Analysis of Competitive Conditions Among Major UAE Banks
See the file
Econometric Modelling
Assessed Coursework/Project
Task: Use appropriate econometric techniques to critically assess competitive conditions of the banking industry in an allocated country.
This coursework exercise should be completed individually. This coursework requires significant time commitment.
A good way to approach this coursework would be to carefully read the published paper (Mathews et al 2007), familiarise yourself with the allocated data file.
The required data for this coursework exercise is provided for each student and it is available on the Module Moodle page.
A copy of the following paper is available on the Module Moodle site and you can use this as a blueprint paper:
Matthews, K., Murinde, V. & Zhao, T. (2007). Competitive conditions among the major British banks, Journal of Banking & Finance, 31, 2025–2042.
The maximum word count for this exercise is 4000 words, excluding appendices, graphs and tables
You are expected to address the following points as part of this exercise.
- As part of your introduction, briefly describe the reasons for assessing the competitive conditions (section 1 in the paper) in an industry (5 marks).
- Calculate and explain concentration ratios and Herfindahl–Hirschman Indices (HHI) (section 2 in the paper) using the data file assigned to you and provide a full interpretation of these calculated ratios and indices. An example spreadsheet containing all the steps to calculate these ratios is available on the Module Moodle site. (10 marks)
Following the estimated results given in the academic paper quoted above, carry out your own estimations using your data. Remember, the presentation of your results (e.g. tables etc.) is as important as the estimations.
Carefully interpret your estimation results, pay attention to the statistical significance of the estimated coefficients and clearly outline the null and alternative hypothesis for each test. Draw conclusions based on the results.
- Carry out estimations using the OLS estimation method in Eviews software of equations 3 and 5 ((section 4 in the paper and also given below). (The Number of Branches variable is not available in your data file. Hence, you will be carrying out your estimations without this variable)) given in the paper using only full sample and test H and E statistic [Hint: Wald test coefficient Restrictions]. You are not required to carry out the CHOW test. You are also not required to estimate equation 7 in the paper or carry out any analysis based on that equation. Remember, the presentation of your results (e.g. table 4 etc.) is as important as the estimations.
Carefully interpret your estimation results, pay attention to the sign and size of the estimated coefficients and statistical significance of the estimated coefficients and clearly outline the null and alternative hypothesis for each test. Draw conclusions based on the results. (50 marks).
- Assess whether or not multicollinearity is a feature of the estimated model (Equation 2). Discuss available remedies to tackle the problem of multicollinearity. (15 marks)
- Assess whether or not heteroscedasticity is a feature of the estimated model (Equation 2). Discuss available remedies to tackle the problem of heteroscedasticity. (15 marks)
- Provide brief conclusions. Your overall presentation of the report is as important as the various parts of the report (5 marks).
This assessed coursework counts for 100% of your overall assessment for this module.
Please submit your final report to the drop box provided on the module Moodle page by the due date stated above. Essential workings, results and tables may be included as an appendix.
It is your responsibility to process your report through the University Turnitin software. If your similarity score is higher than the maximum University recommended score of 20, your report will be treated according to the University plagiarism regulations.
Marks and feedback will be made available in 20 working days of the original deadline
Please do not be anxious if you do not have a specialist knowledge of banking. Marks will be awarded based upon your knowledge of econometrics and your ability to interpret/communicate results.
List of variables for the coursework report
You have been individually provided data file containing the following variables which have been downloaded from from the SNL database.
