Some problems of causal inference in agent-based macroeconomics

Guerini and Moneta (2017) have developed a sophisticated method of providing empirical evidence in support of the relations of causal dependence that macroeconomists engaging in agent-based modelling believe obtain in the target system of their models. The paper presents three problems that get in the way of successful applications of this method: problems that have to do with the potential chaos of the target system, the non-measurability of variables standing for individual or aggregate expectations, and the failure of macroeconomic aggregates to screen off individual expectations from the microeconomic quantities that constitute the aggregates. The paper also discusses the in-principle solvability of the three problems and uses a prominent agent-based model (the Keynes + Schumpeter model of the macroeconomy) as a running example.