A New Data Set On Competition In National Banking Markets

• DOI: http://doi.org/10.1111/fmii.12030
• Published date: 01 May 2015
• Date: 01 May 2015

A New Data Set On Competition In National Banking

Markets

BYSOFRONIS CLERIDES,MANTHOS D. DELIS,AND SOTIRIOS KOKAS

We estimate the degree of competition in the banking sectors of 148 countries over the

period 1997–2010 using three methods: the Lerner index, the adjusted Lerner index, and

the profit elasticity. Marginal cost estimates required for all methods are obtained using a

flexible semi-parametric methodology. All three indices show that competitiveconditions

in banking deteriorated during the period 1997–2006, improveduntil 2008, and deteriorated

again thereafter.Levels of competition differ across regions and income groups, but there is

gradual convergence over time. Banking system is less competitivein sub-Saharan Africa

and low income countries and more competitive in Europe and Central and South Asia and

OECD countries.

Keywords: Bank market power, competition, world sample.

JEL Classification G2, D40.

I. INTRODUCTION

The issue of banking sector competition has attracted much interest in recent

years, not least because of the financial crisis. Alongside the standard objective

of achieving effective market competition, the issue has additional significance in

banking because of the sector’s crucial role in the allocation of credit. Economic

development relies upon financial intermediation services that link users with

providers of capital and allow consumption decisions to be smoothed over time.

There are at least three key questions of interest in the theoretical and empirical

literature. First, does the degree of bank competition impact the efficiencyof credit

allocation (Cetorelli and Strahan, 2006; Bonnacorsi and Dell’Ariccia, 2004)?

Second, how does the intensity of competition affectthe financial system’s stability

(Keeley, 1990; Boyd and De Nicolo, 2005)? Third, what are the macroeconomic

outcomes of banking-sector competition (Cetorelli, 2004)?

To address these important questions, one first needs to come up with mean-

ingful measures of the intensity of bank competition. Some studies (e.g., Cetorelli

and Strahan, 2006) followed the early industrial organization tradition and used

concentration measures as a proxy for bank competition. There is however a

growing consensus that concentration measures – useful as they may be in re-

vealing important structural characteristics of the industry – are not good proxies

for bank competition (Beck, Demirguc-Kunt and Levine, 2006; Claessens and

Laeven, 2004). Instead, recent literature favors measures like the price-cost mar-

gin or Lerner index (Lerner, 1934), the adjusted-Lerner index (Koetter, Kolari and

Spierdijk, 2012), the H statistic (Panzar and Rosse, 1987), and the profit elasticity

(Boone, Griffith and Harrison, 2005). Computing any of these measures (with the

Corresponding author: Sotirios Kokas, Essex Business School. Email: skokas@essex.ac.uk.

C2015 NewYork University Salomon Center and Wiley Periodicals, Inc.

268 Sofronis Clerides et al.

exception of the H statistic) requires knowledge of marginal cost. Given that data

on marginal cost are not usually available, an important first step in the construc-

tion of a competition index is the estimation of marginal cost using econometric

methods.

The objective of this paper is to present a new set of estimates for bank competi-

tion in 148 countries for the period 1997–2010 and to analyze trends and patterns

in the evolution of competition during that period. Competition is measured in

terms of the Lerner index, the adjusted-Lerner index and the profit elasticity. The

paper contributes to the literature on bank competition in four important ways.

First, we use a novel technique to obtain accurate estimates of marginal cost and

market power for each observation in the sample. The smooth coefficient model

we employ is a semiparametric approach that allows for a flexible cost structure.

Second, we have the broadest coverage compared to existing studies, with 148

countries from 1997 to 2010. While most studies focus on a specific region or

income group, our data set allows studying the degree of within-country bank

competition in a large number of countries. With coverage up to 2010, we are able

to analyze the evolution of bank competition during the financial crisis. Third, we

compute three different indicators favoredby the recent banking literature, namely

the Lerner index, the adjusted-Lerner index and the profit elasticity. Fourth, we

clean the raw data required to estimate these indices from double-counting stem-

ming from mergers and acquisitions, ownership issues, inflexible features of the

Bankscope database, and other problems.

