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MAKING THE MOST OF IMPERFECT DATA: A CRITICAL EVALUATION OF STANDARD INFORMATION COLLECTED IN FARM HOUSEHOLD SURVEYS

机译:充分利用最完美的数据:农场家庭调查中收集的标准信息的关键评估

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摘要

Household surveys are one of the most commonly used tools for generating insight into rural communities. Despite their prevalence, few studies comprehensively evaluate the quality of data derived from farm household surveys. We critically evaluated a series of standard reported values and indicators that are captured in multiple farm household surveys, and then quantified their credibility, consistency and, thus, their reliability. Surprisingly, even variables which might be considered ‘easy to estimate’ had instances of non-credible observations. In addition, measurements of maize yields and land owned were found to be less reliable than other stationary variables. This lack of reliability has implications for monitoring food security status, poverty status and the land productivity of households. Despite this rather bleak picture, our analysis also shows that if the same farm households are followed over time, the sample sizes needed to detect substantial changes are in the order of hundreds of surveys, and not in the thousands. Our research highlights the value of targeted and systematised household surveys and the importance of ongoing efforts to improve data quality. Improvements must be based on the foundations of robust survey design, transparency of experimental design and effective training. The quality and usability of such data can be further enhanced by improving coordination between agencies, incorporating mixed modes of data collection and continuing systematic validation programmes.
机译:家庭调查是对农村社区洞察力的最常用工具之一。尽管他们普遍存在,但很少有研究全面评估农场家庭调查的数据质量。我们批判性地评估了一系列标准报告的价值观和指标,这些价值观和指标在多个农场户口调查中捕获,然后量化了他们的可信度,一致性,从而定化了它们的可靠性。令人惊讶的是,甚至可能被认为是“易于估计”的变量有不可信的观察的实例。此外,发现玉米产量和土地的测量被认为比其他固定变量更可靠。这种可靠性缺乏可靠性对监测粮食安全状况,贫困地位和家庭的土地生产力的影响。尽管存在这种情况相当黯淡的图片,我们的分析还表明,如果同一农场家庭随着时间的推移,检测大量变化所需的样本尺寸是数百个调查,而不是数千个。我们的研究突出了有针对性和系统化的家庭调查的价值以及持续努力提高数据质量的重要性。改进必须基于强大的调查设计,实验设计透明度和有效培训的基础。通过改善机构之间的协调,包含混合数据收集和持续系统验证程序的混合模式,可以进一步提高这些数据的质量和可用性。

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