Three essays on bank technology, cost structure, and performance

THREE ESSASYS ON BANK TECHNOLOGY, COST STRUCTURE,
AND PERFORMANCE





BY


DAN WANG

M.A., Binghamton University, 2003
M.A., Xiamen University (China), 2001
B.A., ZhongNan University of Economics and Law (China), 1996






DISSERTATION
Submitted in partial fulfillment of the requirements for

the degree of Doctor of Philosophy in Economics
in the Graduate School of Binghamton University
State University of New York
2007

UMI Number: 3266486
3266486
2007
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© Copyright by Dan Wang 2007
All Rights Reserved


iii











Accepted in partial fulfillment of the requirements for
the degree of Doctor of Philosophy in Economics
in the Graduate School of
Binghamton University
State University of New York

2007



Feb 28, 2007
Chairman, Subal C. Kumbhakar, Department of Economics, Binghamton University
Christopher L. Hanes, Department of Economics, Binghamton University
Daniel J. Henderson, Department of Economics, Binghamton University
Jian Zhou, School of Management, Binghamton University


iv



ABSTRACT

This dissertation addresses the issues around the technology and cost structure in
commercial banking industries in both industrialized economy (US) and transitional
economy (China). In addition, internal and external factors that affect bank performance,
in terms of technical change, technical efficiency and total factor productivity, are
examined to provide policy and business implications to regulatory authorities and
banking managers.
The first paper investigates the existence of strategic group and heterogeneous
technology in the US banking industry. Two stages of analyses are conducted. First,
cluster analysis is carried out to segment the US commercial banks into seven distinct
strategic groups in terms of their product mix and allocation of inputs. The membership
shifts across strategic groups during the sample period (1991-2000) are traced to explore
the response of banks to the changes of market conditions and regulatory environments.
Second, based on the segmentation by cluster analysis, we further investigate the

production technology and cost structures for each strategic group in the US commercial
banking industry. A system of cost function and derived share equations are used to
estimate the technology for each group. The distributions of returns to scale and technical
change for each strategic group are also examined. The results provide the evidence of the
presence of distinct strategic groups and heterogeneous technologies in the US banking
industry. We find returns to scale and technical change vary substantially across strategic


v
groups. Based on our findings, we conclude that the traditional application of a single
homogeneous technology to the entire industry is likely to misrepresent the US banking
industry.
The second paper examines how and why the de novo banks in the US banking
industry distinguish from their peer established banks. Using a selected sample data of
2001-2005, we find that a typical de novo bank has higher capital equity ratio, higher
concentration in real estate loans, higher cost of deposits and labor, and higher average
quality of loans as well. In terms of profitability (ROA), our observation on the de novo
banks in recent years is consist with previous studies on the de novo banks active in the
1980s: negative earnings in first two or three years followed by substantial improvement
in their profitability, though still lagging behind a typical established bank at least in their
first eight years of operation. In order to link profitability with production process, we
introduce a cost metafrontier model that enables us to compare technologies across
different groups of banks by using measures of technology gap and global technical (cost)
efficiency. Empirically, we find that improving cost efficiency leads higher profitability
for the de novo banks. In contrast, this effect is absent for the established banks. Scale
economy exhibits its most advantageous effects on the smallest new banks by improving
their technology, cost efficiency and thus profitability, while these advantages of scale
diminish with the increase in size and finally they disappear when bank size reaches
certain level.
In the third paper, focus is shifted from industrialized economy (US) to transitional

economy, China, where markets and institutional structures are different from those of


vi
developed countries. We employ an input distance function approach to analyze the
impact of banking deregulations/reforms in China since early 1990s on the efficiency and
the total factor productivity (TFP) change in Chinese banking industry. We find that the
joint-equity banks are more efficient than the wholly state-owned banks (WSOBs).
Furthermore, both the WSOBs and the joint-equity banks are found to be operating
slightly below their optimal size, suggesting potential advantages of expansion of their
businesses. Overall, TFP growth in Chinese banking industry was 4.4% per annum for the
sample period 1993-2002. Joint-equity banks experienced much higher growth in TFP
(5.5% per annum) compared to the WSOBs (1.4% per annum).







