The natural sciences have established a general scaling law that relates metabolism and body size of animals. Recently this association - known as Kleiber's law - has received deep theoretical foundation by network theory and has been fruitfully applied to explain various biological phenomena,...

The natural sciences have established a general scaling law that relates metabolism and body size of animals. Recently this association - known as Kleiber's law - has received deep theoretical foundation by network theory and has been fruitfully applied to explain various biological phenomena,...

We present a multi-country theory of economic growth in which countries are connected by a network of mutual knowledge exchange. Growth is generated through human capital accumulation and knowledge externalities. The available knowledge in any country depends on its connections to the rest of...

Recent empirical research has shown that income per capita in the aftermath of natural disasters is not necessarily lower than before the event. Income remains in many cases not significantly affected or, perhaps even more surprisingly, it responds positively to natural disasters. Here, we...

We present a multi-country theory of economic growth in which countries are connected by a network of mutual knowledge exchange. Growth is generated through human capital accumulation and knowledge externalities. The available knowledge in any country depends on its connections to the rest of...

In this paper I investigate the nexus between life time utility (life satisfaction) and income predicted by the standard model of endogenous economic growth under different behavioral assumptions. The solution rationalizes why the empirical association between income and life satisfaction is...

This paper considers an overlapping generations model of economic growth populated by two types of individuals. Competitive types compare future consumption (i.e. wealth) with the mean. Self-sufficient types derive utility simply from their own consumption and do not compare themselves with...