The US commercial banking system has undergone dramatic consolidation. This consolidation has been in response to fundamental changes in regulation and technology. The banking and finance literature is abound with research attempting to quantify and evaluate a wide range of outcomes arising from consolidation. After more than three decades of microeconometric empirical analysis on bank consolidation, researchers remain unable to provide clear evidence on: (1) how the rate of consolidation is measured, (2) if there is a relation between efficiency gains and size heterogeneity in the banking sector, and (3) how commercial banks managed their risk and responded to the very recent subprime crisis.

One of the problems with studying banks is that the bank is a unique microeconomic entity that does not conform to standard definitions of a firm or production entity. The literature has not been able to reconcile the econometric results of many studies with what is actually being observed in the banking world. This is not surprising, as standard econometric analyses require assumptions on the underlying distribution of the data. In practice, the underlying distribution is rarely, if ever, known. Despite voluminous prior work in this area, none have sought to consolidate bank consolidation with risk management or estimating efficiency gains within an information theoretic approach.

These issues are addressed through three essays employing the Federal Reserve’s Call Report Data. The first essay focuses on the impact of banking policy legislation and reforms, bank specific profitability measures and the macroeconomic environment on the measurement and rate of US commercial bank consolidation. The modeling approach focuses on employing a Generalized Maximum Entropy (GME).

The second essay explicitly models both size and variance heterogeneity simultaneously. Since the one-sided error structure does not conform to standard distributional assumptions, we adopt a maximum entropy estimation procedure to estimate both cost frontier, as well as the second moments of the one-sided inefficiency term. We find that non-performing loans, federal insurance premium, legal expenses and director fees drive bank inefficiency as the bank becomes larger. Moral hazard, bank management and a “too-big-to-fail” doctrine are likely explanations for the results we see.

The final essay is an initial study establishing a direct link between bank efficiency, mortgage-backed securities usage, and residential loan holdings and monitoring the quality of banks. This study calculates an efficiency measure of commercial bank efficiency in a multiple input and output framework and evaluates the effects of mortgage-backed securities, residential loans and monitoring indices on performance of commercial banks as measured by these efficiency indicators for states that have the highest level of bank capitalization.