Make-up strategies with incomplete markets and bounded rationality - Michael Dobrew; Rafael Gerke; Sebastian Giesen; Joost Röttger (Deutsche Bundesbank, 2023)
We study the impact of market incompleteness and bounded rationality on the effectiveness of make-up strategies. To do so, we simulate a heterogeneous-agent New Keynesian (HANK) model with reflective expectations and an occasionally-binding effective lower bound (ELB) on the policy rate. Our simulations show that make-up strategies can mitigate the negative consequences of the ELB for inflation and real economic activity. This result holds both for our HANK model as well as a corresponding representative-agent (RANK) model with complete markets, suggesting that market (in)completeness is not important for the effectiveness of make-up strategies. However, the stabilisation benefits of make-up strategies are small when agents' cognitive ability is consistent with micro-evidence. This result is independent of market (in)completeness, emphasising the importance of rational expectations for make-up strategies. Furthermore, while market incompleteness and bounded rationality complement each other in attenuating the effects of forward guidance in our model, we do not observe such a complementarity with respect to the benefits of make-up strategies.
Keywords: C63; D31; E21; E31; E52; E58; E70; 330; Make-Up Strategies; Incomplete Markets; Bounded Rationality; HANK; Effective Lower Bound; Average Inflation Targeting