|
|
Variables |
SNL Path |
|
X1 |
Total Revenue |
Summary Banking Financials / Income & Expenses / Operating Income |
|
X2 |
Net Profit |
Summary Banking Financials / Income & Expenses / Net Profit |
|
X3 |
Provisions for Loan Losses |
Summary Banking Financials / Income & Expenses / Customer Loans Impairment Expense
|
|
X4 |
Total Assets |
Financials / Assets / Total Assets |
|
X5 |
Fixed Assets |
Financials / Assets / Fixed Assets
|
|
X6 |
Personnel Expense |
Financials / Expenses / Personnel Expense |
|
X7 |
Depreciation and Amortisation |
Financials / Expenses / Depreciation and Amortisation |
|
X8 |
Total Interest Expense |
Financials / Expenses / Interest Expense |
|
X9 |
Total Equity |
Financials / Equity / Total Equity |
|
X10 |
Real GDP growth rate |
From Screener, choose Geographic Intelligence / Select Country / Add-Edit Report Fields / Type ‘Real GDP growth’ |
Following Matthews, Murinde & Zhao (2007), the following variables have to be generated using the above variables which have been stored in a data file allocated to you individually. The Eviews data file containing the above variables is available on the module moodle page and the name the allocated individual has been given in a spreadsheet file.
|
|
|
|
REV |
Ratio of bank total revenue to total assets (Total Revenue/Total Assets) (X1/X4) |
|
ROA |
Net profits to total assets (Net Profit/Total Assets) = (X2/X4) |
|
PL |
Personnel expense to total assets (Personal Expense / Total Assets) = (X6/X4) |
|
PK |
Depreciation & Amortisation to fixed assets (Depreciation & Amortisation / Fixed Assets)=(X7/X5) |
|
PF |
Ratio of total interest expense to total equity (Total Interest Expense / Total Equity)= (X8/X9) |
|
RISKASS |
Ratio of loan loss provisions to total assets (Provisions for Loan Losses / Total Assets) = (X3/X4) |
|
ASSET |
Total Assets = (X4) |
|
GROWTH |
Real GDP growth rate = (X10) |
Variables of interest can be generated in EViews by selecting the Quick button from the workfile toolbar and typing in the relevant formulae. Click on Quick, Generate series button and type learnings = log(earnings) to create log of the variable.
When you create the variables for the coursework assignment, some of these will have negative values. If you attempt to take log of these variables in Eviews which has negative values, Eviews may give you an error message. This is because log can’t be taken of negative values. However, you can use the following formula to take log of a variable which has negative values.
lny =log(y+sqrt(y^2+1)
For example
lnREV = log(REV+sqrt(TREV^2+1))
Revised Equation 3 (Matthews, Murinde & Zhao (2007)). You will be estimating this equation in Eviews using the above variables.
ln REVit = a0+ a1 ln PLit + a2 ln PKit + a3 ln PFit + b1 ln RISKASSit + b2 ln ASSETit + c3 GROWTHt + eit
Revised Equation 5 (Matthews, Murinde & Zhao (2007)). You will be estimating this equation in Eviews using the above variables.
ln ROAit= a0 + a01 ln PLit + a02 ln PKit + a03 ln PFit + b01 ln RISKASSit + b02 ln ASSETit + + c01 GROWTHt + uit
Analysis of Competitive Conditions Among Major UAE Banks
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Professor:
Unit Name & Number:
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Analysis of Competitive Conditions Among Major UAE Banks
Abstract
Any country’s banking sector competitive conditions determine major occurrences in the entire industry. This study looks at the UAE banking sector and determines what leads to the major players' competitiveness. With both local and foreign banks, the UAE plays a key role in the Arabic world across the Middle East. The study uses panel data for 22 banks for a period from 2013 to 2017. The review of Matthews, Murinde & Zhao (2007) paper forms the basis of this study. The results of Rosse-Panzar show that the banking sector in the UAE is based on the monopolistic competition.
Introduction
The United Arabs Emirates (UAE) is a favorite investment hub for many business people from around the whole world. To do business well in any country, one should seek to understand how the host country's banking systems work. There are various categories of banks in the UAE such as commercial banks, merchants/investments banks, Islamic and industrial banks. Islamic rules influence major banks in the UAE. Thus, Islamic banks are becoming more influential. Islamic banks don't have borrowing rate and economic activities regarded non-religious such as gambling, alcohol and tobacco consumption can't be financed through this system. UAE also has foreign banks through taxation is different from the local counterparts. The local banks are exempted from taxation while the foreign banks have to pay 20 per cent on their profits.
