Bank Competition and Banking System Stability - Research Paper Example

BANK COMPETITION AND BANKING SYSTEM STABILITY By Introduction The banking systems fall under the financial system of any defined economic setting or market place. The banking system regulates the manner in which funds exchange hands from one individual to another and from business to business (Ruiz-Roses, 2008). With reference to globalization and use of virtual means of sending and receiving funds, the banking system provides a platform that facilitates the exchange of funds. However, as economies around the globe strive for better management strategies to improve output, the banking system continues to face various challenges, some of which showcase instability in the system. In this research paper the stability of the banking system will be analyzed while at the same time considering competitiveness. Competition in the banking system can be measured through the consideration of key performance indicators. Some of the key performance indicators to test the competitive and stability of the banking system include return on assets, capital, equity, information ratio, and the interaction between deposits & loans (Jing, 2009). . The overall structure of this research paper considers and comprises of four sections. The first section comprises of the introduction section which provides an insight of the variables that will be tested, the approach of analysis, methods applied, and anticipated outcome. The second section of the research indicates the model to be tested as well as the hypothesis of the study. The section comprises of empirical framework which provides the in-depth analysis of the topic at hand. The third section is the data description section which states the data for use, the market explored, the source of the banking information to be tested, and statistics regarding the system under investigation. The fourth section comprises of the presentation and discussion section which provides descriptive analysis of the results of the model to be tested. The fourth section is designed to provide a detailed analysis of the topic through the consideration of the statistical output of the model. In this section, visual aid such as graphs and charts are used to present data in a comprehensible manner. The last section in this research will be the conclusion which is not considered a major section of the research. However, the conclusion is a vital section of the research as it provides a recap on the main points (Johansson, 2012). In the analysis of the data, this research paper considered the use of Eviews statistical software to provide regression analysis and visual or graphical representation of various variables considered. Considering that Eviews has various other alternatives such as SPSS and MS Excel, the merit of choosing Eviews is concerned primarily with manageable process of analyzing data and better graphical representations as compared to its alternatives. The criteria for inclusion considers data from 1988 to 2013. The raw data is collected from China’s banking system. The exclusion criterion considers China Mainland and does not consider Hong Kong banks. Although the economic interaction of China and Hong Kong have a close relationship and interdependency. However, the competitiveness and stability of the banks in the two regions does not compare with each other (Elsinger, Lehar, & Summer, 2006). Empirical Framework There are two major hypotheses that this research will aim at testing. These hypotheses include: 1. The Chinese banking system’s stability depends on the influence of capital on information ratio and return of assets 2. The competitiveness of Chinese banks depends on customer banking trends and relevance of capital to equity and return on assets. The two hypotheses aim at showing how competition and banking system stability depend on customer trends and capital investment. The information ratio variable on hypothesis one indicates the ability of manager’s to beat benchmarks (Chung, & Tongzon, 2004). Every manager in the banking system and/or other industries is entitled to making business decisions. Business decisions comprise of courses of action that managers take to improve productivity and to cut costs. Following the theory of the firm, a corporation seeks to make profits and grow its business foundation. However, for productivity to be valuable and optimal, the manager must ensure that his/her approach is able to beat certain benchmarks. Since the banking system comprises of many competitors and service users, different banks strategize on applying customized approaches to manage means of production. However, as the banking sector is a service industry, managers in this sector must make decisions that consider industry’s best practices at all times. By setting benchmarks, a manager is able to tell whether his/her approach in accumulation of surplus is competitive or under par. Considering statewide results, this research will test how capital investment relates and influences information ratio and return on assets. Nationally, Chinese banking sector stability can therefore be interpreted by running regressions considering capital, information ratio, and return on assets (Lemos, 2012). Since Eviews is the statistics software of choice in this case, the equation of testing hypothesis one is as follows; Capital c roa information ratio Since the analysis considers two hypotheses, the second hypothesis which connects customer trends with the role equity plays aims at identifying the stability of the banking system. When considering capital, corporations such as the publicly traded companies, trade shares/stock in order to raise additional funds for expansion of the companies. After trading shares, a corporation is able to generate capital for other investments. However, these investments relate with the company’s mission and goals. One among the company’s goals when trading shares is to increase capital which can be used to attract a market share for an additional service or product. However, the banking system involves the development of service packages such as accounts for deposits and provision of loans. Based on the interaction between how customers bank and how they request for loans (Gale, & Vives, 2002), the stability of the banking system can be measured based on how inputs relate with outputs. Inputs in the banking system can be interpreted as the amount of money customers are willing to deposit in their bank accounts with respect to various account types. Fixed accounts and other types of accounts are examples of service packages that banks extend to their customers. On the other hand, for banks to generate income, they require borrowers