Efficiency Analysis of Macedonian and Croatian Banking Sectors with DEA

Abstract

The aim of this paper is to measure the relative efficiency of commercial banks in two developing countries, the Republic of North Macedonia and the Republic of Croatia under the operating (incomebased) approach by using the leading non-parametric methodology data envelopment analysis (DEA). We follow Banker et al. (2010) in the selection of the approach, variables (two inputs: interest expense and other operating expense, and two outputs: interest revenue and other operating revenue) and the model (output-oriented BCC DEA model) as in their first stage. The observed period is five years (2015-2019) and we use a balanced panel data for both samples (total of 65 Macedonian and 100 Croatian bank-year observations). Outliers are identified and excluded by using the Banker and Gifford (1988) super-efficiency procedure, and the BCC output-oriented model is rerun for both samples (total 55 Macedonian and 95 Croatian bank-year observations). We provide relative efficiency scores for each bank in both sectors, as well as an average score for the banking sectors. In addition, we analyse few banks for both sectors that have decreased or increased the efficiency, or show variable results over time. Besides, we explain how inefficient banks can improve the efficiency in future by setting targets for improvement. Our study provides valuable information for banking management and regulatory bodies.

Efficiency Evaluation in the Tourism Sector in Croatia and Serbia: Applications of Data Envelopment Analysis

“…Another advantage of this methodology is there is no requirement for assessment or a priori knowledge of the weights of the inputs and outputs. The most important advantage when employing this methodology is "the possibility to include more than one output and to not set assumption for the production function" (Cvetkoska & Fotova Čiković, 2021).…”

“…DEA is a primarily "data-oriented" approach that uses the conversion of multiple input variables to multiple output variables for the evaluation of the DMUs (Cvetkoska, 2011). As a nonparametric methodology, it focuses on the extreme observations, whereas the parametric methods "focus on average tendencies and deviations from it" and they can employ only one output, which is one of their biggest limitations (Cvetkoska & Fotova Čiković, 2021).…”

“…Efficiency can also be defined as the ability to achieve goals with the minimal use of available resources. Efficiency represents one of the most crucial principles in organisations' operations and one of "the most important indicators for the successful operation" (Cvetkoska & Fotova Čiković, 2021;Cvetkoska, 2011) which "refers to the relationship between the input and the output, i.e., using the minimum resources (human, organizational, financial, material, physical) to produce the desired production volume" (Cvetkoska & Barišić, 2020). In this context, if the level of output has increased with the same level of input, or the level of output has remained unchanged, but the level of used inputs has decreased -this means the efficiency has increased.…”

Application of Data Envelopment Analysis (DEA) in Information and Communication Technologies

“…The evaluation is based on the implemented inputs and on the produced outputs. One of the main strengths of this approach (unlike the parametric approaches) is the possibility to include more than one output and to not set assumptions for the production function [11].…”

“…Thus, Data Envelopment Analysis is a nonparametric approach that implements a linear programming to discover the efficiency frontier for a company or DMU. The relative efficient DMUs form the efficient frontier that presents an envelope for the analysed DMUs [11]. This way, DEA is used to solve an individual linear programming problem for each analysed organization or DMU, considering the organization's "input and output data are assigned a set of weights to maximize the ratio of inputs and outputs" [13].…”