Competition in the banking industry

rival in the banking patienceThe banking brass of a country plays a vital role in societal welf atomic cast 18 of the people in the country and of people of the world in everyday. It offers services to enterprises and consumers to down the stairstake their business activities and to easily per phase angle their day-to-day transactions. It is required to ensure an economical snuff iting of the banking remains otherwise, a dull and fake banking system brings about an ultimate threat of potential for fiscal instability. That is the causa why the argument in financial area is of much impressiveness. The importance is for m either powers i.e. it relates to the efficiency, quality and innovation of the production of financial services. Most importantly, it helps in taking cargonful decisions in policy making for banks (Claessens and Laevens, 2003).In new-made geezerhood, a lot of research work has been carried out, investigating the nature of contention in the banking pains a capacious with the form of rivalry, elements affecting the argument and the make of contention on other securities industry factors on micro take as well as on macro economic level.An bill for the vast amount of studies on this topic is that tilt enkindle non be measured directly imputable to the lack of detailed selective information on legal injurys and lives of the various banking products (Bikker et al., 2007). This topic has alike gained popularity among bankers, economists and policy makers because of globalisation, relaxation method of financial trade place places and banking harmonization followly everywhere the world, e circumscribedly in the European Union.Since early 90s, in that obeisance argon a lot of regulatory metamorphoses discover in the banking industry in order to achieve the establishment of a single, agonistical securities industry in the financial sector of Europe. It was initially triggered with the capital punishment of the Second Banking Coordination Directive defining conditions for Single Banking License.As a consequence, presentation barriers give birth been removed substantially for the new entrants increasing competition, coupled with a world-shaking integrating process. The intuition behind this was Market Contestability a market is contestable if there are no barriers to entry, exit is absolutely gratuitous and the prices are highly elastic to leases for industry output. The key idea is that a firm whitethorn be compelled to be much hawkish and efficient by the prospect of new entrants (Allen and Engert, 2007). Further more(prenominal), embody little exit hold still fors that if a firm enters into a new market and hence decides to withdraw, it is required to chance sunk entry costs. These features insure that even if a market has a small identification turn of active firms, it is still effectively contestable and war-ridden (Nathan A. and Neave E., 1989).Moreover, the pro- matched deregulation process has appendd the level of competition (Cetorelli, 2004), particularly in non-traditional and non- worry bearing areas of banking activity (Goddard et al. 2001).Trivieri F. (2005) documents that in the course of the 1990s, the Italian banking system chthonicwent intemperate changes at normative and institutional levels, which led among other things to a signifi beart relaxation of the entry barriers, to the liberalisation of bank branching, to the redefinition of ownership social system and to a walloping number of mergers and acquisitions.The set up of these transformations and, in particular, of those linked to the process of consolidation have been studied by many authors (see, among others Resti, 1997 Angelini and Cetorelli, 2000 Messori, 2001 Sapienza, 2002 Focarelli et al., 2002 Focarelli and Panetta, 2003). concord to European key Bank 1999, 29 part banks had been merged or shrunk amongst 1985 and 1997. In Italian banking industry, the Se cond Banking Directive was implemented in 1993, followed by a 20 percent reduction in the number of banks as a result of consolidation. It is ob managed that competition has been change magnituded in recent historic period in European banking markets which is likewise generally true for Italy.Angelini and Cetorelli (2000) cite that a rise in the competition is easily found in European banking markets during recent years. Danthine, Giavazzi, Vives and von Thadden (1999) report a somewhat generalized decrease in banks net interest margins across Europe during the 1990s. Consistent with the European evidence, a declining trend in bank margins is also observed across distinguishable markets in Italy.This paper focuses only on the banking industry of Italy and analyzes the evaluation of hawkish conditions, nature and the degree of competition in the Italian banking industry exploitation firm-level balance sheet entropy.In this paper, we explore more thoroughly the hawkish nature and degree of competition in the Italian banking industry by adopting a methodology demonstrable in existential industrial presidency and employ extensively in banking. Further more, we exit compare our results with former results to find out that whether the degree of competition