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Home , Gini coefficient, Poverty reduction

How are Inequality and Linked?

Abigail McKnight

Associate Director Centre for Analysis of , London School of

UN expert meeting: New Research on Inequality and Its Impacts 12 th and 13 th September 2018 Motivation • There is a well documented upward trend in inequality in high and middle countries since 1970s; although not everywhere, and trends are not uniform across countries and vary across different measures • A growing concern about potential harmful effects of inequality on societies, including the role inequality played in the lead up to the financial crisis • Recent shift in thinking away from the assumption that policy can successfully target (including in rich and middle income countries) without addressing income inequalities • Big players - , , World Economic Forum, OECD, , etc – setting twin goals and outlining recommendations that policy needs to simultaneously tackle poverty and inequality in rich as well as poor countries • … but knowledge and evidence gaps on the of the relationship between and poverty Measurement issues

• Measures of income inequality and poverty are summary often calculated from the same (household income), therefore we would expect these measures will be linked in a ‘mathematical/mechanical’ sense • The strength of the relationship between inequality and poverty will depend on the extent to which any inequality measure is sensitive to dispersion of income in the lower half of the • Theoretically it is possible to have: (1) no relative income poverty (income < 60% median income) but high inequality (high concentration of income among a small group of very rich households); high relative income poverty but low inequality (very low dispersion of income above the median) but in practise this is rarely observed UK Poverty and Income Inequality Trends 1961-2015/16

5.0 40

4.5 35

4.0 30 3.5

25 3.0

2.5 20

2.0 15

1.5 10 1.0

5 0.5

0.0 0 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993-94 1994-95 1995-96 1996-97 1997-98 1998-99 1999-00 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 90/10 ratio (BHC) 50/10 ratio (BHC) 90/50 ratio (BHC) (BHC) (RHS) <60% median (AHC) (RHS) Top 1% income share-married couples & single adults (RHS) Top 1% income share-adults (RHS) UK Poverty and Income Inequality Trends 1961-2015/16

5.0 40

4.5 35

4.0 30 3.5

25 3.0

2.5 20

2.0 15

1.5 10 1.0

5 0.5

0.0 0 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993-94 1994-95 1995-96 1996-97 1997-98 1998-99 1999-00 2000-01 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 90/10 ratio (BHC) 50/10 ratio (BHC) 90/50 ratio (BHC) Gini coefficient (BHC) (RHS) <60% median (AHC) (RHS) <60% median (BHC) (RHS) Top 1% income share-married couples & single adults (RHS) Top 1% income share-adults (RHS) Relationship between UK poverty and income inequality (Gini)

Before housing costs After housing costs 0.25 0.30

y = 0.7261x - 0.0496 y = 0.5735x - 0.0132 0.25 0.20 R² = 0.6862 R² = 0.8819

0.20

0.15

0.15

0.10

0.10 Poverty rate (<60% median) (<60% rate Poverty Poverty rate (<60% median) (<60% rate Poverty

0.05 0.05

0.00 0.00 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 Inequality (Gini) Inequality (Gini) Relationship between poverty and income inequality (decile ratios) – before housing costs

0.25 0.25

0.20 y = 0.2432x - 0.3061 0.20 y = 0.165x - 0.1528 R² = 0.9246 R² = 0.7022

0.15 0.15

0.10 0.10 Poverty rate (<60% median) (<60% rate Poverty median) (<60% rate Poverty

0.05 0.05

0.00 0.00 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 Inequality (50/10 ratio) Inequality (90/50 ratio) Relationship between poverty and income inequality (decile ratios) – after housing costs

0.30 0.30

0.25 y = 0.161x - 0.1518 0.25 y = 0.2308x - 0.2636 R² = 0.8772 R² = 0.8926

0.20 0.20

0.15 0.15

0.10 0.10 Poverty rate (<60% median) (<60% rate Poverty median) (<60% rate Poverty

0.05 0.05

0.00 0.00 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 Inequality (50/10 ratio) Inequality (90/50 ratio) Relationship between poverty and top 1% share – before housing costs

