Carlos Lopes will deliver an overview of the critical development issues facing the African continent today. He will talk about a blueprint of policies to address issues, and an intense, heartfelt meditation on the meaning of economic development in the age of democratic doubts, identity crises, global fears and threatening issues of sustainability.
This talk will be followed by a book signing and drinks reception, all welcome.
Economics is in crisis. On one hand, behavioural economics is now well-established, but on the other hand, most economics models are still based on rational expectations with constraints, called “frictions”. The standard program adds more and more constraints to rationality in hopes that this will approximate real behaviour, but this may never work. It is increasingly clear that heterogeneity (the fact that people and institutions are diverse) is essential to understand problems such as inequality. There is a major effort to address this challenge, but the models that do this are technically complicated and rapidly become intractable as they become more realistic. Finally, there is a fundamental challenge due to the fact that we have very little historical data available to fit models for a complicated and evolving economy.
Complexity economics offers solutions to these problems. It advocates modelling behaviour in terms of heuristics and myopic reasoning, as observed in behavioural experiments. It advocates the use of simulations, making it much easier to incorporate heterogeneity in a tractable manner. Finally, it advocates using highly granular data, that accurately captures heterogeneity, to fit the models. Professor Doyne Farmer will present examples where this approach has had success, including applications to technology forecasting, economic growth and climate change, and present a vision of what it can do in the future.
Like the wind, knowledge can be difficult to see or grasp, but if well-harnessed, it can help us do extraordinary things. In this talk, Dr Penny Mealy will discuss how novel analytical tools are providing new insights into the use of knowledge in society, and highlight implications for economic development, inequality and the transition to the green economy.
In Origin of Species, Charles Darwin described how a population explosion occurs and called the time of population explosion “ favourable seasons”, he was not to know it, but such circumstances arose for his own species at around the time of his own birth. However, the favourable seasons for human population growth were not experienced favourably, with times of great social dislocation from small scale enclosure to global colonisation. Now those seasons are over, we have experienced the first ever sustained slowdown in the rate of global human population growth. This has been the case for at least one human generation. However, we are not just slowing down in terms of how many children we have, but in almost everything else we do, other than in the rise in global temperatures that we are recording and that we have to live with. It can be argued that there is even a slowdown in such unexpected areas as debt, publishing, and in the total amount useful information being produced.
If this is true – that humanity is slowing down in almost everything that we do – what does this mean? What measurements suggest that slowdown is true? And if so much is still rising, albeit at slower and slower rates – is that such a great change? Finally how might the slowdown impact on economic thought. In many ways economics was the science of the great acceleration; a science that makes most sense when markets are expanding and demand is rising. What kind of an economics is needed in a world where enormous and accelerating growth has stopped being the normality?
Digital technologies are changing economics in two ways. The characteristics of an increasingly digital economy raise questions about economic analysis in domains ranging from competition policy to corporate finance, while new data sources and methodologies challenge economists to develop new empirical approaches.