vii



To Quan and Julie



viii

ACKNOLEGEMENTS

I am greatly indebted to Subal C. Kumbhakar, my dissertation advisor, for his
thoughtful guidance, critical comments, and constant encouragement. Throughout my
tenure as a Ph.d. student, Subal has been a teacher, a mentor, and a friend. Thanks to
Subal, I have enjoyed learning econometrics and research skills from scientific writing to
structural way of thinking. He gave me his hearty support during the time when I was on
the job market.
Additional thanks go to other members of my dissertation Committee. I am very
grateful to Christopher L. Hanes and Daniel J. Henderson for their intuitive questions and
invaluable comments on my dissertation. I thank Jian Zhou, who joined my dissertation
committee as an outside examiner, for his tireless reading and commenting. I would also
like to thank Neha Khanna, Clifford Kern and staffs in the Economics Department at
Binghamton University for many helps and considerations along the way in the years
back in Binghamton.
My mother-in-law, JieZhi Hu came to the States and took care of my daughter during
my hectic days of preparing my dissertation. Without her help, I couldn’t have gone so far
with family obligations. I greatly appreciate all she has done. I am deeply indebted to my
parents for their unconditional love and support during all these years when I am away
from them.
Julie, my daughter, is my angel and brings endless joys and laughs to my life.


ix
Without her, I couldn’t have been so energetic and kept pushing myself beyond what I
thought I was capable of. Last but not least, I cannot express the level of gratitude and
love that I have for my husband, Quan Zhou. He witnessed and shared every difficult and
happy moments of my research. His encouragement, support and help are so appreciated

that my feelings are beyond any words to describe.


x


TABLE OF CONTENTS

Page
ABSTRACT IV
ACKNOLEGEMENTS VIII
LIST OF TABLES XII
LIST OF FIGURES XIII
INTRODUCTION 1
CHAPTER 1 8
STRATEGIC GROUPS AND HETEROGENEOUS TECHNOLOGIES: AN APPLICATION TO
THE US BANKING INDUSTRY 8

1.1 INTRODUCTION 8
1.2 CLUSTER ANALYSIS AND STRATEGIC GROUPS 11
1.2.1 CLUSTERING VARIABLES 15
1.2.2 NUMBER OF CLUSTERS 16
1.3 COST ANALYSIS 17
1.3.1 METHODOLOGY 17
1.3.2 VARIABLES 22
1.4 RESULTS AND FINDINGS 26
1.4.1 DIFFERENCES ACROSS CLUSTERS AND IDENTIFICATION OF STRATEGIES 26
1.4.2 MEMBERSHIP SHIFT OF STRATEGIC GROUPS 28
1.4.3 BANK SIZE DISTRIBUTIONS OF STRATEGIC GROUPS 30
1.4.4 COST STRUCTURE, RETURNS TO SCALE AND TECHNICAL CHANGE 31

1.4.5 COMPARISON OF RTS AND TC ACROSS STRATEGIC GROUPS WITHIN BANK SIZE GROUP 34
1.5 SUMMARY AND CONCLUSIONS 36
CHAPTER 2 54
THE PERFORMANCE OF DE NOVO COMMERCIAL BANKS:
A COST METAFRONTIER APPROACH 54
2.1 INTRODUCTION 54
2.2 LITERATURE REVIEW 58


xi
2.2.1 BALANCE SHEET COMPOSITION OF DE NOVO BANKS 59
2.2.2 EVOLUTION OF PERFORMANCE IN THE LIFE CIRCLE OF DE NOVO BANKS 59
2.2.3 DETERMINANTS OF PERFORMANCE 61
2.3 METHODOLOGY 64
2.4 DATA 73
2.5 MODEL SPECIFICATION AND ESTIMATION 76
2.5.1 MODEL SPECIFICATION 76
2.5.2 VARIABLES 78
2.5.3 ESTIMATION AND TESTS 80
2.6 RESULTS 83
2.6.1 SIZE, AGE AND PROFITABILITY 83
2.6.1.1 Size and Profitability 83
2.6.1.2 Age, Profitability and Convergence 84
2.6.2 ESTIMATION RESULTS OF COST METAFRONTIER MODEL 85
2.6.2.1 Test Results for Heterogeneous Technologies 85
2.6.2.2 Effects of Z Variables on the Cost Frontier 86
2.6.2.3 Technology Gap and Technical Efficiency Relative to Metafrontier 89
2.6.3 RELATIONSHIP BETWEEN PROFITABILITY AND COST EFFICIENCY 90
2.7 SUMMARY AND CONCLUSION 96
CHAPTER 3 110

