T h e J o u r n a l o f D e v e l o p i n g A r e a s Volume 47 No. 2 Fall 2013

HOW CAN BANK REFORMS ASSUAGE

SOCIOECONOMIC ORDEALS IN EMERGING

ECONOMIES? LESSONS FOR EGYPT FROM

THE TURKISH EXPERIENCE

Monal Abdel-Baki

Durban University of Technology, South Africa

ABSTRACT

This research utilises a three-stage Stochastic Frontier Analysis/Data Envelope Analysis to

investigate the relationship between post-crisis banking reforms, bank efficiency and

macroeconomic performance from 2000 till 2010. The study draws lessons for Egypt from the

Turkish bank reforms which successfully addressed the popular economic aspirations of growth,

employment and stable prices. Whilst Turkey ensured that economic and banking reforms trickle

down to all income groups, soaring food prices and high youth unemployment exasperated living

conditions in Egypt, which helped trigger the Revolution of January 2011. The contribution of this

study is to measure bank efficiency in accomplishing popular macroeconomic aims, instead of

fulfilling the bank-centric goals of enhancing bank profitability and cost efficiency. The results

reveal that the average-sized banks and domestic private banks display highest efficiency. Public

debt, inflation and concentrated markets have unfavourable influences on bank efficiency.

JEL Classifications: E240; G210; G280

Key words: youth unemployment; inflation; growth; bank efficiency; banking regulation

Corresponding Author’s Email Address: monala@dut.ac.za; monalbak@aucegypt.edu

INTRODUCTION

Whilst most emerging economies have adequately weathered the global financial crisis

(GFC), the protracted impact on youth unemployment has proved quite detrimental.

Soaring food prices are also exerting additional pressures on the lowermost

socioeconomic groups of these nations, hence raising concerns of looming social hazards

and political instability (Boorman, 2009). In actuality, these two factors have fed into

deepening the apprehension of scholars and policymakers of the populous emerging

world, especially in the wake of the Egyptian Revolution of 2011. Since the escalating

anti-government demonstrations raised fears of contagion among other developing and

emerging nations, governments were alerted to the dire need of utilising all accessible

tools to enhance the living conditions of their people. Researchers have also started to

realise that partial and segregated solutions to these entrenched problems do not suffice.

At the twilight of the elapsed millennium, most emerging market economies

(EMEs) encountered home-grown banking crises. Bank reforms, financial innovation and

stringent regulations have been the major forces advancing the performance of the

banking sectors of these nations. Subsequently, an extensive literature evolved exploring

methods of enhancing the efficiency of the banking sector and augmenting its financial

intermediation role (Vittas, 1991). In this context, various parametric and non-parametric

38

approaches have been employed, but there has been no uniform consensus on the inputs

and outputs (Berger and Mester, 1997). While earlier research was primarily bank-centric

focusing on increasing profitability and reducing costs (Battese and Coelli, 1995;

Altunbas et al., 2001), recent studies explored the combined roles of regulation and bank

reforms in enhancing overall banking performance (Demirguc-Kunt et al., 2009).

Only lately have sparse studies started to broach the effect of bank efficiency on

segregated macroeconomic variables. Lucchetti et al. (2001) studied the role of bank

efficiency in boosting growth, while Ordine and Rose (2008) investigated its impact on

employment. However, almost no concerted research has been conducted to relate the

efficiently operating banking sectors to the overall national macroeconomic goals. This

paper expands the literature by comparing the efficacy of bank reforms conducted in

Egypt and Turkey and contrasting the underlying effects of the augmentation of bank cost

and profit efficiency levels on addressing macroeconomic problems, sustaining human

development and raising living standards in emerging economies. Secondly, the paper

attempts to draw lessons for EMEs, to enable the banking sector to fulfil the broad

aspirations of the society. Hence, while the analysis draws heavily on the Egyptian and

Turkish experiences, the implications may prove useful to other emerging economies that

are currently facing similar calamities.

Turkey and Egypt are selected as case studies since they represent two emerging

nations that introduced highly comparable versions of banking reforms and were

encountering quite similar macroeconomic challenges at the turn of the millennium.

Moreover, Egypt’s societal makeup bears significant resemblance to that of Turkey,

where both nations comprise of a predominantly young population with a secular-

religious divide. Hirschl (2004) explains that in spite of the fact that both national

characters may differ in some ways, with Turkey adhering more to the European

paradigm, the openness of the majority of the young Egyptian population to western

media and social networking in addition to the strict constitutional division between the

state and religion renders both collective identities rather similar. To ensure cohesion of

all societal factions, both governments have taken strides in harmonising Islamic

traditions with a market economy (Acar, 2009). Another similarity between Egypt and

Turkey is the selection of both nations among the “Next-11” EMEs that are apt to catch

up with the rapid and robust macroeconomic growth of the so-called “newly

industrialized nations” (Wilson and Stupnytska, 2007).

Yet, while Egypt has orchestrated economic reform that liberalized the economy

during the last two decades, the poorest members of its population failed to reap the

benefits of economic growth. As a result, the indefatigably Egyptian youth uprising took

policymakers and economic analysts by surprise. But the monumental political gains,

national pride and self-empowerment of the long-repressed Egyptians were earned at the

cost of interrupting the formerly rigorous economic growth. Tourism and construction

industries have been pounded, national savings have leaked out of the financial sector,

the nationwide labour strikes that voiced long-held grievances paralysed production, and

private investment substantially declined. As much as this might lead to an economic

meltdown in the short-term, the newly acquired democracy and the redesign of economic

policies towards egalitarianism will expectantly set the stage for a stable investment and

socio-political environment in the long-run. But the road to exhuming the

accomplishments realized during the previous decade and to overturn the monotonic

39

pattern of downward sovereign credit revisions is fraught with difficulties. The banking

sector is one of the prime catalysts that could help expedite the recovery process.

