This presentation is part of the programme of the International Seminar "Social Protection, Entrepreneurship and Labour Market Activation: Evidence for Better Policies", organized by the International Policy Centre for Inclusive Growth (IPC-IG/UNDP) together with Canada’s International Development Research Centre (IDRC) and the Colombian Think Tank Fedesarrollo held on September 10-11 at the Ipea Auditorium in Brasilia.

1. The impact of Sierra Sur for JUNTOS
beneficiaries
The case of Chumbivilcas, Cusco,
Perú
Ursula Aldana
Tania Vásquez
Johanna Yancari
Victor Huamaní

2. Introduction
Objetive of this research:
• Gain knowledge on the impact of the productive
project Sierra Sur for JUNTOS beneficiaries.
• Important social impact because JUNTOS
beneficiaries are poor and live in underdeveloped
areas of the country.
• The correct application of a productive project can
help smooth the change in welfare when the transfer
is removed.

3. The Sierra Sur project
Components
1- Natural resource management (NRM)
2- Strengthening local markets (SLM).
Subcomponents of NRM
1- Contests at the comunal and at the family level
2- Technical assistance
Subcomponentes of SLM
1- Business Development: technical assistance and local
development projects (internet)
2- Financial inclusion

4. The Sierra Sur project
Selection process:
The users, grouped in organizations, present their
workplans. These workplans include their technical
assistance requirements.
First supply filter:
The local office evaluates the workplans. In the case of
BD there is a evaluation in the field.

5. The Sierra Sur project
Second supply filter:
The organizations present their workplans in a contest
(CLAR).
The individuals of the organizations that pass this
second filter can:
- Participate in the contests and in the technical
assistance activity, in the case of the NRM component.
- Participate in the technical assistance activity, in the
BD sub component.

6. Methodology
The treatment groups are given by households of the
individuals that have participated in the CLAR contests
(for NRM and/or BD) and that belong to JUNTOS.
The control groups are given by JUNTOS households
that live in the control area and would participate if SS
were offered in their area.
This potential participation is assessed through
hypothetical questions.

7. Methodology
To control for the first supply filter, we include as control
variables the ones considered in this filter (experience
and assets assessed on the field).
Control groups
The first control group is given by the hh were the
person surveyed responded that she was willing to
participate in SS and to pay at least the minimum
amount paid in Chumbivilcas.

8. Methodology
80% of the surveyed persons passed this filter.
In contrast, only 20% of the hh in Chumbivilcas
participated in SS.
It is likely that persons that say they are willing to
participate will decide not to do so at the moment of
really investing time and money.
We check if the results persist if we shorten the control
sample to include those that are willing to pay a higher
amount.

9. Methodology
Number of observations in the treatment and control groups
Number of observations
Pre-matching Post-matching
Groups
According to SS 382 321
According to organization survey 219 187
According to household survey 317 265
Did not pass the filter 30 -
Passed the filter 388 366
WTP > 20th pctile 221 210
WTP > 50th pctile 125 117
Treatment
groups
Control
groups

10. Treatment groups
Three treatment groups:
-Passed the first filter according to SS
-Received training according to the survey + non benef
-Received SS training according to the leader of the
organization + non benef
We also control for a group of socio-economic and socio-demographic
characteristics using propensity score
matching.
Methodology

11. Results
Impact on the implementation of new practices
Treatment
Genetic
New pasture
New tree
Control groups
groups
improvement 1/
species 2/
species 3/
0.180 *** 0.156 *** 0.157 ***
0.179 *** 0.181 *** 0.153 ***
0.180 *** 0.161 *** 0.114 ***
0.224 *** 0.159 *** 0.173 ***
0.220 *** 0.184 *** 0.168 ***
0.224 *** 0.155 *** 0.137 ***
0.191 *** 0.180 *** 0.157 ***
0.187 *** 0.207 *** 0.151 ***
0.190 *** 0.187 *** 0.115 ***
Treated
according to
SS
Passed the fi lter
WTP > 20th pcti le
WTP > 50th pcti le
Passed the fi lter
WTP > 20th pcti le
WTP > 50th pcti le
Treated
according to
organization
survey
Passed the fi lter
WTP > 20th pcti le
WTP > 50th pcti le
Treated
according to
household
survey
1/ The dependent is one if the household made genetic improvement for the first time after 2006, at
least for one animal species
2/ The dependent is one if the household installed new pasture species for the first time after 2006
3/ The dependent is one if the household installed new tree species for the first time after 2006
4/ * Significant at 10%, ** significant at 5%, *** significant at 1%

12. Results
Impact on organizational capital
Treatment
groups
Control groups
Activities with
organization
Remains in
organization
Passed the filter -0.002 0.012
WTP > 20th pctile -0.009 0.006
WTP >50th pctile -0.054 ** -0.035
Passed the filter -0.012 -0.014
WTP > 20th pctile -0.024 -0.029
WTP >50th pctile -0.027 -0.040
Passed the filter 0.005 0.023
WTP > 20th pctile 0.000 0.017
WTP >50th pctile -0.037 -0.011
Treated
according to
SS
Treated
according to
organization
survey
Treated
according to
household
survey
1/ The dependent is one if the household done any activity with the organization in
the last 5 years
2/ The dependent is one if any household member belongs to an organization which
became part in 2005
3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

13. Average impact
Results
There is an important average impact (btw 10 and 20%)
on:
– Genetic Improvement
– Use of new vaccines
– Use of new antiparasites
– Installation of terraces
– Installation reservoirs
– Installation of pasture
– Installation of trees

14. Results
• We found no impact on organizational capital.
• We found no robust evidence of impact on gross
income.
• In the case of net income the estimated impact is
negative, even though not always statistically
significant.

