Social security administrative data are increasingly becoming available in many countries. These data have a long panel structure (large N, large T) and allow for the measurement of many different variables with high accuracy. It also captures short-term unemployment spells which are normally unavailable in survey data due to its design. However, the measurement of unemployment differs in both types of datasets. The resulting gap between total unemployment and registered unemployment is not constant across workers characteristics or time. In this paper, I present a simple, systematic method to expand the raw Spanish Social Security administrative data. I identify unemployed workers who are not receiving unemployment benefits, using information from the institutional framework and using the Labour Force Survey as a benchmark. The resulting unemployment rates and labour market flows are comparable across both datasets. Administrative data can also overcome some of the problems of the Labour Force Survey, such as changes in the structure of the survey. This paper aims to provide a comprehensive guide on how to adapt administrative datasets to make them useful for studying unemployment.

中文翻译：

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以调查数据为基准的行政数据中的失业人数

许多国家越来越多地使用社会保障行政数据。这些数据具有长的面板结构（大N，大T），并允许高精度地测量许多不同的变量。它还捕获由于设计而通常在调查数据中不可用的短期失业法。但是，两种类型的数据集的失业率测量方法都不同。在不同的工人特征或时间范围内，总失业率与登记失业率之间的差距并不是恒定的。在本文中，我提出了一种简单，系统的方法来扩展原始的西班牙社会保障管理数据。我使用制度框架中的信息并以“劳动力调查”为基准，确定没有领取失业救济金的失业工人。由此产生的失业率和劳动力市场流动在两个数据集之间是可比的。行政数据还可以克服劳动力调查的一些问题，例如调查结构的变化。本文旨在提供有关如何调整行政数据集以使其对研究失业有用的全面指导。