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This is money received on a regular basis. It can come from earnings (employment), benefits (pension, tax credits), investments and other income sources (e.g. private pension). From a policy perspective, there are four main categories of income: (1) original income: this is the amount of money you receive before taxes and benefits; (2) gross income: this is your total income after benefits but before tax; (3) disposable income: this is the amount of money left over after direct taxes are deducted from your gross income; and (4) post tax income: the amount of money remaining after direct and indirect taxes and benefits are deducted. There are two measures of income: (i) household living standards [money shared amongst household members]; and (ii) individual incomes [money kept at an individual level].
The term ‘income inequality’ is used to describe the extent to which income is distributed in an uneven manner within a given population. A range of income and income distribution metrics are used by academics and policy makers to measure inequality.
In the UK, statistics on household incomes are ‘equivalised’: adjusted for household size and composition to enable better comparisons and to identify trends in living standards over time. This is because a larger household is likely to need a higher income to enjoy the same standard of living as a smaller household. The Department for Work and Pensions (DWP) publishes incomes data from the Family Resources Survey.
The Households Below Average Income (HBAI) dataset reveals how an individual was in the top 10% of the distribution in 2016-2017 if his or her disposable weekly household income before housing costs was:
An individual is in the bottom 10% if she or he had household income of less than:
For gross income before housing costs, an individual is in the top 10% if he or she had a household income greater than:
An individual is in the bottom 10% if he or she had a household income of less than:
The OECD uses the Gini coefficient [based on the comparison of cumulative proportions of the population against cumulative proportions of income they receive – ranging between 0 in the case of perfect equality and 1 in the case of perfect inequality]; and the Palma ratio [the share of all income received by the 10% people with highest disposable income divided by the share of all income received by the 40% people with the lowest disposable income]. According to the Gini coefficient, the UK has some of the highest levels of income inequality in the European Union. The UK is 11th on a list of 28 countries – with Bulgaria, Lithuania and Romania having the highest levels of income inequality; and Slovenia, Slovakia and Iceland the lowest levels. The OECD ‘Better Life Index’ reveals the average household net-adjusted disposable income per capita in the UK is $28,408 per year (compared to an OCED average of $30,562); and describes how the top 20% of the UK population earn nearly six times more than the bottom 20%.
The London School of Economics (LSE) Centre for Analysis of Social Exclusion (CASE) has explored income inequality and wealth, from 1961 to 2016. Their report, ‘Double Trouble’, which was commissioned by Oxfam, shows a positive correlation between income inequality and income poverty in the UK. The analysis shows that, on average, during the last 50 years a one point increase in income inequality - as measured using the Gini coefficient – was associated with an increase in relative poverty of 0.6 percentage points.
In March 2017, the Institute for Fiscal Studies (IFS) published its findings on changes in inequalities between and within regions, by examining data that follows the same people over time. The IFS found that while income inequality remains highest in London, the rate here is falling. Average income in the highest-income region of Great Britain (South East) is around 25% more than that in the poorest region (West Midlands). Incomes in the West Midlands (and in fact the East Midlands, Wales and the North of England) are no higher than incomes were in the South East in the late 1990s. According to the IFS, 13% of the population saw their real household income fall by less than 5% or rise by less than 5% between 2010–2011 and 2014–2015. Over this time period, 87% of people saw their household income change by at least 5%; with 37% experiencing a fall in income of 5% or more and 50% seeing a rise of 5% or more.
In Scotland, Oxfam has produced an income inequality calculator This shows the distribution of the Scottish population by equivalised household net income for 2015-2016 – dividing the population into equally sized groups known as percentiles to identify the poorest and richest households. Users enter basic information about their household and council tax to then view which percentile they fit into.
At a global level, there are various measures for comparing standards of living across countries. The World Bank’s World Development Indicators (WDI) builds measures of Gross Domestic Product (GDP) to identify high, middle and low income countries. ‘Basic needs’ data [e.g. income, consumption, wellbeing, education, health care, security] is collated from which the World Bank defines the ‘extreme poor’ as those low-income countries where people are living on less than $1.90 a day and those middle-income countries where people are living on $3.20 - $5.50 a day. The Penn World Table (PWT) is a set of national accounts data that includes information on capital, productivity, employment and population – the table allows comparisons of relative GDP per capita as a measure of standard of living. The Maddison Historical Statistics Project gathers historical economic statistics including GDP and GDP per capita.
To overcome the differences in economic variables in various countries (i.e., how exchange rates may distort comparisons); the European Commission uses GDP per capita adjusted for purchasing power parity (PPP) in allocating structural funds. Interestingly, the Economist has used PPP to construct ‘The Big Mac index’: a burger exchange rate [i.e., the dollars needed to buy a Big Mac in different countries].
Looking at data about income inequality opens up discussions about the relationship between gross income and disposable income; the relationship between individual income and household income – and what this comprises (where housing costs fit); how the flow of money into an individual or household is built up or retained over time; and the tax and benefits systems in different countries (and whether/how these redistribute income). This opens up further discussions around how data about income inequality is collected and analysed – and where/how distribution is segmented (i.e., where the line gets drawn between low, middle and high percentiles).
