SPSS in Banking or Audit Company - Math Problem Example

Introduction In the last decade there has been liberalization of bank activities which have been traditionally been under very strict regulation and given protection from external competition. This has resulted in a situation where foreign banks that initially played a marginal having substantial investments in foreign countries especially in the middle-income and developing countries (Dunning, 1977) . The activities of the foreign banks come in various forms including acquiring domestic institutions that have extensive branch networks to establishing representative offices with the aim of serving a niche market segment. It has been the interest of researchers to find out what determines the form of investments banks takes and the effect of this on their overall performance. Banks may have several modes of investments when venturing in foreign countries including operating as locally chartered, operating as independently capitalized subsidiaries or operating as branches on the mother banks in the foreign countries (Clarke, 2003). There are two prominent reasons that make bankers, bank users and policy makers to have keen interest on operations of foreign banks in host countries. The foreign bank operations may affect to a great extent the competitiveness of the domestic banking systems, having a threat on the market share and profits in addition to having a considerable effect on the price and quality of services offered in the host country. Foreign subsidiaries which have extensive networks give direct competition to local banks for clients while on the other foreign banks with single branch will tend to concentrate on specific segments like wholesale and investment banking which have a tendency to have low development in the host countries. second , branches and subsidiaries involve a varied level of parent bank responsibilities and financial involvement. More often subsidiaries act as separate entities from the parent banks, while for cases of branches the parent banks will be responsible for the liabilities under their branches. This often has implications for both the parent banks and the local regulators (Focarelli, 2001; Galindo 2003). Research Objectives The study aim was to investigate the difference in the performance banks with international operations considering the following variables: home origin, number of foreign countries with investments, turnover in home country, turnover in foreign country, profit in home country and profit in foreign country. The variable in this study were a- The number of country where the bank operates gives the details on the number of countries in which the banks in this study is operating. b- Home country turnover gives the margin of the turnover of the banks in this study in their home country. c- Foreign country turnover gives the total margin of turnover of banks in this study in all the foreign countries they operate. d- Profit made in home country (loss) which is a representation of the amount of profit (loss) that that is in its country of origin. e- Profit made in foreign country (loss) which is a representation of the amount of profit (loss) that that is in all the foreign countries that the bank is operating. f- Type of invest : clarify whether the bank has a subsidiary or branch as its form of foreign investment Data Analysis The data analysis involved four methods: descriptive statistics, Mann-Whitney test correlation and regression. Descriptive statistics In this section basic descriptive statistics about the variables under investigation have been give. In each of the variables the data was divided according to the type of investment. The aim of exploration of the data was the identification of the normality of the data as this determines the suitable test to be used. Parametric and non-parametric are the two main statistical test available for use. The basic assumptions for parametric tests are (Field 2002): 1- Data need to be normally distributed. 2- There should be homogeneity in variance. 2- Interval data where the distance between points in a scale is equal. 3- There should be independence in the different objects being observed. In case any of the assumptions is violated the research need to be engaged. Non-parametric tests have some advantages (Siegel and Castellan 1988): 1- It holds few assumptions regarding the data. 2- Their interpretation is more direct compared to parametric tests. 