Accordingly, the Central Bank of Egypt (CBE) needs to attune bank activities towards

the recently defined national goals of income redistribution and generating jobs for the

youth, in addition to the dire need to resume economic growth and to manage inflation.

The results of the paper will confidently shed some new insights for emerging economies

about the need to design bank reforms that explicitly address their inherent societal and

economic predicaments instead of blindly copying bank reform paradigms that were

tailor-made to suit advanced economies.

The rest of the paper is designed as follows. The second section provides an

analysis of the root causes of the socioeconomic problems shouldered by both Egypt and

Turkey. The third section outlines the DEA/SFA econometric model. The fourth section

reports the results and the last section concludes with policy implications.

THE ANTECEDENTS OF SOCIOECONOMIC PROBLEMS IN EMES

Labour markets in populous emerging economies are under immense pressures to absorb

the scores of the unemployed, the rising numbers of the youthful new entrants and the

increasing numbers of women seeking work. In addition, EMEs that are over dependent

on imported food like Egypt, are exposed to the risk of skyrocketing inflation, which is

asserted to be among the prime factors that have triggered the recent popular uprising

(Krugman, 2011). In addition to shouldering the inherent problems of population

explosion and rapid urbanization, structural imbalances have posed more challenges to

EMEs and deprived the very poor from sharing the fruits of macroeconomic growth.

Many of these structural weaknesses date back to the implementation of

disparaging economic policies, many of which were imposed by intra-governmental

donor institutions. Bordering on many other developing nations, both Turkey and Egypt

adopted the Structural Adjustment Programs (SAPs) in the eighties and nineties in order

to access the conditional loans of the World Bank and the International Monetary Fund

(IMF). The SAPs might have provided short-term solutions to the monumental

outstanding public and national debts, but this was achieved at the expense of the poor

(Akyurek, 2006). Aside from the venomous post-privatisation unemployment, another

serious drawback of the one-size-fit-all SAPs was the premature liberalization of

financial markets prior to the introduction of adequate banking supervision (Freedman,

1989). More maliciously, the Bretton Woods programs focused on the modernisation of

the banking sector, whilst ignoring its role in enhancing macroeconomic performance

(Goldstein and Turner, 1996).

Bank Regulatory Reforms in the Wake of Home-grown Financial Crises

The premature liberalisation of the financial sector lead to the birth of fragile banking

sectors, and exposed the Turkish and Egyptian economies to home-grown financial crises

and severe contagion from the series of financial calamities that infested emerging

economies during the nineties. The consequential banking crises caused capital outflows

of $10.5 billion from the Turkish banking sector (Conkar et al., 2009) and $40 billion

from its Egyptian counterpart (Mohieldin and Nasr, 2003). Moreover, the weakly

40

supervised financial institutions resulted in huge amounts of non-performing loans

(NPLs) due to corruption and the covert subsidization of the public sector by state-owned

banks (Sayilgan and Yildirim, 2009).

More deplorably, the delay in introducing regulatory reforms culminated in the

eruption of the 2000/2001 Turkish banking and foreign exchange crises. The subsequent

liquidity crunches lead to the failure of many undercapitalized banks (Ozatay and Sak,

2003). The costs to the Turkish economy exceeded US$50 billion due to the bankruptcy

of thousands of businesses, losses of hundreds of thousands of jobs and the general

economic meltdown. Further austerity measures were enacted, which enraged the low-

paid workers, leading to the one million person strike of 2001. Ten years later, Egypt

found itself encountering a largely analogous situation, shouldering a high public debt, an

unmanageable fiscal budget deficit and plummeting national savings. Hence a

comparison is very much in order. In reaction, the Central Bank of the Republic of

Turkey (CBRT) implemented a twofold market-oriented strategy namely Transition to a

Strong Economy and Banking Sector Restructuring and Rehabilitation Program. The

combined effects of the enhanced regulatory framework and the restructured banks

helped Turkish banks to adopt cost-effective techniques and to restructure their portfolios

away from government securities (Sayilgan and Yildirim, 2007). Since a more egalitarian

income distribution was among the prime objectives of the CBRT, it gave banks access to

subsidised loans in order to channel them to low income borrowers (IMF, 2005).

Similarly, the banking crisis and the huge outstanding debts urged the Central

Bank of Egypt to embark on its Banking Reform Plan (BRP) in 2004, which aimed at

enforcing regulatory capital requirements; restructuring and privatizing state-owned

banks; addressing the NPL problem; and enhancing banking regulation. Table 1

elucidates that the reform policies culminated in bank consolidation, where the number of

banks declined by 37% for both nations since the dawn of the new millennium. One

worthy observation is the apparent decline in the number of private and foreign banks,

which were forced to fulfil regulatory capital requirements. However, unlike the

introduction of outright deposit insurance in Turkey, the CBE merely provides implicit

insurance to its depositors.

