In their article “The corrosive effect of corruption on trust in politicians: Evidence from a natural experiment”, the authors Macarena Ares and Enrique Hernàndez (2018) statistically exploit the coincidence of the disclosure of the Spanish 2013 Bárcenas corruption scandal during the survey collection for the European Social Survey (ESS). I replicate the paper and find some coding errors.
Adding to the omnipresent discussion of Artificial Intelligence (AI), this paper examines whether spiking US venture capital developed into a dotcom-like AI bubble. Analysing venture capital, patent, and stock market data from 1990 to 2018, the paper finds little evidence for an AI-related bubble. To avoid throwing all caution of AI bubbles to the winds, the paper recommends two policy approaches to take advantage of the development and avoid harmful future bubble spread.
Contributing to counter-racism strategies, this data essay analyses two data sets of survey experiments to give recommendations on how to react to subtly racial messages by the sitting President Donald Trump. The paper finds that pointing racism out works and should hence be done to make voters aware of the socially not acceptable behaviour. Furthermore, the limited impact from a single intervention on binary decisions encourages campaigners to call out repeatedly.
Following its research question “What welfare production regime can the Russian Federation be assigned to?”, this paper applies the “social protection/skill regime” concept, developed by Estevez-Abe et al. (2001), to the Russian Federation. OECD and World Bank data show that Russia provides a relatively high employment protection (EP) and dangerously low unemployment protection (UP), who are both mismatched with the industry-specific skill regime provided by state education.