ABSTRACT
 
This study investigated the Nigerian Banks’ Efficiency Performance. The period studied was 2005-2009.In addition to the  above,  the extent of the effect of the bank’s fixed assets,
operating expenses and total deposit on  their efficiency was investigated. The effect of  the bank’s efficiency on their profitability was also examined. In recent years  emphasis is now on
using frontier analysis methods in measuring bank efficiency instead of using financial ratios. In frontier analysis, the institutions that perform better relative to a particular  standard are
separated from those that perform poorly. Such separation is done either by applying a
parametric or non parametric frontier analysis to firms within the financial services
industry.This study employed the   Non parametric Data Envelopment Analysis (DEA)under
the assumptions of Constant return to scale (CRS),Variable Return to Scale (VRS) and Scale
Efficiency(SE) to estimate the efficiency scores of the banks .A bank with a score of 1 is
efficient, while a score below 1 means the bank is inefficient. The tests of the four hypotheses
were carried out using Vector autoregressive Analysis (VAR).  The findings of the study
revealed that GTB was the most efficient bank and it has the least reduction in inputs (4.93%)
needed to produce the same amount of output. Moreover it remained efficient throughout the
years 2006-2009.Overall, the worst performers are Unity bank, Afribank and UBA. Also the
banks did not achieve full efficiency under the CRS, VRS and SE in any of the five years. The
findings on the hypothesis tested revealed that fixed assets have a negative relationship with
efficiency, operating expenses has no long run relationship with the efficiency variable and
total deposit does not affect efficiency. Lastly, efficiency has a positive significant relationship
with profitability. This study therefore recommend that the banks that are not efficient should
study the operations of GTB the best performer to see if could be adopted to improve their
efficiency and the banks should moderate their use of inputs as they could have used fewer
amount of inputs to achieve the same level of output. Finally, the acquisition of fixed assets
should be reasonable. This is to prevent it from reaching a point where it will impact
negatively on the bank’s efficiency.

TABLE OF CONTENT

Titlepage - - - i
Certification - - ---ii
Declaration - - - iii
Dedication - - - -iv
Acknowledgements - - - --v
Table of Content - - -vii
List of Figures - - xii
List of tables - - --xii
List of Abbreviations - - - -xiii
Abstract - - - xiv

CHAPTER ONE: INTRODUCTION
11Background of the study - 1  
12Statement of the Problem -   4
13Research Questions - 7
14Objectives of the study - 7
15Hypothesis of the study - - - -   8
16Significance of the Study - 8  
17Scope - 10
18Limitation of the Study - - 10
19Outline of the study - -   11
110Definition of Terms - 11

CHAPTER TWO:LITERATURE REVIEW
21 Introduction -   14
22 The Conceptual framework on Efficiency - - - 15
23 Efficiency measurement according to Farrell - - 16
231 Technical efficiency - - - - 18
232 Technical and Allocative (price) efficiency - - 20
24 Efficiency measurement in banks defined - - -   23
241 Revenue Efficiency - - - -   24
242 Cost Efficiency - - - - 25
243 Profit Efficiency - - - - 26
2431 Standard profit Efficiency - 27
2432 Alternative profit x-Efficiency - 28
24321 Substantial Unmeasured Differences in Quality of Output - - 29
24322 Output is Not Completely Variable - - -   31
24323 Output Markets are Oligopolistic - - -   31
24324 Output Prices are not Accurately Measured - - - 32
25 The Return to Scale Concept - - 33
26 Theoretical Framework on Efficiency Measurement - -   34
261 The Parametric Techniques - - -   34
2611 Stochastic Frontier Analysis (SFA) - - - 34
2612 The Thick Frontier Approach (TFA) - - - 35
2613 Distribution-Free Approach (DFA) - - 37
262The Non Parametric Methods - - - 38
2621Data Envelopment Analysis - 38
2622 Choosing DEA Model - 42
2623 Benchmarking in DEA - 44
2624 Sensitivity Analysis in DEA - - -   45
263 The Free Disposal Hull (FDH) - -   46
27 Alternative way to measure Efficiency -   46
271 Risk Ratings -   47
272 Banking productivity per Employee Hour - 47
273 Minimum Reserve - 48
274 Monetary Aggregates - 48
275 Interest Spreads and Margins -   48
276 Accounting Ratios - 49  
277 Using Frontier Analysis to capture the Derivation between Actual and Desired Performance - - 50
278 Market -based Approaches - 51
28 The Definition of Bank Inputs and Outputs -   52
29 Empirical Evidence on Efficiency measurement in Banking - 54

