Fiscal and monetary policies in complex evolving economies

Abstract

In this paper we explore the effects of alternative combinations of fiscal and monetary policies under different income distribution regimes. In particular, we aim at evaluating fiscal rules in economies subject to banking crises and deep recessions. We do so using an agent-based model populated by heterogeneous capital-and consumption-good firms, heterogeneous banks, workers/consumers, a Central Bank and a Government. We show that the model is able to reproduce a wide array of macro and micro empirical regularities, including stylised facts concerning financial dynamics and banking crises. Simulation results suggest that the most appropriate policy mix to stabilise the economy requires unconstrained counter-cyclical fiscal policies, where automatic stabilisers are free to dampen business cycles fluctuations, and a monetary policy targeting also employment. Instead, "discipline-guided" fiscal rules such as the Stability and Growth Pact or the Fiscal Compact in the Eurozone always depress the economy, without improving public finances, even when escape clauses in case of recessions are considered. Consequently, austerity policies appear to be in general self-defeating. Furthermore, we show that the negative effects of austere fiscal rules are magnified by conservative monetary policies focused on inflation stabilisation only. Finally, the effects of monetary and fiscal policies become sharper as the level of income inequality increases.

Between Scylla and Charybdis: Income Distribution, Consumer Credit, and Business Cycles

“…Instead of following the standard practice in the ABM literature, which consists in the arbitrary selection of a few values for one parameter at a time (see Cardaci 2018;Delli Gatti et al 2011;Dosi et al 2015), we have decided to introduce a wide random selection of the values of each parameter, while providing some limitations only to the boundaries of the random sample. Instead of following the standard practice in the ABM literature, which consists in the arbitrary selection of a few values for one parameter at a time (see Cardaci 2018;Delli Gatti et al 2011;Dosi et al 2015), we have decided to introduce a wide random selection of the values of each parameter, while providing some limitations only to the boundaries of the random sample.…”

The Agent‐based Approach to Post Keynesian Macro‐modeling

“…Given its nature and scope, AB modeling has been widely used by evolutionary economists. For the purposes of this review, the series of models defined as “Keynes‐Schumpeter” is of particular interest (Dosi et al ., , , , ). This type of models has proved to be able to replicate a large number of stylized facts and to be flexible enough to be adapted in different contexts (see, for example, Dosi et al ., , for an assessment of job market reforms).…”

Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead

“…24 Moreover, Dosi et al (2013) find a strong interaction between income distribution and fiscal policies: the more income distribution is skewed toward profits, the greater the case for fiscal policies to dampen macroeconomic fragility. 25 Different fiscal austerity policies are studied in Dosi et al (2015). They find that fiscal consolidation rules are "self-defeating", as they depress the economy without improving public finances.…”

“…Similar conclusions are reached by Teglio et al (2015) employing the EURACE model (Cincotti et al, 2012b). Moreover, the negative effects of fiscal policies are magnified by higher lever of income inequality (Dosi et al, 2015). Finally, austerity policies can also reduce long-run productivity and GDP growth, by harming innovation rate and the diffusion of new technologies (Dosi et al, 2014b) and firms' investment rates (Bassi and Lang, 2016).…”

“…Section 6.3) in a framework characterized by financial fragility (e.g. Delli Gatti et al, 2005a;Dosi et al, 2013Dosi et al, , 2015Caiani et al, 2015), bankruptcy cascades (e.g. Delli Gatti et al, 2010;Battiston et al, 2012), deleveraging dynamics (e.g.…”