TABLE 1. STRUCTURE OF BANKING SECTORS IN EGYPT AND TURKEY

# of Banks

(December 2000)

# of Banks

(December 2004)

# of Banks

(December 2010)

Egypt Turkey Egypt Turkey Egypt Turkey

State-owned Banks 7 7 7 6 6 6

Private Banks 35 43 33 26 26 25

Foreign Banks 20 18 17 15 7 17

TOTAL 62 79 57 48 39 49

In addition to these banks, the Turkish Saving Deposit Insurance Fund (SDIF) took over and

restructured 11 insolvent banks.

Sources: Central Bank of Egypt. Economic Review, various issues.

The Banks Association of Turkey. Statistical Report, various issues.

41

Outcome of Reforms: Higher Levels of Youth Unemployment and Inflation

Notwithstanding the scope of the aforementioned bank reforms, NPLs accounted for

14.7% of total domestic credit in Egypt (IMF, 2010) compared to only 5.2% in Turkey

(BAT, 2010) as at December 2010. More deplorably, Egyptian savings slid from 16.3%

of GDP in 2007 to the execrable level of 12% in 2010, and the loan-deposit ratio declined

from 54.4% to 51% for the same period (CBE, 2011). Whilst the savings rate has also

decreased in Turkey from 16.8% in 2007 to 12.4% in 2010, the Turkish loan-deposit ratio

stands at 76% for the same period (BAT, 2010).

Among the prime reasons behind the decline in the ability to mobilize savings

are the isolation of the Egyptian and Turkish central banks from the national economic

planning process and their overdependence on monetary experts who may lack adequate

familiarity with the internal social problems (Franck and Krausza, 2008). It might suit the

affluent industrial nations to limit the role of their central banks to inflation targeting, but

countries suffering from low purchasing power and social unrest need to engage their

central banks in alleviating the socioeconomic ordeal of their people (Thronton, 2011).

FIGURE 1. INFLATION AND UNEMPLOYMENT IN EGYPT AND TURKEY

Sources: Turkish Statistical Institute (TURKSTAT) Database

Central Agency for Public Mobilisation and Statistics (CAPMAS) Database

It is apparent from Figure 1 that the comprehensive restructuring and

stabilisation policies adopted by Turkey since the 2000-01 crisis have commendably

cooled down the inflationary pressures. Undoubtedly, lowering the intermediation costs

42

of Turkish banks has been of substantial help in this respect (Ersel and Özatay, 2008).

The Turkish government has successfully bridged socio-economic disparities through

enhancing public investment in education, health, social protection and human

development. The ultimate result was a relatively acceptable level of youth

unemployment, yet the problem started to resurface again after the eruption of the GFC.

Given that both nations have a predominantly young population of a median age of 23.9

years in Egypt and 28.3 years in Turkey (UNDP, 2010) youth employment has become

the prime goal of fiscal and monetary agents. Moreover, the Gini Index has deteriorated

for both nations, and currently stands at 0.31 for Egypt and 0.38 for Turkey (UNDP,

2010). To address the macroeconomic challenges facing EMEs, they have to rely on a

permutation of fiscal and monetary policies, and a congregation of restructuring schemes.

THE EMPIRICAL MODEL

Literature Review

It is generally alleged that central bank tools in many emerging economies require more

time to gain efficiency and credibility (Freedman, 1989), which might increase the

overall costs to the economy either in terms of loss in employment and output or in the

form of price hikes (Bernanke et al., 1999; Cecchetti and Ehrmann, 1999; Durhan, 2001).

Once trustworthiness is built, supply and demand shocks exert less inflationary pressures

(Laxton and N’Diaye, 2002) and improve the trade-off faced by the monetary authority

(Ce´spedes and Soto, 2005). The role of the banking sector and monetary policy in

managing imported inflation is generally overlooked by researchers beyond devaluing the

domestic currency (Yeldan and Ertugrul, 2003), yet research efforts have been

undertaken to develop methods of enhancing bank efficiency and reducing intermediation

costs in order to manage inflation (Andrade et al., 2001). In a study covering the banking

sector in the Gulf Cooperation Countries, Srairi (2010) finds that banks in oil-rich Arab

nations have high profit efficiency but low cost efficiency, which contributes to

inflationary pressures in these emerging economies. In such cases it becomes absolutely

imperative for regulatory agents to intervene to help boost cost efficiency of banks

(Paiouras et al., 2009).

However, there has been no consensus as to whether societal gains have been

reaped in response to an enhanced financial and monetary system (DeLong and

DeYoung, 2007). Undoubtedly, banking efficiency increases with consolidation,

recapitalisation and regulation, hence reducing costs, taming inflation and generating

jobs. In addition to capitalizing on economies of scale and scope, a consolidated banking

sector enhances its geographical reach, expands the range of its products and attracts

more deposits (Focarelli et al., 2002). Larger banks can significantly improve returns by

diversifying activities into a wide range of financial and non-financial products (Yildirim

and Philippatos, 2007) as well as consolidate risks (Group of Ten, 2001). Even if smaller

banks exert all efforts to enhance their efficiency and recapitalisation, larger banks are

able to access cheaper deposits and attract customers of higher creditworthiness

(Demirguc-Kunt et al., 2008). As for their role in creating jobs, larger banks’ easy access

to funds obliges them to seek alternative outlets for lending, including small and medium

enterprises (SMEs) (Berger et al., 1998).

