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  • Author or Editor: Ilona Cserháti x
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Abstract

The expected future impact of the fourth industrial revolution is a hotly debated issue in the literature. The majority of papers focus on quantifying the expected impacts on labour demand, or on a specific country, or on huge macro-regions – and the estimates differ widely. Our paper focuses on the impact assessment of Industry 4.0 on the expected structure of employment, wages and inequalities in Hungary. We built a static microsimulation model for our analysis, where the “EU Survey of Income and Living Conditions Hungary 2017” dataset was used as a starting point. Projections by the European Centre for the Development of Vocational Training (CEDEFOP) were used for policy simulations on future employment by sector and by occupational group for each European Union (EU) member state. The analysis also elaborates our own augmented vision about the expected labour demand changes and expected wage trends. Based on this information, the spill-over effects were calculated regarding wage structure and inequalities by sector, region and the highest educational attainment.

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EU transfers play a significant role in the long-term convergence of the Hungarian economy. The paper presents several channels through which transfers can be effective. First the modelling experiences and other techniques are summarised which can be useful to estimate the impact of EU transfers.Next we present the so-called ECO-TREND model developed in the ECOSTAT, suitable for both mid- and long-term forecasts and scenario analysis. The assessment of the model parameters has been based on standard statistical methods and on experts’ estimations. Such a model can be a useful decision-making tool for the economic policy. Finally, forecasts are presented for the Hungarian economy until 2020, which is completed by the analysis of three different macroeconomic scenarios based on different subsidy-absorption rates and different structures of expenditure.

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Effective decision making uses various databases including both micro and macro level datasets. In many cases it is a big challenge to ensure the consistency of the two levels. Different types of problems can occur and several methods can be used to solve them. The paper concentrates on the input alignment of the households’ income for microsimulation, which means refers to improving the elements of a micro data survey (EU-SILC) by using macro data from administrative sources. We use a combined micro-macro model called ECONS-TAX for this improvement. We also produced model projections until 2015 which is important because the official EU-SILC micro database will only be available in Hungary in the summer of 2017. The paper presents our estimations about the dynamics of income elements and the changes in income inequalities. Results show that the aligned data provides a different level of income inequality, but does not affect the direction of change from year to year. However, when we analyzed policy change, the use of aligned data caused larger differences both in income levels and in their dynamics.

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