From CATS to CAOS: Fiscal Multipliers and Agents’ Expectations in a Macroeconomic Agent-Based Model
ExSIDE Working Paper Series, No. 25-2020
49 Pages Posted: 20 Jun 2020
Date Written: May 18, 2020
This paper uses a macroeconomic agent-based model building on Delli Gatti et al. (2011) to investigate the influence of agents’ expectations and consumption choices on government expenditure multipliers. Following a thorough investigation of the size of the multiplier in the pre-existing baseline model, a modification is introduced, allowing agents to engage in inter-temporal optimization of consumption subject to a budget constraint which is based on estimates of future income. Compared to the baseline, the fiscal multiplier is strongly affected by this alternative consumption behavior, becoming significantly smaller. In a further step, agents’ beliefs about the effects of government expenditure shocks are explicitly introduced. In the case of exogenously imposed beliefs coupled either with adaptation of individual beliefs or switching behavior between different types of beliefs, it is shown that both optimistic and pessimistic expectations can be temporarily self-fulfilling and either increase or decrease the value of the multiplier. Both forms of belief dynamics also allow for the incorporation of announcement effects of fiscal policy. In a final experiment, agents are allowed to engage in least-squares learning in order to gain an estimate of the effect of government expenditure shocks on future income. It is shown that under least squares learning, beliefs are ‘rational’ insofar as they lead to broadly correct predictions on average. The paper hence contributes to addressing aspects of the Lucas critique as applied to macro-ABMs, since agents react systematically (and reasonably) to announcements of changes in fiscal policy.
Keywords: Agent-Based Models, Expectations, Learning, Fiscal Policy
JEL Classification: C63, E62, D84, E71
Suggested Citation: Suggested Citation