43

On the other hand, there is an opposing viewpoint asserting that banking reforms

and recapitalization are ineffective if lending to small businesses is elbowed out by larger

borrowers (Koutsomanoli-Filippaki et al., 2009). Moreover, excessive diversification of

bank lending and investment must be avoided since it might increase systematic market

risk (Stiroh and Rumble, 2006). Since the eruption of the global meltdown, researchers

accentuate that banking reforms should no longer solely focus on enhancing bank safety,

profitability and efficiency, but are required to provide lower costs for borrowers, more

predictable returns for investors and a highly efficient allocation of resources (Brissimis

et al., 2008). In the same vein, post-GFC research reveals that it is imperative to reduce

systemic risks and to gear corporate governance (Black et al., 2003) and regulation (Beck

et al., 2006; Institute of International Finance, 2010) towards attaining national

macroeconomic goals (Pasiouras, 2008).

Banking sectors of emerging economies were hailed for their immunity against

contagion from severe illiquidity and toxic assets amidst the GFC (Boorman, 2009).

Studies applying the stochastic frontier approach (SFA) and the data envelopment

approach (DEA) to the Egyptian and Turkish cases conclude that this is mainly attributed

to the previously enacted banking reforms in these nations (El Shazly, 2009; Aysan and

Ceyhan, 2008). Using the SFA model Chan and Abd Karim (2010) show that the

protection from contagion hinges on the volume of credit extended to domestic private

producers and the level of foreign ownership in the banking sector. As much as this may

be true, the relatively shallow financial sectors of Egypt and Turkey, which prohibit

dealings in sophisticated financial instruments, have isolated them from the toxicity of

the global turbulence (Loser, 2009).

This explains why measuring efficiency of the Turkish and Egyptian banking

sectors is being linked to achieving national macroeconomic objectives (Ihsan and Darrat,

2009). Ozkan-Gunay and Tektas (2006) utilise the DEA method to examine how bank

efficiency in Turkey can contribute to enhancing economic growth. Focusing on the case

of the Middle East and North Africa (MENA) Region, Aysan et al. (2008) emphasise that

banking efficiency needs to be supported by an all-inclusive amalgamation of sound

economic policies, supervisory controls, political stability and internal governance. But

the main contribution of this study is that, unlike previous research, bank efficiency is

measured in accordance with its ability to fulfil popular macroeconomic goals.

The DEA/SFA Methodology and Data Collection

This study uses a three-stage integrated DEA-SFA approach, à la Avkiran and Rowlands

(2008), to compare the effect of a number of bank inputs on macroeconomic outputs in

Turkey and Egypt from 2001 to 2010. In response to the 2001 banking crisis, the Central

Bank of the Republic of Turkey provided emergency responses, granting stabilising

funding and bailout funds to depositors and creditors.

The main advantage of the linear programming DEA approach is that it works

on the principle of capturing the interaction amongst multiple inputs and outputs. Also, it

is an efficient frontier technique that relies on relative evaluation by comparing the

position of the inefficient decision making unit (DMU), or banking unit, to the frontier.

As such, the management can select the efficient or best-practice DMU to be emulated.

Both the BCC model, i.e. Banker, Charnes and Cooper (1984), and the CCR model i.e.

44

Charnes, Cooper and Rhodes (1978) do not generate units-invariant estimates of non-

radial inefficiency. The DEA method stipulates that there is no noise in constructing the

frontier indicating that any error in the data of a DMU might be reflected as a change in

its measured efficiency. Thus, for a consistent interpretation of DEA estimates, the non-

oriented slacks-based measure (SBM) of efficiency is employed (Cooper et al., 2006).

Then, a second stage SFA technique is used to decompose the slacks into other effects

that are beyond the control of the bank management. This is mainly due to the fact that

SFA takes into account the exogenous events in the residue or the distance from the

efficiency frontier, hence unravelling statistic noise (Berger and Mester, 1997).

Another rationale behind using both approaches is the randomness of internal

macroeconomic conditions and external shocks. Hence, the intrinsic difficulty of

predicting depositors’ and borrowers’ demand renders customer behaviour unpredictable

and accordingly the input-output relationship becomes stochastic. This was especially

evident during the massive wave of capital flight and deposit run witnessed by both

nations in the wake of banking crises of the nineties and the recent Egyptian socio-

political turmoil of January 2011. Moreover, various studies show bias in some of the

results of the DEA methodology (Hughes and Yaisawarng, 2004) and imprecision of the

SFA technique (Cooper and Tone, 1997). For this reason several researchers are

increasingly employing comparative analyses of parametric and non-parametric

approaches to ensure accuracy of results (Resti, 1997; Kohers et al., 2000; Chen, 2002).

One of the latest studies applying both the DEA and SFA methodologies to a number of

post-crisis Asian banking sectors concludes that the level of bank efficiency is highly

affected by country-specific conditions, namely interest rates, competition levels and the

degree of economic development (Thoraneenitiyan and Avkiran, 2009).

The data for Egyptian banks is collected from the individual financial statements

of the 39 Egyptian banks and the CBE database. As for Turkey, the data is accessed from

the databases of the Banks Association of Turkey (BAT) and the Central Bank of the

Republic of Turkey. The study covers the entire 87 banks operating in Egypt and Turkey

and yields 4187 observations. Macroeconomic data for both nations is collected from the

database of the World Bank and the International Financial Statistics published by IMF.

Values are converted to US dollars at market exchange rates to ensure comparability of

cross-country data. Figures are adjusted for inflation, with 2000 being the base year.

Input and Output Variables

The three-stage model starts with the DEA to measure bank efficiency, and then uses

stochastic frontier analysis to exclude the effects of external macroeconomic

environmental factors and statistical noise. Banks are assumed to minimize inputs. The

fractional program for the non-oriented variable returns to scale SBM is shown in

Equation 1, where ρ is the scalar that captures radial and non-radial slacks.

