Information and Communications Technology, Agricultural Profitability and Child labour in Rural Peru

South America

Peru

Social Protection

Infrastructure

DW Beuermann

2015

Beuermann, Diether W. “Information and Communications Technology, Agricultural Profitability and Child Labor in Rural Peru.” Review of Development Economics 19.4 (2015): 988–1005. Web.
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Secondary Data: Peruvian Living Standards Measurement Survey (PLSMS) and Peruvian National Household Survey (ENAHO). Shuttle Radar Topography Mission (Nasa). FITEL’s administrative information contains the GPS location of each phone and the date at which the phone became operative. Data is not available online.

2015

N. A.

2001-2004 (beginning and end of rollout)

The program consisted in providing at least one public payphone to each targeted rural village in Peru. The paper examines the impact of providing public payphones among isolated villages in rural Peru to identify the effects of information and communication technology (ICT) on agricultural profitability and child labor.

The 6296 targeted villages situated across rural Peru had not any kind of phone services (either fixed lines or mobile coverage) before the intervention, so these payphones were the first opportunity for villagers to communicate with the rest of the country without having to physically travel.

The intervention was carried out by the Peruvian Fund for Investments in Telecommunications (FITEL), which provided at least one public (satellite) payphone between the years 2001 and 2004 to each of the 6296 targeted villages situated across rural Peru. None of these villages had any kind of phone services (either fixed lines or mobile coverage) before the intervention, so these payphones were the first opportunity for villagers to communicate with the rest of the country without having to physically travel. According to FITEL’s documents, the intervention reduced the average distance from any rural village in Peru to the nearest communication point from 60 to 5 kilometers.

• Enrollment in School
• Engagement in any combination of school and work (work in agriculture or others)

Difference-in-difference

Study design: the author exploits differences in the timing of the intervention across villages to identify the impacts of payphones on agricultural profitability and the utilization of child labor, after showing that these differences in timing were orthogonal to the baseline levels of the outcomes. This intervention occurred in places where neither mobile phones nor fixed-line phones were available. The treated villages were located in zones where mobile phone coverage was technically and economically unfeasible. The satellite technology

implemented did not require villages to possess fixed lines or electrical supply to enjoy the service. Therefore, phone placement only followed the criteria of being provided to villages without prior access to ICT. This, coupled with differences in timing for phone placement that were uncorrelated with baseline characteristics, allows us to identify the impacts of interest using a panel of intervened villages.
Sample: the sample includes only villages situated within a radius of 30 minutes of traveling time to the nearest phone (the mean travel time in the final sample is 6 minutes). Then, within these villages, we only

focused on households that reported both agricultural production and agricultural costs. Our final sample consists of 15,242 household-year and 15,501 children (6–13 years old)-year observations, distributed across 2453 village-year observations. The difference between the intervention timing patterns provided by the sample and the overall program timing is statistically indistinguishable from zero.
Survey Instrument: The first data source is the Peruvian Living Standards Measurement Survey (PLSMS) for the years 1997 and 2000, succeeded by the Peruvian National Household Survey (ENAHO) for the years 2001–2007. The ENAHO replaced the PLSMS and most of their questionnaires mimic those of the PLSMS ones. Both surveys are nationally representative. These surveys contain information on demographics, education, income, and expenses.

The income shock that resulted from the intervention was translated into a reduction in the share of children that combine work with school equivalent to 36%. This reduction translated into an increase in the share of children fully dedicated to the school by 32%.

Child Labour

Households

Local

The income shock that resulted from the intervention was translated into a reduction in the share of children that combine work with school equivalent to 36%.

The program has led to an increase in the share of children fully dedicated to the school by 32%.

The positive adult labor supply effects were consistent with a substitution for lower child labor utilization. The likelihood of being engaged only in school was affected more heavily for boys than for girls (20 vs 14 percentage points). Impacts within the age range of 6–9 years old are evenly distributed between boys and girls, but for the age range 10–13 years old, boys show stronger effects than girls.