Defra’s Statistical Digest of Rural England (March 2019) includes information on household expenditure and its relationship to disposable income. Households in rural hamlets & isolated dwellings have both the highest disposable incomes and the highest levels of expenditure – compared to households in urban areas which have the lowest levels of expenditure and disposable income. On average, households in rural hamlets and isolated dwellings have a weekly expenditure of £643 (£170 higher than urban households) and a weekly disposable income of £870 (£177 more than the urban average). When looking at the proportion of average weekly disposable income left over after weekly expenditure (excluding mortgage payments), this is higher in urban areas at 32% compared to 26% in rural areas. Rural households spend a higher proportion of their disposable income on ‘transport’ and ‘recreation’ than they do on housing and utilities. In the year ending March 2017, average weekly transport costs for those living in rural hamlets and isolated dwellings was £132 - or 15.1% of their total weekly disposable income and £58 higher than urban areas.
In rural areas the proportion of disposable income left over once average weekly expenditure has been deducted (excluding mortgage payments) had also declined – from 29% in December 2013 to 26% in March 2017.
Using the HBAI statistics, the proportion of rural households in relative low income was 16% before housing costs and 17% after housing costs – in urban areas these figures are 18% and 24% respectively. 13% of households in rural areas are in absolute low income before housing costs and 15% after housing costs – this compares to 15% and 22% in urban areas respectively. The dashboard in the Statistical Digest showing relative and absolute income (on page 142) therefore suggests that the percentage of people living in relative low income [before and after housing costs] has decreased compared to urban areas where these figures are increasing.
In 2018, median workplace based earnings in predominantly rural areas were £21,900 compared to £23,300 in predominantly urban areas. Between 2009 and 2018 median workplace earnings increased by 15.1% for mainly rural areas and by 13.7% for largely rural areas.
The ratio between the lowest quartile (25% of house prices and the lowest quartile earnings) reveals in 2017 in predominantly rural areas the average lower quartile house price was 8.6 times the average lower quartile earnings – compared with 7.4 times in urban areas excluding London.
The Joseph Rowntree Foundation (JRF) has developed a Minimum Household Income (MIS). MIS is based on the items that members of the public think UK households need to be able to afford in order to meet material needs (e.g. food, shelter, clothing) as well as opportunities and choices to participate in society (e.g. transport, communication and computing, to be able to take part in activities). The amount that households need to earn in order to reach MIS in 2018 was £18,400 for a single adult and £20,000 for a dual-earner couple with two children. Back in 2010 JRF did a specific piece of work on a MIS for rural households. Researchers found people living in rural areas typically spent 10-20% more on meeting their everyday requirements compared to their urban counterparts. In 2010 it was suggested that single working adults in rural towns needed to earn at least £15,600, in villages £17,900 and £18,600 in hamlets – compared to £14,400 in urban areas. For couple with two children the annual earning requirement increased to £33,000-£42,000.
Every man is rich or poor according to the degree in which he can afford to enjoy the necessaries, conveniences, and amusements of human life—Adam Smith
Geographer Danny Dorling uses the term ‘peak inequality’ to describe circumstances under which the places that we live in have become so segregated that the best-off do not mix with the less well-off. Dorling describes how equality of the bottom 90% of UK citizens peaked in 1978 when they took home 72.2% of the income that there was to take that year. Since then there has been rising inequality. The income share of the next 9% above the 90% peaked in 1993 (at 28% of all income) but fell to 25% in 2014. By 2013 the income of the top 0.1% peaked at 5.8% or 58 times average incomes.
In the United States, the MIT Media Lab project is mapping income inequality not just according to where people live, but also where they shop, eat and spend their free time in Boston. The researchers have identified ‘place inequality’ and ‘income segregation’ to describe how the places where people live and the people around them can be radically different. i.e., at one coffee shop visitors come from a variety of household income levels but at a second coffee shop, a 2 minute walk away, people are mainly from the lowest income bracket.
Living Standards research by The Resolution Foundation explores the prospects for household incomes and inequalities over the next five years. The researchers found that typical incomes stagnated in 2017-2018 and are projected to grow slowly over the next five years – reaching only 1.3% by 2022-2023. For the ‘just about managing’ low to middle income working age households, this means three years of falling or flat incomes (reflecting weak real term pay growth, cuts to working age benefits and housing costs). These findings suggest income inequality in the UK is likely to increase over the next 4-5 years without public policy interventions.
We need to (re)think how we measure ‘money received on a regular basis’ (for rural residents and households) and determine the ‘disposable income’ left over. For some people living in rural areas their income can fluctuate on a regular basis. I am thinking here of job jugglers – people who have more than one type of work (some of it seasonal, temporary or part time leading to low pay); people out of work and trying to get by without seeking support from the state; and people barely scraping a living or workers accepting lower wages or working fewer hours. We also need to take into account where people work and the kinds of work that they do. People do not necessarily work in the same place as where they live, workplace and residence based average earnings differ – with average residence based earnings in rural areas typically higher than workplace earnings because people living in rural settlements may commute to work in urban areas for higher paid jobs.
We also need to understand how much it costs to live in rural England (and different types of rural areas – from the sparse/dispersed to town and fringe) i.e., expenditure on housing, utilities, transport, access to services, food and so on. And not merely the expenditure required to meet ‘basic needs’ but those that enable an individual to live a fulfilling life in rural areas. How much does it cost, on a regular basis, to live in the countryside?
Both strands of information would then provide a means of measuring the dispersion of incomes and benchmarking them (across different types of places and areas). This may further provide a means of forecasting how changes in income will affect different individuals and households in rural England. It may also be possible then to see how public policy may further be harnessed to reduce the gap between the richest and poorest households in our rural areas.
Reference:  Smith, Adam. "An Inquiry into the Nature and Causes of the Wealth of Nations." Edwin Cannan ed., 1904. Chicago: University of Chicago Press, 1976.
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