The impact of Sierra Sur for JUNTOS

beneficiaries

The case of Chumbivilcas, Cusco,

Perú Ursula Aldana

Tania Vásquez

Johanna Yancari

Victor Huamaní

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.

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

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.

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.

The Sierra Sur project

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.

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.

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.

Methodology

Number of observations in the treatment and control groups

Methodology

Pre-matching Post-matching

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

GroupsNumber of observations

Treatment

groups

Control

groups

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

Results Impact on the implementation of new practices

Treatment

groupsControl groups

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 ***

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%

Treated

according to

SS

Passed the fi lter

WTP > 20th pctile

WTP > 50th pctile

WTP > 20th pctile

WTP > 50th pctile

Treated

according to

organization

survey

Passed the fi lter

WTP > 50th pctile

1/ The dependent is one if the household made genetic improvement for the first time after 2006, at

least for one animal species

Treated

according to

household

survey

Passed the fi lter

WTP > 20th pctile

New tree

species 3/

New pasture

species 2/

Genetic

improvement 1/

Impact on organizational capital

Results

Treatment

groupsControl groups

Activities with

organization

Remains in

organization

Passed the filter -0.002 0.012WTP > 20th pctile -0.009 0.006

WTP >50th pctile -0.054 ** -0.035Passed the filter -0.012 -0.014WTP > 20th pctile -0.024 -0.029

WTP >50th pctile -0.027 -0.040Passed the filter 0.005 0.023WTP > 20th pctile 0.000 0.017

WTP >50th pctile -0.037 -0.011

3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

2/ The dependent is one if any household member belongs to an organization which

became part in 2005

Treated

according to

household

survey

1/ The dependent is one if the household done any activity with the organization in

the last 5 years

Treated

according to

SS

Treated

according to

organization

survey

Average impact

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

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.

Results

Diferentiated impact on the quantity index of productive assets 1/

Results

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

*** *** ***

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%

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

Group

Treated

according to SS

Passed the

filter

WTP > 20th

pctile

Diferentiated impact on the quantity index of productive assets 1/

Results

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

*** *** ***

1/ Change in the value of productive assets between 2005 and 2013, in soles

2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

Group

Treated

according to

SS

Passed the

filter

WTP > 20th

pctile

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Diferentiated impact on gross income 1/

Results

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

* ***

1/ In logs. The original variable is in soles

2/ Thousands of new soles

3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

Group

Treated

according to SS

Passed the

filter

WTP > 20th

pctile

Diferentiated impact on gross income 1/

Results

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

1/ In logs. The original variable is in soles

2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

Group

Treated

according to

SS

Passed the

filter

WTP > 20th

pctile

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Diferentiated impact on net income 1/

Results

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

* ***

1/ Only considered daily wages paid. In soles.

2/ Thousands of new soles

3/ * Significant at 10%, ** significant at 5%, *** significant at 1%

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

Group

Treated

according to SS

Passed the

filter

WTP > 20th

pctile

Diferentiated impact on net income 1/

Results

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

*** **

1/ Only considered daily wages paid. In soles.

2/ * Significant at 10%, ** significant at 5%, *** significant at 1%

Group

Treated

according to

SS

Passed the

filter

WTP > 20th

pctile

Treated

according to

household

survey

Passed the

filter

WTP > 20th

pctile

Treated

according to

organization

survey

Passed the

filter

WTP > 20th

pctile

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