In many different surveys we need an estimate of the characteristic under study before the end of the survey. To achieve this goal, this paper presents a general approach that uses a dynamic linear model for repeated surveys based on a specific partition of the sample observations, which considers as total non-response all the responses not available within the time point set for obtaining the preliminary estimate. The proposed method is illustrated with an empirical application to monthly data on the index of industrial turnover in Italy.
Naccarato, A., Lamberti, A., Pallara, A. (2004). Improving Timeliness of Short-Term Business Statistics through State-Space Modelling of Preliminary Survey Data. In Proceedings of Q2004 European Conference on Quality and Methodology in Official Statistics, Mainz, Germany, 24-26 May 2004. Federal Statistical Office Germany.
Improving Timeliness of Short-Term Business Statistics through State-Space Modelling of Preliminary Survey Data
NACCARATO, ALESSIA;
2004-01-01
Abstract
In many different surveys we need an estimate of the characteristic under study before the end of the survey. To achieve this goal, this paper presents a general approach that uses a dynamic linear model for repeated surveys based on a specific partition of the sample observations, which considers as total non-response all the responses not available within the time point set for obtaining the preliminary estimate. The proposed method is illustrated with an empirical application to monthly data on the index of industrial turnover in Italy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