ECONOMIC REFORMS, EFFICIENCY, AND PRODUCTIVITY IN CHINESE BANKING 110
3.1 INTRODUCTION 110
3.2 INSTITUTIONAL AND REGULATORY CHANGES IN THE CHINESE BANKING
INDUSTRY 114

3.3 METHODOLOGY 118
3.4 DATA 125
3.5 EMPIRICAL RESULTS 130
3.5.1 RETURNS TO SCALE (RTS) 131
3.5.2 TECHNICAL EFFICIENCY 131
3.5.3 EFFECT OF EXOGENOUS FACTORS (THE ZS) ON TECHNICAL EFFICIENCY 132
3.5.4 PRODUCTIVITY GROWTH 135
3.6 SUMMARY AND CONCLUSIONS 136
BIBLIOGRAPHY 149




xii



LIST OF TABLES

Table 1. 1: Definitions of the Variables 38
Table 1. 2: Descriptive Statistics of Variables in Cost Function for Selected Years 40
Table 1. 3: Means of Selected Variables for Different Clusters 41
Table 1. 4: Total Assets, RTS and Technical Change by Strategic Groups 42
Table 1. 5: RTS of Bank Size Groups across Strategic Groups 43
Table 1. 6: Technical Change of Size Groups across Strategic Groups 44

Table 1. 7: Stochastic Dominance Tests of RTS and Technical Change 45
Table 2. 1: Definitions of the Variables 99
Table 2. 2: Descriptive Statistics of Relevant Variables 101
Table 2. 3: Effects of Z variables on Cost Functions 102
Table 2. 4: Summary of Technical Efficiency and Technology Gap Ratio 103
Table 2. 5: Estimation Results of Regression of ROA 104
Table 3. 1: Descriptive Statistics of Key Variables 138
Table 3. 2: Estimation Result of the Input Distance Function 139
Table 3. 3: Efficiency, RTS,
Δ
TFP and TFP Index by Ownership 140




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LIST OF FIGURES

Figure 1. 1: Share of Non-interest Income, 1984-2004 46
Figure 1. 2: Membership of Different Strategic Groups, 1991-2000 47
Figure 1. 3: Percent of Total Assets for Different Strategic Groups, 1991-2000 48
Figure 1. 4: Average Bank Size for Different Strategic Groups, 1991-2000 49
Figure 1. 5: Distribution of Total Assets (Logs) For Different Strategic Groups 50
Figure 1. 6: Kernel Density of Returns to Scale by Strategy Group 51
Figure 1. 7: Empirical CDFs of Returns to Scale by Strategy Group 52
Figure 1. 8: Empirical CDFs of Technical Change by Strategy Group 53
Figure 2. 1: Trends of De Novo Banks and Total Commercial Banks 105
Figure 2. 2: Metafrontier Cost Function Model – Simple Case 106

Figure 2. 3: Bank Size and Profitability (ROA) 107
Figure 2. 4: Age and ROA 108
Figure 2. 5: Comparison of Profitability: De Novo Bank Vs Established Bank 109
Figure 3. 1: An Input Distance Function with Two Inputs 141
Figure 3. 2: Asset Distribution of Banking Institution (end of 2000) 142
Figure 3. 3: Labor Productivity of Chinese Banks (1993-2002) 143
Figure 3. 4: Returns to Scale of WSOBs and Joint-Equity Banks (1993-2002) 144
Figure 3. 5: Technical Efficiency of WSOBs and Joint-Equity Banks (1993-2002) 145


xiv
Figure 3. 6: Dynamics of Total Factor Productivity Change (1993-2002) 146
Figure 3. 7: Dynamics of Components of TFP Change (1993-2002) 147
Figure 3. 8: Dynamics of Total Factor Productivity Index (1993-2002) 148


