In this paper we present a macroeconomic microfounded framework with heterogeneous agents -households, firms, banks -which interact through a decentralized matching process presenting common features across four markets -goods, labor, credit and deposit. We study the dynamics of the model by means of computer simulation. Some macroeconomic properties emerge such as endogenous business cycles, nominal GDP growth, unemployment rate fluctuations, the Phillips curve, leverage cycles and credit constraints, bank defaults and financial instability, and the importance of government as an acyclical sector which stabilize the economy. The model highlights that even extended crises can endogenously emerge. In these cases, the system may remain trapped in a large unemployment status, without the possibility to quickly recover unless an exogenous intervention.
In this paper we build on the network-based financial accelerator model of Delli Gatti et al.(2010), modelling the firms’ financial structure following the ‘‘dynamic trade-off theory’’, instead of the ‘‘packingordertheory’’. Moreover,we allow for multi periodal debt structure and consider multiple bank-firm links based on a myopic preferred-partner choice. In case of default, we also consider the loss given default rate (LGDR).We find many results:(i) if leverage increases, the economy is riskier; (ii) a higher leverage pro- cyclicality has a destabilizing effect; (iii) a pro-cyclical leverage weakens the monetary policy effect;(iv) a central bank that wants to increase the interest rate should previously check if the banking system is well capitalized;(v) an increase of the reserve coefficient has an impact similar to that produced by raising the policy rate, but for the enlargement of bank reserves that improves the resilience of the banking system to shocks
We investigate the interplay between increasing inequality and consumer credit in a complex macroeconomic system with financially fragile heterogeneous households, firms and banks. Simulation results show that there are pros and cons of introducing consumer credit: on the one hand, for a certain time, it leads to lower unemployment through boosting aggregate demand; on the other hand, it accelerates the system tendency to the crisis. Since the increase of financial profits goes with a decline of households’ real wealth, a policy trade-off emerges
Asset managers are often given the task of restricting their activity by keeping both the value at risk (VaR) and the tracking error volatility (TEV) under control. However, these constraints may be impossible to satisfy simultaneously because VaR is independent of the benchmark portfolio. The management of these restrictions is likely to affect portfolio performance and produces a wide variety of scenarios in the risk-return space. The aim of this paper is to analyse various interactions between portfolio frontiers when risk managers impose joint restrictions upon TEV and VaR. Specifically, we provide analytical solutions for all the intersections and we propose simple numerical methods when such solutions are not available. Finally, we introduce a new portfolio frontier
We allow firms and banks to entertain multiple credit connections in a financially constrained production framework, resorting to a random network model whose parameters are calibrated with real data. The calibration is successful since the network model is able to reproduce the degree and strength (debt and loan) distributions of the Japanese credit market. We run simulations over the parameter space using an efficient design, and compare a number of alternative statistical metamodels in order to select the best specification for the relationship between the parameters and a set of endogenous variables of the model. We show that the metamodeling approach can be usefully extended to economic models in order to bridge the gap between micro and macro variables through a rigorous statistical analysis of ABMs, without imposing unrealistic restrictions on the micro model such as the representative agent hypothesis.
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