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More Less | | Skrill, Wire transfer, Money order | Sample translations submitted: 1 French to English: Structure et pouvoir de marché des banques islamiques et conventionnelles
General field: Bus/Financial
Detailed field: Finance (general) | | Source text - French
Le système financier international a connu une accentuation de la concurrence bancaire alimentée par l’essor des nouvelles techniques d’ingénierie financières et l’expansion de l’industrie bancaire islamique. La portée du changement que connaisse le paysage bancaire ainsi que l’importance de la banque dans le système financier alimentent un grand débat sur les conditions concurrentielles du secteur bancaire. C’est dans ce contexte que s’inscrit notre recherche avec une problématique axée sur l’analyse du pouvoir de marché et les conditions concurrentielles du secteur bancaire conventionnel et islamique dans un cadre comparatif en utilisant les deux types d’indicateurs : les indicateurs de l’approche traditionnelle et ceux de la nouvelle approche empirique de l’organisation industrielle. Les résultats indiquent que les deux marchés se caractérisent par une concurrence monopolistique. L’industrie bancaire islamique est plus concentrée que l’industrie conventionnelle où elle est plus proche à la situation de monopole qu’à la situation de concurrence parfaite. Le marché islamique a une tendance oligopolistique dans le sens où le marché est dominé par un petit nombre de banques qui ont un pouvoir de marché plus important que leurs consœurs conventionnelles. Cela justifie que cette nouvelle industrie est dans une phase de développement et elle n’a pas encore atteint le stade d’une concurrence égale à celle du secteur bancaire classique.
Mots clés:
JEL:
1. Introduction
L’industrie bancaire islamique a vu le jour au milieu des années soixante-dix comme une nouvelle forme d’intermédiation financière. L’expansion de cette nouvelle alternative de la finance classique s’est traduite par l’augmentation de la valeur des actifs de cette industrie qui était d’environ cinq milliard de dollars américain en 1985, et elle est de 1 trillion de dollars en 2012. Dans de nombreux pays, on voit les banques islamiques cohabitent avec leurs consœurs classiques et affrontent ensemble les conditions concurrentielles du marché. Contrairement aux banques classiques, les banques islamiques effectuent des opérations bancaires conformes à la Charia où l’intermédiation est basée sur le paradigme de partage des profits et des pertes. Avec l’expansion des banques islamiques, la concurrence au sein de l’industrie bancaire s’est accentuée. Dans cet environnement de plus en plus concurrentiel, chaque type de banque est appelée à analyser la structure de son marché et ses conditions concurrentielles, afin d’arrêter une stratégie d’activités et des plans d’actions efficaces.
La mesure du pouvoir de marché des firmes et l’évaluation du degré de concurrence d’un marché donné ainsi que sa structure sont des sujets qui ont suscité beaucoup d’intérêt dans la littérature de l’organisation industrielle. Sur un plan conceptuel, il existe deux approches qui traitent la problématique des conditions concurrentielles et du pouvoir de marché. La première approche se base sur le concept de SCP et la deuxième sur le concept de l’efficience bancaire. Ces deux approches proposent un ensemble d’indicateurs permettant de mesurer la structure de marché et d’évaluer le pouvoir de fixation des prix par les banques. Plusieurs travaux ont cherché à identifier les conditions concurrentielles du secteur bancaire dans différents pays en l’occurrence Shaffer (2004), Boyd et de Nicolo (2005), Schaeck & Cihak (2007), Berger, Klapper et Turk-Ariss (2009), Turk-Ariss (2010a).
Cependant, peu d’études ont traité ce sujet dans un cadre d’une analyse comparative entre les banques islamiques et celles conventionnelles. C’est dans ce contexte que s’inscrit cet article qui a pour objectif d’analyser le degré de pouvoir de marché des banques islamiques et conventionnelles. Tout au long de cette étude, nous nous proposons d’apporter des éléments de réponse aux questions suivantes : Quelles sont les conditions concurrentielles du secteur bancaire islamique et conventionnel ? Quel est le pouvoir de marché de chaque type de banque.
Pour répondre à ces deux questions, nous partons des hypothèses de départ inspirées du cadre théorique de notre recherche. La question de détermination des conditions de concurrence dans le secteur bancaire conventionnel et islamique a fait l’objet de plusieurs recherches approfondies qui ont porté sur le pouvoir de marché des banques conventionnelles et islamiques. En effet, plusieurs travaux empiriques ayant analysé la structure des marchés bancaires tels que Murjan et Ruza (2002), Mharrami, Matthews et Khabari (2006), Abdul Majid et Sufian (2007) ont montré que les banques conventionnelles sont généralement en concurrence monopolistique. Vu l’état embryonnaire de l’industrie bancaire islamique et le nombre faible de ses institutions financières par rapport aux banques conventionnelles, nous prévoyons que les banques y opérant détiennent un degré de pouvoir de marché plus élevé que celui des banques classiques.
Pour se faire, notre article sera divisé en trois sections : La première section présentera les concepts théoriques et une revue de la littérature. La deuxième section présente les indicateurs et les méthodes de mesure de la concurrence et du pouvoir de marché. La troisième section aborde l’étude comparative des conditions concurrentielles du marché bancaire islamique et classique moyennant des données de panel de 62 banques islamiques et 128 banques conventionnelles.
2. Concurrence bancaire et pouvoir du marché : Revue de la littérature
Le paradigme SCP (structure – conduite- Performance) a été développé par Edward.S. Mason en 1939 au sein de l’université de Harvard puis poursuivi par Bain (1956). Ce paradigme est une approche descriptive du fonctionnement de l’entreprise stipulant que la performance d’une industrie et sa capacité de satisfaire les besoins des consommateurs dépend de la conduite des firmes en d’autres termes de leur comportement qui est déterminée par la structure du marché (l’ensemble des facteurs qui concourent à sa compétitivité). L’approche SCP dite l’approche structurelle fournit un lien causal entre les caractéristiques structurelles d’un marché donné, le comportement des firmes qui y opèrent et les performances économiques
L’hypothèse du modèle SCP stipule que la concentration du marché incite les entreprises à agir de concert sous la forme d’une collusion. Selon cette hypothèse il existe une relation positive entre la concentration du marché et la performance mesurée par les bénéfices ou les profits. Ainsi, les entreprises opérant dans les secteurs les plus concentrés dégagent des profits plus importants que dans des industries moins concentrées sans tenir compte de leur efficience. L’augmentation de la concentration d’un marché provoque une collusion entre les firmes dominantes ce qui renforce le pouvoir de marché de chacune d’entre elles. L’entente entre les intervenants du marché peut prendre la forme d’un accord sur le partage du marché ou sur des prix élevés ce qui engendre un relâchement de la concurrence et l’obtention des profits plus élevés qu’en concurrence normale ou même monopolistique. De ce fait, la concentration d’un marché est en relation positive avec la performance des entreprises y opérant.La structure de marché selon l’approche SCP peut être évaluée par diverses mesures y compris les parts de marché, les ratios de concentrations des groupes d’entreprises les plus importantes et l’indice de Herfindahl-Hirschman.
A partir des années 80, on a assisté au développement de diverses solutions alternatives à cette approche dites les mesures de la nouvelle approche empirique de l’organisation industrielle, poussé par un besoin de mesures plus précises et concordantes du pouvoir de marché. La nouvelle approche est basée sur l’hypothèse de la structure d’efficience (ES) qui stipule que la performance de l’entreprise est positivement dépendante de son efficience. En effet, la concentration du marché émerge de la concurrence où les entreprises à faible structure de coûts augmentent leurs profits en réduisant leurs prix et en développant leurs parts de marché. Donc, une relation positive entre les profits des entreprises et la structure du marché est attribuable aux gains en termes de part de marché réalisés par les firmes les plus efficientes. Ces gains engendrent ainsi, un accroissement de la concentration du marché. En conséquence, les profits réalisés sont le fruit de l’efficience de l’entreprise et non pas engendré par les activités collusoires comme le suggère le paradigme traditionnel SCP de Molyneux et Forbes (1995). Selon L’hypothèse effeciency structrure ou la nouvelle approche empirique de l’organisation, la performance des firmes affecte la structure du marché. Les entreprises les plus efficientes augmentent leurs parts de marché au détriment des entreprises les mois efficientes de sorte qu’elles engendrent un accroissement de la concentration du marché. On peut dire donc qu’un marché concentré d’avantage est plus efficient.
