This project investigates complex system approaches for modelling the economy. Our models are based on 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 behaviour underlying business cycles, inflation and interest rates, innovation, and long-run growth.
The importance of empirically supported microfoundations is well acknowledged in modern macroeconomics, but traditional models struggle to go beyond perfect rationality, or to incorporate more than one form of bounded rationality. Our goal is to develop approaches such as agent-based modelling, because they are capable of incorporating an ecosystem of behavioural models and make it possible to characterise the resulting non-equilibrium dynamics.
We developed a theory for the amplification of technological improvement by the production network structure of the economy. The idea is that improvements are passed down the chain formed by industries and accumulate multiplicatively. Using a simple model for technological improvement, we show how to compute the overall improvement factor for the general case where the production network has a complicated structure containing cycles. This improvement factor is related to the output multiplier. This leads to testable predictions of about GDP growth. When added to other standard explanatory variables, we find the output multiplier remains a robust and statistically significant contributor. We studied the evolution of the length of the production network along the development path and we identified that it provides a comprehensive framework to study the acceleration and deceleration of economic growth, and is useful in forecasting growth.
The project covers several areas:
- Structure and dynamics of the global production and credit network
- Understanding the economic effects of Covid-related lockdown.
- Heterogeneous dynamics of inflation at a fine-grained level
- How ecological properties of economic production networks amplify growth
Structure and dynamics of the global production and credit network
We are developing models of the global production and credit networks. This involves developing methods to reconstruct missing data and agent-based modelling of supply chain and trade credit.
Understanding the economic effects of Covid-related lockdown
During the first wave of Covid-19, we developed methods and models to understand the economic effects of lockdown, by evaluating the shocks at the industry and occupation level and by evaluating the effects of these shocks in a non-equilibrium network model of the economy.
Heterogeneous dynamics of inflation at a fine-grained level
Inflation rates at the product level are highly heterogeneous and highly persistent. We are developing methods to characterise groups of products or services that have similar patterns of price changes.
Impact:
Rebuilding Macroeconomics prize awarded for Propagation of supply and demand shocks in a dynamic input-output models
Funders include:
Baillie Gifford, IARPA