Short recall periods and phone surveys improve fisheries data in Cambodia

What is it about?

This paper looks at how well household surveys capture what small‑scale fishing families actually catch and earn in Cambodia. It compares different “recall periods” in which fishers are asked to remember their catches, costs, and fishing days over a week, a month, a season, or a full year. The study uses randomized survey experiments to see how much people over‑ or under‑report when asked to remember farther back in time. It also tests whether using mobile phone interviews, instead of only face‑to‑face visits, can collect more accurate and cost‑effective fisheries information. The authors find that longer recall periods lead fishers to significantly overstate how much fish they caught and how much income they earned, and to understate how many species they caught. In contrast, fishers are fairly accurate when recalling more stable information like prices and days spent fishing. Seasonal phone interviews show less exaggeration of catch and income than in‑person seasonal interviews, suggesting that mobile surveys can help improve data quality while reducing costs. Overall, the paper provides practical evidence on how to design better survey questions and fieldwork strategies so that national statistics on small‑scale fisheries are closer to reality.

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Why is it important?

Many countries rely on household and agricultural surveys to understand the contribution of small‑scale fisheries to jobs, income and food security, especially where most fish is caught and traded informally. If recall periods are too long, the resulting data can be badly biased, with catch and income overstated by more than 200 percent in some cases and species diversity understated, which in turn can distort policies, resource assessments and poverty analysis. This study is one of the first to quantify recall bias for fisheries outputs across weekly, monthly, seasonal and annual reference periods using a randomized experimental design in a real‑world setting. The work shows that shorter and more frequent recall periods, such as weekly or monthly, clearly improve accuracy for key variables like volumes and values, while longer seasonal or annual recall used in many existing surveys can severely inflate estimates. It also demonstrates that phone‑based seasonal interviews can reduce some of the upward bias seen in seasonal face‑to‑face interviews, pointing to a scalable way for low‑ and middle‑income countries to collect higher‑frequency fisheries data at lower cost. The findings give concrete guidance to survey designers and statistical offices on how to balance recall bias, seasonality, and budget constraints when measuring fisheries production and income.

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