Interactions Among Populations and Effects on Founding Rates: the Case of Financial Intermediary Institutions in Turkey: 1986-2005 (original) (raw)
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The history of the studies on traditional industrial economics goes back to 1940's. These studies (Mason, 1939; Bain, 1951) were in general conducted to provide information about market structure. The structure-conduct-performance (SCP) approach stemmed from these studies argues that, in the case of hindered market entry, the higher the concentration ratio and collusion among firms, the lower the level of competition in the market. Later on, a number of authors have contributed to the traditional SCP approach to improve it in a number of ways: The first hypothesis is called "the collusion hypothesis" and developed by Bain (1952); the second one was due to Demsetz (1973) and called the "efficient structure hypothesis." This study aims at testing the applicability of the SCP approaches using the data related to 23 Turkish commercial banks operating over the period 2008-2013. The empirical results have shown that the modified efficient structure hypothesis holds for the Turkish banking sector over the sample period.
Purpose – The purpose of this paper is to examine the development cycle of Brazilian banking sector during the lengthy period between 1889 and 2009, also identifying an equilibrium number of financial institutions based on the carrying capacity of the environment. Design/methodology/approach – The number of institutions in equilibrium is calculated based on the population density dependence model adopted under the organizational ecology theory. Quantitative data of founding and failure and qualitative data (interviews with the directors, officers and CEOs of selected companies) were used. Findings – In all three bank segments (commercial, investment and multiple), the total number of banks in operation on December 31, 2009 was below the carrying capacity. However, in the multiple bank segment, the gap between the actual and potential figures is slightly smaller. As indicated by the respondents, there is almost no room for newcomers in the major bank segments. In counterpart, there is still space for new arrivals in the mid-market bank sector. Research limitations/implications – The findings presented here may change, as carrying capacity is determined by political, legal and economic factors, including the availability of resources in niches and constraints imposed through laws, rules and other regulatory aspects. However, raising the life cycle of the entire population offers opportunities for future research on individual organizational trajectories, using new theoretical and methodological perspectives, such as dynamic capabilities and process theory. Practical implications – The main contribution of this paper lies in indicating the growth potential for banking institution populations in Brazil, and may be used not only by potential newcomers eager to enter the sector, but also as a tool for assessing antitrust policies. Originality/value – The development cycle of Brazilian financial institution populations is unknown, and carrying capacity is a construct less explored by academic literature, particularly in Brazil. This is a unique study since a demography of an entire banking population in a developing country does not exist, besides there is not such a financial institution like the multiple bank in Brazil.
Due to the complex and close interaction of banks with other economic units, any trouble in banking sector might have repercussion on the whole economy which makes the market structure and competition in banking sector as a cynosure. Business world is facing with gradually increasing competition. It seems that the existence of firms depends on the power and the advantage of their competitiveness. The purpose of this study is to analyze the competition structure and the market conditions of Turkish banking system for the periods 1997-2014. Despite the existence of a number of studies about competition in banking sector, there is still a lack of the studies which has been done with Lerner's Index. Due to this fact, Lerner’s Index is used in this study. Bank level determinants of Lerner Index are analyze using Panel Data Regression Method and were reached of actors effecting competitive behavior in Turkish Banking Sector.