Poverty in low-income countries is usually measured using large and infrequent household consumption surveys. The challenge is to find methods to measure poverty rates more frequently. This study validates a survey-to-survey imputation method, based on a statistical model utilizing consumption surveys and light surveys to measure changes in poverty rates over time. A decade of poverty predictions and regular poverty estimates in Malawi provides a unique case study. The analysis suggests that this modelling approach works within the same context given that households’ demographic composition is included in the model. Predicting poverty using different surveys is challenging because of different aspects of comparability. A new way to account for seasonal coverage strengthens the model when imputing for surveys covering different seasons. It is important for national statistics offices and supporting agencies to prioritize maintaining consistency in the way data are collected in surveys to provide comparable trends over time.

中文翻译：

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通过调查对调查估算预测贫困趋势：可比性的挑战

低收入国家的贫困通常使用大型且不频繁的家庭消费调查来衡量。挑战在于找到更频繁地衡量贫困率的方法。本研究验证了一种调查到调查的插补方法，该方法基于一个统计模型，利用消费调查和轻度调查来衡量贫困率随时间的变化。马拉维十年的贫困预测和定期贫困估计提供了一个独特的案例研究。分析表明，鉴于模型中包含了家庭的人口构成，这种建模方法在相同的背景下有效。由于可比性的不同方面，使用不同的调查预测贫困具有挑战性。在对涵盖不同季节的调查进行估算时，一种解释季节性覆盖的新方法可以加强模型。