Performance Analysis of Listed Companies in the UAE-Using DEA Malmquist Index Approach

Abstract

Data Envelopment Analysis (DEA) is becoming an increasingly popular tool for assessing the relative performance of industries and companies. By applying DEA theory to the non-financial sector, the relative efficiency of 27 listed corporations in the United Arab Emirates (UAE) has been analyzed in this paper. The focus of the study has been on the impact of the financial crisis and the recovery thereafter. Further, the productivity change was decomposed into technical efficiency change and technological change by using the non-parametric Malmquist Productivity Index (MPI) over the period from 2007 to 2014. Based on Malmquist analysis, we find that the most efficient industries during the post-crisis period were food and beverages, telecommunication and pharmaceuticals. In contrast, the sectors that were adversely affected by the crisis were services, real estate, construction and cements. The break-up of the TFP indicated that the efficiency indices in the top performing industries were driven by technological improvements or frontier effects. The top-performing companies in the UAE during the 2007-14 period demonstrated innovation-led growth, aided by the use of better technology, investments in capital equipment, and adoption of new production processes.

Assessing the Relative Efficiency for Listed Manufacturing Firms in Jordan Using Data Envelopment Analysis

“…In the work of (Zhiyong et al, 2017) the cross-sectional DEA models were extended to time -varying malmquist DEA, results based on a sample of 742 Chinese listed companies observed over 10 years suggested that malmquist DEA offers insights into the competitive position of a company in addition to accurate financial distress predictions based on the DEA efficiency measures. (Majumdar and Asgari, 2017) applied DEA theory to analyze the relative efficiency of 27 listed corporations in the United Arab Emirates, and studied the impact of the financial crisis and the recovery thereafter. They used malmquist productivity Index to study the decomposition of the productivity change for the period (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014).…”

“…Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) are the most employed parametric and non-parametric methods in the literature respectively (Silva et al, 2017). DEA is an optimization method that uses linear programming for assessing the efficiency and productivity of decision making units (DMUs) in term of proportional change in inputs or outputs (Majumdar and Asgari, 2017). Data envelopment analysis method was first introduced by (Charnes et al, 1978), and for this reason it is known as the CCR model, the CCR model assumes constant return of scale production function, then (Banker et al, 1984) modified this model and assumes the variable return to scale (VRS) efficiency measurement model, which is also known as the BCC model according to the names of the authors.…”

Evaluating the Performance of Colombian Banks by Hybrid Multicriteria Decision Making Methods

“…In Van der Westhuizen (2008) the efficiency and causes for efficiency change were evaluated for the four largest banks in South Africa for a period of 36 months. Majumdar and Asgari (2017) studied the performance measurement of UAE companies by DEA Malmquist. They used labor, capital, materials, revenue and EPS as the inputs and outputs of the model.…”

Efficiency of Listed Manufacturing Firms in Jordan: A Stochastic Frontier Analysis

“…Different measures have been used as a proxy for the capital input, namely: Total fixed physical capital in money term (Lee and Tyler, 1978), value of tangible fixed assets other than land (Tsukamoto, 2019), the replacement value of Capital (Suyanto et al, 2014), the net book value of the property, plant, equipment under the non-current assets of the Balance Sheet (Majumdar and Asgari, 2017), the replacement cost of existing machinery and other equipment employed in the production process, corrected by the degree of capacity utilization (Lundvall and Battese, 2000) the net value of fixed assets at the end of the survey year (Hailu and Tanaka, 2015), total assets (Dietrich, 2010) and (Le et al, 2018). The noncurrent asset is used in this study for the capital input.…”