Dr Abigail McKnight Associate Professorial Research Fellow and Associate Director, CASE, LSE Dr Chiara Mariotti Inequality Policy Manager, Oxfam

Hosted by LSE Works: CASE The Relationship between Inequality and Poverty: mechanisms and policy options Dr Eleni Karagiannaki Research Fellow, CASE, LSE Chris Goulden Deputy Director, Policy and Research, Joseph Rowntree Foundation Professor Stephen Machin Chair, LSE Dr Abigail McKnight Associate Professorial Research Fellow and Associate Director, CASE, LSE Dr Chiara Mariotti Inequality Policy Manager, Oxfam Hashtag for Twitter users: #LSEworks

Understanding the relationship between poverty and inequality Eleni Karagiannaki and Abigail McKnight LSE Works Public Lecture 8 February 2017

Motivation Well documented upward trend in inequality in high and middle income countries since 1970s; although trends are not uniform across countries Growing concern about 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 poverty reduction in rich and middle income countries without addressing income inequalities Big players World Bank, United Nations, World Economic Forum, OECD, Oxfam, 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

CASE research programme Joseph Rowntree Foundation funded a three year programme of research which is part of a wider partnership with the LSE s International Inequalities Institute Improving the evidence base for understanding the links between inequalities and poverty Oxfam funded a rapid Review of the evidence on the relationship between economic inequality and poverty

Approach Examining the conceptual basis Documenting measurement issues Extending the empirical evidence base Understanding the mechanisms Exploring potential policy responses

Measurement issues Measures of income inequality and poverty are summary statistics calculated from the same distribution (household income), therefore we would expect these measures will be linked in a 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 income distribution 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 not what we observe We are interested in identifying what mechanisms underlie distributions of income (eg) where there is high inequality/poverty versus low inequality/poverty

UK income distribution 2014/15 HBAI 2016, BHC

The empirical relationship between inequality and poverty in rich and middle income countries: Evidence from the EU Income and Living Conditions Database Eleni Karagiannaki LSE works February 2017

Plan of the presentation Using comparative distributional statistics from the Eurostat Income and Living Conditions database I will present evidence on: (1) the extent to which higher levels of inequality are associated with higher levels of poverty and (2) whether increasing levels of income inequality across a number of European countries have been associated with increasing poverty.

Key findings Levels of inequality and poverty are highly correlated This correlation is stronger for inequality measures that summarize the degree of inequality at the bottom of the distribution and stronger when poverty is measured by poverty rates than poverty gaps A positive (albeit slightly weaker) correlation is estimated examining the relationship between changes in inequality and changes in the incidence and the depth relative income poverty as well as between changes in inequality and in the incidence of anchored poverty Despite the positive correlation between poverty and inequality trends there is substantial degree of heterogeneity across countries in how poverty and inequality evolved over this period: there are countries where inequality and poverty have moved in different directions

I. Differences in the level of inequality and poverty across different European countries in 2014

Levels of income inequality and relative income poverty are strongly correlated Inequality and relative income poverty risk in 2014 for 26 European countries Relative poverty risk (%) 5 10 15 20 25 greece spain latvia italy portugal lithuania malta luxembourg germany poland unitedkingdom sweden belgiumhungary ireland austria cyprus finland slovakia france denmark netherlands czechrepublic iceland r=0.87*** Relative poverty risk (%) 5 10 15 20 25 luxembourg malta germany unitedkingdom poland sweden belgium hungary ireland austria cyprus finland france denmark slovakia netherlands czechrepublic iceland greece spain latvia italylithuania portugal r=0.95*** 20 25 30 35 40 Gini 2 3 4 5 6 P90:P10 Relative poverty risk (%) 5 10 15 20 25 greece spain latvia italy portugal lithuania germany poland malta luxembourg unitedkingdom sweden belgium hungary ireland austria cyprus finland france denmark slovakia netherlands czechrepublic iceland r=0.81*** Relative poverty risk (%) 5 10 15 20 25 latvia lithuania italy portugal luxembourg unitedkingdom malta germany poland ireland cyprus sweden belgium hungary austria finland france denmark slovakia netherlands czechrepublic r=0.94*** iceland greece spain 1.6 1.8 2 2.2 2.4 P90:P50 1.6 1.8 2 2.2 2.4 2.6 P50:P10