1


INTRODUCTION

As an intermediary between investors and depositors, bank plays a special and
critical role in an economy. The fundamental functions of a bank as an intermediary can
be basically simplified as “transforming” money and maturities from depositors to
borrowers at its own risk. It accomplishes this by reducing overall risks through
diversification in both its borrowing activities and its lending business. What makes a
bank different from most of other businesses in the economy is manifested in two major
aspects: the extent of potential damages of a bank it could cause were it to collapse and
the distinct production process of a bank. If a bank fails, it would not only be its
employee losing their jobs, shareholders losing their capitals, but also clients potentially

losing their entire savings and financial assets, which usually poses more serious
chain-reacting dangers that could penetrate into other fields of the economy. On the
production technology side, by granting loans, providing payment services, carrying out
investments, etc, a bank is creating added values by its ‘production’ activities, like any
other businesses. However, unlike the traditional production process in most of the other
industries, both the inputs (except labor) and outputs are nominal money: a bank
generally transforms deposits and other types of borrowed funds, with the input of labor
and its fixed assets, into loans, securities and other types of earning assets. It is these two
distinct features of bank that make banking industry a highly regulated sector in an
economy and attract broad interests on banking studies. The last two decades have
witnessed a wave of flourished studies on the production technology and the performance


2
of banking industries across many countries in the world (See Berger and Humphrey
(1997) for an international survey of banking studies of production, efficiency and
performance).
This dissertation consists of three independent but related studies on the US
commercial banking industry, the de novo banks in the US and the banking industry in
China, respectively. All of the three chapters address the topics around technology, cost
structures, and performance of commercial banks with different emphasis in each chapter.
Being the most profound banking system in the world, the US banking industry has
always been the focus of banking studies (for example, Hunter & Timme (1986), Bauer,
Berger & Humpherey (1993), Berger and Mester (2003), among many others). The past
decade was a fascinating time for the US banking industry, which features trend of
consolidation and expansion of interstate banking, renewed energy for changes after the
dismal days of the early part of the 1990s, the laid-out of legislative ground work for
Gramm-Leach-Bliley, the ever intense competition in the broader financial services arena,
etc. To complement the existing literature, the first chapter in this dissertation addresses
the issues of technology, cost structure and performance of the US commercial banking

industry from 1991 to 2000.
Instead of following the traditional cost function approach that assumes single
technology for all the firms in the industry, the first paper hypothesizes the existence of
heterogeneous technologies in the US commercial banking industry. The hypothesis arises
from the observation that the US banks have been creating their own niches by adopting
different business strategies in order to retain their competitive advantages in the market.


3
This study takes two steps. First, it carries out a cluster analysis that is purely data based
without any assumption on why clusters exist. As the result of cluster analysis, the US
banks are segmented into different strategic groups. Within each strategic group, banks
share similar characteristics of major attributes, like product specialization, cost shares,
etc, while across strategic groups, banks are dissimilar to each other by the attributes.
Then, in the second step, a system of cost function and derived share equations are
introduced to estimate the underlying production technology for each strategic group. The
returns of scales (RTS) and technical change (TC) for each bank are derived from the
parameter estimates of the cost function system. The substantial variations of RTS and TC
across strategic groups provide the evidence of heterogeneous production technologies
and cost structures within the US banking industry. As a result, in order to reduce
estimation biases and accurately measure the production technology (or/and cost structure)
of the US banking industry, it is necessary to treat different strategic groups separately.
Otherwise, misleading conclusions are very likely to be drawn, based on the analysis by
pooling all banks together. This is the major conclusion and contribution of the first paper.
Concurrent to the overall trend of diminishing banks in the US, there was a
rejuvenated wave of new banks (de novo banks) since the middle of 1990s. What makes
the bankers of these de novo banks decide to enter the market while others are retreating?
By common sense, a new bank is usually more financially fragile and has higher chances
to fail than an established bank, even though they are in similar scale. The questions
arising from the common sense are: in what aspects these de novo banks distinguish