3- It is suitable in cases where the sample size is relatively small. The basic statistics for the dependent and independents variables are discussed in turn below. Cross Tabulations country of origin of bank and number of countries of operation Across tabulation was done to investigate which regions had the widest foreign bank investments. From table 1 it can be seen that Europe had two banks that operates in more than 15 countries which represent 66.7% of banks in the category while North America had one bank which that operates in more than 15 countries representing 33.3% of banks in the category. For banks operating in 11 to 15 countries North America is represented by 6 banks (26.1%) same number as Asia, Europe has 5 banks that fall in this category representing 21.7% while South America and Africa have 4 and 2 banks in this category respectively. it can also be seen that Africa has the highest number of banks operating in one to thee foreign countries followed by Asia with their number of banks falling in this category being 9 and 5 respectively. Table 1 Number of countries where bank operates * Origin of Bank Crosstabulation Origin of Bank Total North America South America Asia Europe Africa Number of countries where bank operates 0ne to three Count 1 3 5 0 9 18 % within Number of countries where bank operates 5.6% 16.7% 27.8% .0% 50.0% 100.0% 4 to 6 Count 3 10 8 0 11 32 % within Number of countries where bank operates 9.4% 31.3% 25.0% .0% 34.4% 100.0% 7 to 10 Count 1 0 1 2 1 5 % within Number of countries where bank operates 20.0% .0% 20.0% 40.0% 20.0% 100.0% 11 to 15 Count 6 4 6 5 2 23 % within Number of countries where bank operates 26.1% 17.4% 26.1% 21.7% 8.7% 100.0% More than 15 Count 1 0 0 2 0 3 % within Number of countries where bank operates 33.3% .0% .0% 66.7% .0% 100.0% Total Count 12 17 20 9 23 81 % within Number of countries where bank operates 14.8% 21.0% 24.7% 11.1% 28.4% 100.0% The researcher was interested in establishing the correlation between some the variables. From the correlation tests it was established that there was a significant correlation between all the tested variables as can seen from table 2. The strongest correlation was between turnover in foreign countries and the profit made abroad with a Pearson correlation value of 0.800 with the second strongest correlation being between turnover in foreign countries and number of countries in which the bank operates. The lowest Pearson correlation value was between profit made abroad and the profit made in the home country with a value of 0.427 being registered. Another small correlation value was between turnover in foreign countries and profit made in home countries of the banks with a pearson correlation value of 0.485 Table 2:Correlations Profit made abroad Profit made in home country Home country turnover Turnover in foreing country Number of countries where bank operates Profit made abroad Pearson Correlation 1 .427** .619** .800** .678** Sig. (2-tailed) .000 .000 .000 .000 N 81 81 81 81 81 Profit made in home country Pearson Correlation .427** 1 .727** .485** .594** Sig. (2-tailed) .000 .000 .000 .000 N 81 81 81 81 81 Home country turnover Pearson Correlation .619** .727** 1 .672** .703** Sig. (2-tailed) .000 .000 .000 .000 N 81 81 81 81 81 Turnover in foreing country Pearson Correlation .800** .485** .672** 1 .723** Sig. (2-tailed) .000 .000 .000 .000 N 81 81 81 81 81 Number of countries where bank operates Pearson Correlation .678** .594** .703** .723** 1 Sig. (2-tailed) .000 .000 .000 .000 N 81 81 81 81 81 **. Correlation is significant at the 0.01 level (2-tailed). Independent t-Tests: There was preparation of t-tests where comparison of means for subsidiary and branch operations was made. It can be seen from the cross tabulations that the subsidiary investment performed better than the performance of the branch investments. Two tables were generated by SPSS when the t-test was conducted. In table3 the summary statistics for the subsidiary and branch has been given. From the table, we can see that there were 45 subsidiary and 36 branch investment. The table also gives the mean, standard deviation and the standard error of the mean for the four variables. From the table it can be seen that the mean values for subsidiaries are higher than the mean values of the branch type of investment. The mean home country turn over of the subsidiary type of investment has been given as 2.9778. According to the SPSS coding used a value