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In this paper, we present the results of a dynamic microsimulation analysis that examines how changes in the educational integration of first- and second-generation immigrants would affect the future size of the Austrian labour force. Due to population ageing and migration, the number and proportion of people with a migration background will increase significantly in the coming decades. Differences in educational careers, as well as differences in labour market participation between the second generation of migrants with EU or EFTA backgrounds and people without a migration background, would have only a minor impact on future labour force participation dynamics. In contrast, closing education and labour force participation gaps for the second generation of migrants with a third country background would lead to a significant increase in the size and qualification structure of the working population.

We propose a modelling approach involving a series of small-scale factor models. They are connected to each other within a cluster, whose linkages are derived from Granger-causality tests. GDP forecasts are established across the production, income and expenditure accounts within a disaggregated approach. This method merges the benefits of large-scale macroeconomic and small-scale factor models, rendering our Cluster of Dynamic Factor Models (CDFM) useful for model-consistent forecasting on a large scale. While the CDFM has a simple structure, its forecasts outperform those of a wide range of competing models and of professional forecasters. Moreover, the CDFM allows forecasters to introduce their own judgment and hence produce conditional forecasts.

In dieser Studie wird eine große Zahl hochfrequenter Indikatoren gesammelt und hinsichtlich ihres Informationsgehaltes im Hinblick auf die Aktivität der österreichischen Volkswirtschaft analysiert. Dies geschieht anhand von Kreuzkorrelationen dieser und anderer häufig verwendeter Indikatoren für verschiedene Referenzreihen, u. a. für das BIP, das verarbeitende Gewerbe, den Bausektor, Teile des Dienstleistungssektors, Investitionen, Konsum, Importe und Exporte. Auf Basis dieser Erkenntnisse werden dynamische Faktormodelle (DFM) für die Referenzreihen spezifiziert. Dies ermöglicht eine Echtzeiteinschätzung und eine Prognose des BIP sowohl durch einen direkten (wöchentlicher WIFO-Wirtschaftsindex – WWWI) als auch durch einen indirekten Ansatz (Cluster dynamischer Faktormodelle – CDFM). Eine Auswahl an hochfrequenten Indikatoren ist auch über den IHS Economic High-Frequency Monitor abrufbar.

In the EU, all components of demand were impacted by the economic downturn in the second quarter; in the UK, France and Italy, private consumption was affected to an above-average extent. In Austria, economic output in the second quarter was one eighth down compared to the previous year's level, the decline thus being less pronounced than the EU average. Tourism suffered less than in Italy or Spain; the development of overnight stays by German and domestic visitors cushioned the drop in demand in July. Only a good third of the unemployment caused by the crisis has so far been recuperated. As a result, long-term unemployment has continued to rise recently.

Der vorliegende Bericht fasst zusammen, welche Maßnahmen von Ländern und Gemeinden finanziert werden und wie groß der Anteil der Umweltmaßnahmen daran ist. Ausgewählte Indikatoren zur Transformation des Wirtschaftssystems werden vorgestellt und in den Kontext der nationalen Umwelt- und Klimapolitik gestellt. Dieses Material bildet den Hintergrund einer Bewertungsmatrix, in der auf Grundlage der Einschätzung von Expertinnen und Experten Maßnahmen beurteilt werden, die im Zuge der Bewältigung der COVID-19-Krise implementiert bzw. diskutiert werden. Die Wirkungen von Maßnahmen werden im Hinblick auf folgende Zieldimensionen bewertet: Beschäftigung im Inland, Wertschöpfung, Klimaanpassung und Klimaschutz sowie Energieeffizienz und erneuerbare Energiequellen. Da die Wirkungen vom jeweiligen Kontext abhängen und nicht von anderen, ergänzenden oder hemmenden Faktoren losgelöst betrachtet werden können, wird bei der Bewertung kurz skizziert, worauf die Beurteilung basiert. Der Bericht endet mit Überlegungen, wie es gelingen kann, die Maßnahmen verschiedener Gebietskörperschaften in kohärenter Weise so zu bündeln, dass die ambitionierten Ziele der Transformation erreicht werden können.

As part of a larger research project, we survey existing data sets and research results on immigrants' integration success in Austria focusing on educational and labour market outcomes. We consider different registers as well as survey data available to researchers on a regular basis and compare to what extent these data contain relevant information on immigrants and their educational and employment careers and survey the research that has been conducted based on the different datasets. We also aim to identify research gaps and potential data gaps resulting from the fragmentation of relevant information over different data sets. While different data sources contain different aspects relevant for integration research, a "complete" picture of integration processes as well as the identification of supporting and hindering factors for successful integration typically requires a combination of different data sets that may also enrich longitudinal (register-based) individual data by more detailed characteristics from survey data.

This paper studies how changes in the population composition by education and family characteristics impact on indicators of the economic effects of population ageing based on National Transfer Accounts (NTAs). NTAs constitute cross-sectional per-capita age-profiles of the key variables of national accounts consumption, income, saving, and public transfers, incorporating an estimation of private transfers. A variety of indicators based on NTA data combined with population projections was developed in the literature, of which we have selected two for our analysis: the Support Ratio (SR) and the Impact Index (IMP). We complement existing projections by using new disaggregated NTA data by education and family type, contrasting the results to the same indicators based on NTAs by age. Our projection analysis is performed using the dynamic microsimulation model microWELT. The model provides the required detailed socio-demographic projections and incorporates the NTA accounting framework. Our results show that indicators based on disaggregated data can give a very distinct picture of the economic effects of population ageing, as the burden of ageing is alleviated by the education expansion. Our study compares results for Austria and Spain.

The aim of this paper is twofold: First, it provides an overview of the socio-demographic core modules of the dynamic microsimulation model microWELT. Second, it describes the essential socio-demographic characteristics of four European countries – Austria, Spain, Finland, and UK as representatives of four welfare state regimes (conservative, mediterranean, universalistic, and liberal) – and the processes that drive socio-demographic change which we aim at capturing with the model. MicroWELT is developed as a tool for the comparative study of the distributional effects of four welfare state regimes, represented by the four studied countries. Processes with potential links to welfare state types include 1. the intergenerational transmission of education, 2. childlessness and fertility by education, 3. partnership behaviours and lone parenthood, 4. age at leaving home, and 5. mortality differentials by sex and education. Through microWELT projections, we identify the impact of these processes on the future population composition by age, sex, education, and family characteristics of the studied countries. This paper is part of a series of related papers and other resources which together build comprehensive documentation and presentation of the research performed developing and using microWELT. All materials are available at the project website www.microWELT.eu.