Welfare State Matters: Welfare State Matters: A Typological Multilevel A Typological Multilevel

Analysis of Wealthy Analysis of Wealthy CountriesCountries

Hae-Joo Chung, RPh, MScDepartment of Health Policy and Management,

The Johns Hopkins School of Public Health

Summary of Today’s Summary of Today’s PresentationPresentation

To assess the relevance of ‘welfare-state typologies’ to public health research,

And to extend the social epidemiology based on the ‘income inequality paradigm’

We analyzed 3 level conditional hierarchical models of the population health data from 19 wealthy countries of the last 35 years

As a result, the regime-type effects, especially social democratic regime type had a strong explanatory power

And we could see that the social democracies had maintained better population health status for the last 35 years

Welfare State TypologiesWelfare State Typologies

Welfare-state typology has been proved to be a useful explanatory device for the emergence of welfare states, including national health policies

Three (Esping-Andersen) or four (Huber & Stephens) regime-type clusters based on qualitatively different arrangements between state, market and family “Liberal” Welfare States “Wage Earner” Welfare States “Conservative-Corporatist” Welfare States “Social Democratic” Welfare States

Esping-Andersen G. (1990) The Three Worlds of Welfare Capitalism

Huber E and Stephens JD (2001) Development and Crisis of the Welfare State

More generous

The Field of Political · Welfare The Field of Political · Welfare State Determinants of HealthState Determinants of Health

The “Relative Income Hypothesis” and “Political and Welfare-state determinants of Health”, two possible mechanisms

Welfare state variables are used to determine the structural mechanism through which economic inequality affects population health status

Studies suggest that welfare state variables (e.g., access to health care) could be important predictors of population health outcomes

However, only one study included a comprehensive number of political variables that adjust for economic determinants

Coburn, 2000; Conley & Springer, 2001; Navarro & Shi, 2001; Macinko, Starfield, & Shi, 2003; Macinko, Shi, & Starfield, 2004; Muntaner, Lynch, Hillemeier, Lee, David, Benach et al., 2002

Methodological Individualism in Methodological Individualism in Comparative Health Policy Comparative Health Policy AnalysesAnalyses

Assumes covariances Among the observations within

each country Not between/ among countries

Outcomes of a country are explained by explanatory variables of that country

Countries are independent from each other

Country A

Year Obs1990 a 1991 b 1992 c

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.

Country A

Year Obs1990 a 1991 b 1992 c

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.

.

Country B

Year Obs1990 a´ 1991 b´ 1992 c´

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.

.

Country B

Year Obs1990 a´ 1991 b´ 1992 c´

.

.

.

Country-level fixed-effects Country-level fixed-effects models using panel datasetsmodels using panel datasets

These are dependentThese are dependent

These are independentThese are independent

AimAim

To develop a more realistic model for comparative health policy analyses than widely used country-level fixed effects model

To examine the change in selected population health indicators in advanced capitalist countries in the last 35 years (1965-1994), especially before and after the neo-liberal welfare reform

HypothesisHypothesis

Generosity of the Welfare-state System

Better Health

Worse Health

Generosity of the Welfare-state System

[ A “Linear” Distribution ] [ A Distribution as “Clusters” ]

Social Social DemocraciesDemocracies

ChristianChristianDemocraciesDemocracies

WageWageEarnerEarner

LiberalLiberal

Countries and CategorizationsCountries and Categorizations

19 wealthy countries, 1960 - 1994 (35 years) Social Democratic

Denmark Finland Norway Sweden

Christian Democratic Austria Belgium France Italy Luxembourg* Netherlands Switzerland (West) Germany

Wage Earner Australia Japan* New Zealand

Liberal Canada Ireland The United Kingdom The United States of America

Outcome Variables and Data Outcome Variables and Data SourcesSources

Outcome variables The infant mortality rate (IMR) The Low birth weight rate (LBW)

Data source The OECD Health Data 2000

k2=0k2=0 k2=1k2=1

Three-level Conditional Three-level Conditional Hierarchical Mixed-effects Hierarchical Mixed-effects Models: A DiagramModels: A Diagram

Level k: Welfare state regimes k1=0, 1, 2, 3, or

k2=0, 1 Fixed effects

Level j: Countries j=1, 2, 3, …, 19 Random effects

Level i: Years i=0, 1, 2, …, 34 Random effects

k1=0k1=0 k1=1k1=1 k1=2k1=2 k1=3k1=3

…

…

…

Statistical AnalysesStatistical Analyses

Two outcomes (IMR and LBW) were analyzed separately SAS version 8.2 was used to obtain the estimates through the REML method

Type of the ModelType of the Model No. of Welfare No. of Welfare State CategoriesState Categories

Years analyzedYears analyzed

3-level conditional hierarchical mixed-effects model

4 (SD, CD, WE, L)

1960-1994 (35 years)