CHAPTER THREE: RESEARCH METHODS
31 Introduction - - - - 60
32 Model Approach and its justification - 63  
33 Sources and Choice of Data - - - - 63
341 The DEA Model - 66
342 Model 1 for Hypothesis one, two and three - -   68
343 Model II for Hypothesis four (4) - 69
35 Model Validity and Reliability -   69  
36 Sample Size Determination -   70
37 Method of Data Analysis -   70
371 Method of Data Analysis using DEA - - -   71
372 Techniques of Estimation for the four Hypotheses -   72
 
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
41 Introduction - - 76
42 Model Solution Procedure and Results - - - 76
421 The Bank‘s Efficiency Analysis - - - 78
43 Discussion of the Technical Efficiency Scores of each DMU using VRS, CRS and SE - 82
44 Ranking of the Bank‘s Efficiency using VRS, CRS and SE - - 99
45 Testing of Hypotheses - - - 102
451 Presentation and Interpretation of Result on Hypothesis tested on the effect of FA, OE and TD on Efficiency - - - -   103
452Test of Hypothesis tested on the effect of Efficiency on Profitability - - 111
 
CHAPTER FIVE: FINDINGS, CONCLUSION AND RECOMMENDATIONS
51 Summary of Work Done - - - - 116
52 Summary of Findings - - - - 117
521 Findings on the Hypotheses tested - - - 119
53 Conclusion - - - - -   121
54 Recommendations - - - -   121
55 The Research‘s contributions to knowledge - - - 123
56 Suggestion for further research - - - - 123
References - - - -   125
Appendix i-v - - - - 132

LIST OF FIGURES
Figure21 Farrel Efficiency - 17
Figure22 Technically Efficient Production Possibilities Frontier -   19
Figure23 Technical and Allocative Efficiencies (Input Orientation) - 21
Figure24 Technical and Allocative Efficiencies (output Orientation) - 22
Figure41 Columns showing the bank‘s score under VRS, CRS and SE - 101

LIST OF TABLES
Table 41 Efficiency Scores for the banks in each year - - - 77
Table 42 Technical Efficiency Scores of DMUs (Banks) -   82
Table 43 Ranking of the Banks ‘efficiency level using VRS, CRS and SE - 99  
Table 44 Unit Root Test at Level - 103
Table 45 Unit Root Test at First Difference -   104
Table 46 Johanson Co intergration Rank test result - 105
Table 47 Single Equation Equilibrium Correction Models for Efficiency Model - 107
Table 48 Table for Test of Hypothesis on the Effect of Efficiency on Profitability - 111
Table 49 Co integration Result - 112
Table 410 Vector Error Correction Estimates - 113
Table 411 Single Equation Equilibrium Correction Model for the Efficiency model  114
Table 51 Table Summary of Banks and their year of Efficiency under VRS, CRS and SE 118
 
LIST OF ABBREVIATIONS AND ACRONYMS
FIR- First Bank Plc
ZEN-Zenith Bank Plc
PHB-Platinum Habib Bank Plc
UNION- Union Bank Plc
UBA-United Bank for Africa Plc
GTB- Guaranty Trust Bank Plc
FID- Fidelity Bank Plc
DIA-Diamond Bank Plc
ECO-EcobankPlc
STIBTC-Stanbic-IBTC  
INT-Intercontinental Bank Plc
WEMA- WEMA Bank plc
UNITY-Unity bank Plc
CITI- Citi bank
AFRIB- AfribankPlc
SPRING-Spring Bank Plc
SKYE-SKYE Bank Plc
FCMB-First City Monument BankPlc
OCEANIC- Oceanic Bank Plc
ACCESS- Access Bank Plc
STERLING- Sterling Bank Plc
STCHART-Standard Chartered Bank
FINBANK- Finbank Pl