.150 0.205 0.0157 -0.433
(0.714) (2.466) (0.394) (1.990) (0.633) (0.205) (0.432) (0.669)
Input_market
linkage
-0.989 3.083*** 2.858 -0.646 -0.231 -0.223
(2.583) (0.873) (4.983) (0.481) (0.459) (1.031)
lnCredit_amout 0.894 -1.377 0.249 -1.271 -0.210 -0.280 -0.184 0.715
(0.578) (1.475) (0.351) (1.760) (0.325) (0.183) (0.373) (0.510)
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

21. Estimation Result 5 : On farm
VARIABLES Fun_
Probit
Sales_
OLS
Sales_Robust
Reg
Sales_
Tobit
RR_
OLS
RR_Robus
t Reg
RR_
Tobit
Perfo_
Probit
Consmeeting -0.0543 -0.777 0.0607 -0.758** -0.494 -0.0198 -0.542 -0.0975
(0.195) (0.500) (0.0857) (0.383) (0.777) (0.103) (0.462) (0.201)
Business_Plan 0.00125 0.190 0.0765 0.365 -0.0063 -0.0369 -0.346 -0.143
(0.228) (0.350) (0.0940) (0.429) (0.237) (0.113) (0.504) (0.231)
IGA_training 0.49*** 0.45** 0.192*** 0.703** 0.454 0.242*** 0.484 0.528***
(0.153) (0.204) (0.0652) (0.295) (0.415) (0.0781) (0.355) (0.159)
IGA_adivice 0.250 0.460* 0.0840 0.530 0.72** 0.151 1.12** 0.312
(0.199) (0.270) (0.0854) (0.385) (0.297) (0.102) (0.475) (0.208)
Input_market
linkage
0.230 0.173 0.158** 0.294 0.274 0.246*** 0.378 0.266*
(0.155) (0.204) (0.0674) (0.295) (0.296) (0.0807) (0.358) (0.155)
lnCredit_amout -0.0868 -0.536* -0.0792 -0.606** -0.161 -0.121* -0.0878 -0.0844
(0.126) (0.306) (0.0546) (0.241) (0.285) (0.0654) (0.290) (0.127)
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

22. Estimation Result 6: Functionality of IGAs
VARIABLES Probit xtProbit
Consmeeting -0.0506 -0.180
(0.180) (0.186)
Business_Plan 0.0288 0.0966
(0.202) (0.338)
IGA_training 0.596*** 0.578***
(0.140) (0.140)
IGA_adivice 0.188 0.191
(0.179) (0.179)
Input_marketlinkage 0.114 0.0937
(0.149) (0.189)
lnCredit_amout -0.109 -0.114
(0.119) (0.150)
Observations 586 586
Number of IGA_5 5
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

23. Estimation Result 7 : Percapita Sales
VARIABLES OLS Robust Reg Tobit xtReg xtTobit
Consmeeting -1.775** 0.0755 -1.860*** -1.775 -1.966***
(0.750) (0.0876) (0.520) (1.407) (0.522)
Business_Plan -0.264 0.173* 0.0619 -0.264 0.0682
(0.556) (0.0919) (0.559) (0.641) (0.557)
IGA_training 0.360* 0.191*** 0.741* 0.360* 0.685*
(0.217) (0.0648) (0.391) (0.212) (0.391)
IGA_adivice 0.106 0.0189 0.0932 0.106 0.0953
(0.382) (0.0846) (0.506) (0.365) (0.502)
Input_market linkage 0.361 0.127* 0.592 0.361 0.588
(0.270) (0.0704) (0.411) (0.258) (0.416)
lnCredit_amout -0.914** -0.0644 -0.990*** -0.914* -1.007***
(0.422) (0.0552) (0.324) (0.549) (0.323)
Observations 586 586 586 586 586
Number of IGA_5 5 5
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

24. Estimation Result 8: Rate of Return
VARIABLES OLS Robust Reg Tobit xtReg xtTobit
Consmeeting -0.630 -0.0468 -0.711* -0.630 -0.759*
(0.717) (0.0952) (0.414) (0.814) (0.419)
Business_Plan 0.0132 0.0847 -0.177 0.0132 -0.160
(0.215) (0.0998) (0.434) (0.256) (0.435)
IGA_training 0.367 0.168** 0.404 0.367 0.402
(0.390) (0.0704) (0.308) (0.329) (0.308)
IGA_adivice 0.611** 0.155* 0.988** 0.611* 0.982**
(0.278) (0.0919) (0.411) (0.344) (0.410)
Input_marketlinkage 0.303 0.221*** 0.375 0.303** 0.312
(0.268) (0.0764) (0.328) (0.149) (0.343)
lnCredit_amout -0.222 -0.121** -0.181 -0.222 -0.186
(0.263) (0.0600) (0.257) (0.359) (0.257)
Observations 586 586 586 586 586
IGA_5 5 5

25. Estimation Result 9 : Over all performance of IGAs
VARIABLES Probit xtProbit
consmeeting -0.130 -0.236
(0.184) (0.226)
Business_Plan -0.129 -0.0651
(0.202) (0.323)
IGA_training 0.603*** 0.566***
(0.143) (0.148)
IGA_adivice 0.255 0.255*
(0.183) (0.141)
input_marketlinkage 0.164 0.174
(0.149) (0.182)
lnCredit_amout -0.0902 -0.0777
(0.118) (0.166)
Observations 586 586
Number of IGA_5 5
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

26. Conclusion
 The findings of the different regression outputs show that the effectiveness
of program supports varies across type of IGAs,
 C-1: Training specific to an IGA is effective program support to both on-
farm and off-farm activities
 C-2: while frequent technical advice positively contributes to the success of
on-farm IGAs , it adversely affects success of off-farm IGAs
 C-3:Market linkage support significantly increases the probability of
success in rural income diversification specially for on-farm activities
 C-4: While credit amount has no relevance for off-farm IGA success, it has
an adverse effect for on-farm IGAs
 Business plan has no significant effect on all IGA’s success.
 C-4 : Consultation meeting has shown an adverse impact for IGA’s Success
?????

27. Thank you!