Abstract
Does the welfare state affect human well-being outside the developed OECD world? For decades scholars have assessed the impact of the welfare state on a variety of outcomes, largely economic and social (for reviews see Kenworthy, Social Forces. 77:1119–1039, 1999; Kenworthy & Pontusson, Perspectives in Politics. 3:449–471, 2005; O’Connor, Review of Behavioral Economics. 4:397–420, 2017). While more recent focus has shifted to the impact of welfare programs on human well-being, this literature has suffered from several shortcomings. First, there has been an overriding focus on developed core OECD countries. Second, the primary outcome of interest has been on subjective well-being (life satisfaction, happiness). In this paper, we try to address these shortcomings to some extent. First, we extend the analysis to a wider and more diverse sample of countries. Second, we focus on a range of aspects of human well-being beyond life satisfaction. Third, we rely on a new measure of welfare impact that goes beyond mere overall spending—expert survey based coding of social security protections from the global Quality of Government 2021 data set. We find that in our sample of countries, this welfare measure exerts a positive and significant effect on a range of well-being outcomes. Implications for the study of the welfare state and well-being are discussed.
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Notes
The measure ranges from 1–10, and countries are scored in the following manner based on the following question: To what extent do social safety nets provide compensation for social risks? 1. Social safety nets do not exist. Poverty is combated hardly at all, or only ad hoc. 4. Social safety nets are rudimentary and cover only few risks for a limited number of beneficiaries. The majority of the population is at risk of poverty. 7. Social safety nets are well developed, but do not cover all risks for all strata of the population. A significant part of the population is still at risk of poverty. 10. Social safety nets are comprehensive and compensate for social risks, especially nationwide health care and a well-focused prevention of poverty.
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Appendices
Appendix A: Countries in Sample
Czech Republic, Slovenia, Slovakia, Poland, Croatia, Kazakhstan, Lithuania, Belarus, Moldova, Estonia, Albania, Russia, Romania, Ukraine, Kyrgyzstan, Hungary, Latvia, Bosnia & Herzegovina, China, Serbia, Azerbaijan, Tajikistan, Macedonia, Armenia, Georgia, Bulgaria, Costa Rica, Panama, Venezuela, Mexico, Brazil, Singapore, Argentina, Colombia, Chile, Guatemala, Taiwan, Uruguay, Thailand, Malaysia, El Salvador, Bolivia, Jordan, Ecuador, Paraguay, Vietnam, Peru, Algeria, Honduras, Turkey, Pakistan, Nicaragua, Indonesia, South Africa, Dominican Republic, Iran, Tunisia, Laos, Lebanon, Morocco, India, Ghana, Philippines, Bangladesh, Egypt, Iraq, Mongolia,, Ethiopia, Mauritania, Nepal, Syria, Uganda, Cameroon, Yemen, Sri Lanka, Afghanistan, Burkina Faso, Cambodia, Liberia, Tanzania.
Appendix B: Main Variable Descriptions (Variable code from Quality of Government data base, Basic data set https://www.gu.se/en/quality-government/qog-data). Original data sources listed below,some of which are also from the QoG version as indicated by *
Principal Independent Variable
Social Safety Nets (bti_ssn)
1–10 scale based on the extent social safety nets provide compensation for social risks.
-
1.
Social safety nets do not exist. Poverty is combated hardly at all, or only ad hoc.
-
2.
Social safety nets are rudimentary and cover only few risks for a limited number of beneficiaries. The majority of the population is at risk of poverty.
-
3.
Social safety nets are well developed, but do not cover all risks for all strata of the population. A significant part of the population is still at risk of poverty.
-
4.
Social safety nets are comprehensive and compensate for social risks, especially nationwide health care and a well-focused prevention of poverty.
*Source: Bertelsmann Stiftung Transformation Index 2020 (http://www.bti-project.org/en/home). Indices based on questions asked of countries experts on 137 middle and low income countries.
Life Satisfaction
Cantril Self-Anchoring Scale of “best possible life” with 0 as lowest possible score and 10 as highest.
Source: Gallup World Poll, accessed through World database of Happiness (worlddatabaseofhappiness.eur.nl).
Healthy Life Expectancy (who_halet)
Healthy life expectancy at birth (years).
*Source: Global Health Observatory, World Health Organization (http://www.who.int/data/gho).
Human Capital Index (pwt_hci)
Human capital index based on years of schooling and assumed returns, based on Mincer equation around the world.
*Source: Feenster, Inklaar and Timmer (http://www.rug.nl/ggdc/productivity/pwt/).
Details on variable construction (https://www.rug.nl/ggdc/docs/human_capital_in_pwt_90.pdf).
*Women Political Empowerment Index (vdem_gender).
Index capturing greater choice, agency, and participation for women in societal decision-making. Index formed by taking the average of womens’ civil liberties index, womens’ civil society participation index, and womens’ political participation index.
Details on construction of the index can be found here: (https://v-dem.net/media/publications/v-dem_working_paper_2015_19.pdf).
Source: Varieties of Democracy (v-dem.net/en/data/).
Principal Dependent Variables
*Gender Inequality Index (gii_gii): Index (0–1) measures gender inequality in three aspects of human development-reproductive health, measured by maternal mortality ratio and adolescent birth rates, empowerment measured by proportion of parliamentary seats occupied by women vs. men, and economic status expressed as labour market participation rate of women vs. men. The higher the GII value, the more disparities between women and men and the more loss to human development.
Source: United Nations Human Development Reports (https://hdr.undp.org/data-center/thematic-composite-indices/gender-inequality-index#/indicies/GII).
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Schmidt, E., Pacek, A.C. & Radcliff, B. The Welfare State and Human Well-Being Around the World: A Cross-National Analysis. Applied Research Quality Life 19, 365–380 (2024). https://doi.org/10.1007/s11482-023-10247-z
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DOI: https://doi.org/10.1007/s11482-023-10247-z