3-level conditional hierarchical mixed-effects model

2(SD, Others)

1960-1994 (35 years)

3-level conditional hierarchical mixed-effects model

2(SD, Others)

1960-1969, 1970-1979, 1980-1989, 1990-1994, separately

11

22

33

Values for Fixed Intercepts for Values for Fixed Intercepts for IMR and LBW in the 4 Regime IMR and LBW in the 4 Regime TypesTypes

10.5

15.6

13.0

15.1

4.85.5 5.8 6.1

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

IMR (n=665) LBW (n=475)

Social Democratic

Christian Democratic

Wage Earner

Liberal

All intercepts p<0.001

Results from the Analysis with Results from the Analysis with 4 Welfare State Regime Types4 Welfare State Regime Types

Results from the Analysis with Results from the Analysis with 2 Welfare State Groups, 1960-2 Welfare State Groups, 1960-19941994

Variance components for ‘year’ and ‘country’-level random-effects are highly significant

All fixed-effects intercepts for ‘welfare state regime types’ are highly significant

F-test is significant for both outcomes

Change in Excess Infant Change in Excess Infant Mortality Rate and Excess Low Mortality Rate and Excess Low Birth Weight Rate:Birth Weight Rate:Social Democracies vs OthersSocial Democracies vs Others

0.27

0.220.25

0.26

0.43 0.40

0.28

0.21

0.00

0.10

0.20

0.30

0.40

0.50

1960-1969 1970-1979 1980-1989 1990-1994

IMR

IMRIMR

LBWLBW

(μ(μ00 -

μ -

μ11) )

μμ00

Variance ComponentsVariance Components

44.4

5.3

8.7

9.8

22.3

22.0

16.4

2.9

4.9

2.5

1.5

1.5

0.6

0.7

0.6

0%

20%

40%

60%

80%

100%

Overall(1960-1994)

1960-1969

1970-1979

1980-1989

1990-1994

Error Country Welfare State

0.23

0.53

0.48

0.06

0.53

0.69

0.19

0.51

0.56

0.11

0.49

0.60

0.06

0.68

0.66

0%

20%

40%

60%

80%

100%

Overall(1960-1994)

1960-1969

1970-1979

1980-1989

1990-1994

Error Country Welfare State

IMRIMR LBWLBW

SummarySummary

Our results provide a more appropriate account of country and regime effects than the usual pooled regression analysis used in comparative health policy analysis.

Our results confirm that countries as clusters or groups share certain characteristics pertaining to them, as opposed to countries as individuals

The Social Democratic regime was significantly different from other countries as a whole

During the era of welfare state retrenchment, the difference in the low birth weight rate between social democracies and other countries was magnified

These Findings Could Be Due These Findings Could Be Due to,to,

The development of domestic welfare state social policies universal access to health care higher female employment in the labor market higher unemployment compensation subsidies to single mothers and divorced women active labour-market intervention to ensure full employment,

especially among women Or any supra-national structure: EU, NAFTA, etc. Or the geographical proximity (policy diffusion)

Implications of the Different Implications of the Different Pattern between IMR and LBWPattern between IMR and LBW

The Social Democratic countries managed to maintain a healthier social environment, including smaller economic inequality, even after 1979, the era of welfare state retrenchment

This finding is also consistent with Huber & Stephens’ (2001) finding: in the changed environment of the 1980s, “the active, service-oriented Social Democratic welfare states were in a stronger position than the passive, transfer-oriented Christian Democratic welfare states” (p.321)

This statement also applies to the Liberal and Wage Earner welfare states that had started “ideologically driven cuts” (p.320) in the state welfare funding much earlier in time

Contributions and LimitationsContributions and Limitations

This study shows that population-level health indicators, such as infant mortality rate and low birth weight, have components of variance at the welfare state type supranational level (15% to 50% or more of the total variability)

This study combined a longitudinal approach with a multi-level modeling approach to get stronger inferences

We do not know for sure if the observed distinctive characteristics in population health are because of policy/ political differences or just reflections of geographical difference. (i.e., All Social Democratic Countries are located in Nothern Europe, whereas all Liberal countries are outside Europe, except the UK, which is a island)

We do not know what aspect of welfare state regimes resulted in the difference in population health levels

CONTRIBUTIONSCONTRIBUTIONS LIMITATIONSLIMITATIONS

Conclusion and Future Conclusion and Future DirectionsDirections

Welfare state policies affecting maternal and child health indicators begin at a supranational level

Comparative health policy studies should not consider countries as being independent from one anther

The differences in population health indicators among these countries distribute as distinctive clusters of welfare state regime types

More protective types of welfare state regimes, namely Social Democratic countries as a group, were able to provide a more population health-friendly environment to its citizens in the last 35 years

Future studies should investigate the specific welfare regime features (i.e., by using explanatory variables) that account for welfare regime effects on maternal and child health and other related population health indicators

CONCLUSIONCONCLUSION FUTURE DIRECTIONSFUTURE DIRECTIONS

ReferencesReferences Abbott, A., & DeViney, S. (1992). The welfare state as transnational event: evidence from sequences of policy adoption.