Les nouvelles mesures, permettant d’analyser le comportement des entreprises en matière de fixation de prix, sont principalement basées sur les mesures de pouvoir de marché et confirment que les prix d’un marché sont déterminés à partir des coûts et non pas par la concentration du marché. L’approche de Panzar et Rosse(1987) mesure l’impact du changement dans le coût moyen des différents facteurs de production sur le revenu ou le prix sous la condition que l’industrie en question soit en équilibre à long terme. Plus les variations des coûts affectent le prix, plus concurrentiel est le marché. Pour l’indice de Lerner, il se base sur un mark-up de prix qui mesure la différence entre le prix et le coût marginal. Plus le mark-up est important, plus grand est le pouvoir de marché.
Sur données européennes et américaines, Parmi les études utilisant la statistique de Panzar et Rosse (1987) comme mesure de la structure du marché, on trouve que Shaffer (1989) est le premier à appliquer cette technique sur deux sous échantillons de banques américaines le premier observé pendant la période 1941-1975 et le deuxième pendant la période 1941-1983. Les résultats obtenus sont cohérents avec l’hypothèse de l’existence d’une concurrence parfaite en rejetant vigoureusement l’existence d’une structure de concurrence monopolistique. En adoptant la même démarche, Shaffer (1993a) a estimé le degré de concurrence dans le secteur bancaire canadien pour la période qui s’étale sur 1965 -1989 pour montrer l’existence d’une concurrence parfaite dans ce secteur. Egalement et moyennant une étude sur quinze pays développés observés pour une période qui va de 1979 à 1991, Shaffer (1993b) a conclu que la majorité des marchés des pays étudiés sont généralement concurrentiels et uniquement le un tiers des pays de l’échantillon ont un pouvoir de marché.
Molyneux et Forbes (1995) ont examiné le concept du SCP pour des banques observées entre 1986 et 1989 dans 18 pays différents (QUEL INDICATEUR). L’étude fournit une recommandation empirique pour le concept traditionnel SCP et stipule que le degré de concentration influence le niveau de la concurrence dans l’industrie bancaire.
Claessens & Laeven (2004) ont réalisé une étude importante de concurrence et de concentration dans le secteur bancaire classique d’un échantillon qui comprend 50 pays développés et en développement observé durant la période 1994-2001. A l’aide de la statistique H-PR, ils ont pu conclure que la concurrence parfaite décrit chacun des pays étudiés à des degrés différents.
Carbó, Humphrey, Maudos, Molyneux ( 2009) se sont penchés sur la comparaison des indicateurs de compétitivité et de concurrence en observant des banques dans 14 pays européens sur une période qui va de 1995 à 2001 en évaluant la position concurrentielle relative de leurs marchés bancaires , il s’avère que les indicateurs de concurrence donnent des prédictions contradictoires selon les pays et au fil de temps. Cela est dû à ce que ces indicateurs tels que l’indice de Lerner sont influencés par les différences entre les pays en matière de rentabilité, les niveaux de revenus d’honoraires, la croissance économique réelle et l’inflation.
Murjan & Ruza (2002) ont étudié les conditions de concurrence dans neuf pays de la région MENA au cours de la période 1993-1997. A l’aide de la statistique de Panzar et Rosse, ils ont constaté que les secteurs bancaires MENA fonctionnent dans des conditions de concurrence monopolistique, et que les pays du conseil de coopération du Golfe tendent à être moins compétitifs que les pays non producteurs de pétrole.
Muharrami, Matthews, et Khabari (2006) ont utilisé ces mêmes indicateurs tels que les ratios de concentration, l’indice de Herfindahl-Hirschman et la statistique H-PR afin d’étudier la structure du marché de l’industrie bancaire des pays de Golf et évaluer le pouvoir de marché de ces banques pendant la période 1993- 2002. Les résultats montrent que le Koweït, l’Arabie Saoudite et les Emirats Arabes Unis ont des marchés bancaires modérément concentrés et évoluent vers des positions moins concentrée et que leurs banques fonctionnent dans un régime de concurrence parfaite. Tandis que Qatar, Bahreïn et Oman ont des marchés bancaires très concentrés et leurs banques fonctionnent dans des conditions de concurrence monopolistique.
L’étude de Parera et al. (2006) a examiné la nature de la concurrence et la structure des marchés bancaires des 4 pays du sud asiatique : Pakistan, Bangladesh, l’Inde et Sri Lanka pour la période qui s’étale sur 1995-2003. Les auteurs ont utilisé la statistique H-PR et ont montré qu’au cours de la période d’études les revenus bancaires semblent être réalisés dans des conditions de concurrence monopolistique.
Dans le secteur bancaire islamique en Malaisie, Abdul Majid et Sufian (2007) montrent que les conditions de marché sont en concurrence monopolistique en utilisant des mesures traditionnelles de la concentration ainsi que la méthode de Panzar et Rosse (1987). Les résultats de cette étude ont montré que les banques islamiques malaisiennes opèrent dans une situation de concurrence monopolistique.
Khan (2009) a mesuré le degré de concurrence dans le secteur bancaire Pakistanais en utilisant l’approche structurelle de Panzar et Rosse (1987) dans le contexte de la contestabilité des marchés. Une équation réduite du revenu a été estimée à l’aide des données de panel composé de 26 banques de 1997 à 2007. Les différents tests de la statistique H-PR indiquent que les banques du Pakistan opèrent dans une situation de concurrence monopolistique.
Dans la même lignée, on trouve l’étude de Turk-Ariss (2010a), cette étude examine aussi les conditions de concurrence dans 12 pays de la région MENA au cours de la période 2000-2006 et elle cherche aussi à expliquer les différences dans les degrés de concurrence entre les pays étudiés. Conformément aux recherches antérieures, Turk Ariss (2010a) constate que la plupart des secteurs bancaires de la région fonctionnent en concurrence monopolistique. En ce qui concerne les différences des degrés de concurrence entre les pays de la région, l’auteur conclut que les indicateurs de contestabilité du marché et les restrictions des activités sont parmi les facteurs les plus importants.
LE DEUXIEME ARTICLE DE TURK ARISS
Anzoategui, Martinez Peria & Rocha (2010) ont étudié l’ampleur de la concurrence des banques dans le Moyen-Orient et l’Afrique du Nord au cours de 1994- 2008. Les auteurs ont utilisé des mesures non structurelles de la concurrence telles que la statistique H-PR et L’indice de Lerner. Ces deux mesures donnent à penser que la concurrence du secteur bancaire dans la région d’étude est inférieure par rapport à d’autres régions et elle ne s’est pas améliorée pendant ces dernières années. Une analyse des déterminants de la concurrence dans ces pays étudiés suggère que les bas niveaux de concurrence sont expliqués par les informations erronées sur l’environnement de crédit et la faible contestabilité du marché.
Weill (2010) a mené une étude sur un échantillon de banque de 17 pays de la région MENA et les pays du sud est asiatique observé sur une période de 2000 à 2007. L’auteur mesure et compare le pouvoir de marché des banques islamiques et classiques en calculant l’indice de Lerner. La comparaison des indices de Lerner montre qu’il n’existe pas une différence significative entre les banques islamiques et celles classiques sur la période d’étude. En ajoutant des variables de contrôle, la régression des indices de Lerner suggère que les banques islamiques ont moins de pouvoir de marché que les banques conventionnelles. Un test de robustesse avec le modèle de Panzar Rosse (1987) confirme que les banques islamiques ne sont pas moins compétitives que leurs consœurs conventionnelles.
3. Méthodologie
La méthodologie empirique est basée sur deux approches d’évaluation du pouvoir de marché des banques. La première est basée sur un ensemble d’indicateurs de concentration bancaire et la deuxième se focalise sur des estimations économétriques dans le but de qualifier la structure de marché et de mesurer son pouvoir en terme de fixation des prix.
3.1. Les indicateurs de concentration
L’organisation industrielle traditionnelle propose des tests de la structure du marché pour évaluer la concurrence basée sur le modèle Structure –Conduct- Performance (SCP). Les hypothèses de ce modèle supposent qu’une concentration plus élevée engendre des pratiques bancaires moins compétitives et conduit à une plus grande rentabilité et selon cette approche, la concurrence peut être mesurée par les indices de concentrations ou par l’indice de Herfindahl- Hirschman. Ces deux mesures ont été largement appliquées avant les années 1990. Ces deux indicateurs sont connus comme des mesures structurelles traditionnelles de concentration basées sur la part de marché.