Levels of income inequality also tend to be highly correlated with the depth of income poverty but the relationship is weaker Inequality and poverty gap ratio in 2014 for 26 European countries Poverty gap ratio 10 20 30 40 slovakia croatiaitaly fyrom romania bulgaria greece spain portugal germany poland latvia hungary lithuania swedenaustria czechrepublic belgium unitedkingdom denmark malta cyprus iceland netherlands luxembourg france ireland finland r=0.54** serbia 20 25 30 35 40 Gini Poverty gap ratio 10 20 30 40 50 slovakia croatia italy latvia hungary germany poland lithuania sweden austria czechrepublic denmark belgium unitedkingdom iceland netherlands maltacyprus france luxembourg ireland finland romania fyrom bulgaria spain portugal greece r=0.71** 3 4 5 6 7 P90:P10 serbia Poverty gap ratio 15 20 25 30 35 40 slovakia croatia italy fyrom romania bulgaria greecespain portugal germany poland latvia hungary lithuania sweden austria unitedkingdom belgium denmark czechrepublic malta cyprus icelandnetherlands france ireland r=0.43* luxembourg finland serbia 1.6 1.8 2 2.2 2.4 P90:P50 Poverty gap ratio 10 20 30 40 50 slovakia latvia hungary germany poland lithuania austria sweden czechrepublic denmark cyprus belgium unitedkingdom iceland netherlands malta france ireland luxembourg finland fyromromania bulgaria spain portugal greece croatia italy r=0.82*** serbia 1.5 2 2.5 3 3.5 P50:P10

II. Changes in the level of inequality and poverty across European countries in 2005 14

Changes in income inequality are positively correlated with changes in the incidence of relative income poverty % change in inequality and relative poverty risk % change in poverty risk -.6 -.4 -.2 0.2.4 poland portugal italy unitedkingdom iceland irelandlatvia netherlands lithuania austria greece slovakiahungary spain sweden belgium malta czechrepublic finland france luxembourg germany denmark cyprus % change in poverty risk -.5 0.5 poland austria greece slovakia hungary spain germany portugal italy denmark sweden malta belgium czechrepublic finland france cyprus unitedkingdom luxembourg ireland iceland latvia lithuania netherlands r= 0.55** r= 0.74*** -.2 -.1 0.1.2 % change in Gini -.3 -.2 -.1 0.1.2 % change in P90:P10 % change in poverty risk -.5 0.5 portugal poland austria greece slovakia spain hungary germany italy denmark sweden maltabelgium czechrepublic france finland cyprus unitedkingdom iceland luxembourg latvia ireland lithuania netherlands % change in poverty risk -.4 -.2 0.2.4 poland belgium malta finland czechrepublic france cyprus unitedkingdom luxembourg ireland icelandlatvia lithuania netherlands austria greece slovakia germany spain hungary denmark portugal italy sweden r= 0.26 r= 0.81*** -.15 -.1 -.05 0.05.1 % change in P90:P50 -.2 -.1 0.1.2 % change in P50:P10

Changes in income inequality are also positively correlated with changes in the depth of poverty % change in inequality and in the poverty gap ratio % change in poverty gap ratio -.2 0.2.4.6 poland iceland ireland sweden luxembourg finlandhungary malta greece austria netherlands latvia spain belgium portugalitaly france czechrepublic lithuania slovakia unitedkingdom r=0.42 germany denmark cyprus % change in relative poverty risk -.4 -.2 0.2.4 poland sweden germany luxembourg malta austria finland hungary greece latvia netherlands spain belgium portugal france italy denmark czechrepublic slovakia lithuania unitedkingdom cyprus iceland ireland r=0.66*** % change in poverty gap ratio -.2 0.2.4.6 -.2 -.1 0.1.2 % change in Gini portugal sweden germany luxembourg greecemalta finland austria netherlands latvia spain hungary belgium italy france denmark czechrepublic slovakia lithuania unitedkingdom cyprus poland r=0.15 iceland ireland -.15 -.1 -.05 0.05.1 % change in P90:P50 % change in poverty gap ratio -.4 -.2 0.2.4 -.3 -.2 -.1 0.1.2 % change in P90:P10 luxembourg austria latvia finland maltahungary netherlands denmark belgium france portugal italy lithuania czechrepublic slovakia unitedkingdom cyprus poland iceland ireland sweden germany spain greece r=0.77*** -.2 -.1 0.1.2 % change in P50:P10

A positive (though weaker) correlation is also estimated when the poverty line is anchored at 2005 levels % change in inequality and in the anchored poverty risk % change in anchored poverty rate -1.5-1 -.5 0.5 1 poland italy portugal netherlands ireland unitedkingdom iceland belgium finland czechrepublic latvia lithuania slovakia spain hungary austria malta greece luxembourg sweden r=0.41* germany cyprus denmark % change in anchored poverty -2-1 0 1 poland portugal ireland unitedkingdomiceland lithuania czechrepublic malta luxembourg italy cyprus germany spain netherlands austria hungary belgium denmark sweden finland latvia slovakia greece r=0.51*** -.2 -.1 0.1.2 % change in Gini -.3 -.2 -.1 0.1.2 % change in P90:P10 % change in anchored poverty -1.5-1 -.5 0.5 1 portugal poland greece italy luxembourg germany cyprus spain unitedkingdom netherlands austria ireland hungary iceland belgium denmark sweden finland czechrepublic malta lithuania slovakia latvia r=0.19 % change in abs. poverty -1.5-1 -.5 0.5 1 poland greece cyprus luxembourg italy germany portugal spain ireland netherlands hungary austria unitedkingdom iceland denmark belgium sweden finland czechrepublic malta latvia lithuania slovakia r=0.55** -.15 -.1 -.05 0.05.1 % change in P90:P50 -.2 -.1 0.1.2 % change in P50:P10

