![]() Given that the ECB modelling toolbox is overwhelmingly linear, this finding suggests that the expert judgement embedded in the ECB forecast may be characterized by some mild non-linearity. The median forecasts of the quantile regression forest are very collinear with the ECB point inflation forecasts, displaying similar deviations from “linearity”. We show that a quantile regression forest, capturing a general non-linear relationship between euro area (headline and core) inflation and a large set of determinants, is competitive with state-of-the-art linear benchmarks and judgemental survey forecasts. JEL Code J23 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Demand O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion ProcessesĪbstract Density forecasts of euro area inflation are a fundamental input for a medium-term oriented central bank, such as the European Central Bank (ECB). ![]() In contrast to the findings for employment, we find little evidence for a relationship between wages and potential exposures to new technologies. Country heterogeneity for this result seems to be linked to the pace of technology diffusion and education, but also to the level of product market regulation (competition) and employment protection laws. ![]() While there exists heterogeneity across countries, only very few countries show a decline in employment shares of occupations more exposed to AI-enabled automation. This evidence is in line with the Skill Biased Technological Change theory. This is particularly the case for occupations with a relatively higher proportion of younger and skilled workers. ![]() Using data for occupations at the 3-digit level in Europe, we find that on average employment shares have increased in occupations more exposed to AI. Abstract We examine the link between labour market developments and new technologies such as artificial intelligence (AI) and software in 16 European countries over the period 2011-2019. ![]()
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