01

01

1 (1/ )

min

1 (1/ )

ni

i i

mj

j j

sn

x

sm

y

(1)

45

0x X s (2) 0y Y s (3)

where, x0 ≥ 0 is the vector of inputs of the DMU, and y0 ≥ 0 is the vector of the outputs.

X λ and Y λ are the levels of input usage and output production.

s- and s+ are the input and output slacks. Imposing the following constraint in equation (3) introduces variable returns to

scale. A bank is rated as efficient if the optimal value for the objective function equals

one, i.e. if the efficient DMU or bank has zero input and output slacks.

1

1n

k

k

(4)

where, λ ≥ 0

In this first-stage productivity model, four inputs and four outputs are specified

under the intermediation approach. Inputs are chosen to assess the ability of the banking

sector to fulfil its main role of mobilizing savings and channelling them to investors at

the lowest possible price. To this avail, the first three inputs measure the costs of

borrowed funds (BFE), physical capital expenses (PCE) and the costs of human capital

(HCE). Another important factor that indirectly helps with reducing risks is the fulfilment

of the 8% regulatory capital adequacy (CA) requirement as per Basel II (BIS, 2010).

To gauge the ability of the banking sector to achieve social stability, a few

proxies are used to measure how efficiently banks fulfil the targets of job creation, GDP

growth and managing inflation. The following four outputs are selected: the loan-deposit

ratio (L/D), the proportion of funds lent to small and medium enterprises (SME), the

proportion of funds lent to growth enhancing sectors (G) and the spread between

borrowing and lending rates (B/L). The loan/deposit ratio is important since the Egyptian

banking sector has recorded a notoriously low rate that reached 50.2% on December 2010

(CBE, 2010). Also, whereas the reform plan of the CBRT gave instructions and

incentives to banks to direct their funds towards job-generating SMEs and growth

enhancing sectors, namely agriculture, construction and manufacturing, the CBE

instigated such actions as late as 2008 (Hassan and Sassanpour, 2008). An equally

important output is the cost of lending, which impacts the consumer price index.

External macroeconomic environmental factors have a significant impact on the

banking industry and affect the sample homogeneity assumption (Dietsch and Lozano-

Vivas, 2000). Thus, the second stage of the model decomposes the input and output

slacks or inefficiencies that are obtained from the first stage into environmental impacts,

statistical noise, and managerial inefficiency. Examples of these environmental impacts

are the inadvertent measurement errors, labour strikes, closures due to socio-political

unrest, equipment failure, external shocks and deposit runs, which are compliant with the

episodes of social unrest that infested both nations during their financial crises. The

factors that contribute to managerial inefficiency are inconformity with regulatory capital

and other central bank requirements, inadequate staffing, and insufficient inputs.

46

TABLE 2. ENVIRONMENTAL FACTORS (z)

Variable Description

Inte

rna

l fa

cto

rs

Macroeconomic

factors (ME)

Public debt as a percentage of GDP (PD)

Growth of GDP per capita (GDP)

Inflationary shocks (CPI)

Banking

Industry

Variables (BI)

Bank concentration using Herfindahl-Hirschman Index (HHI)

Volume of NPL/Total loan portfolio (NPL/TL)

Regulations (R)

Costs of compliance with 3 pillars of Basel II capital (RC)

Costs & benefits of corporate governance of banks(CG)

External Global

Variables (BS)

GDP change due to external the global shocks (GS)

Imported inflationary pressures (II) HHI is the sum of the squares of banking firms within each banking industry. It ranges from 0,

indicating low market power, to 1, indicating more concentration. Battese and Coelli (1995) assert that inclusion of some variables in stochastic frontier supports

the independence assumption when equations are estimated simultaneously.

Defining the Environmental Factors

In the second stage, the SFA method is used to minimize the chances of distorting the

validity of the previous efficiency analysis. Since even the healthiest banking unit could

be harshly affected by adverse conditions, the overall environment of the banking

industry has to be examined. For example, lower GDP per capita will surely translate into

lower savings and less employment opportunities (de Mendonca, 2009). Input and output

slacks from the first stage across the ten-year period are first pooled and then separately

regressed on the environmental exogenous variables (z). There is little consensus in the

literature on the environmental variables that impact bank efficiency. Table 2 divides

environmental features into country-specific macroeconomic, regulatory, banking and

global external factors.

The legitimacy of selecting macroeconomic factors is that as of 2009 the

outstanding public debt accounted for 72.1% of GDP in Egypt and 46.3% in Turkey, and

the fiscal stimulus packages are likely to prompt future public borrowing (Boorman,

2009). Moreover, amidst the current slowdown in GDP and the looming inflationary

risks, bank efficiency is apt to be adversely affected (Kasman and Yildirim, 2006). Also,

if not properly addressed, bad debts are likely to have detrimental effects on the

economy. But higher concentration could either be cost effective or lead to diseconomies

of scale (Yildirim and Philippatos, 2007). The third group of variables is inherent in

global shocks. Highly relevant to Egypt is imported inflation, which was evident during

the severity of the Global Food Crisis of 2006/07. Finally, the regulatory environment,

and the enhanced corporate governance of banks help in reducing fraudulent transactions

and enhancing the overall functioning of banks (Beck et al., 2006).