Conclusions Levels of income inequality and poverty display a very strong positive correlation This positive correlation is stronger for inequality measures that summarize the degree of inequality at the bottom of the distribution and stronger when poverty is measured by poverty rates than poverty gaps A positive (albeit slightly weaker) correlation is estimated between changes in inequality and changes in the incidence and the depth relative income poverty as well as changes in the incidence of anchored poverty Despite the positive correlation between poverty and inequality trends, the analysis also identified the varying experiences across countries in how inequality and poverty evolved: there were countries inequality and poverty trends have moved in different directions policy and institutions matter

Mechanisms

Mechanisms Economic mechanisms Fundamental drivers distribution of abilities and rates of return acting through the labour market Resource constraints (Scale/the race between the state and the rich) Political mechanisms Self interest of rich and powerful elite Reinforcement mechanisms Social and cultural mechanisms Values, attitudes and beliefs Fear punitive (and impoverishing) reactions to crime Policy plays a key role in ameliorating or exacerbating the extent to which these mechanisms relate inequality to poverty

Economic mechanisms the labour market Skill biased technological change, globalisation and weakening of labour market institutions are thought to be the main drivers behind changes in labour market inequality over the last few decades. These changes provide an explanation for both increases in income inequality and poverty risk. Demand shift in favour of high skilled workers and a weakening in the wage bargaining power of low skilled workers increases the risk of unemployment, low pay and precarious employment for lower skilled workers and increases wage inequality between skill levels; The relationship between individual labour market outcomes (pay/unemployment) and household level outcomes of income inequality and poverty risk is complex; Household formation, household composition, cash transfers and direct taxes all play a key role in defining this relationship.

Economic mechanism the labour market Individual Poverty At risk of poverty rate (% < 60% median income) 30 25 20 15 10 5 y = 23.416x + 24.592 R² = 0.073 0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Individual gross annual earnings inequality (Gini) Inequality Household equivalised income inequality (Gini) 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 y = 0.0718x + 0.3242 R² = 0.0067 0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Individual gross annual earnings inequality (Gini) 32 EU SILC countries (2013) working age population

Economic mechanism the labour market Household 30 Poverty At risk of poverty rate (%<60% median income) 25 20 15 10 5 y = 88.579x 18.028 R² = 0.5 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Household annual total gross earnings inequality (Gini) Poverty At risk of poverty rate (%<60% median income) 30 25 20 15 10 5 0 y = 79.487x 13.962 R² = 0.6332 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Household equivalised annual gross earnings inequality (Gini) 32 EU SILC countries (2013) working age population

Economic mechanism the labour market Household equivalised 0.4 0.35 Less redistribution Bulgaria Household equivalised income inequality (Gini) 0.3 0.25 0.2 0.15 0.1 y = 0.8694x 0.0265 R² = 0.7376 Slovenia Ireland More redistribution 0.05 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Household annual equivalised earnings inequality (Gini) 32 EU SILC countries (2013) working age population

Political mechanisms Rise of rich and powerful elite (Stiglitz, 2012; Gilens and Page, 2014; Piketty, 2014) Influence government policy (opportunity hoarding and the role of donors to political campaigns and political parties) 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) Electoral systems and their propensity for redistribution (Iversen and Soskice, 2006) The electoral system in which individuals cast their votes plays a key role in shaping political parties, the composition of governing coalitions, and the likelihood of redistribution Centre right governments tend to dominate in majoritarian systems whereas centre left governments tend to dominate in PR systems Winner take all politics into loser take all poverty and inequality (Hacker and Pierson, 2010)

Social and Cultural mechanisms Commonly held belief that inequality is too high but people tend to underestimate the true level of inequality some evidence suggests that this is influenced by various types of segregation (geographical/media/jobs/social networks/schools) Political economy models (Meltzer and Richard, 1981) predict that in democracies an increase in inequality will lead to an increase in redistribution, but the literature shows that this prediction doesn t always hold due to a number of factors shaping individuals redistributive preferences: Own income Expectations of upward/downward mobility Values and beliefs (why some people are poor/rich) Under estimate of the level of inequality and overestimates of social mobility Beliefs on the effectiveness/impact of certain policies (eg social security and work incentives) Persistently high inequality can influence social norms Increases in income inequality correlated with increases in public punitiveness (Côté Lussier, 2016) and rates of incarceration. Those with no capital get the punishment (Sim, 2009)

Summary Measurement: The statistical measures we commonly use to assess levels of inequality and poverty give rise to correlations between these two concepts; Empirical evidence: The positive correlation between income poverty and inequality is stronger for inequality measures that summarise the degree of inequality at the bottom of the distribution, and stronger for headcount measures than poverty gaps; Mechanisms: The literature identifies a number of mechanisms which help to explain the shape of the income distribution and why increases in inequality can lead to increases in poverty; Policy: The evidence suggests that tackling poverty without addressing inequality will be ineffective in the long run unless the mechanisms that link the two are broken.