has been increase or it has been as alike(p) as it was in the past.The setup of the remainder of this paper is as follows. Section 2 contains some important information about structure and features of a war-ridden banking industry which helps in understanding the competition more thoroughly. Next Section 3 introduces the original Panzar-Rosse vex along with the antecedent studies in the field. Section 4 gives a brief explanation of the general Panzar and Rosse copy. This section also shows the interpretation of the H-statistic along with the description of the testing guessing. pursual Section 5 deals with the data-based manikin used in this consider including long-run offset test. This section also contains the banks selective information used for the empirical illustration for our theoretical findings. Finally in the last Section 6 empirical results and conclusion is discussed.OPTIMAL COMPETITIVE STRUCTURE OF THE pious platitudeING SYSTEMAccording to Northcott C. (2004), competition improves efficiency and growth in the banking sector nonwithstanding market power or concentration is necessary for stability in the industry. Moreover, belligerent environment promotes productive and allocative efficiency leading towards economies of scale while market power improves credit availability, stability, quality of banks loan portfolios, screening of loans and monitoring them.As a result, market power should not be eliminated, that quite used to facilitate an environment that promotes competitive behaviour.FEATURES OF A COMPETITIVE BANKING intentnessConcentration weakens competition by fostering collusive behaviour among firms. increase market concentration was foun d to be associated with high prices and considerableer than prevalent profits (Bain, 1951). Smirlock (1985) and Evanoff and Fortier (1988) argue that higher profits in concentrated markets could be the result of greater productive efficiency. Berger (1995) finds some evidence that the efficiency possible action holds in US banking. In Europe, on the other hand, morphologic factors appeared to be more important and the SCP hypothesis seemed to hold (Goddard et al., 2001).If a well-developed financial system is provided then contestability improves with new entrants. Contestability is not necessarily related to concentration or the number of banks. Concentration and competition can exist together because of the presence of asymmetric information and branches and the effect and use of new technologies. (Northcott C, 2004)LITERATURE revue AND THEORETICAL ISSUESAccording to Bikker and Haaf (2000), initially the economic literature on the screw of competition in the industrial sec tor can be shared out into two main categories geomorphological approach and non-structural approach. Structural approach can be further divided into two main paradigms.First casing of structural approach is Structure-Conduct-Performance (SCP) paradigm, which make outs us that the degree of competition is determined by the structural characteristics of the market, such as, number of firms, size of the firms, etc. The SCP was developed in the early 1950s by Mason (1939) and Bain (1951). Bain (1951) constructs the market power hypothesis that collusive behaviour is initiated by high concentration which results in large profits for firms. Later, Stigler (1964) and Demsetz propose efficiency hypothesis in contrast of mark power hypothesis stating that the efficiency of bigger firms may be the reason for high concentration instead of collusive behaviour of firms, while during 1980s, Baumol, Panzar and Willig (1983) var. contestability hypothesis. Their hypothesis states that if entr y and exit barriers are relaxed then competition may be prevailed (Mkrtchyan A. 2005).Second approach is Efficient-Structure-Hypothesis (ESH), which states that greater concentration in the industry not only increases the level of efficiency in the sector but also increases the degree of competition in that sector.Non-structural approach is based on describing the nature of competition in the context of the studies of New Economic industrial Organization (NIEO). It stirs non-structural models to analyse the competition in markets which do not rely on the markets structure. Particularly, Klein (1971), Baumol, Panzar, and Willig 1982 provide a surmise that shows that market competitiveness can be inferred ir leverive of the structure of the market.NIEO studies include Iwata pattern (1974), Brasnahan Model (1982), Rosse and Panzar (1977), Panzar and Rosse (1982), Panzar and Rosse Model (1987), etc. Non-structural method or firms enter-output cost studies have gained more popularit y than the structural approach among academics, researchers, analysts and policy makers. Particularly Panzar and Rosse model (1987) is the most widely used and is very popular model for competition.Duncan (2003) mentions that the Panzar and Rosse (P-R) model provides a comprehensive and plain method to calculate the competition. It does not require intensive data as compared to other models and has been firmly related to theoretical side. The information required for this model is easily available as it calculates the sum of the factor prices elasticities