themselves from the established banks and what enables them to compete again the


4
established banks? The second paper in the dissertation attempts to answer the above
questions by examining the characteristics of the de novo banks in the US that were
established since early 1990s.
There are a handful of studies on the de novo banks (for example, Hunter and
Srinivasan (1990), DeYound and Hasan (1998), Seelig and Critchfield (2003), etc). The
major focuses of these studies are on the balance compositions of de novo banks, the
entry and exit of de novo banks, the evolution of performance in the life circle of de novo
banks, and the determinants of their performance. The second chapter in the dissertation
complements the existing literature in two aspects. First, almost all prior studies dealt
with the de novo banks that were established in the 1980s, and their performance during
the 1990s was investigated in those studies. The study in the second chapter explores the
performance and its determinants of the de novo banks that were established after 1993
and are active in recent five years (2001-2005). A study on the most recent data should
apparently be better suited than those on historical data for providing reliable inference on
the policy implications in the current economic and banking industrial environments.
Second, the study employs a cost metafrontier model, which is relatively new and has
only been applied in a few recent empirical studies. The cost metafrontier approach
provides a tool to assess technological gaps and technical efficiencies across different
production technologies, which is an unattainable task by the traditional cost function
approach.
Specifically, following the standard approach in the existing literature, the second
chapter starts with the examination of the de novo banks’ assets structure, funding mix,


5
capital levels, asset quality, credit risk, profitability (ROA), etc. Next, the study assumes

again the existence of heterogeneous technologies in the de novo banks in the US, and
then employs a cost metafrontier model and estimates a cost function for each of the five
groups of the de novo banks. Furthermore, for comparison purpose, a population of
established banks with similar scale as the de novo banks is included in the study. Cost
structures and cost efficiencies across the groups of de novo banks and between
subpopulations of the de novo banks and the established banks are examined and
compared. Last, one step further, the study links cost efficiency and profitability with
controls on other factors, attempting to identify whether cost factor or revenue factor is
the driving force for profitability. Overall, the approaches employed in the study provide
a thorough examination on the de novo banks and help capture the variations of
performance caused by embedded heterogeneous technologies across different groups in
the de novo banks and between the de novo banks and the established banks.
Transitional economies distinguish themselves from developed economies in a
number of ways, which makes them deserve special attention of research. Since 1980s,
many studies have shown increasing interests on the banking industries in the transitional
economies, including former Soviet republics, east European countries, China, India, etc.
China’ central government has launched a series of financial reforms since 1980s, aiming
to tackle the problems caused by its dysfunctional banking sector. The issues with
Chinese banking industry have attracted a great deal of interests from academic and
governmental/organizational research institutions. However, the studies on Chinese
banking industry are limited and insufficient, mainly due to the difficulty of obtaining


6
reliable data. Most of the existing studies are case studies with emphasis on the
comparison of financial ratios. The third chapter contributes to the Chinese banking
studies by focusing on the assessment of effectiveness of the reforms using a
regress-based input distance function. The study uses the data of 14 major domestic banks
from 1993 to 2002. During this period of time, the banking sector reforms were
strengthened and the domestic banks had experienced gradual transformation in many

aspects, which were supposed to aid in improving the performance and enhancing the
competitive capacity of these domestic banks. The objective of the study is to answer the
questions whether the reforms achieved the goals that were originally set at the start, and
how the performance of these domestic banks was affected by various internal and
external factors.
An input distance function approach is employed in the study. Distance functions
have the advantage of accommodating multiple inputs and multiple outputs, which is
quite common in the banking industry. Furthermore, they provide cost implications
without requiring price information for estimation, which is particularly important when
assumptions about competitive markets are unlikely to be met or when price information
is not available or accurate. Based on these two major advantages, an input distance
function approach is well suited for the study in Chinese banking in the dissertation. The
third chapter first investigates the effects of possible forces on technical efficiency of the
domestic banks in China, including ownership type, capital adequacy ratio, bank size and
environmental factors. Second, it examines the dynamic pattern of total factor
productivity changes of these domestic banks by decomposing them into scale effects,


7
technical change, technical efficiency change and change induced by bank characteristics
and environmental forces. Through the examination, the third chapter provides a
comprehensive assessment of the performance of Chinese domestic banks, and the
internal and external factors that affect their performance.
All in all, the dissertation enriches the body of literature of banking studies on
production and performance with some new perspectives. The results from these three
studies strengthen the findings from prior studies and offer new insights to understanding
production technologies and cost structures of banking industry in both developed
economy and transitional economy. This more in-depth understanding of technologies and
cost structures further helps assess the performance of the banking industries in a more
accurate way and provide more relevant policy implications.