Les ratios de concentration
Les ratios de concentration représentent une mesure de la concentration du marché souvent utilisée pour illustrer l’étendu du contrôle des plus grandes firmes d’un secteur donné et identifier l’existence d’une concurrence oligopolistique.
Un ratio de concentration est le pourcentage de la part de marché d’un certain nombre de firmes par rapport à un échantillon donné du secteur étudié. Les taux de concentrations les plus courants sont C3 et C 5 les ratios des trois et des cinq plus grandes firmes de l’échantillon étudié, soit :
C_n=∑_1^n▒X_i
C_n=S_1 S_2 ⋯ S_n
Avec Xi : la part de marché de la banque i, n : le nombre des banques
Sn : est la part de marché de la n éme banque
Les ratios de concentrations varient de 0 à 100 % et on distingue quatre niveaux de concentrations :
- Aucune concentration : 0 % cela signifie l’existence d’une concurrence parfaite ou une concurrence moins monopolistique.
- Une faible concentration : entre 0 à 50% cette catégorie va de la concurrence parfaite à l’oligopole.
- Concentration moyenne : entre 50% à 70% le secteur est susceptible d’un oligopole.
- Concentration élevée : entre 70% et 100% cette catégorie va d’oligopole au monopole.
- Concentration Totale : 100% c’est le cas d’un oligopole extrêmement concentré, et si CR 1= 100% on parle d’un monopole.
L’indice de Herfindahl-Hirschman HHI
L’indice de Herfindahl-Hirschman (HHI) est une autre mesure traditionnelle de la concurrence et de la concentration du marché conçu par Albert O.Hirschman (1945) et Orris C .Herfindahl (1950). Il est largement appliqué pour évaluer le niveau de concurrence d’un marché et sa structure.
HHI =S1 ² S2 ² S3 ² ⋯ Sn ²
HHI= ∑_(i=1)^n▒Si²
Où Sn est la part de marché de la néme banque.
S2i est la part de marché de l'entreprise i et n est le nombre d’entreprises.
Cet indice est calculé en additionnant les carrés des parts de marché de chaque banque d’un marché ou d’un pays et il varie entre zéro (situation de concurrence pure et parfaite) et 10,000 (100² : situation de monopole). Selon le Ministère Américain de la Justice et la commission fédérale de commerce, un marché dans lequel le HHI est inférieur à 1000 points est considéré comme non concentré, entre (1000 et 1800) comme moyennement concentré, et au dessus de 1800 comme très concentré.
Le HHI prend en compte la taille relative et la distribution des entreprises dans un marché et tend vers zéro lorsque le marché se compose d'un grand nombre de banques de taille relativement égale. Plus la valeur de l’indice augmente, plus le marché est concentré, et plus faible est la concurrence entre les agents. Le marché tend donc vers une situation de monopole. En résumé, l’augmentation de l’indice de Herfindahl-Hirschman indique généralement une diminution de la concurrence et une augmentation du pouvoir de marché, alors que la diminution indique le contraire.
3.2. L’approche de Panzar et Rosse (H-PR)
La nouvelle approche empirique de l’organisation industrielle offre des tests non structurels afin de contourner les problèmes des mesures de concurrences prévues par l’approche traditionnelle. Contrairement aux mesures classiques, ces mesures non structurelles ne déduisent pas le comportement concurrentiel des banques à travers l’analyse de la structure du marché, mais plutôt à travers l’évaluation de la conduite des banques directement.
En 1987, Panzar et Rosse ont développé un test examinant si le comportement au niveau des entreprises est conforme soit avec le modèle de concurrence parfaite, le modèle de concurrence monopolistique ou bien le modèle de monopole. Ce test se base sur l’examen empirique de l’impact des variations des prix des inputs sur le revenu de la firme. Il se traduit par la somme des élasticités prix des inputs.
Ce modèle non structurel suggéré par Panzar et Rosse (1987) est largement utilisé dans l’examen du pouvoir de marché et la structure concurrentielle du secteur financier et plus particulièrement le secteur bancaire dans différents pays. Sa première application a été offerte par Shaffer (1989) lors d’une étude menée sur deux sous échantillons de banques américaines. Ensuite, il a été adopté par plusieurs études telles que Molyneux et al. (1994), Bikker et Groeneveld (1998) pour le secteur bancaire européen, Abdul majid et Sufian 2007 pour les banques malaisiennes, Vesala (1995) pour le marché bancaire finlandais ainsi que d’autres études substantielles portant sur plusieurs pays dont on peut signaler Bikker et Groeneveld (2002) et Cleassens et leaven (2004 et 2005).
La statistique H-PR détermine le comportement concurrentiel des banques en se basant sur une équation de forme réduite des revenus. Pour que cette méthode obtienne des résultats plausibles, deux conditions nécessaires doivent être vérifiées. La première condition exige que les banques en question soient en équilibre de long terme et la deuxième nécessite que la performance des banques soit influençable par le comportement des autres agents du marché.
Le calcul de la statistique H-PR nécessite l’estimation de la fonction de revenu suivante exprimée en log :
Ln〖(TR〗_it)= α β_1 Ln(W_(L,it) ) β_2 Ln(W_(F,it) ) β_3 (W_(k,it) ) (1)
γ_1 Ln (Y_(1,it) ) γ_2 Ln(Y_(2,it) ) ε_it
Les variables utilisées au niveau de la fonction de revenu sont définies comme suit :
TRit : revenu total représenté par le ratio des revenus d’intérêt et revenus autres que d’intérêt) à l’actif total.
W L,it : le coût du travail représenté par le ratio des dépenses de personnel au total actifs.
WF, it : le coût des fonds représenté par le rapport des charges d'intérêt au total des dépôts.
WK,it : le coût du capital fixe représenté par le rapport des autres charges administratives à l'actif total ou l’actif fixe.
Y1,it : variable spécifique de contrôle du portefeuille des activités de la banque représenté par le ratio des capitaux propres / total des actifs (Equity to total assets).
Y2,it : variable spécifique de contrôle du portefeuille des activités de la banque représenté par le ratio des prêts nets / l'actif total (Loans to total assets).
Après avoir estimé la fonction (1), on peut calculer la statistique H-PR qui n’est autre que la somme des trois élasticités prix :
H=∑_(i=1)^3▒βi
H < 0 : il s’agit d’une situation de monopole ou d’oligopole collusoire.
0 | Translation - English
Summary
The international financial system knew an accentuation of the banking competition fed by the development of new financial techniques of engineering and the expansion of the Islamic banking industry. The impact of the change which knows the banking landscape as well as the importance of the bank in the financial system feed a big debate on the competitive conditions of the banking sector. It is in this context that joins our research with a problem centered on the analysis of the power of market and the competitive conditions of the conventional and Islamic banking sector in a comparative frame by using both types of indicators: the indicators of the traditional approach and those of the new empirical approach of the industrial organization. The results indicate that both markets are characterized by a monopolistic competition. The Islamic banking industry is more concentrated than the conventional industry where it is closer in the monopoly position than in the situation of perfect competition. The Islamic market tends oligopolistic in the sense that the market is dominated by a small number of banks who have a power of market more important than their conventional colleagues. It justifies that this new industry is in a phase of development and it has not reached the stage of a competition equal to that of the classic banking sector yet.
1. Introduction
The Islamic banking industry was born in the middle of the seventies as a new shape of financial intermediation. The expansion of this new alternative of the classic finance was translated by the increase of the value of the assets of this industry which was about five billions of American dollars in 1985, and it is of a trillion of dollars in 2012. In numerous countries, we see Islamic banks living with their classic colleagues and face together the competitive conditions of the market. Contrary to the classic banks, the Islamic banks make bank transactions corresponding to the Sharia where the intermediation is based on paradigm of the sharing of profits and losses. With the expansion of the Islamic banks, the competition within the banking industry became more marked. In this more and more competitive environment, every chap of bank is called to analyze the structure of his market and his competitive conditions to stop a strategy of activities and an effective action plans.
The measure of the power of market of firms and the evaluation of the degree of competition of a given market as well as its structure are subjects which aroused a lot of interest in the literature of the industrial organization. On an abstract plan, there are two approaches which treat the problem of the competitive conditions and the power of market. The first approach bases itself on the concept of SCP and the second on the concept of the banking efficiency. These two approaches propose a set of indicators allowing to measure the structure of market and to estimate the power of price setting by banks. Several works tried to identify the competitive conditions of the banking sector in various countries in this case Shaffer (2004), Boyd & de Nicolo (2005), Schaeck & Cihak (2007), Berger, Klapper & Turk-Ariss(2009), Turk-Ariss (2010).