portendd from a decrease form of receipts function.The Rosse-Panzar test has been developed to examine competitive conditions in the light of the contestability theory (Rosse and Panzar, 1977 1982 1987). This approach measures the degree of competition by analyzing how from each virtuoso banks tax incomes react to changes in infix prices. It has primarily emerged to test market conditions that wrap up all spectrums of compe titiveness away from the restrictions brought about by the structural concepts. Basically, it depends on the consanguinity between gross tax incomes of the firm and the change in its input prices by using a statistic which is called the H-statistics that measures the sum of elasticities of total revenue with approve to each input price. As this approach includes the revenue equivalence so for banks, mainly the revenues are interest revenue. In this approach, h-statistics is used to measure the degree of competition. The H-statistics testament tell us the responsiveness of revenues to the changes in input prices. If h-statistics is less than or pit to nothing then there will be monopoly, if it is between secret code and one then there will be monopolistic competition and if it is equal to one then there will be better competition (Greenberg J. and Simbanegavi W.).This approach is preferred when testing the data of different individual banks. Moreover, P-R approach yields similar results without any ambiguity as it has clearly restraind hypotheses with detail interpretations.PREVIOUS GENERAL STUDIES nigh BANK COMPETITIONRearrange the literature review according to the claessens and neave.A great number of papers have been written on investigating competition in the banking industry using Panzar and Rosse model (1987). But the motivations for analyzing the nature of the competition are vastly varied like contribution of institutional and structural factors, growth, regions, stability, financing, efficiency, contestability, consolidation, cross-border capital flows, risks etc.The summary of the previous full treatment and their findings can be seen in the Appendix Table 1.Panzar J. and Rosse J. (1987) develop test for Monopoly and use running(a) regression model to estimate the H-statistic for the newspaper industry, reporting that it is vague to cerebrate that the newspaper firms earn oligopoly profits. Looking at the cross-country studies carri ed out in the EU banking markets, one of the earliest compendium is undertaken by Molyneux et al. (1994) who test the Panzar-Rosse statistics on a sample of banks in France, Germany, Italy, Spain and the UK for the period 1986-89. Results indicate monopolistic competition in all countries except Italy where the monopoly hypothesis can not be rejected.Shaffer and Disalvo (1994) use this test to analyze the data of a duopoly banking market in south central Pennsylvania to exercise the procedure for concentration and competitive conduct.Waleed Murjan and Cristina Ruza (2002) examine the Arab Middle Eastern banking markets with this test concluding that the banking sector is more competitive in non-oil-producing countries than the banking industry in oil-producing countries.Gelos and Roldos (2002) apply this method on 8 different countries of Latin America and Europe, finding that market contestability prevents the competitive pressure from declining which can happen because of the con solidation while Claessens and Laeven (2003) process the data of 50 countries obtaining the said(prenominal) results.Bikker and Haaf (2002) assess the banking industry in 17 European countries and six countries that are outside of Europe comparing competitive conditions and market structure.Goddard, J. and Wilson, J. (2006) report misspecification bias in the revenue equation for the banking sectors of 19 developed and developing countries. They suggested a dynamic revenue equation for unbiased regard rather than fixed effects estimation which is severely biased towards zero. gibibyte (1984) and Berger (1995) test the data for 8,235 banks in 23 developed nations producing the results that a higher degree of market power has less risk exposure.Yuan Y. (2005) assesses the competition in Chinese Banking sector and comes up with the results that China already has had dead competitive condition before new foreign entrants and it still has the same situation.Duncan D. (2003) presents t he empirical assessment of the market structure of the Jamaican banking sector and competitive trends in the market finding monopolistic behaviour.Al-Muharrami S. et al. (2006) take GCC Arab countries into observation and suggest that Kuwait, Saudi Arabia and the UAE operate under stark(a) competition and Bahrain and Qatar operate under conditions of monopolistic competition.Nathan A. and Neave E. (1989) exercise the test on Canadian financial industry and reject the hypothesis of monopoly power in Canadas financial system.PREVIOUS STUDIES ABOUT COMPETITION IN ITALIAN BANKING INDUSTRYA great number of studies on competition in financial sector of EU countries have been reported which also include Italy in general. But there are also some research-papers which are produced specifically for Italy. Some of