Single-Month Unemployment Rate Estimates for the Brazilian Labour Force Survey Using State-Space Models
本文提出状态空间模型，利用调查数据和辅助信息估计巴西各州单月失业率，考虑了抽样误差和新冠疫情的影响，为官方统计提供新方法。
Abstract The Brazilian Labour Force Survey publishes monthly national indicators based on 3-month rolling data. This paper presents state-space models to produce state-level single-month unemployment rate estimates. The models account for sampling errors and the increased dynamics in the labour force series due to the unforeseen SARS-COV-2 pandemic. Bivariate time series models with claimant count auxiliary data and multivariate models combining survey data of several states are investigated. The results demonstrated the benefits of the univariate state-space approach to produce unemployment official statistics for Brazil. Additionally, the regional multivariate model shows promising results but requires further investigation.