Estimating the prevalence of child labour in the cocoa industry via indirect elicitation methods: a mixed-methods study

Abstract Data from children suggest that the prevalence of child labour in the cocoa industry in Côte d’Ivoire is a worrying 38%. However, while surveying children has the potential to reduce sensitivity biases such as social desirability bias, it presents significant ethical dilemmas and may also be associated with other reporting biases, making accurate estimates of child labour difficult. To address this, we collected data from 1741 cocoa producers to assess whether parents could provide more accurate estimates using indirect survey methods. We compared direct questioning with a list experiment and a novel non-verbal method (‘colorbox’). We found higher prevalence rates of child labour using indirect elicitation methods, but lower than those obtained from children’s surveys. Qualitative in-depth interviews revealed motivations for underreporting, including fear of legal consequences and mistrust of stakeholders. Indirect methods alone are not sufficient to correct for underreporting when child labour is collected from parents. Future research should prioritise direct data collection from children and address ethical concerns to obtain more accurate estimates of child labour.

Authors

Institutions

Publication Details

Journal
Journal of Population Economics
Published
2024-11-11
DOI
https://doi.org/10.1007/s00148-024-01054-3
Citations
5
Primary Topic
Poverty, Education, and Child Welfare
Type
article
Field-Weighted Citation Impact
2.10
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimating the prevalence of child labour in the cocoa industry via indirect elicitation methods: a mixed-methods study

Carole Treibich, Henry Cust, Megan Passey, Aurélia Lépine et al.
5 citations
Journal of Population Economics
Poverty, Education, and Child Welfare
2.10
article

Estimating the prevalence of child labour in the cocoa industry via indirect elicitation methods: a mixed-methods study

Carole Treibich, Henry Cust, Megan Passey, Aurélia Lépine, Ariane Ndiore, Laurent Foubert, Selina Binder
article en
5 citations

Abstract

Abstract Data from children suggest that the prevalence of child labour in the cocoa industry in Côte d’Ivoire is a worrying 38%. However, while surveying children has the potential to reduce sensitivity biases such as social desirability bias, it presents significant ethical dilemmas and may also be associated with other reporting biases, making accurate estimates of child labour difficult. To address this, we collected data from 1741 cocoa producers to assess whether parents could provide more accurate estimates using indirect survey methods. We compared direct questioning with a list experiment and a novel non-verbal method (‘colorbox’). We found higher prevalence rates of child labour using indirect elicitation methods, but lower than those obtained from children’s surveys. Qualitative in-depth interviews revealed motivations for underreporting, including fear of legal consequences and mistrust of stakeholders. Indirect methods alone are not sufficient to correct for underreporting when child labour is collected from parents. Future research should prioritise direct data collection from children and address ethical concerns to obtain more accurate estimates of child labour.

Journal of Population EconomicsVol. 37(4)
Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Laboratoire d'Economie Appliquée de Grenoble (FR), University College London (GB), Université Félix Houphouët-Boigny (CI), Université Grenoble Alpes (FR)
Decent work and economic growth
Openalex Percentile: Top 11%
Poverty, Education, and Child Welfare
2.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.