Nowcasting Austrian Short Term Statistics

Author:

Fröhlich Markus1

Affiliation:

1. Statistics Austria , Guglgasse 13, 1140 Vienna , Austria .

Abstract

Abstract Early estimates for Austrian short term indices were produced using multivariate time-series models. The article presents a simulation study with different models (vector error correction models, vector autoregressive models in levels – both with unadjusted and seasonally adjusted time-series) used for estimating total turnover, production, etc. In a preliminary step, before time-series were provided for nowcasting, the data had to undergo an editing process. In this case a time-series approach was selected for data-editing as well, because of the very specific structure of Austrian enterprises. For this task basically the seasonal adjustment program X13Arima-Seats was used for identifying and replacing outlying observations, imputation of missing values and generating univariate forecasts for every single time series.

Publisher

Walter de Gruyter GmbH

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1. Nowcasting short-term indicators with machine learning methods;Statistical Journal of the IAOS;2022-12-16

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