The above specifications are intended to separate and highlight the role of

banking units in efficiently attaining the macroeconomic goals of the nation after

segregating the four aspects of environmental influences.

( ; )ip p i ips f z (5)

where, βi is the parameter vector for the feasible slack frontier

47

ip ip i pv u

( ; )jq q j jqs f z (6)

where, jq jq jqv u

The composite error terms ip and jq comprise a random stochastic term vip

representing statistical noise, and uip denoting managerial inefficiency. After obtaining

the parameters from the SFA regressions, the observed inputs (x) are adjusted for

environment and statistical noise. Therefore, banks enjoying a favourable environment

and/or statistical noise will find their efficiency scores decreased as inputs are adjusted

upwards. Conversely, banks operating under less attractive environments and/or

statistical noise have their efficiency scores increased as outputs are adjusted upwards.

Equation 7 shows how inputs are adjusted for environment and statistical noise (xa).

max maxair iri iir ir r rx x z z v v

(7)

where, a

irx is the adjusted value of i th bank input in jth bank unit

irx is the observed value of i th bank input in jth bank unit

irz

is the i th input slack in rth unit due to environmental factors

irv

is the i th input slack in rth unit due to statistical noise

Equations 8 through 10 display the adjustments attributable to the operating

environment and statistical noise, which is best done by using ratios comprising of

adjustment factors. The first adjustment variable (μ) represents the percent upward

adjustment of the observed input attributable to the operating environment, and the

second (η) represents the percent upward adjustment of the observed input attributable to

the statistical noise.

1a

ir x xx (8)

max

1

max

ir

irx

irir

zz

xz

(9)

max

1

max

ir

ir

x

irir

vv

xv

(10)

The outputs of the units suffering from unfavourable operating environments

and statistical noise are adjusted upwards as shown in equations 11 through 14. This is

done by comparing the slacks of these units to the ones generated by the best performers.

48

While (μy) captures the percent upward adjustment of the observed output due to

environmental influence, (ηy) represents the percent upward adjustment attributed to

statistical noise.

min minasr srs ssr sr r ry y z z v v

(11)

1a

sr y yy (12)

min

1sr

sry

srsr

zz

y z

(13)

min1

srsry

sr sr

vv

y v

(14)

It is essential to distinguish between input-sourced statistical noise (v) from the

managerial inefficiency (u) in the composite error term ( ) of the SFA regressions.

When (v) is estimated for each unit, the observed input usage can be adjusted à la

Jondrow et al. (1982) to separate the composed error term into its components. Then, the

input-sourced statistical noise, which is conditional on the composed error structure, is

residually estimated by subtracting from the first stage input slack the estimate of that

input’s slack for a given unit as follows.

| +E u v u

depending on

, 2

u

and 2

v

| + | +iir ir ir r ir ir irE v v u s z E u v u

(15)

The same method is reused by estimating statistical noise in output generation as follows.

| + | +ssr sr sr r sr sr srE v v u s z E u v u

(16)

The third stage repeats the non-oriented SBM data envelopment analysis of bank

efficiency that was performed in the first stage after using the adjusted input and output

data obtained from the second stage. Since the operating environment and statistical noise

influences have been removed, banking units will neither be blamed for external

environmental conditions, nor unduly rewarded for operating in a favourable

environment to which they did not contribute.

Interpretation of the Results

Results of the First Stage DEA

The results of the first stage DEA are estimated and presented in Table 3 against a

common efficient frontier referred to as an “intertemporal production set”. This method is

used since bank reforms in both Egypt and Turkey were enacted at virtually the same

period and the level of technology and banking knowhow was almost analogous in both

49

nations. Moreover, comparing bank efficiency over a ten-year period necessitates

measuring efficiency relative to a common frontier (Tulkens and Eeckaut, 1995).

TABLE 3. FIRST STAGE AGGREGATE WEIGHTED AVERAGE

EFFICIENCY SCORES BY BANK CATEGORY

Mean Median Min Max CV* n

Public commercial banks 0.507 0. 517 0.337 0.891 0.192 6

Public specialized banks 0.503 0.516 0.311 0.8 0.189 6

Private domestic banks 0.528 0.598 0.634 0.969 0.221 51

Foreign banks 0.511 0.585 0.681 0.791 0.348 24

Total 0.518 0. 534 0.494 0.714 0.292 87

* Coefficient of variation

Source: Author’s calculations

FIGURE 2. BOX-PLOT OF EFFICIENCY SCORES BY BANK CATEGORY

Source: Author’s calculations of median, 25th percentile, 75th percentile and lower and upper

adjacent values

The results displayed by Table 3 and Figure 2 suggest low mean efficiencies and

evident variability. The best performers are private and foreign banks. The lowest

average cost efficiency is scored by public specialized banks, which also display the

highest variability in efficiency scores. Inter-quartile ranges are confined to the central

50% of the sample in each category, bounded by the 25th and 75th percentile. Public banks

show wide inter-quartile ranges and longer whiskers.

50

Results of the Second Stage SFA

The possible explanation of the low efficiency levels is that input and output

inefficiencies are simultaneously captured. More importantly, at this initial stage,

efficiency estimates might have been influenced by the aforementioned environmental

factors and statistical noise. To rule out environmental and random error effects, input

and output slacks obtained from the previous stage are pooled, and then separately

regressed on input and output slacks to allow for variation. Most of the results in Table 4

are in line with the existing literature and the overall verdict is that the operating

environment exerts a statistically significant influence on bank inefficiency. Most of the

observations are significant in the regressions; most of the coefficients are statistically

significant at 5% or less, which confirms that differences in economic conditions are

beyond the control of the bank management influence.