All indices indicate substantive changes in bank competition over time and

across income and regional classification. The Lerner index, the adjusted-Lerner

index and the profit elasticity produce similar overall patterns of competition over

time. We observe a gradual decline in the intensity of competition from 1997 to

2006. The trend reverses for a brief period (2007–2008) but then market power

increases again in 2009 and 2010. This pattern raises interesting questions about

the relationship between competitive conditions and financial stability. Notably,

bank competition seems to weaken during the upward phase of the business

cycle and to become more intense when economic conditions worsen. We do not

formally explore this link in the current work but leave it open as an important

question for future research.

The empirical results also highlight important differences across regions and

income groups. On average, the banking systems of Sub-Saharan Africa are the

least competitive, followed by East Asia and Pacific. Europe and Central and

South Asia have the most competitivebanking sectors. Non-OECD countries with

either high or low income levelshave less competitive banking sectors than middle-

income countries. OECD countries have lowerbank market power overall. Despite

the differences, competition levels across income and regional groups seem to be

converging over tim e.

The three competition measures largely coincide when it comes to the main

overall trends but do differ when compared at a finer level. We do not take a

stand on which index is best. Each measure has its own theoretical interpretation

A New Data Set On Competition In National Banking Markets 269

and its calculation presents different empirical challenges. Rather than propose a

specific measure, we provide (section 2) an extensive discussion of the theoretical

justification for each index that we hope will be a useful guide to potential users

seeking to identify their preferred measure.

The structure of the paper is as follows. Section II presents an overview of bank

competition measures. Section III describes our data and the empirical method-

ology. Section IV presents the empirical results on the various indices of bank

competition. Section V concludes.

II. EMPIRICAL METHODS FOR THE ESTIMATION OF

COMPETITION

Estimation of competition has a long history in industrial organization, dating

back to Lerner (1934). Lerner defined his “index of the degreeof monopoly power”

(or “degree of monopoly” for short) as

Lerneri=Pi−mci

Pi

,(1)

where Piand mciare firm i’s price and marginal cost respectively. The index

ranges between 0 and 1, with zero corresponding to perfect competition and larger

values reflecting a greater degree of market power. The Lerner index remains to

this day the most widely and popular measure of market power and the intensity

of competition.1The main reasons for its popularity are simplicity, an intuitive

interpretation, and relatively mild data requirements. The Lerner index measures

the ability of an individual bank to charge a price above marginal cost. When

data on prices and marginal cost are available, the Lerner index can be computed

as a simple ratio. Because marginal cost is rarely available, researchers have to

either estimate a cost function or impose equilibrium conditions derived from

theoretical models in order to obtain marginal cost estimates. The former method

is usually used in the banking literature, while the latter is preferred by industrial

organization economists.2In this paper we will follow the banking literature

approach of estimating a cost function.

Koetter,Kolari and Spierdijk (2012) have argued that the conventional approach

of computing the Lerner index assumes both profit efficiency (optimal choice of

prices) and cost efficiency (optimal choice of inputs by firms). As a result, the

estimated price-cost margins do not correctly measure the true extent of market

power. The argument reflects a distinction pointed out by Lerner (1934) himself,

who states that “for practical purposes we must read monopoly power not as

potential monopoly, but as monopoly in force” (p. 170; italics as in the original).

1Throughout the paper we will use market power as a measure of competition intensity.This is usually

an innocuous assumption, although research has shown that the Lerner index does not always point in

the expected direction when competitive conditions change (Stiglitz, 1989; Boone, 2008).

2The use of equilibrium conditions is the hallmark of the New Empirical Industrial Organization

(NEIO) literature; see Bresnahan (1989) for an overview.