Wir untersuchen die kurz- und langfristigen Auswirkungen eines starken Anstiegs chinesischer Importe auf Wahlergebnisse in Europa. Populistische sowie links- und rechtsextreme Parteien gewannen erst viele Jahre nach dem Höhepunkt des China-Schocks bedeutenden Zuwachs an Wählerstimmen. Wir zeigen, dass die Auswirkungen von Importschocks überwiegend zugunsten populistischer Parteien ausfallen. In geringerem Maße profitieren in der kurzen Frist zudem linksextreme Parteien, langfristig hingegen rechtsextreme Parteien. Die Effekte auf das Wahlverhalten sind jedoch moderat und wir schlussfolgern, dass Importschocks den Aufstieg der politischen Ränder nur in begrenztem Maße erklären können.

This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.

We analyze how skill transferability and the local industry mix affect the adjustment costs of workers hit by a trade shock. Using German administrative data and novel measures of economic distance we construct an index of labor market absorptiveness that captures the degree to which workers from a particular industry are able to reallocate into other jobs. Among manufacturing workers, we find that the earnings loss associated with increased import exposure is much higher for those who live in the least absorptive regions. We conclude that the local industry composition plays an important role in the adjustment processes of workers.

The recent advances in automation technology, robotics in particular, have sparked a heated debate over the future of labor and human society at large. The ongoing process of robotization may engender profound impacts on various segments of the labor market. Given the far-reaching implications of robots, it is thus very important to understand the scale and scope of robot use and characteristics of robot users. However, the main challenge is the limited availability of robot data at the microeconomic level (Raj and Seamans, 2018). Due to the data constraint, the bulk of the existing literature relies on cross-country industry-level data from the International Federation of Robotics (IFR). The lack of micro-level robot data makes it difficult to paint a comprehensive picture of robotization in industrial settings, and perhaps more importantly, to assess how within-industry firm level heterogeneity manifests itself in robot use and adoption.