Social Science History, 16(2), 245-274. Alesina, A., & Glaeser, E. (2004). Fighting Poverty in the Us and Europe: A World of Difference Oxford: Oxford University

Press Breen, R., & Rottman, D.B. (1998). Is the national state the appropriate geographical unit for class analysis? Sociology,

32(1), 1-21. Castles, F., & Mitchell, D. (1993). Worlds of welfare and families of nations. In F.G. Castels (Ed.), Families of Nations:

Public Policy in Western Democracies (pp. 93-129). Brookfield, VT: Dartmouth. Cho, Y. (2001). Confusionism, conservatism, or liberalism? A study on the typology of Korean Welfare State. Korean

Journal of Sociology, 35(6), 169-191. Coburn, D. (2000). Income inequality, social cohesion and the health status of populations: The role of neo-liberalism. Social

Science and Medicine, 51(1), 135-146. Conley, D., & Springer, K. (2001). Welfare state and infant mortality, American Journal of Sociology pp. 768-807). Esping-Andersen, G. (1990). The Three Worlds of Welfare Capitalism Princeton: Princeton University Press Esping-Andersen, G. (1999). Social Foundations of Postindustrial Economies Oxford: Oxford University Press Goodman, R., & Peng, I. (1996). The East Asian Welfare States: Peripatetic Learning, Adaptive Change and Nation-

Building. In G. Esping-Andersen (Ed.), Welfare States in Transition.London: SAGE. Hong, K. (1991). A Qualitative comparative study on the welfare state typology: Interventionist, Liberal, and Confucian

Welfare State, A Study of Korean Welfare System (pp. 119-151). Seoul: Na-Nam. Huber, E., & Stephens, J. (2001). Development and Crisis of the Welfare State- Parties and Policies in Global Markets

Chicago: University of Chicago Press Jones, C. (1993). The pacific challenge: Confucian Welfare States. In C. Jones (Ed.), New Perspectives on the Welfare

State in Europe.London: Routledge. Korpi, W., & Palme, J. (2003). Class politics and "new polibcs" in the context of austerity and globalization: Welfare state

regress in 18 countries 1976-1995. Sociologisk Gorskning, 4, 45-85.

References (Cont’d)References (Cont’d) Littlell, R., Smith, G., & Harper, S. (1996). SAS System for Mixed Models Cary, NC: SAS Institute Inc. Lynch, J., Smith, G., Harper, S., Hillemeier, M., Ross, N., Kaplan, G., & Wolfson, M. (2004). Is income inequality a

determinant of population health? Part 1. A systematic review. Milbank Quarterly, 82(1), 5-99. Macinko, J., Starfield, B., & Shi, L.Y. (2003). The contribution of primary care systems to health outcomes within

Organization for Economic Cooperation and Development (OECD) countries, 1970-1998. Health Services Research, 38(3), 831-865.

Macinko, J.A., Shi, L.Y., & Starfield, B. (2004). Wage inequality, the health system, and infant mortality in wealthy industrialized countries, 1970-1996. Social Science & Medicine, 58(2), 279-292.

Muntaner, C., Lynch, J., Hillemeier, M., Lee, J., David, R., Benach, J., & Borrell, C. (2002). Economic inequality, working-class power, social capital and cause-specific mortality in wealthy countries. International Journal of Health Services, 32(4), 629-656.

Navarro, V., & Shi, L. (2001). The political context of social inequalities and health. Social Science and Medicine, 52(3), 481-491.

Navarro, V., Borrell, C., Benach, J., Muntaner, C., Quiroga, A., Rodriguez-Sanz, M., Verges, N., Guma, J., & Pasarin, M. (2004). The importance of the political and the social in explaining mortality differentials among the countries of the OECD, 1950-1998. International Journal of Health Services, 33(3), 419-494.

Preston, S.H. (1975). The changing relation between mortality and level of economic development. Population Studies, 29(2), 231-248.

Rodgers, G. (1979). Income and inequality as determinants of mortality: An international cross-section analysis. Population Studies, 33(3), 343-351.

Shi, L., Macinko, J., Starfield, B., Wulu, J., Regan, J., & Politzer, R. (2003). The relationship between primary care, income inequality, and mortality in US states, 1980-1995. The Journal of the American Board of Family Practice, 16, 412-422.

Wagstaff, A., & van Doorslaer, E. (2000). Income inequality and health: What does the literature tell us? Annual Review of Public Health, 21, 543-567.

Wilkinson, R. (1996). Unhealthy Societies: The Afflictions of Inequality New York: Routledge