Banking structure of UAE
The competitiveness of the UAE banking sector can't be underestimated in the Middle East. The country has 57 banks, of which 23 are domestic, and 34 are foreign. Majority of the domestic banks are owned majorly or minorly by local emirates. The local laws require foreign banks to have a representative office in the UAE. The country boasts of the largest banking sector amongst the Arab League countries and the second-largest Arabic economy with the highest deposits. The banks are regulated and supervised by the Central Bank of UAE created under Federal Law 10.
UAE banking during 2013-2017
Concentration Ratios and Herfindahl-Hirschman Indices (HHI) for the top two banks and five top banks (Assets-based)
Table 1: Concentration ratios and HHI for the biggest two and biggest five banks
Year/Measure
CR2
CR5
HHI
2013
0.3835
0.6518
961.539
2014
0.3837
0.6470
1001.4772
2015
0.3824
0.6450
977.0314
2016
0.3396
0.6152
964.8289
2017
0.4332
0.6801
1020.3729
Source: Author's computation using Excel
Table 1 above represents concentration ratios and HHI for the period stretching from 2013 to 2017. The evidence of this analysis shows the CR2 and CR5 have been fluctuating within this period of study. Also, the HHI has been fluctuating over the study period.
Theoretical and Methodological approach
Panel data for 22 selected banks for a period from 2013 to 2017 was used for this study. Many researchers have undertaken empirical studies on the extent of competition in the UAE's Banking industry. Various studies on the banking sector market structure have applied the structure-conduct-performance (SCP) approach. Most of these studies assume that the structure of the market is exogenous and profitability is regressed on the concentration ratio and involved several control variables. These studies' results have majorly involved absolute profitability and the concentration ratio to predict the banks' market power. On the other hand, the efficient-structure hypothesis (ESH) suggests that larger lenders seem to outdo smaller ones in terms of profitability since they have higher operating efficiency.
These theories don't answer why the banks are competitive; rather, they dwell more on the banks' profitability. Many scholars argue that these two theoretical approaches are not conclusive in determining the banks' competitive edges. Berger and Humprey (1997) argue that the SCP and ESH majorly explain the profitability and concentration to determine the banks' competitiveness. Paul (1999) argues that the two approaches don't explain the output price’s deviation from marginal cost to explain the banks' competitive conditions.
To explain the banks' market competitiveness, Rosse and Panzar's reduced form revenue model was adopted a. It is derived from profit-maximizing equilibrium assumptions. Firm-specific revenue data and factors prices are used in this model and doesn't involve output equilibrium prices. Also, this approach is robust with small samples. This approach assumes that firms enter and leave the market at will with no loss of capital. Potential competitors will operate at similar cost functions as the current well-established firms.
REVit=∝0+ ∝1lnPLit+∝2PKit+∝3PFit+β1RISKASSit+β2ASSETit+β3BRit+γ1GROWTHt+εit
Where the REV = ratio of bank revenue to total assets; P.L. = personnel expenses to employees (unit price of labour); P.K. = capital expenses to fixed assets (unit price of capital); P.F. = ratio of annual interest expenses to total loanable funds (unit price of funds). The i-subscript denotes banks (i=1… N); and the t-subscript denotes time (t=1…, T). the model assumes a one-way error component.
ROAit=∝0+ ∝1lnPLit+∝2PKit+∝3PFit+β1RISKASSit+β2ASSETit+β3BRit+γ1GROWTHt+εit
Where: ROA denotes return on assets. The Rosse-Panzar methodology is used to measure the nature of competitive conditions
Empirical analysis and results
Esquations (1) and (2) above have the dependent variables as the ratio of total earnings and net profit to total assets. Inclusion of non-interest revenue and fees will show their significance to profitability of banks.
Table 2: Regression results using REV as the dependent variabl...
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