However, few studies treated this subject in a frame of a comparative analysis between the Islamic banks and those conventional. In this context that joins this article which has for purpose to analyze the degree of power of market of the Islamic and conventional banks. Throughout this study, we suggest bringing elements of answer to the following questions: What are the competitive conditions of the Islamic and conventional banking sector? Which is the power of market of every type of bank?
To answer these two questions, we start from the hypotheses of departure inspired by the theoretical frame of our research. The question of determination of the conditions of competition in the conventional and Islamic banking sector was the object of several detailed researches that concerned the power of market of the conventional and Islamic banks. Indeed several empirical works having analyzed the structure of the banking markets such as Murjan & Ruza (2002), Mharrami, Matthews & Khabari (2006), Abdul Majid &Sufian (2007) showed that the conventional banks are generally in monopolistic competition. Seen the embryonic state of the Islamic banking industry and the low number of its financial institutions with regard to the conventional banks, we plan that the operating banks detain one degree of market power higher than the classic banks one.
To be made, our article will be divided into three sections: the first section will present the theoretical concepts and a review of the literature. The second section presents indicators and methods of measure of the competition and the power of market. The third section approaches the comparative study of the competitive conditions of the Islamic and classic banking market for data of panel of 62 Islamic banks and 128 conventional banks.
2. Banking competition and power of the market: review of the literature
Paradigm SCP (structure –conduct-Performance) was developed by Edward. S Mason in 1939 within the university of Harvard then pursued by Bath (1956). This paradigm is a descriptive approach of the functioning of the company stipulating that the performance of an industry and its capacity to satisfy the needs of the consumers depends on the conduct of firms in other words of their behavior which is determined by the structure of the market (all the factors which contribute to its competitiveness). The said approach SCP the structural approach supplies a causal link between the structural characteristics of a given market, the behavior of the firms that operate in it and the economic performances.
The hypothesis of the SCP model stipulates that the concentration of the market incites companies to act in unison under the shape of a collusion. According to this hypothesis there is a positive relation between the concentration of the market and the performance measured by profits or profits. So, companies operating in the most concentrated sectors make more important profits than in less concentrated industries without taking into account their efficiency. The increase of the concentration of a market provokes a collusion between the dominant firms what strengthens the power of market of each of them. The agreement between the participants of the market can take the shape of an agreement on the sharing of the market or on the high prices what engenders a slackening of the competition and the obtaining of the profits higher than in even monopolistic or normal competition. Therefore, the concentration of a market is in positive relation with the performance of companies operating there. The structure of market according to the SCP approach can be estimated by diverse measures including market shares, ratios of concentrations of the groups of the most important companies and the Herfindahl-Hirschman index.
From the 80s, we assisted the development of diverse alternative solutions to this approach called the measures of the new empirical approach of the industrial organization, pushed by a need of more precise and corresponding measures of the power of market. The new approach is based on the hypothesis of the efficiency structure( ES) which stipulates that the performance of the company is positively dependent on its efficiency. Indeed, the concentration of the market appears from the competition where companies with weak structure of costs increase their profits by reducing their prices and by developing their market shares. Thus, a positive relation between the profits of companies and the structure of the market is attributable to the earnings in terms of market share realized by the most efficient firms. These gains engender an increase of the concentration of the market. As a consequence the realized profits are the fruit of the efficiency of the company and not engendered by the secret activities as suggests the traditional SCP paradigm of Molyneux and Forbes (1995). According to the effeciency structrure hypothesis or the new empirical approach of the organization, the performance of firms affects the structure of the market. The most efficient companies increase their market shares to the detriment of the least efficient ones so that they engender an increase of the concentration of the market. We can say thus that a more concentrated market is the most efficient.
The new measures, that allow analyzing the behavior of companies in price fixation, are mainly based on the measures of power of market and confirm that the prices of a market are determined from the costs and not by the concentration of the market. The approach of Panzar and Rosse (1987) measure the impact of the change in the average cost of the various factors of production on the income or the price under the condition that the industry in question is in long-term balance. The more the variations of the costs affect the price, the more competitive is the market. For the Lerner index, it bases itself on a valuable mark-up which measures the difference between the price and the marginal cost The more the mark-up is important, the bigger is the power of market.
On European and American data, Among the studies using the statistics of Panzar and Rosse(1987) as measure of the structure of the market, we find that Shaffer ( 1989 ) is the first one to apply this technique to two under samples of American banks, the first one observed during the period 1941-1975 and the second during the period 1941-1983. The obtained results are coherent with the hypothesis of the existence of a perfect competition by rejecting strongly the existence of a structure of monopolistic competition. By adopting the same approach Shaffer (1993a) estimated the degree of competition in the Canadian banking sector for the period which spreads out over 1965 1989 to show the existence of a perfect competition in this sector. Also and for a study on fifteen developed countries observed for a period which goes from 1979 till 1991, Shaffer (1993b) concluded that the majority of the markets of the studied countries are generally competitive and only a third of the countries of the sample have a power of market.
Molyneux and Forbes (1995) examined the SCP concept for banks, observed between 1986 and 1989 in 18 different countries (QUEL INDICATOR). The study supplies an empirical recommendation for the traditional SCP concept and stipulates that the degree of concentration influences the level of the competition in the banking industry.
Claessens and Laeven (2004) realized an important study of competition and concentration in the classic banking sector of a sample which includes 50 developed countries and in development observed during period 1994-2001. By means of the RP H-statistics, they were able to conclude that the perfect competition describes each of the countries studied in different degrees.
Carbó, Humphrey, Maudos, Molyneux (2009) bent over the comparison of the indicators of competitiveness and competition by observing banks in 14 European countries over a period which goes from 1995 till 2001 by estimating the relative competitive position of their banking markets, it turns out that the indicators of competition give contradictory predictions according to the countries and in the course of time. It is due to the fact that these indicators such as the Lerner index are influenced by the differences between countries in profitability, the levels of income of fees, the real economic growth and the inflation.
Murjan and Ruza (2002) studied the conditions of competition in nine countries of the MENA (Middle East and North Africa) region during period 1993-1997. By means of Panzar and Rosse statistics, they noticed that the MENA banking sectors work in conditions of monopolistic competition, and that the countries of the gulf cooperation council tend to be less competitive than the not oil-producing countries.
Muharrami, Matthews, and Khabari (2006) used these same indicators such as the ratios of concentration, the Herfindahl-Hirschman index and the Rosse & Panzar H- statistics to study the structure of the market of the banking industry of the Golf countries and estimate the power of market of these banks during the period 1993-2002. The results show that Kuwait, Saudi Arabia and United Arab Emirates have moderately concentrated banking markets and evolve towards positions less concentrated and that their banks work in a regime of perfect competition. Whereas Qatar, Bahrain and Oman have very concentrated banking markets and their banks work in conditions of monopolistic competition.
The study of Parera and Al. (2006) examined the nature of the competition and the structure of the banking markets of 4 countries of the Asian South: Pakistan, Bangladesh, India and Sri Lanka for the period which spreads out over 1995-2003. The authors used the RP H-statistics and showed that during the period of studies the banking income seems to be realized in conditions of monopolistic competition.
In the Islamic banking sector in Malaysia, Abdul Majid and Sufian (2007) show that market conditions are in monopolistic competition by using the traditional measures of the concentration as well as the method of Panzar and Rosse (1987). The results of this study showed that the Malaysian Islamic banks operate in a situation of monopolistic competition.
Khan (2009) measured the degree of competition in the Pakistani banking sector by using the structural approach of Panzar and Rosse (1987) in the context of the questionability of the markets. A reduced equation of the income was estimated by means of panel data constituted of 26 banks from 1997 till 2007. The various tests of the RP H-statistics indicate that the banks of Pakistan operate in a situation of monopolistic competition.
In the same lineage, we find the study of Turk-Ariss (2010a), this study also examines the conditions of competition in 12 countries of the MENA region during period 2000-2006 and it also tries to explain the differences in the degrees of competition between the studied countries. According to the previous researches Turk Ariss (2010a) notices that most of the banking sectors of the region work in monopolistic competition. As regards the differences of competition degrees between the countries of the region, the author concludes that the indicators of questionability of the market and the limitations of the activities are among the most important factors.
