Good Essay On Data From The World Bank.

Type of paper: Essay

Topic: Countries, Information, Range, World, Value, Distribution, Taxes, Income

Pages: 4

Words: 1100

Published: 2021/02/21

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20 Richest Countries in the World
Gross National income (GNI) is one of the most widely used metrics for assessment of economic development of different countries as well as average income of their residents. GNI is total value of all goods and services, produced by residents of particular state within one year. Technically, GNI is GDP less net taxes on production and imports, less compensation of employees and property income payable to the rest of the world plus the corresponding items receivable from the rest of the world (in other words, GDP less primary incomes payable to non- resident units plus primary incomes receivable from non-resident units) (OECD, 2003).
For the purposes of this study data from the World Bank database was used (The World Bank, 2014). There are different approaches to calculation of national accounts indicators. A main reason for such differences and difficulties is a need to value all the data in terms of a single currency. So the most straightforward method is to convert indicator value, denominated in local currency, into US dollars at the official exchange rate. Over time second approach emerged, according to which usage of official exchange rate does not always return accurate results due to lower prices in less developed countries. Under this method, exchange rate, computed on the basis of the same consumer basket in different countries shall be used (Callen T., 2012). Furthermore, the World Bank used one more approach, so called Atlas method. It entails computation of GNI on the basis of official exchange rates during the last 3 years in order to smooth their fluctuations. Another difference from nominal conversion rate is adjustment for inflation under Atlas method (The World Bank, 2008). This study uses as a proxy for income GNI per capita, calculated on the basis of purchasing power parity.
GNI data for the wealthiest 20 countries, obtained from the World Bank, is presented in table 1. Most of countries from the table are developed postindustrial states, which are members of the OECD, though some big oil producers such as Qatar and Saudi Arabia are also among the countries with the highest income.
20 countries with the highest GNI per capita (PPP)
Note: Adapted from http://data.worldbank.org/indicator/NY.GNP.PCAP.PP.CD
The data above is quantitative, since GNIs of different countries are continuous numerical values and do not have some finite set of values as qualitative data. That`s why it can be analyzed with the use of traditional quantitative methods like those used in descriptive statistics.
Qatar is the country with the highest national income of $128530 while the United Kingdom is 20th country in this list with GNI amounting to $38160. So a range of the data is $90370, which is quite a big number, especially in relation to the lowest value, $38160. Very wide range of the data, which is almost 3 times bigger than the lowest value in the set under examination, indicates large inhomogeneity of the largest GNIs, meaning that some countries have very high incomes even by the standards of the wealthiest states. For example, Singapore, the second wealthiest country, has GNI of $76860, which is $51670 lower than this value for Qatar. It should be noted that most part of this range is due to extremely high income of Qatar, since the range from 2nd to 20th values is only 43% of the overall range. Taking into account the fact that minimum GNI values are restricted due to economic reasons, because they can not fall below zero, such range ($90370) may be considered very large amount and signifies significant degree of variation of GNI levels across countries.
The mean of the data set is $52418 while the median amounts to $45535. Such a shift can be attributed to extremely high values for the wealthiest countries and infers that the distribution of national incomes of the 20 wealthiest states is right-skewed, meaning that there are some values that deviate to the right from the average significantly, while range of values, lying to the left from mean, is much smaller. It is well-known that median is better estimate for average value of a variable in case of large deviations from a mean, since it is not sensitive to amount of values and accounts only for their relative positions. So $45535 lies at the center of the range of GNIs, dividing this range into two equal parts, while mean value is significantly higher than median, which can be attributed to the fact that mean is sensitive to extreme values, because they can influence a mean sufficiently, shifting it to the right.
The standard deviation of the data amounts to $20070, indicating that GNI is unlikely to deviate from the mean more than $60210 (three standard deviations). The standard deviation is a measure of concentration of data near a mean and such value indicates that if this distribution was close to normal, about 68% of all values would lie in the interval of $52418 -/+ 20070. Inconformity of the data set values to these measures proves that distribution of top 20 GNIs is far from normal.
First 7 countries have GNI higher than mean values while incomes of the rest of countries are lower than average. This is another evidence of skewness of the distribution. The degree of concentration of GNIs below average can be shown using lower 10% of the range. 10% of the range equals to $9037, so the lowest 10% of the range accounts for GNIs from $38160 to $47197. 13 lowest values lie within this interval, which prove high concentration of low GNI values. For example, there is only one value within top 10%, 20%, 30%, 40% and 50% range.
Histogram is useful tool indicating empirical distribution of observed data set. It shows that the distribution looks like some variation of a normal distribution with extremely fat tails, cut off a bit to the left from its mean value (see figure 1). In fact, it is true to some extent, because we have taken only 20 highest values, cutting off the rest from the distribution.
Figure 1. Histogram of GNI for the first 20 countries.

Note: Adapted from http://data.worldbank.org/indicator/NY.GNP.PCAP.PP.CD.
So statistical analysis of the dataset of 20 countries with the highest GNIs reveals significant inequality in distribution of GNIs. A range of data set is very wide, amounting to $90370, and shows significant variability of income levels among the wealthiest countries. For higher values of GNI difference between two adjacent values becomes higher and reaches maximum between first and second values. From statistical point of view, it means that the mean is greater than the median, so the distribution is right-skewed and has outliers with very high GNI.

References

The Organization for Economic Co-operation and Development. (2003, March 25). Gross National Income (GNI). Retrieved from: https://stats.oecd.org/glossary/detail.asp?ID=1176
The World Bank. (2008). World Bank Atlas Method. Retrieved from: http://econ.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS/0,,contentMDK:20452009~pagePK:64133150~piPK:64133175~theSitePK:239419,00.html
Callen T. (2012, March 28). Purchasing Power Parity: Weights Matter. Retrieved from: http://www.imf.org/external/pubs/ft/fandd/basics/ppp.htm
The World Bank. (2014). GNI per capita, PPP (current international $). [Data file]. Retrieved from: http://data.worldbank.org/indicator/NY.GNP.PCAP.PP.CD

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