from whose loans they can generate interest from. The banks would therefore give loans from customer deposits and make profit from interests gathered from those loans. However, the hypothesis in this case intends to showcase how more of deposits and less of loans may affect the competitiveness of the banks. With no money to lend, a bank is unable to function as it would not have any source of income. Hence, for a banking system with higher deposits and no loans, its competitiveness can be easily be viewed as a competitive problems. To test for the interaction between customer trends of depositing and borrowing, capital, equity, and return on assets are correlated to showcase whether the hypothetical model compares with a corporations balance of trade (Yeung, 2009). The idea behind the connection of customer trends with capital, equity, and return on assets aims at analyzing whether there are anomalies in the manner in which banks generate revenue from assets while at the same time considering how profitability interacts with the rates of deposits and loans (Wu, & Chen, 2010). An anomaly is expected if the return on assets is high and the interaction between loans and deposits do not balance to support the banks’ return on assets. On the other hand, a bank with manageable or sustainable balance of trade between deposits and loans can experience operational anomalies if return on assets is too little. Anomalies, whether in favor or in favor or unfavorable of the banks revenue generation shows instability in the system (Yan, & Huang, 2008). The interaction between capital, equity, and return on assets uses the following Eviews function; Capital C Equity ROA The Eviews function above aims at showing the correlation among capital, equity, and return on assets. The significance of the correlation will be used to predict whether customer trends in borrowing and depositing support the models output. One assumption in this model is that a bank will only make profits if it attracts customer deposits and borrowers to generate revenues. Regardless of how much capital is needed, equity and return on assets much be generated from customer trends (Huang, 2012). The data for use in this analysis targets the Chinese banking system which relies heavily on how the current economic development within the nation. As the Chinese continue to invest heavily in various industries, the availability of affordable labor has attracted foreign companies to invest in the Chinese labor market (Johansson, 2012). Although the Chinese are not consumers of most of the products developed by foreign companies, the compensation of labor, acquisition and payment of materials, taxation, and personal banking are activities that require the input of a banking system (Roth, 1994). The data collected for this analysis considers China Mainland banking system and considers the operations of these banks from the year 1988 to 2013. Among the variables for testing in the analysis will include capital, equity, return on assets, and information ratio. These variables are tabulated and presented as raw data in Eviews. The variables are selected from a list of variables which affect the stability of the banking system as well as competition within the market place (Elsinger, Lehar, & Summer, 2006). The Chinese market place is a hub of activities where large sums of money have to be handled on a daily basis to support the economic ambition of the Chinese (Naylor, 2006). On the other hand, the manner in which customers deposit and borrow from the system is a consideration that will make use of the banking system’s capital and its influence on equity and return on investment (Carlson, & Mitchener, 2009). With loans and deposits considered, the competitiveness of the banking sector functions by lending and generating profits from deposits. Thus, for a banking system, competition is measured with reference to how much banks are able to attract depositing customers and borrowing clients (Kirdina, & Vernikov, 2013). With reference to equity, the analysis in this case makes use of equity as the stake owned by investors. This stake has to be managed and its value upheld in a successful banking system. Thus, while considering the effect of capital on return on assets, the level of equity also provides an insight on how capable the sector is at attracting investors (Bonin, 2012). Hence, as a bank’s operational stability is tested through the consideration of how it attracts investors and balances its inputs and outputs, return on assets can interpret whether the bank is competitive or not and whether the banking system is stable enough to sustain the operations from demanding customers and international banks. The criteria for inclusion takes China Mainland as a different entity as compared to Hong Kong (Kirdina, & Vernikov, 2013). Additionally, variables that do not add up to the current analysis such as residual value, labor, and so on are excluded from the regression analyses conducted herein. Graph 1: Capital, Equity, and ROA Graph 1 above shows the interaction among capital, equity, and return on assets. Since the regression analyses will attempt to showcase whether interaction of the variables indicates stability and/or competitiveness of the Chinese banking system. The above graph indicates the relationship among capital, equity, and return on assets (Yeung, 2009). Return on assets is considered an achievement that a corporation is able to generate returns from its investment on assets. Companies that are unable to generate enough returns on assets are deemed unstable and likely to collapse since they are unable to breakeven on time. With reference to the interaction between capital and equity, it is seen on the graph above that return on assets fluctuates around -2 and +2 points on the above graph. This trend shows a normal distribution of return on assets across the sample data. Additionally, the graph indicates that equity is high than capital. This situation shows that the capital generated from the system is less and the system relies heavily on customer equity (Prasad, 2009). Equity in banking comprises of the funds in reserves and in bankers checks that can be cashed and offered to borrowers. In this case, as graph 2 suggests, the funds in reserves or at the bank’s possession should be more such that it can supply the demand for loans and at the same time sustain short-term customer withdrawals. More loans than deposits indicate instability of the system and banks cannot survive without accumulating funds to loan out to customers (Brandt, 2007). Graph 2: Equity against Loans Presentation and Discussion Through running simple regressions to correlate capital, return on investment, and information