0.250

19901992 1989 1988 1991 0.200 1993 19961997 1998 1994 1999 20012000 2007 1987 1995 2002 2006 2003 2005 2004 2009 1972 1986 2010 2011 2014 2012 2013 0.150 1971 1963 1985 197419811973 1969 19781979 1970 19671966 19621965 1975 19831984 1976 1982 1968 1964 1977 y = 0.0057x + 0.1039 0.100 R² = 0.3308 Poverty (<60% median) (<60% Poverty

0.050

0.000 0 2 4 6 8 10 12 14 16 18 20 Top 1% income share (%) Levels of income inequality and relative income poverty are strongly correlated across countries Inequality and relative income poverty risk in 2014 for 26 European countries 25 25 greecespainlatviaestonia latviaestoniagreecespain 20 portugallithuania 20 italy lithuaniaportugal germanypolandunitedkingdom germanyunitedkingdompoland maltaluxembourgireland belgiumluxembourgmaltaireland 15 15 sweden hungarycyprus franceaustria finlandslovakiadenmark denmarkfinlandslovakia norwaynetherlands 10 czechrepublic 10 czechrepublic Relative poverty risk (%) risk poverty Relative (%) risk poverty Relative iceland

5 r=0.87*** r=0.95*** 5 20 25 30 35 40 2 3 4 5 6 Gini P90:P10 25 25 latviaestonia greecespain 20 italy 20 lithuania italy portugal polandunitedkingdom belgium maltaluxembourg ireland luxembourgmalta unitedkingdomgermanypoland 15 sweden irelandbelgium austriahungary cyprus 15 swedenhungary france francecyprusaustria denmarkslovakiafinland finlanddenmarkslovakia norway netherlands norwaynetherlands 10 czechrepublic 10 czechrepublic

Relative poverty risk (%) risk poverty Relative iceland (%) risk poverty Relative iceland r=0.81*** r=0.94*** 5 5 1.6 1.8 2 2.2 2.4 1.6 1.8 2 2.2 2.4 2.6 P90:P50 P50:P10

Eleni Karagiannaki (2017) “The Empirical relationship between income poverty and income inequality in rich and middle income countries”, LIPpaper 3, Centre for Analysis of Social Exclusion, London School of Economics …so are changes in inequality and changes in poverty – European countries 1996-2014

Eleni Karagiannaki (2017) “The Empirical relationship between income poverty and income inequality in rich and middle income countries”, LIPpaper 3, Centre for Analysis of Social Exclusion, London School of Economics Relationship between income inequality and material deprivation and multidimensional poverty

• We also examined the link between the way a country's most deprived individuals experience disadvantage across multiple dimensions of life and its level of income inequality. • By expanding the definition of disadvantage beyond income poverty, we sought to overcome some of the criticisms that might be levelled at a mechanical link between strictly income-based measures of poverty and inequality. • We used three measures of material deprivation and multidimensional poverty, and focused our analysis on European countries. • The main findings are that broader multidimensional poverty measures are also positively linked to income inequality, but (over a short period) changes in them are not.