of 2 represents a turnover of 1 to 5 million dollars while 3 represent a home country turnover of 6 to 10 million dollars. Therefore the home turnover of for the subsidiary is taken to be between 6 to 10 million while the home turnover of the branch type of investment is between 1 to 5 million dollars as it is represented by a value of 1.75. The mean turnover in the foreign country for the subsidiary type of investment is given as 2.5333 which is lower than the subsidiary turnover value in home country (2.9778) while the turnover for branch type of investment has a value of 1.5 which is lower than the branch home country turnover (1.75). Just like the case of the home country turnover a value 2.5333 which is between 2 and 3 will represent a turnover of 6 to 10 million dollars while a value of 1.5 represents a turnover of 1 to 5 million dollars. From the table it can be observed that the profit made abroad by the subsidiary investment has a mean value of 2.1556 which represents a turnover of 1 to 3 million dollars while the profit made abroad by branch investment has a mean value of 1.3 which represents a profit of 0.2 to 1 million dollars. It is also observed from the table that the profits made by both the subsidiary and branch type of investment in home country are higher compared to those made abroad with values of 2.4444 and 1.4444 respectively. These values represent profit margins of 1 to 3 million dollars and 0.2 to 1 million dollars respectively according to the SPSS coding. Table 3: Group Statistics type of operation N Mean Std. Deviation Std. Error Mean Home country turnover Subsidiary 45 2.9778 1.15776 .17259 Branch 36 1.7500 .76997 .12833 Turnover in foreign country Subsidiary 45 2.5333 1.15994 .17291 Branch 36 1.5000 .56061 .09344 Profit made abroad Subsidiary 45 2.1556 1.16688 .17395 Branch 36 1.3056 .46718 .07786 Profit made in home country Subsidiary 45 2.4444 1.05649 .15749 Branch 36 1.4444 .60684 .10114 From table generated by performing independent t-test (figure 10), prevents the Levene’s test for the equality of variances and the t-test for the equality of means. The Levene’s test has two rows in each case. Row 1 is used where equal variances are assumed and row 2 is used where equal variances are not assumed. We use the first row if sig. ≥ 0.05 (equal variances assumed) and the second row if sig. ≤ 0.05 (equal variances not assumed). From the table it can be observed that here significant difference in all the four variables tested when the score of the subsidiary and branch type of investments are compared. For home country turnover there is a significant difference in subsidiary and branch values (t = 5.4666, df = 79, p = 0.000) while there is a significant difference in scores for subsidiary and branch investments for foreign country turnover (t = 4.902, df = 79 p= 0.000). When the scores for profits in foreign countries are compared in subsidiary and branch investments there is also significant difference ( t= 4.111, df =79 p = 0.000) just lke in scores for profits in homecountry ( t = 5.048, df = 79 , p = 0.000) Table4 : Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence Interval of the Difference F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference Lower Upper Home country turnover Equal variances assumed 6.173 .015 5.466 79 .000 1.22778 .22463 .78065 1.67490 Equal variances not assumed 5.709 76.649 .000 1.22778 .21507 .79949 1.65607 Turnover in foreing country Equal variances assumed 20.932 .000 4.902 79 .000 1.03333 .21079 .61378 1.45289 Equal variances not assumed 5.258 66.336 .000 1.03333 .19654 .64096 1.42571 Profit made abroad Equal variances assumed 32.731 .000 4.111 79 .000 .85000 .20677 .43844 1.26156 Equal variances not assumed 4.460 60.352 .000 .85000 .19058 .46883 1.23117 Profit made in home country Equal variances assumed 16.594 .000 5.048 79 .000 1.00000 .19809 .60571 1.39429 Equal variances not assumed 5.343 72.314 .000 1.00000 .18717 .62691 1.37309 Cross-tabulation of turn-over and type of foreign investment A cross tabulation was done between the turnover in foreign countries and the type of investment as away of further investigation on the performance on the two types of investments. From the table 5 it can be seen that there were 29 banks with turnover of less than 1 million dollars 10 being subsidiary and 19 having branches as a form of foreign investments. From the table it can also be seen that the 19 branches makes 23.5 % of the total turnover