This paper assesses the impact of US policy responses to the Covid-19 pandemic on various cryptocurrencies and also technology stocks using fractional integration techniques. More precisely, it analyses the behaviour of the percentage returns in the case of nine major coins (Bitcoin - BITC,...

The COVID-19 pandemic holds at least seven lessons for the relationship between data-driven decision making, the use of artificial intelligence, and development. These are that (1) in a global crisis, the shifting value of data creates policy pitfalls; (2) predictions of crises and how they play...

We model economic policy uncertainty (EPU) in the four largest euro area countries by applying machine learning techniques to news articles. The unsupervised machine learning algorithm used makes it possible to retrieve the individual components of overall EPU endogenously for a wide range of...

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...