8

CHAPTER 1

STRATEGIC GROUPS AND HETEROGENEOUS TECHNOLOGIES:
AN APPLICATION TO THE US BANKING INDUSTRY
1



1.1 INTRODUCTION

Deregulation and technological innovations since the 1980s have provided great
opportunities for many banks in the US to create their own niche in the ever increasing
competitive environment. If one takes a cursory look at the operations of banks today, one
will observe that banks tend to exhibit less resemblance to each other and follow widely
divergent business strategies. Some banks specialize in a particular area of products and
services, while others follow a strategy of diversification by participating in a wide range
of activities. Banks also differ in terms of their funding sources. Some utilize core
deposits as their main source while others rely more on federal purchased funds.
Therefore, traditional partitioning of the banking industry into wholesale and retailing
appears to be too broad to represent the existing diverse strategies in the US banking
industry.
The theory of strategic groups proposes the possibility of existence of multiple

1
Coauthored by Subal. C. Kumbhakar

9
strategic groups within the same industry. The concept of strategic groups was first
introduced in the work of Hunt (1972), Caves and Porter (1977), and Porter (1980), and it
was used to explain the observed heterogeneity of firm’s conduct and performance within
industries. In this literature, strategy groups are commonly classified by a set of strategic
variables (or several strategic dimensions) that affect the decision making of a firm. Firms
in the same group have similar values of those strategic variables, and tend to react in a
similar way to the changes in market conditions. Porter (1980) pointed out that one
cannot determine a priori whether all firms in the same industry will adopt the same
strategy or each firm will choose a unique strategy. Therefore, the issue of existence and
identification of meaningful strategic groups, if there are any, is left to empirical studies.
Strategy is usually manifested in several dimensions simultaneously. In the banking
industry, these dimensions include product mix, funding sources, customer focus, size,
geographical scope, etc. Grouping banks by only one predetermined variable, as usually
done in past studies (for example, Grifell and Lovell (1997), Wheelock and Wilson (2001),
and Berger et al. (1987), ignores other key components of a business strategy, which
might result in false classifications and wrong conclusions. Cluster analysis can be used
as a sorting mechanism to classify banks into various strategy groups. Cluster analysis
allows one to conduct multi-dimensional analysis by utilizing an array of relevant
information that might reflect the business strategy a bank adopts, and it requires
minimum assumptions with regard to statistical inference. One implication of cluster
analysis is that members in a given cluster tend to be similar to each other in some sense,
and members in different clusters tend to be dissimilar. In the context of our study of the


10
US banking industry, banks in the same group are assumed to be adopting similar
business strategies while banks in different groups are adopting different strategies.
To address the significance of strategic groups on issues related to estimating

production technology, one has to estimate either production or cost functions. However,
most studies of production or cost functions rely on the assumption of a single technology
in the industry, ignoring the existence of diverse strategic choices within the industry. The
aim of our study is to offer reconciliation between the strategy studies and the
production/cost function studies. By conducting a two-stage analysis, our study provides
a thorough examination of both business strategies and technologies in the US banking
industry. At the first stage, we carry out a cluster analysis on a large sample of the US
banks to identify various business strategies based on banks’ product mix and allocation
of inputs. The shifts of membership among different strategic groups over time are traced
to investigate the banks’ response to changes of market conditions and regulatory
environments. Moreover, we look into the total assets distributions across different
strategic groups to check the validation of bank size as a proxy for strategy.
At the second stage, we further explore the relationship between business strategy
and production technology. The underlying production technology, represented by a cost
function, is estimated for each strategic group, and heterogeneity of cost functions is
tested econometrically. Furthermore, returns to scale (RTS) and shifts in the underlying
technology (technical change) of each group are evaluated in order to investigate the
difference in the performance of banks under different business strategies. Specifically, a
system of translog cost function and derived share equations is used for estimation