Beyond the records: Data quality and COVID-19 vaccination progress in low- and middle-income countries
Journal of Development Economics · 2025 · Yannick Markhof、Philip Wollburg、Alberto Zezza
中文摘要
利用36个低收入和中等收入国家（LMICs）的电话调查和行政数据，我们发现，基于调查的COVID-19疫苗覆盖率系统性高于行政数据，平均高出47%。这种差异在撒哈拉以南非洲最为突出，引发了对数据质量如何影响我们理解疫苗接种进展的疑问。我们利用在五个撒哈拉以南非洲国家开展的六项调查实验，分离出抽样误差和测量误差对疫苗接种率估计值的影响。将受访者选择效应纳入考虑后，不同数据来源之间的不一致平均减少了42%。其他通常令人担忧的误差来源，包括策略性误报、面板条件效应和调查模式效应，均不影响调查估计值。在对调查数据中的误差进行调整后，其与官方数据之间仍存在平均9个百分点的实质性差距；这一差距似乎与行政记录中的缺陷有关，我们利用覆盖全球全部136个低收入和中等收入国家的数据记录了这些缺陷。我们的研究结果就现代数据源中测量误差的大小及来源提供了新的证据；近年来，发展经济学家对这类数据源的使用大幅增加。尽管在撒哈拉以南非洲，经误差校正后的疫苗覆盖率估计值平均仍仅为当时高收入国家疫苗接种率的三分之一，但这些估计值表明，疫苗接种进展本身可能比公众讨论中对非洲国家的认可更快。• 数据质量问题影响了我们对36个低收入和中等收入国家样本中COVID-19疫苗接种进展的理解 • 基于调查估计的疫苗覆盖率表明，撒哈拉以南非洲的疫苗接种进展比行政记录所显示的快得多 • 在调查设计中考虑受访者选择效应，可使不同数据来源之间的不一致平均减少42% • 社会赞许性、面板条件效应和调查模式效应均不影响估计值 • 剩余差异似乎与行政记录中的缺陷有关，我们利用覆盖全球全部136个低收入和中等收入国家的数据记录了这些缺陷
Abstract
Using phone surveys and administrative data in 36 LMICs, we find survey-based COVID-19 vaccine coverage to systematically exceed administrative figures by 47% on average. This discrepancy is strongest in Sub-Saharan Africa, raising questions about the role of data quality for our understanding of vaccination progress. We isolate the effect of sampling and measurement errors on the estimated vaccination rate in six survey experiments conducted in five Sub-Saharan African countries. Accounting for respondent selection effects reduces misalignment between data sources by 42% on average. Other commonly feared error sources including strategic misreporting, panel conditioning, or survey mode effects do not affect survey estimates. After adjusting for errors in the survey data, a substantial average gap of 9 percentage points remains with the official figures and seems to relate to flaws in administrative records that we document using data covering all 136 LMICs worldwide. Our results provide novel evidence on the size and sources of measurement error in modern data sources that have seen a surge in use by development economists over the last years. While our error-corrected estimates of vaccine coverage are still, on average, only a third as high in Sub-Saharan Africa as vaccination rates in high-income countries at the time, they imply that vaccination progress itself may have been quicker than what African countries were credited for in the public discourse. • Data quality issues impact our understanding of COVID-19 vaccination progress in a sample of 36 LMICs • Vaccine coverage estimated with surveys suggests much quicker progress than administrative records in Sub-Saharan Africa • Accounting for respondent selection effects in survey design reduces misalignment by 42% on average • Social desirability, panel conditioning, or survey mode effects do not affect estimates • Remaining differences seemingly relate to flaws in administrative records that we document with data for all 136 LMICs worldwide