ratio, Table 1 below shows regression output to test hypothesis 1 of this research which states that the Chinese banking system’s stability depends on the influence of capital on information ratio and return of assets. To test whether there is a correlation among these variables, the regression output shows standard deviation, R-squared, and or capital as measures for testing the model’s statistical significance. Table 1: Regression output for capital against ROA and IR. S.D. dependent Variable From table 1 above, it’s observed that the standard deviation of the dependent variable, capital, is 0.852922. The significance of the standard deviation to the data set is that it shows how much the data set’s entries deviate from the mean of the sample data. At 0, the standard deviation shows that there are not differences in the values of a data sample. Thus, the current standard deviation is less than 1.0 and more than 0.5 meaning that the deviation is statistically significant and has the potential of affecting the outcome of the regression analysis. Thus, while the competitiveness of Chinese banks may rely on return on assets and information ratio, the extent dependent variable is significant in that too low capital or too high capital would affect the output since managers would be able to beat benchmarks that information ratio relies on. On the other hand, information ratio and return on assets should indicate significance such that they are affected by changes in capital (Fai, 2006). In order to test the model for hypothesis 1, R2 in the regression analysis is used to indicate how close data is to the model. With reference to the value of 0.25385 showing that the variability of the data around its mean cannot be explained in the model. In this case, the data points are only explainable up to 25.8357%. Provided that the number of points to be assessed sis equivalent to the observations made, it is true to conclude under R2 value in this case cannot be considered a reliable point of explaining the variability of each data point. This means that the model under investigation does not provide room for relating all the data points with capital as the dependent variable. Thus, while the model sort to show how capital relates to or affects return on assets and information ratios, the model does not provide statistical significance reliable to indicate that changes in capital have a significance spread all around the data for the 25-years covered in the data set (Prasad, 2009). Table 2: Regression out on Capital against Equity and ROA From table 1 above, it’s observed that the standard deviation of the dependent variable, capital, is 0.897726. The significance of the standard deviation to the data set is that it shows how much the data set’s entries deviate from the mean of the sample data. As earlier stated, at 0, the standard deviation shows that there are no differences in the values of a data sample. Additionally, the current standard deviation is less than 1.0 and more than 0.5 deviation is statistically significant and has a probability of more than 0.00 and can affect the outcome of the regression analysis. Thus, while the competitiveness of Chinese banks may rely on equity and return, the extent dependent variable is significant in that too low capital or too high capital would affect the output since credited accounts must provide resource, finances, to facilitate borrowing. On the other hand, equity and return on assets should indicate significance such that they are affected by changes in capital (Ping, 2001). To test the model for hypothesis 2, R2 in the regression analysis is used to indicate how close data is fitting into the model. With reference to the value of 0.246455 showing that the variability of the data around its mean cannot be explained in the model. In this case, the data points are only explainable up to 24.6455%. The total points assessed is equivalent to the observations made, in this case 1464, it is significant to conclude that under R2 value of 0.246455 in this case is not significant considered that a reliable point of explaining the variability of each data point. The model tested does not provide room for relating all the data points with capital as the dependent variable. Thus, while the model sort to show that capital relates with equity and return on assets, stability of the banking system cannot be predicated accurately. The R2 value misses more than 75% of the data points meaning that the significance level is too low to indicate that each data set is closely related to the depend variable. Hence as hypothesis 2 states, capital does not influence equity and return on assets significantly enough to validate the model for hypothesis 2. Conclusions The Chinese banking system’s stability depends on the influence of capital on information ratio and return of assets. While the competitiveness of Chinese banks may rely on return on assets and information ratio, the extent dependent variable is significant in that too low capital or too high capital would affect the output since managers would be able to beat benchmarks that information ratio relies on. According to the regression analysis, the model falls short of showing how capital influences information ratio and return assets. The competitiveness of Chinese banks depends on customer banking trends and relevance of capital to equity and return on assets. Under this model, the total number of points assessed is equivalent to the observations made, with R2 of 0.246455 is not significant considering that variability of each data point is outside the scope of the R2’s value. The model in this case does not provide room for relating all the data points with capital as the dependent variable. Thus, while the model sought to display that capital relates with equity and return on assets, stability of the banking system cannot be predicated accurately and therefore China’s banking system does not rely on capital to sustain equity and returns on assets significantly to validate the model under assessment (Roth, 1994). References Bonin, J. (2012). Dilemmas of Chinas growth in the Twenty-First Century China’s opening up of the banking system: Implications for domestic banks. ANU E Press; pp. 55-72. Brandt, L. (2007). Chinas Financial Transition at a Crossroads; China’s Banking Sector and Economic Growth. Columbia University Press, pp. 86-136 Carlson, M., & Mitchener, J. (2009). Branch Banking as a Device for Discipline: Competition and Bank Survivorship during the Great Depression. Journal of Political Economy, Vol. 117, No. 2; pp. 165-210 Chung, C., & Tongzon, J. (2004). A Paradigm Shift for Chinas Central Banking System. 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