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In traditional analysis of economic well-being we usually focus on income as a single dimension of an individual’s economic resources. Income is one of the most important ways to meet our everyday living expenses and satisfy all our needs and wants. Information on wealth, however, can further enhance understanding of financial resources within a country. This article explores Euromonitor International’s newly developed bivariate income-wealth distribution. In particular, we obtain a significant reduction of population “at risk for poverty” when data on wealth is added to the analysis of poverty rates.
Income is a ‘flow’ indicator, which can be quite volatile with time, because of individuals changing their jobs, working hours or taking breaks from work, eg maternity leave. Wealth is a ‘stock’ measure, which is more stable over time, and reflects accumulated savings and investments, together with household real estate and durables assets. Individuals can use wealth to boost their consumption exceeding their income. This implies that wealth, in addition to income, can be used to sustain certain levels of consumption.
In the chart above (Figure 1 – US, 2013) we provide a typical example of bivariate income-wealth distribution, where adults are sorted by annual disposable income and net-wealth brackets. The chart shows that wealth and income strongly correlate (the diagonal yellow of the graph is characterised by a larger number of adults). In addition, joint distribution provides the possibility to take a closer look at the outer edges, ie blue corners, of the distribution.
When considering the joint distribution of income and wealth, we find that many people with low income have a substantial net wealth.
It is a common practice to define individuals with an income below a certain threshold to be at risk of poverty. In Europe and OECD countries this threshold is usually equal to 60% of median disposable income. However, those individuals who have low income may still be in a financially better position when their wealth is taken into consideration.
A wealth study of Luxembourg (together with other national wealth distribution surveys, eg Norway) shows that it is mainly older individuals that belong to this category[GD1] . Further, the importance of considering income and wealth together when assessing the economic wellbeing of individuals was also pointed out in Stiglitz-Sen-Fitoussi Commision Report on the Measurement of Economic Performance and Social Progress (2009), when they stated that “After all, a low-income household with above average wealth is not necessarily worse off than a median-income household with no wealth”.
In our analysis, we applied Euromonitor International’s estimated joint income and wealth distribution for revision of income-based poverty rates in a wide list of countries. Just like the choice of the low-income cut-off, all choices regarding the size of the net-wealth buffer are rather arbitrary and mainly depend on the ability to secure a certain standard of living for a given period of time. We define an adult to be at risk of poverty if disposable income is below 60% of the median and net-wealth is less than twice the income-based poverty line (a similar definition is used in some national asset-based measurements of poverty, eg Norway).
When both income and wealth are taken into consideration, this has a substantial impact on the proportion of the population at risk of poverty. Quantitative results are summarised in the chart below.
Further, we rank all countries by the reduction of income-based poverty rates after wealth is included in the definition of poverty. The smallest reductions were in India (-8%) and several Eastern European and Northern European countries. In Australia, adding wealth information has reduced the number of at-risk-of-poverty individuals from 29% to 7% (-22% reduction).
In general we observe a 50% drop (on average) in the share of at-risk-of-poverty adults after the implementation of income-wealth based poverty definition. Different levels of reduction of poverty rates are mainly due to differences in wealth inequalities across countries, ie allocation of assets among the population. The relationship is presented in detail in the scatterplot above. For instance, the reduction of poverty rates in US and India, where highly-skewed distribution of wealth is observed, results in a twice smaller drop in the share of ‘poor’ adults in comparison with Australia and Japan, which have a moderate levels of wealth Gini index.
The availability of bivariate income-wealth distribution data opens new opportunities for analysis of financial resources of a population that among other things can be used to predict potential consumption levels. The upcoming Income-Wealth Tool will have flexibility to calculate income/wealth distribution by user selected specific income/wealth bands.