Through a generous donation from Baillie Gifford, the Complexity Economics Group at INET Oxford is starting a new project on “Understanding business cycles, long-run growth, inflation and credit from the bottom-up”.
Led by Doyne Farmer, the project will investigate complex system approaches for modeling the economy. Our models will be based on the collection of fine-grained data sets at the level of firms, products and industries, with the goal of providing a detailed understanding of the rich and heterogeneous behavior underlying business cycles, innovation, long-run growth, inflation and interest rates.
Well-known limitations of traditional macro models include an over-reliance on rationality and equilibrium, difficulties in incorporating distributional properties and naïve modeling of the financial sector. We believe that another important reason is the use of aggregate models. Because the economy is an evolutionary process there are fundamental differences between the economy now and the economy a hundred years ago. This means that the time series that the economy generates are inherently nonstationary and the data available for statistical estimation at an aggregate level are extremely limited.
The evolving nature of the economy makes it necessary to understand innovation and structural change over the long run. To understand the emergent properties of our complex economy we need to model it at a fine-scale. Modeling at this scale also greatly increases the data available, improving the problems of statistical estimation. Thus modeling the economy at a fine-grained level potentially solves several problems at once. The importance of empirically supported microfoundations is increasingly acknowledged in mainstream macroeconomics; we plan to go beyond this approach by directly aggregating up micro-data and micro-behaviors to the macro scale and using approaches such as agent-based modeling to incorporate behavioral models of decision making and capture the dynamics of non-equilibrium behavior.
The project will encompass different scales of aggregation and different time scales, with five main related areas:
- Volatility and cycles on different scales
- Structure and dynamics of the global production network
- Structure and dynamics of the global credit network
- Heterogeneous dynamics of inflation at a fine-grained level
- Innovation, inflation, long-run economic growth and technological change