Comparative Methods in Research on Gender Wendy Sigle-Rushton ESRC Methods Festival 2 July 2008 St. Catherine’s College, Oxford
Comparative Methods Why compare What to compare How to compare Benefits of comparison Caveats
Why compare Pragmatic concerns International agendas Broaden perspective Quasi-natural experiment Allows for theory building/testing
What to compare Comparisons across Countries Regions within countries (e.g. US States) Time
What to compare Variables to compare Inputs and Institutions Expenditure and welfare effort Aims and ideologies Politics Financing and delivery of policies Welfare mix Example: Jane Lewis – gender roles
What to compare Variables to compare Outcomes, for example Income distribution/poverty alleviation Social exclusion/inclusion Gender equality Decommodification Studies of outcomes Maitre et al – income packaging Rake – elderly, gender equality Christopher – (lone) mothers Sainsbury – gender equality Sigle-Rushton and Waldfogel – earnings, household income Hobcraft and Sigle-Rushton – social exclusion
How to compare Identify broad similarities and differences Exploit variation across space Simulations
Benefits of comparison Common and dissimilar problems/patterns Quasi-natural experiment Inspire best practice Inspire and inform good measurement
Caveats Reliance on similar, available measures Harmonisation Proxy variables Validity
Occupational Segregation, 2000 Source: OECD 2002
Gender Wage Gap and Employment, 2000 Source: OECD 2002
Caveats Reliance on similar, available measures Harmonisation Proxy variables Validity Tensions: Difference and sameness Static measures Geographical variations often ignored Explanans et explanandum Requires a lot of detail
Data: Luxembourg Income Study Strengths: Harmonised data, large number of countries Relatively recent data available for many countries Countries Anglo-Saxon: Canada, United Kingdom (UK), United States Continental Europe: Germany, the Netherlands Nordic: Norway, Sweden, Finland Example from my research on motherhood gaps in earnings
Using the regressions: Estimated wages for each age assuming different fertility histories Estimate motherhood gaps Estimate gender gaps by fertility history
Example from my research on motherhood gaps in earnings Using the regressions: What the regressions show Average gross earnings What they don’t show The reasons for the differences Economic well-being
Overall patterns Large earnings penalties for each child, little catch-up Germany, Netherlands, UK (esp. first) Moderate earnings penalties for first child, differences persist Canada Small earnings penalty for each child, some catch-up US, Norway Moderate penalties for the first child, rapid catch-up Sweden, Finland Example from my research on motherhood gaps in earnings
Overall patterns Large earnings penalties for each child, little catch-up Germany, Netherlands, UK (esp. first) Moderate earnings penalties for first child, differences persist Canada Example from my research on motherhood gaps in earnings
Overall patterns Large earnings penalties for each child, little catch-up Germany, Netherlands, UK (esp. first) Moderate earnings penalties for first child, some catch- up Canada Small earnings penalty for each child, some catch-up US, Norway Example from my research on motherhood gaps in earnings
Overall patterns Large earnings penalties for each child, little catch-up Germany, Netherlands, UK (esp. first) Moderate earnings penalties for first child, some catch- up Canada Small earnings penalty for each child, some catch-up US, Norway Moderate penalties for the first child, rapid catch-up Sweden, Finland Example from my research on motherhood gaps in earnings
Cumulative earnings of mothers aged with medium education relative to non-mothers One child, age 27 Two children, ages 25, 27 Germany Netherlands UK Canada United States Norway Sweden Finland Example from my research on motherhood gaps in earnings
No ChildrenOne child, age 27 Two children, ages 25, 27 Germany Netherlands UK Canada United States Norway Sweden Finland Cumulative earnings of mothers aged with medium education relative to men Example from my research on motherhood gaps in earnings
Summary Comparative studies can Highlight similarities and differences Inspire best practice But Direct of causation is rarely clear Explanatory processes are rarely clear Important measures may be omitted Individuals vary as well as policies Important to keep in mind when looking at “simulations” Predictive power is tentative
References Christopher, K. (2002) “Helping mothers escape poverty.” LIS working paper No Figari, F., Immervoll, H., Levy, H. and Sutherland, H. (2007) "Inequalities within Couples: Market Incomes and the Role of Taxes and Benefits in Europe". IZA Discussion Paper No Lewis, J. (1992) ‘Gender and the Development of Welfare Regimes’, Journal of European Social Policy 2(3): Maitre, B., Nolan, B. and Whelan, C.T. (2005) “Welfare regimes and household income packaging in the European Union.” Journal of European Social Policy 15(2): Rake, K. (1999) Accumulated disadvantage? Welfare state provision and the incomes of older women and men in Britain, France and Germany. In J. Clasen (ed.) Comparative Social Policy: Concepts, Theories and Methods Oxford, Blackwell. Sigle-Rushton, W. and Waldfogel, J. (2007) “Motherhood and women’s earnings in Anglo-American, Continental European, and Nordic countries.” Feminist Economics 13(2):