THE SECOND ARTICLE OF TURK ARISS
Anzoategui, Martinez Peria and Rocha (2010) studied the scale of the competition of banks in the Middle East and North Africa during 1994-2008. The authors used not structural measures of the competition such as the H-PR statistics and the indication of Lerner. These two measures give to think that the competition of the banking sector in the region of study is lower with regard to other regions and it did not improve during these last years. An analysis of the determiners of the competition in these studied countries suggests that the low levels of competition are explained by the erroneous information on the environment of credit and the weak questionability of the market.
Weill (2010) led a study on a sample of bank of 17 countries of the MENA region and the countries of the Asian Southeast observed over a period from 2000 till 2007. The author measures and compares the power of market of the Islamic and classic banks by calculating the indication of Lerner. The comparison of the Lerner index shows that there is no significant difference between the Islamic banks and those classics over the period of study. By adding variables of control, the regression of the indexes of Lerner suggests that the Islamic banks have less power of market than the conventional banks. A test of robustness with the model of Panzar & Rosse (1987) confirms that the Islamic banks are not less competitive than their conventional colleagues.
3. Methodology
The empirical methodology is based on two approaches of evaluation of the banks’ power of market. The first one is based on a set of indicators of banking concentration and the second focuses on econometric estimations with the aim of qualifying the structure of market and measuring its power in term of price setting.
3.1. The indicators of concentration
The traditional industrial organization proposes structure of the market tests to estimate the competition based on the Structure-Conduct-Performance (SCP) model. The hypotheses of this model suppose that a higher concentration engenders less competitive banking practices and leads to a bigger profitability and according to this approach, the competition can be measured by the concentrations’ indications or by the Herfindahl-Hirschman index. These two measures were widely applied before 1990s. These two indicators are known as traditional structural measures of concentration based on the market share.
The ratios of concentration
The ratios of concentration represent a measure of the concentration of the market often used to illustrate the extent of the control of the biggest firms of a given sector and identify the existence of an oligopolistic competition.
A ratio of concentration is the percentage of the market share of certain number of firms with regard to a sample given by the studied sector. The most common rates of concentrations are C3 and C 5 the ratios three and five bigger firms of the studied sample, that is;
C_n=∑_1^n▒X_i
C_n=S_1 S_2 ⋯ S_n
With Xi: the market share of the bank i, n: the number of banks
Sn: is the market share of the nth bank
The ratios of concentrations vary from 0 to 100 % and we distinguish four levels of concentrations:
- No concentration: 0 % it means the existence of a perfect competition or a less monopolistic competition.
- A low concentration: between 0 in 50 % this category goes from the perfect competition to the oligopoly.
- Average Concentration: between 50 % a 70 % the sector open to oligopoly.
- High Concentration: between 70 % and 100 % this category goes from oligopoly to the monopoly.
- Total Concentration: 100 % it is the case of an extremely concentrated oligopoly, and if CR 1 = 100 % we speak about a monopoly.
Herfindahl-Hirschman index HHI
The Herfindahl-Hirschman Index (HHI) is another traditional measure of the competition and the concentration of the market conceived by Albert O.Hirschman (1945) and Orris C. Herfindahl (1950). It is widely applied to estimate the level of competition of a market and its structure.
HHI =S1 ² S2 ² S3 ² ⋯ Sn ²
HHI= ∑_(i=1)^n▒Si²
Where Sn is the market share of the nth bank, and
S2i is the market shares of the company i and n is the number of companies.
This index is calculated by adding the squares of the market shares of each bank of a market or a country and it varies between zero (situation of pure and perfect competition) and 10,000 (100 ²: monopoly position). According to the American Ministry of Justice and the Federal Trade Commission, a market in which the HHI is lower than 1000 points is considered as not concentrated, between (1000 and 1800) as averagely concentrated, and above 1800 as very concentrated.
The HHI takes into account the relative size and the distribution of companies in a market and aims towards zero when the market consists of a large number of banks of relatively equal size. The more the value of the index increases, the more the market is concentrated, and weaker is the competition between the agents. The market thus aims towards a monopoly position. In conclusion, the increase of the Herfindahl-Hirschman index indicates generally a decrease of the competition and an increase of the power of market, while the decrease indicates the opposite.
3.2. The Panzar and Rosse approach (the Rosse & Panzar H-statistics)
The new empirical approach of the industrial organization offers not structural tests to by-pass the problems of the measures of competitions planned by the traditional approach. Contrary to the classic measures, these not structural measures do not deduct the competitive behavior of banks through the analysis of the structure of the market, but rather through the evaluation of the banks conduct directly.
In 1987, Panzar and Rosse developed a test examining if the behavior at the level of companies is in accordance either with the model of perfect competition, the model of monopolistic competition or the model of monopoly. This test bases itself on the empirical examination of the impact of the variations of the prices of the inputs on the income of the firm. It is translated by the sum of the price elasticity of the inputs.
This not structural model suggested by Panzar and Rosse (1987) is widely used in the examination of the power of market and the competitive structure of the financial sector and more particularly the banking sector in various countries. Its first application was offered by Shaffer (1989) during a study led on two under samples of American banks. Then, it was adopted by several studies such as Molyneux and Al. (1994), Bikker and Groeneveld (1998) for the European banking sector, Abdul majid and Sufian on 2007 for the Malaysian banks, Vesala (1995) for the Finnish banking market as well as the other substantial studies concerning several countries of which we can indicate Bikker and Groeneveld (2002) and Cleassens and leaven (on 2004 and 2005).
The Rosse & Panzar H-statistics determines the competitive behavior of banks by basing itself on an equation of reduced shape of income. So that this method obtains plausible results, two necessary conditions must be verified. The first condition requires that banks in question are in long-term balance and the second requires that the performance of banks is influenceable by the behavior of the other agents of the market. The calculation of the Rosse & Panzar H-statistics requires the estimation of the following function of income expressed on log:
Ln〖(TR〗_it)= α β_1 Ln(W_(L,it) ) β_2 Ln(W_(F,it) ) β_3 (W_(k,it) ) (1)
γ_1 Ln (Y_(1,it) ) γ_2 Ln(Y_(2,it) ) ε_it
Variables used at the level of the function of income are defined as follows:
- TR, it: total income represented by the ratio of the interest income and returned others than interest) in the active total.
- W L, it: the labor cost represented by the ratio of the staff spending in all assets.
-WF, it: the cost of funds represented by the report of the responsibilities of interest all in all deposits.
- WK, it: the cost of the fixed asset represented by the report of the other administrative loads to the active total or the active basic salary. - Y1, it: specific variable of control of the portfolio of the activities of the bank represented by the ratio of own capital / total of assets (total Equity to assets).
- Y2, it: specific variable of control of the portfolio of the activities of the bank represented by the ratio of the net loans / the active total (total Loans to assets).
Having estimated the function (1), we can calculate the RP H-statistics which is not other but the three elasticity prices:
H=∑_(i=1)^3▒βi
H < 0: it is about a position of monopoly or about collusive oligopoly.
0 < H < 1: it is a situation of monopolistic competition;
H = 1: mean that it is about a situation of perfect competition
The estimation of the function of income and the calculation of the RP H-statistics, requires the check of the hypothesis of the long-term balance. In other words the comparison of the values of the statistics between countries requires that the banking systems of these last ones are in balance during all the considered period. The approach of the test of balance is almost the same that which for the calculation of the H-statistics. Indeed, the statistics of the test (E) is the sum of the coefficients ßi of the function (2):
Ln(ROA_it )= α 〖 β〗_1 Ln(W_(L,it) ) β_2 Ln(W_(F,it) ) β_3 (W_(k,it) ) (2)
γ_1 Ln (Y_(1,it) ) γ_2 Ln(Y_(2,it) ) ε_it
With :
E=∑_(i=1)^3▒β_i
The interpretation of this statistics is as follows: a value of E significantly different from zero implies that the market is not in balance because in the long term, the variation of the yields on assets does not relate to the variation of the prices of the inputs. However, in the presence of positive values of the PR H- statistics, Shaffer (2004) underlines that the rejection of the test of balance does not distort inevitably the inferences based on the results of the estimation of this indicator. He also underlines that the imbalance suggests that the industry develops dynamically. The interpretation of the statistics of Panzar and Rosse distinguish three important zones:
3.3. The Lerner index and the power of price fixation:
The power of market can be considered as the capacity to sell products over the marginal cost. The Lerner index is one of the most popular and the oldest indexes of market power. It is a direct measure of competitiveness for it measures the distance between the price and the marginal cost and afterward the capacity of a firm to demand a price upper to its marginal cost. From this index, the firm can determine its level of Markup (1/(1-L)) which is the percentage of margin between the sale price and the marginal cost (Cm), thus:
L= (P-C_m)/P→P=(1/(1-L)) C_m
The calculation of the index requires the estimation of the marginal cost of the product (equation 4) which in his turn requires the estimation of the translog of the function of the cost by a model with fixed effects (equation 3).