15. Results
Diferentiated impact on the quantity index of productive assets 1/
Quantity
index of
productive
assets in 2005
HH
Dependency
ratio
2006/07
Popoulation of the
village 2006/07
Average years of
education (hh head
and partner)
-64.779 506.822 -81.021 957.982
*** *** ***
-63.949 742.752 -85.077 971.023
*** *** ***
-38.426 937.218 -127.709 1,569.174
*** ***
-52.758 761.097 -120.178 1,571.593
*** ***
-71.135 689.349 -83.336 1,087.663
*** *** ***
-78.735 742.557 -87.701 1,090.643
*** *** ***
Group
Treated
according to SS
Treated
according to
organization
survey
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
1/ Change in the value of productive assets between 2005 and 2013, in soles
2/ Thousands of new soles
3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

16. Results
Diferentiated impact on the quantity index of productive assets 1/
Time to the
nearest city
(minutes)
Elderly dependency
ratio in the village
2006/07
Time to the
nearest
city*popoulation
of the village
Intercept
-56.880 -703.073 0.550 5,487.65
*** *** ***
-69.445 -112.129 0.630 5,592.66
*** *** ***
-87.340 -1,968.103 0.839 7,018.63
*** *** ***
-95.994 8,482.992 0.853 6,841.24
*** *** ***
-53.407 1,610.785 0.533 5,346.13
*** *** ***
-68.523 2,825.410 0.635 5,978.84
*** *** ***
Group
Treated
according to
SS
Treated
according to
organization
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
1/ Change in the value of productive assets between 2005 and 2013, in soles
2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

17. Results
Diferentiated impact on gross income 1/
Quantity
index of
productive
assets in 2005
HH
Dependency
ratio
2006/07
Popoulation of
the village
2006/07
Average years of
education (hh
head and partner)
0.004 0.024 -0.000 0.073
** ***
0.004 -0.020 -0.000 0.081
** ***
0.013 0.030 -0.000 0.076
*** ***
0.012 0.044 -0.004 0.080
*** * ***
0.004 0.025 0.000 0.071
** ***
0.003 0.092 -0.002 0.065
* ***
Group
Treated
according to SS
Treated
according to
organization
survey
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
1/ In logs. The original variable is in soles
2/ Thousands of new soles
3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

18. Results
Diferentiated impact on gross income 1/
Time to the
nearest city
(minutes)
Elderly dependency
ratio in the village
2006/07
Time to the
nearest
city*popoulation
of the village
Intercept
0.003 1.405 -0.000 -0.538
*** ** * ***
0.002 1.850 -0.000 -0.643
* *** ***
0.005 -0.341 -0.000 -0.766
*** ** ***
-0.000 2.787 0.000 -0.659
* **
0.003 2.038 -0.000 -0.583
** *** ***
0.000 1.379 0.000 -0.385
Group
Treated
according to
SS
Treated
according to
organization
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
1/ In logs. The original variable is in soles
2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

19. Results
Diferentiated impact on net income 1/
Quantity
index of
productive
assets in 2005
HH
Dependency
ratio
2006/07
Popoulation of
the village
2006/07
Average years of
education (hh
head and partner)
28.527 -100.526 1.414 289.528
** ***
19.738 -150.768 0.066 330.885
** ***
66.225 63.856 -5.426 288.549
*** ***
38.150 123.387 -14.771 384.744
* ***
27.401 -144.729 2.284 278.819
** ***
15.059 -4.914 -7.223 267.334
* ***
Group
Treated
according to SS
Treated
according to
organization
survey
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
1/ Only considered daily wages paid. In soles.
2/ Thousands of new soles
3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

20. Results
Diferentiated impact on net income 1/
Time to the
nearest city
(minutes)
Elderly dependency
ratio in the village
2006/07
Time to the
nearest
city*popoulation
of the village
Intercept
13.033 6,939.041 -0.081 -3,482.38
*** ** * ***
2.209 11,154.358 -0.008 -3,704.34
*** ***
14.621 -1,122.090 -0.063 -3,886.14
** ***
-5.107 14,125.526 0.096 -3,907.09
* ***
10.881 9,962.124 -0.084 -3,262.39
* *** ***
-5.455 10,859.951 0.046 -2,321.09
*** **
Group
Treated
according to
SS
Passed the
filter
WTP > 20th
pctile
Treated
according to
organization
survey
Treated
according to
household
survey
Passed the
filter
WTP > 20th
pctile
Passed the
filter
WTP > 20th
pctile
1/ Only considered daily wages paid. In soles.
2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

21. Conclusions
• We have found an important impact on the
implementation of new technologies.
• Have not found impact on investment or income
• The educational level mediates the impact on new
technologies, investment and income.
• This could be related to a better understanding of
the training or to a higher access to liquidity