Of great interest are the coefficients of macroeconomic variables. There is a

direct relationship between public debt (PD) and most bank input and output slacks. In

other words, the high level of public debt is in no way intuitive of a good management of

resources to produce outputs. On the other hand, the fact that the coefficients for GDP

have negative signs and are statistically significant confirms that a consistently high GDP

growth is apt to reduce incidences of bank inefficiencies (Brissimis et al., 2008). While a

positive relationship exists between the CPI and bank inefficiencies, it is counter-intuitive

and is found to be statistically insignificant for fulfilling the goals of lending to SMEs

and growth-enhancing sectors. This might be attributed to the fact that state-owned banks

tend to take up this role during episodes of banking crises.

As for the general environment in the banking industry, the results reveal that

the highly concentrated banking markets incur additional input and output slacks. The

literature confirms this finding, reflecting the rise of inefficiency in the case of markets

that are dominated by a small number of large banks (Bonin et al., 2005). Also, the result

that more NPLs are associated with inefficiency confirms that outstanding bad debts

cannot be disregarded in efficiency assessment. The result is insignificant for loans

granted to growth enhancing sectors. Conversely, global shocks have a marked effect on

efficiency except for SMEs. This may be explained by the fact that some incentives are

extended to lend to these entities during crises. Another important observation is that

regulatory bank capital is positively associated with bank inefficiency. A significantly

negative coefficient for a dummy variable for CG reveals that an internally regulated

bank is likely to have a more disciplined environment and may enjoy improved

efficiency. Table 4 shows that the (γ) estimates, as explained in equation 17, range from

0.39 to 0.88 and are statistically significant.

2

2 2

u

v u

(17)

51

TABLE 4. SECOND STAGE SFA REGRESSIONS

Input Slacks Output Slacks

BCE PCE HCE CA L/D SME G B/L

Constant -301.4 -283.11 -45.81 -47.5 -55.26 12.55 23.76 -120.11

PD(+) 29.91* 33.11** 181.10 1.21** 80.31** 45.38* 88.81* -7.78

GDP(-) 66.31* 872.22* 177.98* 78.91** 561.11* 381.90 890.1 12.12**

CPI(+) 87.46* 12.41** 852.21* 11.10** 66.12** -12.66 -41.56 191.55

HHI (+) 120.13 311.67* 72.14** 418.11* 581.11* -21.51 331.18 278.09*

NPL/TL(+) 33.12 69.78* 113.81 11.12** 9.31 24.12 -19.99 389.63*

GS(+) 22.12* 12.12 1.33* -22.51 171.31* 921.56 421.81 311.51*

II(+) 33.67* 916.21* 312.16* 39.91** 71.51* -9.13* 22.51* 91.51**

RC(-) -12.81 -11.81 -91.15 91.89** -51.15* -19.67 -14.67 -67.71*

CG(-) -69.91 -31.13* -31.11* -871.11 -91.11* -1.21 -97.45 -66.89*

γ 0.391* 0.5514* 0.782** 0.4081 0.551* 0.394* 0.662* 0.881**

Log

likelihood

-988.1 -834.41 -916.56 -788.45 -989.11 -895.5 -945.3 -788.67

LR test of

one-sided

error

71.11* 118.71* 134.71* 12.21** 18.91** 1.33** 67.83* 181.67*

Mean slacks 14.71 181.11 13.43 12.22 41.11 1.33 169.33 39.99

(γ) measures the variance in disturbance due to bank inefficiency

* and ** indicate 10% and 5% one-tailed significance levels

Results of Third Stage SBM on Adjusted Data

The third stage is a repetition of the non-oriented SBM analysis of the first stage, by

using adjusted input and output data obtained from the second stage. The null hypothesis

stipulating that the SBM scores from the first and third stages are independently drawn

from the same population at 1% significance level is rejected after performing the

parametric t-test and F-test and the non-parametric Wilcoxon signed-rank, Kruskal-

Wallis and Kolmogorov-Smirnov tests. Figure 3 captures comparisons of the third stage

SBM mean efficiency scores after introducing various adjustments. In the first step the

impact of the statistical noise is removed and SBM scores are re-calculated. On average,

bank efficiency shows some improvement, which indicates that the statistical noise has a

negative impact on bank efficiency estimates. When removing the effect of global

shocks, bank efficiency further improves, yet, its effect is not as substantial as the

previous impact of internal conditions. The literature explains that this is due to the fact

that in most post-crisis bank reforms, the reformed banking sector imposes immense

restrictions on banking operations and prohibits trading on many sophisticated and multi-

layered financial instruments, which keeps them relatively sheltered from global financial

markets (BIS, 2010). These results support the private monitoring hypothesis, which

states that the disclosure of accurate and timely information to the public allows private

agents to overcome information and transactions costs and helps monitor banks more

effectively (Pasiouras, 2008). However, Demirguc-Kunt et al. (2009) warn that excessive

restrictions on bank activities impede some banking operations, hence increasing cost

inefficiency. Bank efficiency scores rise even more when the data is adjusted for all three

features of the internal operating environmental conditions. After removing all impacts in

the third stage, it is observed that the bank mean efficiency scores are much higher than

52

the first stage. Thus, the largest impact on bank efficiency is attributed to internal

environmental conditions.

