Affiliations: [a] Center for Operational Research, Miguel Hernández University of Elche, Spain | [b] Geneva School of Economics and Management, University of Geneva, Switzerland
Correspondence:
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Corresponding author: Stefan Sperlich, Geneva School of Economics and Management, University of Geneva, Switzerland. E-mail: [email protected].
Abstract: Nowadays, national and international organizations experience an increasing demand for timely and disaggregated socio-economic indicators. More recently, this demand extends to the request for nowcasting indicators. Small Area Estimation has a long tradition in indicator prediction for high levels of disaggregation; but when speaking of ‘prediction’, this notation refers to the fact that the centre of interest is a random parameter. Prediction of future values, or similarly, nowcasting has hardly been studied so far. Yet, mixed models based Small Area Estimation is designed for imputing (missing) values, and these models can easily account for temporal correlation. Therefore, model assisted nowcasting would be a natural extension. This article reviews existing methods under this perspective to highlight the necessary ingredients, and then propose nowcasting procedures for highly disaggregated indicators that could already be used with the today’s available software.
Keywords: Disaggregated forecasting, nowcasting in small areas, time dependent mixed models
