The paradox of redistribution revisited, or why targeting may matter less than we thought

Transcription

1 The paradox of redistribution revisited, or why targeting may matter less than we thought Ive Marx, Lina Salanauskaite and Gerlinde Verbist 8 March 2013

2 Claim We aim to show that Korpi and Palme s highly influential claim that the more we target benefits at the poor, the less likely we are to reduce poverty and inequality does no longer hold as a robust empirical generalisation. In fact, the relationship between targeting and redistributive impact has become a very weak one We show this finding to be relatively robust across a set of alternative empirical specifications and data sources..but specification matters 2

3 THE STORY SO FAR 3

4 Targeting is good Long standing debate, cfr. Marshall (1950), Titmuss (1952), Tawney (1952), Lampmann (1971), Barth et al. (1974); Tullock (1983), Deleeck et al (1983) Goodin and Le Grand (1987: 215): the beneficial involvement of the non-poor in the welfare state is not merely wasteful it is actually counterproductive. The more the non-poor benefit, the less redistributive the impact of the welfare state will be. 4

5 Targeting is bad Korpi and Palme The Paradox of Redistribution (Am. Soc. Rev, 1998:663): the more we target benefits to the poor the less likely we are to reduce poverty and inequality 5

6 Why targeting is said to be bad K&P claim that in welfare systems that target the poor, less resources tend to be available for redistribution because of less widespread and robust political support for redistribution. As a consequence, despite the pro-poor design the redistributive impact of such systems tends to be smaller. Put another way: some degree of redistributive inefficiency (Matthew effect) is the necessary price to pay for effective redistribution *. 6

7 Targeting may not be so bad after Many subsequent studies: Moene and Wallerstein (2001); Pontusson (2005); Nelson (2007); Whiteford (2007;2008), all Corak, Lietz and Sutherland (2005): Targeting within universalism ; see also Van Lancker et al. (2012); Van Mechelen and Bradshaw (2012), Kenworthy (2011): Targeting may not be so bad 7

8 Korpi and Palme, ASR,

9 Korpi and Palme replication, LIS, mid 2000s AUS DNK GBR FIN SWE BEL CZE DEU NOR IRL CAN CHE EST ISR NLD USA HUN LUX SVN FRA ESP POL AUT ITA GRC Targeting (Concentration index, ranking on gross income) Source: Luxembourg Income Study (mid 2000s) Redistribution index

10 MEASURING TARGETING AND REDISTRIBUTIVE IMPACTS 10

11 Redistribution Redistribution refers to the impact of taxes and transfers on income inequality. It is measured by the difference between pre and post tax/transfer Gini coefficients for overall income inequality Clearly imperfect counterfactual, but no workable alternative for broad cross-country comparisons 11

12 Targeting Captured by the concentration coefficient 0 when neutral, negative when share of transfers exceed share of disposable income (=pro-poor) Is an outcome measure, not a policy design measure; design + context matter Alternative measures of targeting, e.g. transfers going to the bottom quintile of the income distribution 12

13 Concentration coef,icients versus bottom quintile transfers share Targe0ng transfers (CI gi) - Propoorness 45% AU 40% UK DK CA IE CH CZ BE FI NO IL SE DE US EE NL FR SI HU LU AT ES PL EL IT MX 35% 30% 25% 20% 15% 10% Transfers Q1 as % of total R² = 0, % 00% - 0,5-0,4-0,3-0,2-0,1 0 0,1 0,2 0,3 0,4 0,5 Targe0ng (Concentra0on index) 13

14 Concentration index (ranking by gross income) and redistributive impact, LIS, mid 2000s AUS DNK GBR FIN SWE BEL CZE DEU NOR IRL CAN CHE EST ISR NLD USA HUN LUX SVN FRA ESP POL AUT ITA GRC Targeting (Concentration index, ranking on gross income) Source: Luxembourg Income Study (mid 2000s) Redistribution index

15 Recall: two causal mechanisms Universal systems enjoy broader political support, and spending is for that reason larger More spending implies more redistribution 15

16 Concentration index (ranking by gross income) and redistributive effort AUS DNK GBR HUN SVN BEL SWE FIN CZE DEU NOR NLD EST IRL CHE ISR CAN USA Transfers as % of gross income POL AUT FRA LUX ESP GRC ITA Targeting (Concentration index, ranking on gross income) 16

17 Figure: Reduction in inequality due to taxes and transfers compared with size of social transfers (expressed as a share of gross income) USA AUS ISR CAN CHE IRL ITA EST GBR SWE DNK FIN CZE BEL NLD DEU NOR LUX AUT SVN FRA GRC ESP POL HUN Transfers as % of gross income Redistribution index

18 Robustness and specification 18

19 The picture differs somewhat by benefit type (II) BEL NLD DEU POL NOR (I) ITA AUS GBR EST ISR CHE USA Targeting of family benefits DNK FIN BEL HUN CZE POL IRL AUS FRA ITA GBR ISR CHE USA Targeting of old-age benefits GBR BEL IRL AUS CHE DNK CZE FIN FRA USA HUN ISR POL ITA Targeting of other benefits Redistribution index

20 Robustness check for data source: EU SILC HUN DNK FIN DEU BEL SWE NOR SVN CZE NLD FRA SVK LUX AUT GBR IRL POL ISL LTU ITA EST GRC LVA ESP CYP PRT Targeting (Concentration index, ranking on gross income) Redistribution index Source: EU-SILC

21 The impact of occupational pensions: LIS data Part of market income: Part of social transfers: AUS DNK GBR FIN SWE BEL CZE DEU NOR IRL CAN CHE EST ISR HUN NLD USA LUX SVN FRA POL AUT ITA ESP GRC Targeting (Concentration index, ranking on gross income) Redistribution index AUS DNK CZE SWE FIN NOR BEL DEU NLD IRL GBR CHE CAN EST HUN LUX SVN USA ITA AUTPOL FRA ISR ESP GRC Targeting (Concentration index, ranking on gross income) Redistribution index Note: countries with no information available on occupational pensions are in grey font Source: LIS 21

22 DISCUSSION: MAKING SENSE OF THIS REVERSAL 22

23 Are the newly included countries different? K&P included Australia, Canada, Finland, France, Germany, the Netherlands, Norway, Sweden, Switzerland, UK & US Additional countries included in LIS analysis - a) three Southern European countries (Greece, Italy, Spain); - b) post-communist countries now part of the EU (Czech Republic, Estonia, Hungary and Slovenia) - c) advanced economies not included in the original analysis: Austria, Ireland, Israel, Luxembourg. 23

24 Is targeting different today? Political vulnerability of strongly targeted programmes arguably not only due to small electoral base but also to (perceived) perverse work and family formation incentives Work incentives in MIPs have been drastically remodelled and some targeted systems are now integrated systems of support for the non-employed and low-paid workers alike US: AFDC => TANF + EITC France: RMI => RSA 24

25 Conclusion So perhaps we better stop worrying and learn to love targeting? But questions remain.. - Why are some «targeted» systems more redistributive than others? (policy design vs. compositional effects) - Longer term effects of targeting (work, family formation, savings), and political dynamics/robustness 25