in foreign investments while 10 subsidiaries makes 12.3% of the total investments. The 19 banks that have branches in foreign countries with the turnover of less than 1 million dollars makes 52% of all branch type of investment while the 10 subsidiary banks makes 22.2% of all the subsidiary type of investment in the study. Looking at turnover of 6 to 10 millions it can be seen that there are 12 banks out of the total 81 banks which operate as subsidiary in foreign countries and have this margin of turnover while there is only one that has branch as its form of investment and has the turn over margin of 6 to 10 million dollars. The 12 subsidiary investments in this turnover margin is 14.8% of the total investments while the 1 branch type of investment makes 2.8% of the total investments under this study. Table 5: Cross-tabulation of turn-over and type of foreign investment type of operation Total Subsidiary Branch Turnover in foreign country less than 1m Count 10 19 29 % within Turnover in foreign country 34.5% 65.5% 100.0% % within type of operation 22.2% 52.8% 35.8% % of Total 12.3% 23.5% 35.8% 1 to 5 mil Count 13 16 29 % within Turnover in foreign country 44.8% 55.2% 100.0% % within type of operation 28.9% 44.4% 35.8% % of Total 16.0% 19.8% 35.8% 6 to 10m Count 12 1 13 % within Turnover in foreign country 92.3% 7.7% 100.0% % within type of operation 26.7% 2.8% 16.0% % of Total 14.8% 1.2% 16.0% 11 to 15 m Count 8 0 8 % within Turnover in foreign country 100.0% .0% 100.0% % within type of operation 17.8% .0% 9.9% % of Total 9.9% .0% 9.9% 16 to 20m Count 2 0 2 % within Turnover in foreign country 100.0% .0% 100.0% % within type of operation 4.4% .0% 2.5% % of Total 2.5% .0% 2.5% Total Count 45 36 81 % within Turnover in foreign country 55.6% 44.4% 100.0% % within type of operation 100.0% 100.0% 100.0% % of Total 55.6% 44.4% 100.0% From this table it can generally be seen that there is a relationship between the type of investment and the foreign turnover output where low turnover seem to be associated with branch type of investment and high turnover being associated with subsidiary type of investment. This fact come out clearly from the chi-square analysis as shown in table 6 it can be observed that there is significant relationship between the turnover in foreign countries and the type of investment with a chi-square value of 21.679 and p = 0.000 This relationship also exist in the other variables due to the fact that there is inter-correlations in all the vari ables as observed earlier in table 2. Table 6: Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 21.679a 4 .000 Likelihood Ratio 26.982 4 .000 Linear-by-Linear Association 18.660 1 .000 N of Valid Cases 81 a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .89. References Anderson, D. R., Sweeney, D. J., Williams, T. A., Freeman, J. and Shoesmith, E. 2007. Statistics for Business and Economics. London: Thomson Learning. Clarke, G., Cull, R., Martı´nez Perı´a, M., Sa´nchez, S., 2003. Foreign bank entry: Experience, implications for developing countries, and agenda for further research. World Bank Research Observer 18 (1), 25–40. Dunning, J., 1977. Trade, location of economic activity and the MNE: A search for an eclectic approach. In: Ohlin, B., Hesselborn, P., Wijkman, P. (Eds.), The International Allocation of Economic Activity. MacMillan Press, London, pp. 395–431. Field, A. 2002. Discovering Statistics using SPPS for Windows. London: Sage Publications. Hair, J. F., Anderson, R. E., Tatham, r. L. and Black W. C. 1995. Multivariate Data Analysis: with readings. Englewood Cliffs, N.J: Prentice Hall. Focarelli, D., Pozzolo, A., 2001. The patterns of cross-border bank mergers and shareholdings in OECD countries. Journal of Banking and Finance 25 (2), 2305–2337. Galindo, A., Micco A., Serra, C., 2003. Better the devil that you know: Evidence on entry costs faced by foreign banks, Inter-American Development Bank Working Paper No. 477. Kahane, Leo H. 2001. Regression Basics. Thousand Oaks: Sage Publications, Kvanli, A. H., Guynes, C. S. and Pavur, R. J. 1996. Introduction to Business Statistics: A Computer Integrated Data Analysis Approach. 4ed. New York: West Publishing Company. Lewis-Beck, M. S. 1993. Applied Regression: An Introduction. In: Lewis-Beck, M. S. ed. Regression Analysis. New York: Sage Publications. pp. 1-68. Siegel, S. and Castellan, N. J. 1988. Nonparametric statistics for the behavioral sciences 2nd ed. New York: McGraw-Hill. Read More