Autonomous ships have received significant attention in recent years. However, they are not yet widely adopted in the maritime industry yet. A wide range of predictions have been made about when the technological change will occur. This paper analyses technologies that are critical to autonomous...

We propose a simple model where the innovation rate of a technological domain depends on the innovation rate of the technological domains it relies on. Using data on US patents from 1836 to 2017, we make out-of-sample predictions and fond that the predictability of innovation rates can be...

The disequilibrium adjustment frameworks, pioneered by Carlino & Mills (1987) and further extended by Boarnet (1994a), have been widely adopted by various regional and intra-regional studies, 1) determining whether jobs follow people or people follow jobs or the both; 2) examining the...

We build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand...

We produce a social unrest risk index for 125 countries covering a period of 1996 to 2020. The risk of social unrest is based on the probability of unrest in the following year derived from a machine learning model drawing on over 340 indicators covering a wide range of macro-financial,...

Predictive AI is increasingly used to guide decisions on agents. I show that even a bias-neutral predictive AI can potentially amplify exogenous (human) bias in settings where the predictive AI represents a cost-adjusted precision gain to unbiased predictions, and the final judgments are made by...