<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Nowcasting Austrian Short Term Statistics

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Nowcasting Austrian Short Term Statistics"}

Early estimates for Austrian short term indices were produced using multivariate time-series models. The article presents a simulation study with different...

Nowcasting Austrian Short Term Statistics

Online veröffentlicht: 07. Juni 2018

Seitenbereich: 503 - 522

Eingereicht: 01. Nov. 2016

Akzeptiert: 01. Jan. 2018

DOI: https://doi.org/10.2478/jos-2018-0023

Schlüsselwörter
Nowcast, cointegration, outlier adjustment, vector error correction models, (seasonal) unit-roots

© 2018 Markus Fröhlich, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Nowcasting Austrian Short Term Statistics

Online veröffentlicht: 07. Juni 2018

Seitenbereich: 503 - 522

Eingereicht: 01. Nov. 2016

Akzeptiert: 01. Jan. 2018

DOI: https://doi.org/10.2478/jos-2018-0023

SchlüsselwörterNowcast, cointegration, outlier adjustment, vector error correction models, (seasonal) unit-roots

© 2018 Markus Fröhlich, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Nowcast, cointegration, outlier adjustment, vector error correction models, (seasonal) unit-roots