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This paper identifies the determinants of industrialization in 18 African countries, 1965 to 2018, using various estimators and applying a battery of robustness checks. Industrialization in Africa is driven by historical legacies such as colonialism; geographical factors such as rainfall and distance from international markets; economic factors such competition from China, market size and urbanization; and technological factors such as digital technology adoption. An inverse U-shape relationship between industrialization and GDP per capita is consistent with (premature) de-industrialization. Technological change and adoption of digital technologies are found to have an ambiguous relationship with industrialisation in Africa. The establishment of the AfCFTA is timely, but its benefits will only be realised if countries also improve infrastructure to overcome the negative consequences of adverse geography, improve trade facilitation to exploit learning-by-exporting from intra-African trade, and facilitate urbanization.

The possibility that artificial extraterrestrial intelligence poses an existential threat to humanity is neglected. It is also the case in economics, where both AI existential risks and the potential long-term consequences of an AGI are neglected. This paper presents a thought experiment to address these lacunas. It is argued that it is likely that any advanced extraterrestrial civilization that we may encounter will be an AGI, and such an AGI will pose an existential risk. Two arguments are advanced for why this is the case. One draws on the Dark Forest Hypothesis and another on the Galactic Colonization Imperative. Three implications for how we govern AI and insure against potential existential risks follow. These are (i) accelerating the development of AI as a precautionary step; (ii) maintaining economic growth until we attain the wealth and technological levels to create AGI and expand into the galaxy; and (iii) putting more research and practical effort into solving the Fermi Paradox. Several areas where economists can contribute to these three implications are identified.

This paper investigates the relationship between state-based conflict and entrepreneurship. From a survey of the existing literature, we formulate two hypotheses: (1) state-based conflict has a negative association with productive and opportunity-motivated forms of entrepreneurship, and (2) a positive association with unproductive and necessity-motivated forms of entrepreneurship. We test these hypotheses by drawing on several state-based conflict and entrepreneurship measures, using appropriate estimators, and employing robustness checks. The evidence supports our hypotheses. Necessity-motivated start-up entrepreneurship is, on average, almost three times higher in countries in conflict than in countries not in conflict. Development level matters. In countries with less unemployment, more finance, and higher levels of physical, human capital and GDP, entrepreneurship is more resilient, and the ratio of female-to-male entrepreneurs in opportunity-motivated entrepreneurship higher.

Artificial Intelligence (AI) scientists are challenged to create intelligent, autonomous agents that can make rational decisions. In this challenge, they confront two questions: what decision theory to follow and how to implement it in AI systems. This paper provides answers to these questions and makes three contributions. The first is to discuss how economic decision theory – Expected Utility Theory (EUT) – can help AI systems with utility functions to deal with the problem of instrumental goals, the possibility of utility function instability, and coordination challenges in multi-actor and human-agent collectives settings. The second contribution is to show that using EUT restricts AI systems to narrow applications, which are "small worlds" where concerns about AI alignment may lose urgency and be better labelled as safety issues. This papers third contribution points to several areas where economists may learn from AI scientists as they implement EUT. These include consideration of procedural rationality, overcoming computational difficulties, and understanding decision-making in disequilibrium situations.