Corporate Governance in Russia Dissertation Example | Topics and Well Written Essays - 5250 words

Corporate Governance in Russia - Dissertation ExampleA total of 74 companies was analysed, 34 companies from LSE, 4 from outsized board and 36 listed on RTS. The sample sizing was calculated from a Web-based sample sizing calculator using the following parameters (1) a margin of error of 7% (2) a confidence level of 95% (3) a population size of 5,580 and (4) response distri notwithstandingion of 10%. The population size of 5,580 is the total number of companies listed with the Russian Trading constitution (297), the New York Stock Exchange (2,317) and the London Stock Exchange (2,966). The minimum recommended sample was 70 but for contingency, this number was increased by 5%, hence the actual sample size used was 74. Companies which were listed with LSE and NYSE ar categorised as class listed (CL). These are the companies are listed abroad, numbering 38. The non-class listed companies (NCL) are those companies that are listed unaccompanied with RTS in Russia. The list of the com panies and a screenshot of the output from the Web-based sample size calculator can be prime in the Appendix.... The test is repeated until all the outliers are deleted. Grubbs test works on the principle that with the outliers deleted, entropy tend to be normally distributed (Thompson and Lowthian, 2011). In this regard, use of Grubbs test requires prudence in estimating normality of the statistical distribution in the informationset. Moreover, the test may not be applied for a small sample size of six or less since repeated iterations alter the chances of detecting outliers (Thompson and Lowthian, 2011). In the case of this research, CL and NCL data sets made the use of the Grubbs test impossible, because it detected too many outliers, because CL firms tend to be large and well-established, also the specific environment in which firms operate would influence their board characteristics and availability of data. Considering the big information availability difference of the trea tment and benchmark populations comparison between those independent samples can be problematic. Log base 10 Further, enterarithm was applied on operating revenue and number of employees. The just about common description of log or logarithm of a number represents the exponent by which a fixed number, called the base, has to be exponentiated to generate the fixed number (Bland, 2007). For the current research common logarithms (logs to base 10) are useful in a several ways. First of all, they simplify the data output for further calculations. Secondly, log transformation is applicable to data in where the residuals tend to assume bigger evaluate as the values of the dependent variable increases. The danger in this type of scenario is that the error or change in the value of an outcome variable is a percentage and not an absolute value. Hence, similar percentage