Share of population living on less than $30 a day
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Frequently Asked Questions
Much of the economic data we use to understand the world – for instance on the goods and services bought or produced by households, firms and governments, or the incomes they receive – is initially recorded in terms of the units in which these transactions took place. That means this data starts out being expressed in a variety of local currencies – as so many rupees, US dollars, or yuan, etc. – and without adjusting for inflation over time. This is known as being in ‘current prices’, or in ‘nominal’ terms.
Before these figures can be meaningfully compared, they need to be converted into common units.
International dollars (int.-$) are a hypothetical currency that is used for this. It is the result of adjusting both for inflation within countries over time and for differences in the cost of living between countries.
The goal of international-$ is to provide a unit whose purchasing power is held fixed over time and across countries, such that one int.-$ can buy the same quantity and quality of goods and services no matter where or when it is spent.
The price level in the US is used as the benchmark – or ‘numeraire’ – so that one 2017 int.-$ is defined as the value of goods and services that one US dollar would buy in the US in 2017. Similarly, one 2011 int.-$ is defined as the value of goods and services that one US dollar would buy in the US in 2011.
The year 2017 (2011) here indicates two things, related to the two adjustments mentioned. Firstly, it tells us the base year used for the inflation adjustment within countries. This is the year whose prices are chosen to be the benchmark. If prices are higher than this benchmark year, nominal data will be adjusted downwards. If prices are lower, nominal data will be adjusted upwards. In the base year itself, the nominal and inflation-adjusted figures are the same by definition.
Secondly, 2017 (2011) indicates the year in which the differences in the cost of living between countries was assessed.
Purchasing Power Parity rates
Converting data in local currencies to international-$ means dividing the figures by a set of ‘exchange’ rates, known as Purchasing Power Parity (PPP) rates. Unlike the exchange rates between currencies you would see at the foreign exchange counter, these account for differences in the cost of living between countries.
If you have ever shopped or eaten in a restaurant abroad, you may have noticed a country as being a particularly expensive or particularly cheap place to live. A given amount of your own currency, when exchanged for another country’s currency, may buy you considerably more or less there than it would have done at home.
The goal of PPP rates is to account for these price differences. They express, for each country, the amount of local currency that is needed to buy the same goods and services there as 1 US dollar buys in the US.
You can read more about this in our article What are PPP adjustments and why do we need them?
The ‘rounds’ of the International Comparison Program
The calculation of PPP rates is the task of the International Comparison Program (ICP), which gathers data on the prices of thousands of goods and services in each country in a particular year.
The ICP does not calculate PPP rates every year, but rather conducts its work in ‘rounds’ that are several years apart. The most recent round was conducted in 2017 and the previous round was conducted in 2011.
In converting economic data to international-$, which round of PPPs are used to adjust for cost-of-living differences between countries is, in principle, a separate issue to the base year used to adjust for inflation over time. By convention, however, the same year tends to be chosen for both. When converted to 2017 international-$, nominal local currencies are first adjusted for inflation to local 2017 prices, and are then adjusted to US prices using the PPPs calculated in the ICP’s 2017 round. Likewise, 2011 international-$ adjust for inflation using 2011 local prices, and then use the 2011 PPPs to adjust for cost-of-living differences.
Because there is no global survey of incomes, researchers need to rely on available national surveys. Such surveys are designed with cross-country comparability in mind, but because the surveys reflect the circumstances and priorities of individual countries at the time of the survey, there are some important differences. In collating this survey data the World Bank takes steps to harmonize it where possible, but comparability issues remain.
One important issue is that, whilst in most high-income countries the surveys capture people’s incomes, in poorer countries these surveys tend to capture people’s consumption.
Pooling the data available from different kinds of survey data is unavoidable if we want to get a global picture of poverty or inequality. But it’s important to bear in mind that, depending on the country or year, somewhat different things are being measured.
The two concepts are nevertheless closely related: the income of a household equals their consumption plus any saving, or minus any borrowing or spending out of savings.
One important difference is that, while zero consumption is not a feasible value – people must consume something to survive – a zero income is a feasible value. At the bottom end of the distribution, people’s consumption may be somewhat higher than their income. A common example here is retired people who are using their savings: they may have a very low, or even zero, income, but still have a high level of consumption.
Conversely, at the top end of the distribution, consumption is typically lower than income. The gap rises with income, with households generally saving a higher share of their income the richer they are. For both these reasons, the distribution of consumption is generally more equal than the distribution of income.
There are a number of other ways in which comparability across surveys can be limited. In collating this survey data the World Bank takes a range of steps to harmonize it where possible, but comparability issues remain. The PIP Methodology Handbook provides a good summary of the comparability and data quality issues affecting this data and how it tries to address them.
To help communicate this limitation of the data, the World Bank produces a companion indicator that groups data points within each individual country into ‘spells’. The surveys underlying the data within a given spell for a particular country are considered by World Bank researchers to be more comparable. The breaks between these comparable spells are shown in the chart below for the share of population living in extreme poverty. You can select to see these breaks for any indicator in our Data Explorer of the World Bank data. These spells are also indicated in our data download of the World Bank poverty and inequality data.
How does the World Bank produce global and regional estimates of poverty and inequality from national data?
For its poverty and inequality data the World Bank relies on household surveys that are conducted nationally. In order to produce global or regional estimates, the survey data from different countries needs to be lined up and aggregated. For each year, the World Bank finds the closest survey for each country and projects the data forward or backwards to the year being estimated. This is necessary particularly since surveys are less frequently available in poorer countries and for earlier decades.
These projections are generally made on the assumption that incomes or expenditure grow in line with the growth rates observed in national accounts data.
You can read more about the interpolation methods used by the World Bank in Chapter 5 of the Poverty and Inequality Platform Methodology Handbook.
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Notes on our processing step for this indicator
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