them areCetorelli N. and Angelini P. (2000) battlefield the case of the Italian banking industry and cite that competitive conditions have alter substantially after 1992, and it i s believed that the introduction of the Single Banking License in 1993 also helps fostering the competitive behaviour in Italian banking industry.DellAriccia G. and Bonaccorsi E. (2003) investigate the relationship between bank competition and firm creation. They document that the effects of competition in the banking sector on the creation of firms in the non-financial sector are less favourable to the emergence of new firms in industries where information asymmetries are greater.Coccorese P. (2002) rejects the theory that competition can be easily reduced by the collusive behaviour of the firms, and comes up with the conclusion that strong concentration does not necessarily prevent competition among firms.Trivieri F. (2005) compares the banks involved in the cross-ownership and banks that are not involved. He finds that Italian banks involved in cross-ownership are less competitive than the banks which are not involved in cross-ownership, thus proving cross-ownership decreases co mpetition.GENERALIZED PANZAR AND ROSSE (1987) bettermentP-R model assumptionsFirstly, there are some assumptions and conditions in which Panzar and Rosse model works. The model supposes that banks operate in long run symmetry. Although Goddard Wilson (2006), documents that this condition is not necessitate any more if a correctly specified dynamic revenue equation is adopted which permits virtually unbiased estimation of the H-statistic. This eliminates the need for a market equilibrium assumption, but incorpo rank instantaneous adjustments as a special case. So in this paper long run equilibrium get holds. another(prenominal) assumption is that the market participants affect the performance of the banks by their actions. Another postulate is that the price elasticity of demand is greater than unity. Moreover, the model posits that there is a homogenous cost structure. Furthermore, profits are exploitd to obtain the equilibrium number of banks and the equilibrium output. In lon g rum equilibrium, it is known that banks maximise their profits when, marginal revenue equals to marginal cost (Bikker and Haaf, 2000). Trivieri F. (2005) also adds that the banks are treated as single product firms which mainly provide mediation services.EXPLANATION OF PR MODELClaessens and Laeven (2003) cite that the Panzar and Rosse model studies the impact of changes in factor input prices reflected in equilibrium revenues by a specific bank.Bikker and Haaf (2000) write that Panzar and Rosse model gives simple models for oligopolistic, competitive and monopolistic markets. This test works on the reduced form revenue equation and uses H-statistics. This H-statistics can tell us not only the nature of competition but also gives information about the degree of the competition. H-statistics if measures between 0 and 1, it is monopolistic competition, 0 is considered as monopoly and 1 as perfect competition. Here, a general banking market model is used, which determines equilibrium output and the equilibrium number of banks by maximising profits. The model is also able to allow for bank-specific varyings in the equation.According to Bikker and Haaf (2000), in the long run equilibrium, it is known that banks maximise their profits at the break-even straits. The break-even point is where marginal revenue equals marginal cost. So, the bank i maximises its profits, where marginal revenue equals marginal cost(1)Ri refers to revenues and Ci to costs of bank i (the vizor denoting marginal), xi is the output of bank i, n is the number of banks, wi is a sender of m factor input prices of bank i, zi is a sender of exogenic variables that slant the banks revenue function, ti is a vector of exogenous variables that shift the banks cost function. Secondly, it means that in equilibrium at the market level, the zero profit constraint holds (Bikker and Haaf, 2000)(2)Variables marked with an asterisk (*) represent equilibrium values. Panzar and Rosse subtend a measur e of competition H as the sum of the elasticities of the reduced-form revenues with respect to factor prices (Bikker and Haaf, 2000)(3)According to Khan, M. (2009), it measures the percentage change in (equilibrium) revenue due to a one percent change in all input factor prices (change in cost). From duality theory, it is known that one percent increase in factor prices will lead to one percent up shift in cost function. The impact of this shift in cost function on the (equilibrium) revenue of the banks is directly related to the degree of competition in the banking sector.Bikker and Haaf (2000) further explain that Panzar and Rosse prove that under monopoly or under perfectly collusive oligopoly, an increase in input prices will increase marginal costs, reduce equilibrium output and subsequently reduce revenues hence H will be zero or negative. An increase in input prices raises some(prenominal) marginal and intermediate costs by an equal proportion as the cost is homogeneous of degree one in input prices without altering the optimal output of any