Lin Yang and Polly Vizard (2017) “Multidimensional poverty and income inequality in the EU” LIPpaper 4, Centre for Analysis of Social Exclusion, London School of Economics What drives the relationship between inequality and poverty – review of mechanisms • Social aspects: Public opinion and shifts in cultural and social norms – underestimating inequality/perceptions of reasons for ‘success’ and ‘failure’ • Spatial aspects of inequality and poverty – segregation/public expenditure and investment • Political aspects: the relationship between riches and access to political power and decision making, political representation, legal frameworks and voting • Crime and the legal system: crime, punishment and unequal access to justice Public opinion and shifts in cultural and social norms • Standard models predict that an increase in inequality will lead to an increase in demand for redistribution and as a result inequality and poverty will fall (Meltzer and Richard, 1981). However, empirical evidence is mixed. Why? ‹Current income alone doesn’t shape individuals’ redistributive preferences – expectations of upward mobility. ‹Evidence shows that people underestimate the level of inequality and overestimate the level of social mobility. This is important because there is a positive (negative) correlation between people’s perceived level of inequality (social mobility) and the demand for redistribution. ‹People’s knowledge of inequality, the tax and benefit system and redistribution is limited (Orton and Rowlingson, 2007) ‹‘Failure attribution argument’ – redistributive preferences are influenced by beliefs on why individuals are poor or rich (hard work/lazy/luck/etc). Some evidence that these beliefs are malleable. ‹High levels of inequality can become ‘normalised’. Political • Rise of rich and powerful elite: ‹Influence government policy (opportunity hoarding and the role of donors to political campaigns and political parties) (Stiglitz, 2012); ‹Lower income individuals withdraw from the voting booths; ‹Political parties focus on policies that favour the voting electorate (median voter has higher than median income) who are less likely to support redistributive (or ‘pre- distributive’) policies than the population; can generate political instability as disenfranchised members of the population can become attracted to populist parties and candidates (Bonica, McCarty, Poole, and Rosenthal, 2013; Gilens and Page, 2014) • Growing recognition of the role of tax havens in perpetuating inequality and reducing the potential for governments to tackle inequality due to their impact on government revenues. ‹Due to the role that policy and legal rules play in allowing the development of these havens, some legal scholars have argued that inequality is ‘more a question of law then economics’ (Hsu, 2015). Spatial aspects of inequality and poverty

• Research examining the geography of income, poverty and has consistently shown an unequal distribution within countries and some evidence shows an increase in concentration. • Segregation of rich and poor can be important as it can alter people’s perceptions and influence their preferences for redistribution. • Greater spatial inequality can lead to calls for greater devolution with greater freedom for regions to raise revenue and have control over local spending decisions, but there is a danger that spatial inequalities will increase further due to differences in the ability to raise income - tax raising powers are often negatively related to need. Crime, the legal system and punitive sanctions • Economic determinants of criminal activity – an increase in inequality will lead to an increase in crimes particularly those that have the Increase in economic inequality potential for economic gain (those drawn into committing such crimes have the lowest opportunity costs) (Becker, 1968) Increase in the incentive for the • But… crime rates have fallen in many countries including those with economically to high and rising inequality. Criminologists – while inequality commit crime influences criminal behaviour at the margin, the long run downward trend is driven by a range of stronger influences (Very long run: Tonry (2014) – ‘civilising process’; From 1990s: improvements in Increase in preference for technology/demographic change/DNA/CCTV/even lead) punitive santions • However, what we do see in many high inequality countries is an increase in punitive preferences: ‹Despite falling crime rates, incarceration rates and prison populations have increased dramatically in a number of countries Increase in prison population ‹Trend towards tougher sentencing policies and punishment rather than rehabilitation • Unequal access to justice, unequal sentencing, discrimination, a rich and powerful elite shaping legal policy, funding for legal and Increase in the size of the influencing sentencing group most at risk of poverty Summary ° In recent times there has been a move towards addressing poverty and inequality as a joint issue (World Bank twin goals; Oxfam Even it Up; UN sustainable development goals) but the relationship between the two is not well understood. In this programme of research we sought to address this evidence gap. ° We observe that income inequality and income poverty trends have followed similar trends in many countries and find a positive correlation between income inequality and income poverty (levels and change), material deprivation and multidimensional poverty (levels). It seems unlikely that this is purely due to the way we measure the two phenomena. ° We think it is doubtful that one factor is behind this co-relationship and have started to explore potential mechanisms which could drive this relationship: social, spatial, political, economic, dynamics and crime. ° While still more needs to be done, the evidence gathered so far supports the view that to reduce poverty it is also necessary to tackle inequality. Resources:

Project website Improving the Evidence Base for Understanding the Links between Inequalities and Poverty - research programme funded by the Joseph Rowntree Foundation (project background and working papers) http://sticerd.lse.ac.uk/case/_new/research/Inequalities_and_Poverty.asp Project team: John Hills, Tania Burchardt, Eleni Karagiannaki, Polly Vizard, Lin Yang, Magali Duque, Irene Bucelli

Double Trouble (McKnight, Duque and Rucci) report for Oxfam GB https://policy-practice.oxfam.org.uk/publications/double-trouble-a-review- of-the-relationship-between-uk-poverty-and-economic-ine-620373