Chapter 1. Measurement and Decomposition of Cost Inefficiency Using Copulas: An Application to the U.S. Banking IndustryThis paper proposes a model and an estimation strategy using copulas in order to measure and decompose technical and allocative inefficiency in the translog cost system. This study adapts the stochastic cost frontier model from Kumbhakar (1997) and employs the APS copulas developed by Amsler et al. (2021) to capture the dependence between technical and allocative inefficiency. The joint density of the system is derived by the probability integral transform and the copula-based version of the Rosenblatt transformation, leading to the method of simulated likelihood estimation. This study also proposes a strategy to estimate individual inefficiency using density deconvolution and conditional distributions. The new methods are then applied to the U.S. banking industry. The results suggest that U.S. bank costs increased by approximately 20% in 2019 and 2020 due to inefficiency, where technical and allocative inefficiency represented 16~18% and 2.5%, respectively. In addition, ignoring the dependence between technical and allocative inefficiency would produce less plausible results.Chapter 2. Measurement and Decomposition of Cost Inefficiency Using Copulas: Evidence from Monte Carlo SimulationsThe purpose of this paper is to provide methods for copula-based simulations and to demonstrate the performance of the estimation strategy that can measure and decompose cost inefficiency. First, a method to draw random numbers using the APS-3-A copula, which corresponds to the three-input case, is presented. Specifically, copula arguments can be obtained from random numbers distributed independently and uniformly over [0,1] by applying the inverse Rosenblatt transformation, which needs to derive conditional distributions of copulas. Then, dependent random numbers can be generated by the inverse transformation method. Second, quasi-Monte Carlo simulations are conducted given the data generating process. Simulation results suggest that the parameters of the translog cost system that accommodates technical and allocative inefficiency can be reliably estimated when the APS copulas are employed. It would also yield biased estimates when the disturbances in the cost function and the cost share equations of the system are regarded as independent.Chapter 3. Demand Estimation of Deposits: A Case of the Korean Financial IndustryThis paper estimates a structural demand model for deposits in the Korean financial sector in order to measure the effects of deregulation in payment and settlement systems in 2009, which caused cash management accounts (CMAs) of securities companies to become close substitutes for traditional deposit services provided by banks. Following the discrete choice literature, depositors choose among differentiated financial institutions, considering their offered interest rates and other attributes. Although it is also assumed that market discipline in banking exists, it depends on the financial stability situation. The results show that consumers respond favorably to deposit rates, the branch staffing, and the number of branches of depository institutions in tranquil times. On the other hand, they consider the financial institution's capital adequacy ratio more important than interest rates during the financial turmoil. This is similar to the phenomenon referred to as the flight to quality in other financial markets. Therefore, although CMAs have the benefit of higher interest rates compared to traditional deposit services, their market share has remained at low levels due to the prolonged financial stress since the global financial crisis, which results in marginal increases in consumer welfare from the deregulation. This implies that the deregulation would not have successfully achieved the purpose of improving consumer welfare by promoting competition.
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