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Antipoverty Effects of Various Social Transfers and Income Taxes Across Countries

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Abstract

Most welfare states design their tax/benefit-system to combat income poverty. This paper analyzes the effectiveness of social transfers and income taxes in alleviating poverty. We use micro-data from the Luxembourg Income Study to examine the antipoverty effect of social transfers and income taxes. Our data also allow us to decompose the trajectory of the market income poverty to disposable income poverty into 7 different benefits, income taxes and social contributions. On average across 49 countries, 15 percent of the total population is lifted out of poverty via tax/benefit-systems. As far as specific social programs are concerned, only three programs account for the bulk of total poverty reduction: old-age/disability/survivor scheme (81%), social programs for family and children (14%) and the unemployment scheme (8%).

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Fig. 1

Source Caminada and Wang (2019) based on LIS, and own calculations

Fig. 2

Source Caminada and Wang (2019) based on LIS, and own calculations

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Notes

  1. Among others Atkinson (1987), Champernowne (1974), Hagenaars and De Vos (1987). See for an overview Alvaredo and Gasparini (2015) and Caminada et al. (2019c).

  2. OECD (2015) was the third OECD flagship publication on trends, causes and remedies to growing inequalities. The 2008 report Growing Unequal? documented and analyzed the key features and patterns of trends in income inequality in OECD countries (OECD 2008). The 2011 publication Divided We Stand: Why Inequality Keeps Rising analyzed the deep-rooted reasons for rising inequality in advanced and most emerging economies (OECD 2011). The 2015 publication It Together: Why Less Inequality Benefits All highlights the key areas where inequalities originate and where new policy approaches are required (OECD 2015).

  3. Among others Cantillon and Marchal (2016), Lefebvre et al. (2010), Marx et al. (2014), Valls Fonayet et al. (2020).

  4. Among others, Brandolini and Smeeding (2007, 2009), Atkinson and Brandolini (2001), Smeeding (2000, 2004), Gottschalk and Smeeding (1997, 2000), Kenworthy and Pontusson (2005), Alvaredo and Gasparini (2015) and OECD (2016).

  5. The distinctive feature and value-added of LIS is the access it provides to a set of harmonized micro data files supplied by participating statistical agencies at the country level (Ravallion (2015: 529): Harmonization of income data increases quality and comparability across nations and across time. See Smeeding and Latner (2015) for a critical review of three other popular data sets which summarize inequality across countries and years (World Development Indicators (‘WDI’)/ ‘PovcalNet’ and ‘All the Ginis’). Following Ravallion (2015: 529): There are pros and cons of each source. While WIID is the largest (by far) it is probably the least methodologically consistent internally, while LIS is the smallest but most consistent. PovcalNet and the WDI are somewhere between the two.

  6. See Caminada et al. (2019c) and references listed therein. Recent comprehensive reviews on methodological assumptions underlying international levels and trends in inequality are found in Brandolini and Smeeding (2007 and 2009).

  7. See Been et al. (2017) for such an analysis. Preferably, however, the redistributive effects of occupational and private pensions should be analysed on a life time basis.

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Acknowledgements

This study is part of the research program Reform of Social Legislation of Leiden University. This work was sponsored by Instituut GAK, Natural Science Foundation of China (Project 71790615 and 72073091) and Shanghai Pujiang Program (Project 17PJC045). We thank the LIS Cross-National Data Center in Luxembourg for permission to post the Budget Incidence Fiscal Redistribution Dataset on Relative Income Poverty at our website (Leiden Law School / Economics / Data).

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  1. Leiden University and Netspar, 2300RA, Leiden, Netherlands

    Koen Caminada & Kees Goudswaard

  2. Shanghai University of Finance and Economics and Leiden University, Shanghai, 200433, China

    Chen Wang

  3. Central South University China and Leiden University, Changsha, 410083, China

    Jinxian Wang

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  1. Koen Caminada
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Correspondence to Jinxian Wang.

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Caminada, K., Goudswaard, K., Wang, C. et al. Antipoverty Effects of Various Social Transfers and Income Taxes Across Countries. Soc Indic Res 154, 1055–1076 (2021). https://doi.org/10.1007/s11205-020-02572-9

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