商业调查中的回应负担和数据质量

IF 0.5 4区 数学 Q4 SOCIAL SCIENCES, MATHEMATICAL METHODS
Marco Bottone, Lucia Modugno, A. Neri
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引用次数: 2

摘要

摘要响应负担一直是数据生产者关注的问题。在这篇文章中,我们调查了一些实际负担和感知负担的衡量标准之间的关系,并提供了它们与数据质量相关的经验证据。我们借鉴了意大利银行自1970年以来进行的两次商业调查,这两次调查提供了非常丰富和独特的信息来源。我们发现有证据表明,感知负担受到实际负担的影响,但实际负担并不是唯一的驱动因素。我们的研究结果还表明,受访者的感知努力与不回答一些重要问题(如与未来投资和营业额预期有关的问题)或退出调查的可能性之间存在明显联系。相反,我们没有发现对业务营业额和投资等定量问题的答案质量有显著影响。总的来说,这些发现对数据生产者有启示,他们应该针对实际负担之外的感知负担,以提高数据质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Response Burden and Data Quality in Business Surveys
Abstract Response burden has long been a concern for data producers. In this article, we investigate the relationship between some measures of actual and perceived burden and we provide empirical evidence of their association with data quality. We draw on two business surveys conducted by Banca d’Italia since 1970, which provide a very rich and unique source of information. We find evidence that the perceived burden is affected by actual burden but the latter is not the only driver. Our results also show a clear link between a respondent’s perceived effort and the probability of not answering some important questions (such as those relating to expectations of future investments and turnover) or of dropping out of the survey. On the contrary, we do not find significant effects on the quality of answers to quantitative questions such as business turnover and investments. Overall, these findings have implications for data producers that should target the perceived burden, besides the actual burden, to increase data quality.
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来源期刊
Journal of Official Statistics
Journal of Official Statistics STATISTICS & PROBABILITY-
CiteScore
1.90
自引率
9.10%
发文量
39
审稿时长
>12 weeks
期刊介绍: JOS is an international quarterly published by Statistics Sweden. We publish research articles in the area of survey and statistical methodology and policy matters facing national statistical offices and other producers of statistics. The intended readers are researchers or practicians at statistical agencies or in universities and private organizations dealing with problems which concern aspects of production of official statistics.
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