The UK Borrowing and Tax Revenue - Assignment Example

Statistical data analysis Statistical Data Analysis The data provided is the UK borrowing and tax revenue for thefinancial years 2011 and 2012. From Appendix 3 we can see that there is no distinct relationship between tax revenues and borrowing. Therefore, they do not affect each other and are also not affected by the same factors and, therefore, their movements are not correlated. In 2011, the Pearson correlation is zero meaning that the two variables, that is, borrowings and tax revenues are not correlated or they do not cause each other. In 2012, the Pearson correlation (r) is 0.009853 meaning that there is some correlation between taxation and borrowing but it is very weak. They are slightly moving together, there is a 0.5 correlation between borrowing rates of 2011 and those of 2012 which is a weak correlation. The correlation between tax revenues in 2011 and 2012 is +1 which means that they are positively and strongly correlated. (Correlation Coefficient 2001). The Inter-quartile range is highest in the borrowings of 2012; therefore, data was highly dispersed in 2012 and for the borrowing rates. We use the IQR to measure dispersion since it is not affected by outliers in the data as compared to range. The lowest dispersion was in the tax revenue of 2012, followed by tax revenue of 2011 and on a higher dispersion was 2011 borrowings. We can, therefore, conclude that the dispersion rate is higher in borrowings as compared to tax revenues. (Altman & Bland 1994) Standard deviation is a statistic that helps explain how data is clustered around the mean; it is helpful in explaining why the data is the way it is. A lower rate is recommended since it shows that most of the data is spread out around the mean. In 2012 borrowing had the highest deviations, for example the data ranges form -17,039 million dollars in April to $17,395 m. in November. This explains a high deviation from the mean. 2011 borrowing followed with a standard deviation of 5,873 and Tax revenue had a lower standard deviation. We, therefore, conclude that there is high deviation in borrowing since the government can borrow from time to time to fund its operation, but it is hard to vary the tax rates and; therefore, tax revenue tends to be stable. (Niles 1995) Appendix 1 provides the graph on borrowing levels for the 2 years, from the graph it is possible to draw a pattern where borrowings are low in January of both years, that is, -8197 million dollars in 2011 and -10,053 million dollars in 2012. The months of July also have low borrowing rates followed by October. The months with high lending rates from the highest are June, May, November, December and August respectively. There is, therefore, an established trend where the borrowing rates between months are correlated though the correlation is weak, that is, re 0.52. April 2012 had the highest recorded borrowing rate. This was initiated by $8.2 billion budget deficit experienced in that year. For 2011 the mean borrowing was $9,427 M. which was higher than that of 2012 which was $7,411 M. meaning that the borrowing rates decreased from 2011 to 2012 by approximately 27%. This is a good indication for a country as its debt ratio is decreased an hence strengthen sovereignty. In 2011 there was a high shift in borrowing between April and May 2012 with a difference of $35,145 million. According to the Office, for National Statistics there was an increase in overall borrowing rates in 2012 as compared to 2011 due to due to downward revision of the 2011-2012 borrowing rates. Appendix 2 is a graph on the tax revenues of the UK government for the financial years 2011 and 2012. The highest levels of tax revenue received are in the ferry for both years. The two years seem to follow a similar trend with Nov/Dec having the lowest tax revenues and a sharp decline from tax revenues between February and March. There is a strong positive correlation between months in different years implying that it is possible to predict the tax revenues of the next month or years. The correlation coefficients are 1 and, therefore, as the values of 2011 rises those of 2012 also rises. (Correlation Coefficient 2001) The mean rate tax revenue increased from 2011’s rate of $12702 M to $12717 M in 2012, this is progress since despite a low increase of 0.12% there is success in increasing revenue from taxation and is an indicator of economic growth as the government manages to raise more revenue to fund its expenditure. For both 2011 and 2012 the tax revenues are approximately stable but there are hikes in February this is because it reflects sales revenues generated during the holiday season. Higher rates reflect a higher spending rate. (Dries 2014, par.3) Conclusion From the the provided data, it is evident that there in correlation between the borrowing rates and tax revenues. However, there seem to be a trend in both tax and borrowing which can help in forecasting future rates. One year data also seems to affect the next years data for both tax revenues and Borrowings. Although the correlation is higher for tax revenue given that tax rates are in most cases fixed and will only increase in case of increased expenditure especially during holiday seasons. References Altman, D., Bland, J. 1994, Statistics Notes: Quartiles, quintiles, centiles and other quantiles [Online]. [Accessed 22nd May, 2014]. Available from: http://www.bmj.com/content/309/6960/996 Correlation Coefficient 2001. Statistics 2. [Online]. [Accessed 22nd May, 2014]. Available from: http://mathbits.com/MathBits/TISection/Statistics2/correlation.htm Dries, B 2014, February 2014 Economic Report, Sales Tax Revenues Post Record-Setting. [Online]. [Accessed 22nd May, 2014]. Available from: http://www.philadelphiacontroller.org/page.asp?id=967 Niles, R. Standard Deviation. [Online]. [Accessed 22nd May, 2014]. Available from: http://www.robertniles.com/stats/stdev.shtm Appendix 1: Borrowing Graph Borrowing Appendix 2: Received Tax Graph Appendix 3: borrowings and tax revenues, combined graph Appendix 4: Data from Excel UK Govt Borrowings (£ millions) Tax Received (£ millions) 2011 Apr 14,243 13,340 May 15,080 9,578 Jun 15,905 10,409 Jul -2,628 10,856 Aug 12,663 16,108 Sep 13,157 11,613 Oct 4,936 9,675 Nov 14,882 9,687 Dec 14,490 10,504 2012 Jan -8,197 11,299 Feb 10,774 24,942 Mar 7,814 14,412 SUM 113,119 152,423 AVERAGE 9,427 12,702 Standard Deviation 5873 4177 1ST QUARTILE 7,095 10,229 2ND QUARTILE 12,910 11,078 3RD QUARTILE 14,588 13,608 4TH QUARTILE 15,905 24,942 INTERQUARTILE RANGE(Q3-Q1) 7493 3379 PEARSON CORRELATION 0 0 Apr -17,039 13,246 May 18,106 10,396 Jun 13,621 9,471 Jul 236 10,940 Aug 13,895 16,206 Sep 13,593 11,175 Oct 8,273 10,059 Nov 17,395 10,086 Dec 15,207 8,881 2013 Jan -10,053 11,776 Feb 3,136 25,492 Mar 12,563 14,870 SUM 88,933 152,598 AVERAGE 7,411 12,717 Standard Deviation 10776.13 4390.67 1st QUARTILE 2411 10079.25 2nd QUARTILE 13078 11057.5 3rd QUARTILE 14223 13652 4th QUARTILE 18106 25492 Inter Quartile Range(Q3-Q1) 11,812 3,572.75 PEARSON CORRELATION 0.009853 0.009853 Correlation between the two periods 0.519525 0.988872 Read More