FIGURE 3. COMPARISON OF AGGREGATE MEAN EFFICIENCY SCORES

Robustness and Sensitivity Analysis

Three procedures are followed to test the robustness of the results. First, the above

process is repeated separately for each of Egypt and Turkey. Then, the exercise is

repeated after dividing the banking sample according to ownership. Thirdly, the purged

data is applied after dividing banks according to size.

FIGURE 4. COMPARISON OF AGGREGATE MEAN EFFICIENCY SCORES

OF TURKEY AND EGYPT

53

Both the Turkish and Egyptian banking sectors show low efficiency during the

post-crisis period. The results are consistent across each country’s sample and the

country-specific factors retain their significance. Even though the results displayed by

Figure 4 show some difference in terms of average efficiency, the magnitude of changes

by the country-specific factors are still very much in line with those presented in the

initial findings. After segregating the results for each country, it becomes evident that

Turkish banks adequately serve the macroeconomic objectives. Egyptian banks showed a

slight improvement in the wake of the GFC, which might be due to the fact that the CBE

started encouraging lending to SMEs by exempting these funds from the legal reserve

requirements (CBE, 2010).

FIGURE 5. EFFICIENCY SCORES BY BANK CATEGORY

54

Figure 5 uses data that was fully purged in the third stage, where the subsamples

are re-casted by type of ownership. Bank efficiency showed considerable improvement

after reforms were enacted for both countries, with more pronounced effects in Turkey.

On the whole, the highest scores were achieved by private and foreign banks, which

scored above 85%. Public banks lagged behind, where the lowest efficiency was scored

by agricultural specialised banks and the highest by industrial specialised banks. The

superiority of both types of private banks is attributable to the fact that state-owned banks

are inclined to loaning funds to state-owned enterprises (Thornton, 2011). The last check

of robustness is comparing banks by size. Table 5 shows that the highest scores are

achieved by medium-sized banks and the lower efficiency is recorded by large banks,

which indicates that bank size is indeed a determining factor of bank efficiency.

TABLE 5. AVERAGE EFFICIENCY SCORES BY BANK SIZE*

Mean Median Min Max Var n

Small banks 0.713 0.693 0.698 0. 885 <0.001 28

Medium banks 0.933 0.893 0.745 0.973 0.015 44

Large banks 0.804 0.808 0.563 0.878 0.018 15

All banks 0.912 0.831 0.637 0.923 0.012 87

Bank size is measured by assets and equity. Small banks have less than half the mean

assets and equity and large banks possess more than 30% of the mean.

Source: Author’s calculations

CONCLUSIONS AND POLICY IMPLICATIONS

This research uses the DEA/SFA three-stage methodology to estimate the efficiency of

Turkish and Egyptian banks in addressing the problems of inflation, job creation and

economic growth during 2000-2010. The period captures the ante-crisis and post-crisis

reform periods. The main contribution of this study is that bank efficiency is measured in

accordance with its ability to fulfil macroeconomic national goals and not in regard to the

bank-centric goals of enhancing profitability or cost effectiveness. The research is vital

because in spite of the evident improvement in the overall macroeconomic performance

and banking sector efficiency in emerging market economies, very few of these nations

have endeavoured to gear banking reforms towards enhancing the prosperity of the

lowermost income groups (Ihsan and Darrat, 2009). The Egyptian Revolution alerted

policymakers in many EMEs to the urgency of utilising all available resources to address

the socioeconomic calamities of their people. The study focuses on drawing lessons for

Egypt from the more successful Turkish experience in this regard.

In general, bank mean efficiency scores improve over time as restructuring

unfolds. The results of the third stage DEA-SBM show that the mean efficiency scores

slightly improve and exhibit faintly less dispersion once the statistical noise is separated.

The fact that the most sweeping effects are realized once the impact of environmental

factors is separated confirms that policymakers need to redirect their reforms beyond

bank restructuring. The results also reveal that the effect of internal corporate governance

on bank efficiency is relatively low compared to the influences of central bank regulation.

Hence, stronger supervision is more urgent at this point in time in comparison to internal

governance, which Basel III will not impose till January 2019.

55

On the macroeconomic front, Turkish reforms show higher efficacy since the

CBRT urges banks to direct loans towards job-generating and growth-enhancing sectors.

Public debt, high inflation rates and concentrated markets impose adverse influences on

bank efficiency. Imported inflation has a far more pronounced impact in Egypt, which

confirms that there is ample scope for the input of the banking sector in this regard. This

begs the need for the CBE to follow the steps of its Turkish counterpart in specifying an

explicit nominal anchor for inflation targeting.

When the study is repeated after separating banks according to ownership,

private domestic banks score the highest average efficiency followed by foreign banks,

while public banks score the lowest. As for size, average-sized banks display highest

efficiency, with the smallest ones being the least efficient. Thus, the commonsensical

policy implication is to encourage the expansion of domestic private banks, whilst

discouraging mergers and acquisitions beyond the mean-sized banks. It might also be

advisable for state-owned banks to consider going into joint ownership with private banks

as a means of enhancing their efficiency (Acar, 2009).

Finally, a study extended to a larger sample of emerging economies can be a

valuable extension of the current research. A qualitative exploration of the possible

reasons behind the low effect of corporate governance on bank efficiency deserves more

attention and would surely prove to be an invaluable addition to the existing literature.

Moreover, the analysis could be extended to different aspects of environmental

conditions in order to determine the catalysts needed for banking sector reforms to close

the efficiency gap between various banking categories.

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