How are network centrality metrics related to interest rates in the Mexican secured and unsecured interbank markets?

Abstract

In financial stability, it is essential to know the determinants of interest rates in interbank markets because they are important vehicles for liquidity allocation among banks and are relevant for monetary policy transmission. Recent research indicates that banks with excess liquidity exercise their market power by rationing liquidity during periods of financial stress. This confirms the value of knowing the banks connections and identifying liquidity spreaders in such markets to manage contagion risk, liquidity hoarding and to preserve financial stability. In addition to well studied bank features such as size, liquidity and credit risk, we study which network metrics relate to interest rates during different periods. Using transaction level data on unsecured and secured lending, we apply an approach that employs network theory, econometric models and machine learning to analyze the structural properties of the secured and unsecured interbank markets in Mexico. Our findings support the “too-interconnected-to-fail” hypothesis. In the secured interbank market, PageRank shows a relationship with interest rates, while metrics associated with the notion of influence and systemic risk (Katz and DebtRank) are relevant in the unsecured interbank market. In general, a bank with high centrality lends at higher rates and gets funding at lower rates.