Assessing the impacts of a peer-to-peer training programme for women in Peru

ABSTRACT

This article reports on research that aimed to assess the economic and social impacts of a peer-to-peer training programme targeted to women in Peru, looking at overall and differentiated impacts according to design features, on a sample of 300 women in participant and non-participant communities. The study found significant positive impacts on women’s time devoted to work outside the house and in their saving propensity, although no significant change on time allocated to domestic activities. It also detected some effects on an index of family cohesion and on home improvements. Finally, there was evidence that some design features influence the magnitude and significance of these impacts.

KEYWORDS:

• Gender and diversity
• Labour and livelihoods – Economics
• Methods
• Aid – Monitoring and Evaluation, Development policies, Capacity development
• Civil society – NGOs
• Latin America and the Caribbean

Acknowledgements

The authors are grateful to Milagros Panta, Director of Condoray for her support and interest in this research, as well as to Hugo Ñopo (GRADE) and PEP experts for valuable comments and suggestions on a previous version of this article. All remaining errors are ours.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Eduardo Zegarra is an Economist at the Pontifical Catholic University of Peru and has a PhD in Agricultural and Applied Economics at the University of Wisconsin.

Angie Higuchi is an Associate Researcher and Professor at the Department of Management, Universidad del Pacífico, Lima, Peru.

Ricardo Vargas is an assistant researcher at the Grupo de Analisis para el Desarrollo, Lima, Peru.

ORCID

Eduardo Zegarra http://orcid.org/0000-0001-5411-778X

Notes

1 For the control group, we carried out a searching procedure of potential control communities only within the Province of Cañete, restricting the search to the communities with a population between 400 and 3,300, a similar range to that of the treatment group of localities. A total of 52 towns were considered for the random selection process. We classified these in four strata, according to size and percentage of women with higher education (more than high school level). We randomly selected five towns in each of the four strata for a total of 20 potential communities for the control group. For the field work, we took a simple random sample of 15 of these 20 towns to be surveyed (equal to the treatment group), with a target of 10 women surveyed per town. In this case, enumerators were instructed to select in situ a sample of households, and within each household, an adult woman to interview according to the criterion that there was at least one adult woman present in the household to respond to the survey.

2 For the expansion factor of each observation we used the probability of selection from the list on enrolled women in the case of the treated group. For the control group we adjusted the denominator of the probability of selection with an “expected number of enrolees”, that is, an estimate of the number of women that would have enrolled if the programme entered these localities. This was done to avoid inflating the expansion factor for the control group if we merely used the adult women population size of each selected town for the calculation.

3 We used the statistical software Stata, version 12.0, with its ebalance command.

4 These type of effects are reported, for instance, in Singth, Peshin, and Saini (2001) for an urban-agriculture programme in South Africa: “[the programme] is important to women of low-income households in ways less directly related to monetary gain. Women use urban agriculture to establish social networks, to symbolize a sense of security and to encourage community development” (635). Walk et al. (2015) also report a network effect for a job and skills training programme in Canada.

Additional information

Funding

This research was carried out with financial and scientific support from the Partnership for Economic Policy (PEP) (www.pep-net.org) with funding from the Department for International Development (DFID) of the United Kingdom (or UKAid), and the Government of Canada through the International Development Research Center (IDRC).