individual firm. glide by of some firms increases the demand faced by each of the remaining firms, thereby leading to an increase in prices and total revenues by as same amount as the rise in costs, resulting perfect competition where H-statistic is domineering but not greater than unity. In this case marginal and average cost will be increased by the rise in input prices (Nathan A. and Neave H., 1989).INTERPRETATION OF H-STATISTICSPanzar and Rosse prove that, under monopolistic competition, H is between zero and unity. H is a decreasing function of the perceived demand elasticity, so H increases with the competitiveness of the banking industry. As a result, this H-statistic can serve as a continuous interpretation of the competitiveness. Although this is not mentioned by Panzar and Rosse (1987) but with some assumptions this continuous interpretation is correct. So, the testable hypotheses are The banking indu stry is characterised by monopoly for H=0, monopolistic competition for 0HYPOTHESIS TESTINGKhan, M. (2009) mentionsTwo-sided consummate Competition TestMaintaining the long run equilibrium postulate, if banks are operational under perfect competition, a one percent change in cost will lead to a one percent change in revenues. Output will not be changed if the demand function is perfectly elastic under perfect competition, output price and cost both will increase by the same extent. This implies that under perfect competition, H-statistic will be equal to one. Statistically, we will test the following hypothesis.H0 H = 1 Perfect competition prevails in the banking sector.H1 H 1 on that point is no perfect competition in the banking sector.Two-sided Monopolistic Competition TestIf banks are run in monopolistically competitive environment, one percent increase in cost will lead to less than one percent increase in revenue as the bank faces sensibly inelastic demand function. St atistically, we will test the following hypothesis.H0 0 H1 H 0 or H 1 Banks are not operating in a monopolistic competition environment.One-sided Monopoly Test step theory of market structure suggests that the sum of factor input price elasticities should be less than zero if the underlying market structure is monopoly. Statistically, we will test the following hypothesis.H0 H 0 Banks are operating in a monopoly condition.H1 H 0 Banks are not operating in a monopoly condition.(Khan M., 2009)EMPIRICAL FRAMEWORK AND METHODOLOGYThe test is robust with any definition of market whether it is within the national boundaries or it is the global transnational banking industry because there is no need to specify a geographic market. Before testing, it is commonly necessary to obtain a reduced form of revenue equation which consists of revenue as a qualified variable, factor input prices as self-supporting variables and some controlled or firms specific factors. The fundamental equ ation is gist interest revenue = total cost + controlled variables + actus reus termThe panel data is used in the paper which is the data collected over multiple meter periods. It is the combination of cross-sectional and term series dimensions. Hence, it can be derived asCi = a + Byi + Ei (4)Ct = a + Byt + Et (5)Where, C is the dependent variable, a is constant term, B is the coefficient of the independent term, y is the independent variable and E is the error term. Combining both the equations (4) and (5), the final basic equation can be given asCit = a + Byit + Eit (6)But Panzar and Rosse define the H as the sum of the elasticities of the reduced-form revenues with respect to factor prices, so the econometric model of the Panzar and Rosse statistic may be delineated by the following equation(7)For i = 1,..I t = 1,TWhere, R is a measure of gross revenue. W is a vector of factor prices (the H statistic is given by the sum of the estimated coefficients of the variables in this v ector) S is a vector of scale variables X is a vector of exogenous and bank-specific variables that may shift the cost and revenue schedule, indicates the error term I is the total number of banks T is the number of periods observed (Trivieri, 2005). To calculate the sum of elasiticities, it is necessary to estimate the log unidimensional model instead of estimating a simple linear model that is the reason for taking the log of all the variables in equation (7).The sign of the variables of different costs and bank specific variables are unconditional showing a direct relationship to revenues (Trivieri, 2005).In this pooled regression, extra intercepts or dummies for time are used, but dummies for individuals are not included because of the operation of within- convocation-estimators. Because with-in-group estimator takes first difference and removes the individuals dummies variables by itself. Thus being a fixed effects model, it measures differences in intercepts for each group and the differences are compute by a separate dummy variable for each group (Trivieri, 2005).The use of fixed effects panel regression with time dummies allows collusive the relevant parameters of the empirical model. Furthermore, unobserved heterogeneity is controlled by the fixed effects too avoiding omitted variable problems (Trivieri, 2005).In this paper, the intermediation approach developed by Sealey and Lindley (1977), is followed which tells that deposits, labour and capital are inputs for the banks. The empirical model applied in this paper is asLGIRTA =B1LLABCOST + B2LCAPCOST + B3LFUNDCOST + B4LLTA + B5LBMIX(8)Where,LGIRTA = Log of Gross Interest Revenues over Total AssetsLLABCOST = Log of Labour factor priceLCAPCOST = Log of Capital liveLFUNDCOST = Log of Funding CostLLTA = Log of Loans to Total AssetsLBMIX = Log of Loans to Banks and Clients over Total LoansThis paper addresses the banking industry of Italy. The data includes 480 banks approximately, of all sizes in Italy. The data contains two different samples. First sample consists of the data from 1995 to 1997, total 3 years, and the second sample contains data from 1997 to 2000, total 3 years. We make a comparison and inference between the results obtained by these two samples through our empirical model and find out the competitive behaviour of Italian financial market.LONG RUN EQUILIBRIUM TESTAn important underlying condition of the H-statistic for competition is the long run equilibrium. Panzar and Rosse (1987) cite that this postulate is crucial for the cases of perfect competition and monopolistic competition. Though, it is not a fundamental assumption in the case of monopoly because when H is less than or equal to zero then it is a long run assumption for monopoly (Trivieri, 2005).Long run equilibrium test for the observations can be done with the prerequisite that competitive markets mate the return rates across firms, so that in equilibrium these rates should not be correlated wi th input prices (Trivieri, 2005).In our empirical model as in Shaffer (1982), this test can be carried out by re-estimating the equation with the proxy for the return on assets, ROA, as dependent variable in the calculation of H. In this context, H = 0 implies that the data are in long run equilibrium (Trivieri, 2005). The intuition behind this theory is that, return on assets, ROA, should not be related to input prices.De Bandt and Davis (1999), define the equilibrium condition as the state in which changes in banking sector are considered as gradual, long run equilibrium for the observations does not mean that competitive conditions remain the same and do not change through out the period of observations (Trivieri, 2005).Although it is inappropriate to use Rosse-Panzar test which is based on a dormant equilibrium framework, but in the real financial market, the equilibrium adjustments are less than instantaneous, resulting disequilibrium on some points in time or frequently, or a lways. Moreover, when it is known that the adjustments towards equilibrium are partial and not instantaneous then using fixed effects estimation for the static revenue equation will result in biased H-statistics toward zero (Goddard J. and Wilson J., 2006).For the long run equilibrium, we estimate the following equationLROA =B1LLABCOST + B2LCAPCOST + B3LFUNDCOST + B4LLTA + B5LBMIX(9)DATA AND attempt DESCRIPTIONThe empirical part of this paper uses an unbalanced panel data set on which the Panzar and Rosse methodology has been applied containing a range of Italian banking firms. The data and the samples used for the estimation of H indicator are provided by Dr. Leone Leonida, Queen Mary, University of London.The data used in this paper are yearly and refer to the period 1995-1997 (3 years) for the first sample. The first sample for the econometric analysis is made up of an unbalanced panel data of 480 financial institutions of all sizes, for a total of 1401 observations. The number of parameters is 487. The longest time series is 3 years long and the shortest time series is only 2 years long with 2 time dummies.The second sample covers the period of 1998-2000 (3 years) having 1330 number of observation from 474 banks of all sized. The number of parameters is 481. The longest time series is 3 years long and the shortest time series is 2 years long depicting unbalanced panel data with 2 time dummies.In the Appendix, Table 3 provides a summary of the definition of relevant dependent variable, independent variables, bank specific factors variables and control variables.LGIRTA is the log of gross interest revenue over total assets, which is used as dependent variable, also used by De Bandt and Davis (2000), and Trivieri F. (2005). Trivieri (2005) points out that according to Vesala (1995) and De Bandt and Davis (2000) it is the most appropriate pickaxe because it then represents a price equation and not the revenue equation. Moreover, our equation will be consiste nt with the conceptual structure used by the application of Panzar and Rosses statistic to the banking sector. The choice for taking only the interest part of the total revenue of banks is consistent with underlying notion of the P-R model that financial intermediation is the core business of most banks. However, Shaffer (1982) and Nathan and Neaves (1989) have included total revenue instead of only interest revenue because of the fact that banks have increased their non-interest activities and services which have started generating income other than interest. But s