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Three Worlds of Social Insurance: On the Validity of Esping-Andersen's Welfare Regime Dimensions

Published online by Cambridge University Press:  12 September 2012

Robert Jan van der Veen  and
Wouter van der Brug
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Abstract

Esping-Andersen developed a typology of welfare regimes: conservative, liberal and social democratic, which are measured on the basis of seven indicators. We re-examine Esping-Andersen's data as well as replication data compiled by Scruggs and Allan to show that the seven indicators do not form valid measures of these welfare regimes. In addition to divergences in their measurement, the seven indicators are a mixture of institutional characteristics of welfare systems and outcome measures of social stratification. A measurement model based on the five institutional characteristics of welfare regimes that pertain to social insurance, however, does fit both the original and replication data. This article therefore proposes a three-dimensional model of conservative and liberal social insurance, which treats universal insurance coverage as the third dimension, instead of Esping-Andersen's ‘socialist’ regime. Although this does not fundamentally alter the typology of countries, it has implications for previous studies that employ country scores based on Esping-Andersen's method as independent variables in causal models. To illustrate these implications, this article re-examines a study by Noël and Thérien and calls into question their conclusions on the causal connections between the social democratic welfare state and levels of foreign aid.

Type
Articles
Information
British Journal of Political Science , Volume 43 , Issue 2 , April 2013 , pp. 323 - 343
Copyright
Copyright © Cambridge University Press 2012

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Footnotes

*

Department of Political Science, University of Amsterdam (email: [email protected]). An online appendix with supplementary tables and replication data is available at http://dx.doi.org/10.1017/S0007123412000257.

References

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9 Section 4 explains how these index scores were constructed.

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13 It should be noted that Esping-Andersen does not employ the terminology of measurement models in The Three Worlds of Welfare Capitalism.

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17 In the 1980 and 1996–2002 replication datasets of Scruggs and Allan, the correlations of universalism and benefit differentials are 0.19 and 0.06, respectively.

18 SEM analyses are to be preferred over the most widely used alternative approach to assessing the construct validity of measurement models: principal component analysis (PCA). PCA is a form of exploratory factor analysis, which does not test for goodness of fit. Therefore it provides no statistical criteria for judging how well a measurement model fits the data.

19 All variables in the data are measured at interval level, except for corporatism, which is a positive count variable. This is treated as a semi-interval level measure in the analysis. In small samples the results may sometimes be strongly affected by outliers. Yet, there are no variables in the available data with values beyond 3 standard deviations of the mean. These data thus meet the most important requirements to conduct SEM analyses.

20 The RMSEA evaluates the discrepancy between the sample model to be estimated and the notional population model (under the null hypothesis of perfect fit) relative to the degrees of freedom specified for the test model. It is zero for a perfect fit.

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22 First, the regression weights that are necessary to fix the scale of the unobserved error terms of the seven attributes were constrained to one. To fix the scale of the three latent regime dimensions, the regression weights of liberalism on poor relief, of conservatism on etatism and of socialism on universalism were set at one. Estimation then showed that the model was not identified. Therefore, as suggested by the program output notes of AMOS, the three regime variances were constrained to one. As a result of these constraints, the model was identified. However, once estimated, it turned out to be inadmissible, because it included (slightly) negative estimates of the error variances of etatism and universalism. To remedy this defect, these error variances were constrained to zero. Re-estimation then produced an admissible model: the EA test model.

23 First the model estimated regression weights of liberalism on poor relief, of conservatism on etatism and of socialism on universalism set at one. That model was inadmissible because the covariance matrix of latent variables was not positive definite. The three regime variances were then constrained to one, and the error variance of universalism to zero. This produced an admissible model: the EA test model (SA 1980). The choice of constraints for the EA test model (SA 1996–2001) is the same.

24 One might suspect that the EA measurement model does not fit the three datasets, due to the large disagreement between the measurements of the means-tested poor relief indicator (see note twenty-five below). This possibility was checked by deleting the indicator from the measurement model (thus making liberalism depend positively only on private pensions and private health). However, none of the test models specified for this exercise fit the data at all well.

25 Scruggs and Allan, ‘Social Stratification and Welfare Regimes for the 21st Century: Revisiting The Three Worlds of Welfare Capitalism’, p. 653–654Google Scholar

26 See Esping-Andersen, The Three Worlds of Welfare Capitalism, pp. 27 and 69.

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Esping-Andersen, The Three Worlds of Welfare Capitalism, p. 75Google Scholar

28 Esping-Andersen, The Three Worlds of Welfare Capitalism, pp. 68–9 and 75.

29 Esping-Andersen, The Three Worlds of Welfare Capitalism, p. 68Google Scholar

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31 Esping-Andersen, The Three Worlds of Welfare Capitalism, p. 71CrossRefGoogle Scholar

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33 Esping-Andersen, The Three Worlds of Welfare Capitalism, p. 76Google Scholar

34 A problem with this criterion of typicality is that it allows countries to score strong on one regime and have medium scores on both others. For example, the Netherlands, with EA scores of 6 on socialism (strong), 6 on liberalism (medium) and 4 or conservatism (medium) has been repeatedly qualified as a hybrid case in the comparative welfare literature, yet it is regarded as a typical case of socialism based on Esping-Andersen's criterion. It should also be noted that Esping-Andersen qualified Finland as ‘typically’ socialist since he placed that country's conservative EA score of 6 in the medium rather than in the strong category of the conservative regime. This is inconsistent with having Finland in the strong category of socialism, however, since its EA score on this regime is also 6. In Table 1, this inconsistency has been corrected by qualifying Finland as a hybrid case.

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37 Austria's comparatively low ranking of 4 on liberalism in Table 1 is explained by the fact that the EA score of liberalism incorporates a low value of 2.8 on the indicator of means-tested poor-relief, well below the mean of 5.9. Since this indicator is not included in the liberal social insurance dimension, Austria's corresponding factor regression score ends up rather higher in Table 2 at 0.64, just above the borderline of strong and medium.

38 Our social insurance analysis of countries based on Scruggs and Allan's data differs somewhat from their analysis, which follows Esping-Andersen's ranking methods and is based on recalculations of the EA regime scores. Scruggs and Allan's 1980 replication typology diverges far more radically from the original than this study's social insurance typology does (see Scruggs and Allan, ‘Social Stratification and Welfare Regimes for the 21st Century: Revisiting The Three Worlds of Welfare Capitalism’, Table 5 on p. 652). However these results are only of limited interest, because the EA scores are invalid.

39 Noël and Thérien, ‘From Domestic to International Justice’.

40 Noël and Thérien, ‘From Domestic to International Justice’, p. 540Google Scholar

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45 Scruggs and Allan, ‘Social Stratification and Welfare Regimes for the 21st Century: Revisiting The Three Worlds of Welfare Capitalism’.

46 Shalev, Michael, ‘Limits and Alternatives to Multiple Regression in Comparative Research’, Comparative Social Research, 24 (2007), 261–308CrossRefGoogle Scholar

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