Ln cost_it=β_0 β_1 LnQ_it β_2/2 Ln (〖Q^2〗_it ) ∑_(K=1)^3▒〖γ_kt Ln(W_(k,it) ) ∑_(k=1)^3▒〖φ_k Ln Q_it Ln(W_(k,it) ) 〖∑^3〗_(k=1) ∑_(j=1)^3▒〖Ln(W_(k,it) )Ln(W_(j,it)) ε_it 〗〗〗 (3)
The measure of Lerner considers a function of cost which takes into account as explanatory variables: size of the company or the bank (total asset), the cost of work represented by the ratio of the cost of staff brought back to total asset, the cost of funds represented by the ratio of the of interest spending brought back to the total deposit and the cost of fixed asset expressed by the administrative charges and the other operating expenses brought back to the total asset.
Cm_it = □(Cost_it/Q_it ) [β_1 β_2 LnQ_it ∑_(k=1)^3▒〖φ_k Ln W_(k,it ) 〗] (4)
The variables used in the calculation of the cost are:
- Cost: The sum of the costs of staff, the interest expenses and the other administrative charges.
- Q it: total asset of the bank i in time t.
- WK: three charges of entrance defined above, labor cost, funds cost and the fixed asset cost.
〖Lerner 〗_it=(P_it-Cm_it)/P_it (5)
The Lerner index is generally included between 0 and 1.
- Lerner index = 0: mean a perfectly competitive behavior and the firm has no power of market.
- Lerner index close to 1: show the weakness of the competition at the price level and what the firm exercises a power of market thanks to a higher Mark-up.
An increase of the index can be explained by two elements: either the price increase or a decrease of the marginal cost of the company. Generally the index supplies positive values lower than the unit. However, he can register negative values which can be explained as a consequence of a very strong competition obliging the firms to propose a price lower than the marginal cost (Maudos and Of Guevara, on 2006), or they can correspond to the period of introduction on the market which is characterized by a very high rate of charges.
4. Estimation and results
This section presents an analysis of the power of market of both segments of the banking sector in this particular case the Islamic banks and their conventional colleagues, by using various indicators.
4.1. Data and sample
Our annual approach of data collection during period 2004-2009 based itself on annual reports extracted from the official Web sites of banks and database, Bankscope Database (2009) of Fitch-IBCA. At the level of this study, we use a sample of Islamic and conventional banks operating in the same countries with proportionally important market shares. The table 2.1 presents the studied panel which includes 62 Islamic banks and 128 conventional banks operating in 18 different countries.
Table 4.1: Composition of the studied panel
Country B. islamic B. conventional Sum/countries
Saudi Arabia 3 7 10
Bahrain 5 3 8
Bangladesh 5 18 23
Egypt 2 7 9
Indonesia 3 3 6
Iran 3 4 7
Jordan 2 8 10
Kuwait 3 6 9
Malaysia 11 15 26
Pakistan 6 3 9
Palestine 1 1 2
Qatar 2 5 7
Sudan 3 2 5
Thailand 1 9 10
Turkey 4 17 21
UAE 4 14 18
Yemen 3 4 7
Total by market 62 128 190
The table 2.2 present a comparison of the annual averages of the following criteria: total asset, the ratio of the loans in total asset (L / TA), ratio of own capital all in all active (E / TA), the ratio of the yield on the asset (Return On Asset: ROA) and the ratio of the yield on equity (Return On Equity: ROE).
Table 4.2 Comparison of the descriptive statistics between both samples.
year moy TA L/TA E/TA
market isl. Conv. isl. Conv. isl. Conv.
2004 2651.761 6896.67 59.79% 50.97% 18.90% 11.85%
2005 3514.183 8217.75 56.53% 54.14% 19.03% 11.67%
2006 3623.733 10008.45 56.65% 54.92% 19.59% 10.67%
2007 5043.005 12974.39 62.26% 54.25% 17.94% 10.51%
2008 6182.389 15046.10 57.48% 57.42% 16.49% 10.52%
2009 6830.645 15487.50 57.32% 56.09% 15.31% 10.63%
Average 4640.953 11438.48 58.34% 54.63% 17.88% 10.98%
Table 4.3 Comparison of the descriptive statistics between both samples.
year ROA ROE
market isl. Conv. isl. Conv.
2004 1.17% 2.55% 11.17% 20.80%
2005 2.42% 2.61% 19.99% 19,66%
2006 2.08% 1.86% 19.96% 22.73%
2007 2.42% 1.89% 16.49% 25.76%
2008 1.84% 1.71% 14.52% 15.06%
2009 0.87% 1.42% 9.14% 13.57%
Average 1.80% 2.00% 15.21% 19.60%
In spite of the interest growing in the industry of the Islamic financial services, in the countries of the sample the banks of this market remain less numerous than those conventional, and their average size in terms of total asset is lower.
During the period of study, the average of the ratio of the loans all in all asset of the Islamic banks is 58,34 % against 54,63 % for the conventional, and the average of the ratio of own capital all in all active is 17,88 % and 10,98 % respectively. The found figures indicate that the Islamic banks are better capitalized (Turk-Ariss, 2010a).
In terms of measures of profitability of the asset and the equities, we did not notice a big difference between both types of banks, the averages of the ROA of the Islamic banks and the conventional banks are respectively 1,80 % and 2,00 %. Contrary to the result made by Turk-Ariss (2010a, the equity of the conventional banks generates more profit than those of the Islamic banks. This is confirmed by a yield ratio of Islamic banks equity lower than that of the classic banks. The average of the ratio ROE, for studied period, is 15.21 % for the Islamic banks and 19.60 % for the other banks.
4.2. Measures of the concentration and the power of market
4.2.1. Calculation of concentration indexes
At the level of this under section, we estimate the competitive conditions of the Islamic and conventional banking markets for traditional measures of concentration: the ratios of concentration of 3 and 5 bigger banks according to their assets parts, deposits and loans granted in the respective banking sector and the Hirschmann-Herfindahl index calculated by adding the squares of the market shares of all the banks of every segment according to the total asset, total deposits and total granted loans.
Tables (2.4 and 2.5) illustrate a comparison of the ratios of concentration C3 and C5 of both markets for the period going from 2004 till 2009. The table (2.6) illustrates a comparison of the Hirschman-Herfindahl indexes with both Islamic and conventional markets according to three aforesaid criteria. By examining the table (2.4), we notice that for the conventional market, the ratios of concentration respective C3 is more or less stable. This stability reflects the global stability of the market. However, we record a remarkable reduction in 2007 and 2008 for three ratios then an upturn towards the increase in 2009.
Table 4.4 : Ratios of concentration C3 according to the total asset, total deposits and total granted loans
C3 Total actif C3 Dépôts C3 Prêts accordés
year M.islam M.conv M.islam M.conv M.islam M.conv
2004 0.4340 0.1516 0.4120 0.1561 0.4652 0.1970
2005 0.3937 0.1499 0.3615 0.1561 0.4120 0.1849
2006 0.3608 0.1471 0.3390 0.1456 0.3745 0.1791
2007 0.3267 0.1349 0.3183 0.1261 0.3514 0.1627
2008 0.3440 0.1309 0.3310 0.1283 0.3507 0.1415
2009 0.3260 0.1646 0.3105 0.1687 0.3596 0.1625
Average 0.3642 0.1465 0.3454 0.1468 0.3856 0.1713
For the conventional market, the average of the values of the ratio C3 for the total assets, the total of the deposits and the total of the granted loans is situated between 14 and 17 %. These values of concentration belong to the range [0; 50 %] and are weak in a way that all the values do not exceed the 20 % what implies that this market knows a very low concentration and a high fragmentation. In other words, the conventional banking market contains numerous competitors having each of the reduced market shares.
As regards the Islamic market, the average of the values of the ratio C3 for the total assets, the total of the deposits and the total of the granted loans, vary between 36 and 39 % and are higher than the values of the conventional market. However, the values of three ratios of concentration belong to the interval [0. 50 %] and decrease from one year to the other one. These values indicate that the concentration of this market weakens from one year to the other one and its fragmentation becomes more marked what leads to conclude that the Islamic market knows a big expansion that increases in the time and it’s due to the entry of new banks on the market.
