153 Earning up to PPP US$10 a day
The map shows an estimate of the proportion and hence numbers of people living in households with an average income or level of consumption of PPP US$10 a day or less.
Earnings are measured using US dollars adjusted for Purchasing Power Parity (PPP). The PPP value accounts for the costs of goods and services in the territory where the earnings are made, as such this indicates roughly how much purchasing power of the earnings are, as the equivalent of what US$ would buy in the United States. Earnings are averaged out among every person in a household, irrespective of whether a particular individual actually earns.
The main data source used was the United Nations Development Programme’s (UNDP) 2004 Human Development Report. All the UNDP data used from this report had the World Bank cited as the underlying source. The surveys used to estimate income were mostly taken in the 1990s, and a quarter of these were between 2000 and 2002. Four parameters were used to calculate income distributions. Three of these parameters are estimates given in Table 14: mean income, Gini index of inequality, and the proportion of income enjoyed by the richest and poorest tenths of the population. The estimate of total Gross Domestic Product (GDP) in 2002 per territory in US$ adjusted for purchasing power parity was given in Table 13; it is used to scale the separate models made for each territory.
It was necessary to estimate the proportion, and from that the numbers, of people living in households with an average income of or level of consumption equivalent to a fixed amount. For this and equivalent maps, this was done using levels of US$ expressed in purchasing power parity for a daily amount of: less than 10, 10-20, 20-50, 50-100, 100-200, and over 200 dollars a day. These estimate are made using the assumption that the distribution of income in each territory is log normal. This assumption will not hold true in all cases but is a fair approximation in most.
To model the log normal distribution two parameters are needed. Firstly the standard deviation of the distribution of income is required. A method of trial and error found a suitable approximation for this to be the Gini index of income inequality divided by 17, divided by the ratio of the modelled ratio of richest 10 th to poorest 10 th of income to the measured ratio of richest 10 th to poorest 10 th net income. That total ratio itself raised to the power of 1/4.5; to a distribution which produces plausible extremes when compared to those reported from the surveys. Because the approximation includes a parameter which itself depends on the modelled standard deviation the process of approximation is iterative and also tends to converge on a close solution as a result.
The second parameter – the median income – is estimated as the modelled median income divided by the square root of the modelled mean divided by the reported mean. Again the process of estimating this parameter is iterative and tends to converge so that the mean of modelled distribution approximates that reported. Note that the standard deviation and median of each territory's income distribution are both estimated from Table 14, assuming a log normal distribution.
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The quote used for here was sourced from an article written by Angel Paez, entitled ‘ PERU : Veteran Soldiers, Police Recruited for Iraq by U.S. Contractors’. This was published on the 3 rd November 2005 . The quote itself is from Pirana, described by Paez as follows: “"Pirana", a former Peruvian army sergeant who fought the Sendero Luminoso (Shining Path) Maoist guerrillas in the jungles of Peru in the 1990s, decided at the last minute not to travel to Iraq with around 200 former members of the military and police recruited by the U.S.-based private security firm Triple Canopy.” The quote was accessed in June 2006, from www.oneworld.net - the page is noted below:
Below is an explanation of each of the columns in the excel file:
Column A = Unique numerical territory (see 001).
Column B = Region and territory names (see 001).
Column C = Region code (see 001).
Column D = The ISO 3 code, or ISO ALPHA-3 (see 001).
Column E = Number of people in millions living on less than or equal to PPP US$10 a day. This data is taken directly from Column H. Where data are missing from Column H, the regional average for the percentage of the population that have incomes less than or equal to PPP US$10 a day (Column F) is multiplied by the population of that territory (Column G) and then divided by 100 to rescale the result to millions (E = F * G / 100).
Column F = Percentage of the tot al population who live on PPP US$10 or less a day. This is calculated by dividing the tot al number of people, in millions, living on equal to or less than PPP US$10 a day (Column E), by the population in millions (Column G), and then multiplying this by 100 to turn it into a percentage (F = 100 * E / G).
Column G = Population in millions, in 2002. See the technical notes for ‘Total Population’ for the sources of this data (002).
Column H = Estimate of the number of people, in millions, who live on PPP US$10 or less a day. These data are taken from the source data sheet. Where data is missing ‘..’ is shown.