Exploring agent-based methods for the analysis of payment systems: a crisis model for StarLogo TNG

agent-based modeling, payment systems, RTGS, liquidity, crisis simulation Abstract: This paper presents an exploratory agent-based model of a real time gross settlement (RTGS) payment system. Banks are represented as agents who exchange payment requests, which are settled according to a set of simple rules. The model features the main elements of a real-life system, including a central bank acting as liquidity provider, and a simplified money market. A simulation exercise using synthetic data of BI-REL (the Italian RTGS) predicts the macroscopic impact of a disruptive event on the flow of interbank payments. The main advantage of agent - based modeling is that we can dynamically see what happens to the major variables involved. In our reduced-scale system, three hypothetical distinct phases emerge after the disruptive event: 1) a liquidity sink effect is generated and the participants’ liquidity expectations turn out to be excessive; 2) an illusory thickening of the money market follows, along with increased payment delays; and, finally 3) defaulted obligations dramatically rise. The banks cannot staunch the losses accruing on defaults, even after they become fully aware of the critical event, and a scenario emerges in which it might be necessary for the central bank to step in as liquidity provider. The methodology presented differs from traditional payment systems simulations featuring deterministic streams of payments dealt with in a centralized manner with static behavior on the part of banks. The paper is within a recent stream of empirical research that attempts to model RTGS with agent – based techniques.

The under-reporting of financial wealth in the Survey on Household income and Wealth

The sample estimates are uniformly below those of the Financial Accounts, even after harmonising all the definitions and the evaluation criteria. Such a problem can stem from the intervieweeÂ’s unwillingness to disclose the actual value of the asset (under-reporting). The paper presents a method to correct this potential source of bias in order to improve Survey of Household Income and Wealth financial assets. We use a sample survey of customers of the Unicredit group, coupled with administrative data on the assets actually owned, as external sources of information. The adjustment procedure enables to account for a large share of the gap between the figures derived from the sample and from the Financial accounts, significantly increasing the average value of the financial assets (inflating the unadjusted figure of 22.000 euros to 59.000 euros, amounting to about 85 percent of the Financial account estimates). The adjustment produces a larger correction for private bonds and mutual funds. The intensity of the correction is higher for one-person households, when the head of household is less educated or not employed, and it raises with his/her age.Household Wealth, Survey Method, Discrete Regression and Qualitative Choice Models