The analysis of the ratios of concentration C5 of the conventional market shows a certain stability of this market. The average of the values of the ratio C5 for the total assets, the total of the deposits and the total of the granted loans, is situated between 22 and 25 %. The values calculated for 3 ratios are meanwhile [0.50 %] and do not exceed 29 %, this market is thus characterized by a weak concentration. For the Islamic market, the average of the values of the ratio C5 for the total assets the total of the deposits and the total of the granted loans, is situated between 50 and 56 %. We notice that most of the values fit meanwhile [50 %, 70] and are decreasing in the time what reflects that the Islamic market is a market of developing moderate concentration.
Table 4.5: The ratios of concentration C5 according to the total asset total ready deposits and total granted loans
C5 Total asset C5 Deposit C5 granted loans
year M.islam M.conv M.islam M.conv M.islam M.conv
2004 0.5981 0.2383 0.5585 0.2413 0.6371 0.2862
2005 0.5646 0.2323 0.5099 0.2328 0.5808 0.2599
2006 0.5333 0.2193 0.4918 0.2231 0.5506 0.2480
2007 0.5043 0.2072 0.4909 0.1993 0.5286 0.2309
2008 0.5102 0.2077 0.5023 0.2022 0.5315 0.2106
2009 0.4846 0.2526 0.4535 0.2591 0.5128 0.2435
Average 0.5325 0.2262 0.5012 0.2263 0.5569 0.2465
The table 2.4 and 2.5 results show that the ratios of concentration of the Islamic market are twice higher as those of the conventional market: they are around 36.5 % for the C3 and 53 % for C5. Whereas for the conventional market C3 is on 15.5 % average and C5 is on 23 % average. According to the analysis of the ratios of concentration, the conventional market is characterized by a very low concentration: C5 is widely lower than 50 %, while the Islamic market is averagely concentrated and it is dominated by some banks because C5 is between 50 and 70 %. However this concentration decreases more and more in the time thanks to the expansion of this sector and its increase. This result converges with the result found by Turk Ariss (2010a.
Having analyzed the ratios of concentration as first traditional measure of the structure of market, we pass in the analysis of the second measure which is good Hirschmann-Herfindahl index. The values of three indications HHI calculated for both markets at the level of the (2.6) table, are lower than 1000 except for a single value in 2004 for the Islamic market, it implies that these two markets are weakly concentrated according to the Muharrami, Matthews and Khabari (2006) and Gajurel (2010) results for the conventional banks.
Table 4.6 The Hirschmann Herfindahl index on the basis of the Total asset, total deposits, and total granted loans
HHI Total asset HHI Total deposit HHI Total granted loans
year M.islam M.conv M.islam M.conv M.islam M.conv
2004 866 248 830 259 1002 283
2005 771 239 679 244 864 265
2006 703 229 613 231 718 256
2007 639 221 613 219 673 244
2008 641 222 624 222 682 229
2009 597 282 541 294 668 283
Average 703 240 652 244 768 260
The calculation shows that the Islamic market registers values of HHI calculated on the basis of three criteria is three times higher than those obtained for the conventional market describing a more intense concentration in the Islamic market. The 2.6 table also shows a certain stability of the values calculated for the sample of the conventional banks, reflecting the stability of the competitive structure of this banking market. As for the Islamic market, the decrease of the values of the indication in time translates the expansion of the Islamic banking sector and the increase of the number of its financial institutions.
The results of the Hirshmann-Herfindahl index confirm what we obtained by interpreting the ratios of concentration C3 and C5. We can say that the Islamic banking industry is more concentrated than the conventional industry. It justifies that this new industry is in a phase of development and it has not reached the stage of a competition equal to that of the classic banking sector yet.
4.2.2. Calculation of the statistics of Panzar and Rosse
The statistics of Panzar-Rosse ( 1987 ) rest on the estimation of the total income expressed according to the labor cost, the cost of funds and cost of the fixed asset as well as two other specific variables of the control of the composition of the wallet of the bank activities (estimate the equation 1).
Before calculating the statistics of Panzar and Rosse (1987), we have to observe if the market operates in a long-term balance or not. This test is called the test of balance, it is calculated by the addition of the first three coefficients of the equation (2) having for dependent variable the logarithm of the asset yield (ROA). In first stage, we calculate the H-statistic for all the period studied for both markets, Islamic and conventional, as well as test of balance. Then, we calculate it for every year of the period of study for both market, this operation allows us to take into account the changes relative to the technological progress.
Global estimation of the statistics for all the period of study
The 2.7 table presents the test of balance of the statistics of Panzar and Rosse (1987) calculated respectively for the whole Islamic and conventional panel. The statistics of the test for both markets is negative and very close to zero. It is thus not significant. The long-term imbalance does not engender estimations biased by the PR H-statistics, we note that Shaffer ( 2004 ) underlines that the rejection of the test of balance does not distort inevitably the inferences based on the results of the estimation of this indicator because the hypothesis of the long-term balance is not strictly necessary in the presence of the positive values of the statistics (the values obtained at the level of our study are quite positive during the global estimation as well as during the annual estimations). He also underlines that the imbalance suggests a dynamic development of the industry.
Table 4.7 : Result of the test of balance
V. Dépendant Ln (1 ROA)
V.Indépendant M. islam. M.conv.
Ln (WL) 0.0059
(0.0028)** -0.0016
(-0.81)
Ln(WF) -0.0017
(0.0018) -0.0028
(-1.44)
Ln(WK) 0.00077
(0.0014) -0.0028
(-1.16)
Ln(Y1) -0.0001
(0.003) 0.0077
(1.48)***
Ln(Y2) -0.0036
(0.003) 0.0061
(1.73)*
Cons 0.0377
(0.014)*** 0.0104
(0.67)
E-statistic 0.058 -0.0072
The test of balance is translated by the estimation for a model with fixed effects of a function having for dependent variable Logarithm of (1 ROA, and the following independent variables: Ln ( WL): log of the ratio cost of staff / total asset which represents the working cost, Ln ( WF): log of the ratio of the interest charges/ total of the deposits which represents the cost of funds Ln ( Wk): the log of the ratio of the other products and the administrative charges/ active total which represents the cost of the fixed asset as well as two specific variables of control of the wallet of the activities of the bank Ln ( Y1 ): the logarithm of the ratio of equity/ total of assets and Ln ( Y2): the logarithm of the ratio of the granted loans / the active total. The values in brackets represent the statistics of Student. *** significance to 1 %, ** significance is 5 %, * significance in 10 %.
The statistics calculated for both samples belongs to the interval [ 0-1 ], we can thus assert that both markets are in a situation of monopolistic competition correspondingly with the results of Vesala ( 1995 ), Murjan and Ruza (2000), Will Adorn and al ( 2006 ), Abdul Majid and Sufian (2007), Turk-Ariss (2010a), Khan (2009) and Gajurel (2010). According to the2.8 table which presents the result of the estimation of the equation (1) relative to the calculation of the PR H-statistics, we notice that the value of the H-statistics of the Islamic panel is weaker than the conventional sample one: it is equal to 39.56 % it is 24.81 % for the Islamic banking sector and 55.91 % for the classic banking sector. The Islamic market thus turns out more concentrated and it can be only due to its embryonic age and to its activity youth with regard to the classic market.
Table 4.8 : Calculation of RP H-statistic
V.dépendant Ln TR : total revenu logarithm
V.indépendant M. islam. M.conv.
Ln WL -0.5486
(0.07)*** 0.1299
(1.34)***
LnWF 0.1821
(0.044)*** 0.3068
(8.17)***
LnWK 0.616
(0.34)*** 0.1223
(3.35)***
LnY1 -0.0438
(0.0645) 0.0992
(2.02)***
LnY2 0.495
(0.072)*** 0.2600
(2.40)***
Cons 0.3084
(0.339) 0.0184
(0.04)
RP-H 0.2481 0.5591
The (2.8 ) table presents the estimation result for a model of the function to fixed effects having for dependent variable Logarithm of the total income expressed by the ratio (interest revenues revenues others than from interest) / total asset, and the following independent variables: Ln ( WL): log of the ratio cost of staff / total asset which represents the working cost, Ln ( WF): log of the ratio of the interest charges / total of the deposits which represents the cost of funds Ln ( Wk): the log of the ratio of the other products and the administrative charges/ the active total which represents the cost of the fixed asset as well as two specific variables of control of the wallet of the activities of the bank Ln ( Y1 ): the logarithm of the ratio of equity/ total of assets and Ln ( Y2): the logarithm of the ratio of the granted loans / the active total. The values in brackets represent the statistics of Student.. *** Significance in 1 %, ** Significance is 5 %, * Significance in 10 %. (RP- H the sum of the coefficients of Lnwl, LnWf and LnWk).
Annual estimation of the statistics of Panzar and Rosse
The annual calculation of the statistics of Panzar and Rosse for the analysis of the evolution of the competitive conditions allows taking into account the effect of the technological changes on the structure of market. This method gets us a statistics for every sample and for every year of the period of analysis. The estimation of the equation (2) relative to the test of balance gives the results illustrated by the table which follows.
Table 2.9 : Results of the test of balance per annum
Year M.islam. M.conv.
2004 0.00341 -0.00514
2005 0.00627 -0.00705
2006 0.01057 -0.01066
2007 0.00278 -0.00377
2008 0.00356 -0.00377
2009 -0.00297 -0.00382
(2)The display of the results of every annual estimation of the statistics accompanied the test of balance is very voluminous: we thus limit ourselves, in what follows by the presentation of two summary tables the first for the test of balance and the second supplies the annual values of RP-H for each of the markets.
The results presented in the 2.9 table show that all the values found for both markets are very close to zero what implies that both segments of banking market: Islamic and conventional are in long-term imbalance. We explained at the level of the global estimation of this statistics that we can neglect the hypothesis of long-term balance when the values H are positive and by basing it itself on the interpretation of Shaffer (2004).
Table 2.10 : The RP-H statistics per annum
year M.islam. M.conv.
2004 0.0512 0.6622
2005 0.2194 0.6064
2006 0.3858 0.5498
2007 0.4903 0.6068
2008 0.2944 0.6422
2009 0.2207 0.7568
Average 0.2770 0.6373
The 2.13 table presents a comparison of the RP H-statistics calculated for both markets from 2004 till 2009. We notice a certain stability of the values registered for the conventional market during the first 5 years by the period of study (chart 2.4), the values vary of 54.98 % and 66.22 % with an average equal in 61.34 %. This stability of the values of the statistics reflects the stability of the level of competition on this market whereas the increase noted in 2009 can be interpreted as an evolution of the monopolistic competition and the link of the situation of perfect competition.
As regards the Islamic market, with the exception of the value registered for the first year by the study, we can say that it is the market which knows a situation of monopolistic competition with oligopolistic tendency in the sense that the market is dominated by a small number of banks. We notice an increase of RP H in 2006 and in 2007 then a relapse in 2008 and 2009. These reports converge with what we found during the global estimation of the H-statistics and confirm the situation of monopolistic competition as the competitive situation for each of the markets with more concentration in the Islamic banking sector it is closer in the monopoly position than in the situation of perfect competition.
The found results are on-line with those brought backby previous studies such as Vesala ( 1995 ), Murjan and Ruza ( 2002 ), Will Counter and al ( 2006 ), Abdul Majid and Sufian ( 2007 ), Khan ( 2009 ), Gajurel ( 2010 ) for the conventional banks and specially those of Weill ( 2010 ) and Turk-Ariss (2010a and suggest that the monopolistic competition which is characterized by the domination of some banks on all the sector, describes best the competitive situation of both Islamic and conventional markets. However, the RP H-statistics of the conventional market is higher than that of the Islamic banking market, this result diverges with the result of Turk-Ariss (2010a) and Weill (2010).
4.2.3. Calculation of The indication of Lerner
The Lerner index is a measure of power of market which ensues from the model of imperfect competition supposing the narrow link between the prices and the elasticity of the demand of the fact that it measures the distance between the observed price and the competitive price represented by the marginal cost. The limitation in this degree of power depends on the elasticity of the demand with regard to the price. The more the elasticity is strong the more the market price is close to the marginal cost. So, the index measures the capacity of a bank to increase its price with regard to its marginal cost.
The Lerner index varies between zero and one: it is worth zero when the price equals the marginal cost, the bank has, thus, no effect on the prices. The more the index approaches 1, the more the price covers the marginal cost and the more the bank power of market increases and its effect on the prices increases. However, negative values can exist and be interpreted as a sign of an intense competition obliging the bank to propose a price lower than the marginal cost or that corresponds to the period of the introduction of the bank on the market. The coefficients obtained further to the estimation of the function of cost presented by the equation (3) allow us to calculate the marginal cost of the bank illustrated by the equation (4). The passing by these two stages is necessary to calculate the Lerner index which is not other one but the distance between the price and the marginal cost (equation 5).
Table 2.11 :The Lerner index per annum
Year M. islam. M. conv
2004 0.9500 0.3005
2005 0.9460 0.3253
2006 0.9371 0.2907
2007 0.9378 0.2953
2008 0.9443 0.2921
2009 0.9485 0.3700
The 2.11 table summarizes three aforesaid stages above and presents the annual averages of the Lerner index calculated for every type of bank. The average index of the Islamic market for all the period is 94.39 % with annual averages which vary between 93.71 % and 95 % as well as it is 31.23 % for the conventional market what converges with Anzoategui, Peria and Rocho ( 2010 ) and its annual averages vary between 29.07 % and 37 % which registers a hanging reduction during 2006, 2007 and 2008. The period when the Lerner index of the conventional banks registered a reduction, coincides with the period of the subprime mortgage crisis, thus we can report the reduction of the classic banks market power to this crisis as the case of the Thai banks during the financial crisis graft 1993 and 1998 (Lahet and Lapteacru, on 2010).
According to the 2.15 table which summarizes the annual averages of the values of the Lerner index, we notice that the Islamic market registers three times higher values than those calculated for the conventional market. The Islamic banks have a power of market and can influence the prices of goods and services offered on the market, in contrary to the classic banking institutions which are characterized by their atomicity. It can be reported to the reduced number of its financial institutions with regard to the number of the classic banks.
This report diverges with the results found by Weill (2010) who showed the non-existence of a significant difference between both types of banks power of market and it also showed that the Islamic banks have less power of market than their conventional colleagues. At this level our sample is more representative because it includes 62 Islamic banks while that of Weil contains 34 banks.
Within the framework of the measure and of the analysis of the banking competition the traditional indicators of competition showed that the Islamic market is more concentrated than the conventional market while staying both in a situation of monopolistic competition. The measures of the new approach of the industrial organization through the RP H-statistics confirm the situation of monopolistic competition in both markets. The Lerner index allows concluding that the Islamic market benefits of a power of market higher than that of the classic market. Therefore the empirical study of power of market confirmed our hypotheses of departure which stipulate a concentration and a power of market higher at the level of the Islamic banking sector with regard to that conventional.
5. Conclusion
In this article we examined the banking sector market structure and power and its competitive conditions for the Islamic and conventional banks. The comparison between the competitive conditions of both segment of banking market was realized through an analysis on one hand traditional indicators of competition such as the ratios of concentrations and the Hirschman-Herfindahl index and the indicators of structure and power of market on the other hand such as Panzar and Rosse statistics and the Lerner index.
It emerges from it that the Islamic banks, according to the hypothesis of departure, operate in a more concentrated market and being one degree of power of market higher than their conventional competitors while staying both in a situation of monopolistic competition. It is necessary to note that the Islamic market shows an oligopolistic tendency, it justifies that this new industry is in a phase of development and it has not reached a stage of a competition equal to that of the classic banking sector yet. The found results are on-line with those reported by previous studies such as Vesala ( 1995 ), Murjan and Ruza ( 2002 ), Parera and Al (2006), Abdul Majid and Sufian ( 2007 ), Khan ( 2009 ), Gajurel ( 2010 ) for the conventional banks and specially those of Weill ( 2010 ) and Turk-Ariss (2010a) and suggest that the monopolistic competition which is characterized by the domination of some banks on all the sector, describes best the competitive situation of both Islamic and conventional markets. However, the RP H-statistics of the conventional market is higher than that of the Islamic banking market, this result diverges with the result of Turk-Ariss (2010a) & Weill (2010).
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More Less | | cardiology, psychology, stomatology, textile | | Years of translation experience: 8. Registered at ProZ.com: Mar 2012. | | N/A | French to Arabic (Tunisia.FLSHS)
Arabic to French (Tunisia/ Faculté des lettres et sciences humaines)
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Born in 3rd of July 1978 in Bizerte Tunisia.
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