Heiner Meulemann Forschungsinstitut für Soziologie, Universität zu Köln

1. Heiner MeulemannForschungsinstitut für Soziologie, Universität zu Köln Greinstraße 2, D50939 KölnTel. 0221 - 470 5658, Fax 0221 - 470 5169e-mail: meulemann@wiso.uni-koeln.de Finding and Examining Hypotheses on Country Differences Lecture at the University of Limerick, Ireland, January 25, 2011

2. Three topics 1 Country context: Social order and opportunity structure 2 Hypotheses: Mean and effect 3 Systematic comparison: Four criteria

3. Countries as contexts: Social order and opportunity structure

4. Countries = two contexts 1 name and border, constitution and laws, folklore and customs. “Social facts” = social order. 2 resources of action: money, educational degrees, power. Circulate among citizens “Life chances” = opportunity structure.

5. Context 1: Social Order - Definition Norms directly guiding actions. Valid because • most people endorse them • in large parts, written, legal form: constitution. Example: equality in constitutions, achievement (equality’s twin value) only in peoples’ minds Typical variables: federal or unitary constitution, % Protestant Guides actions in same way as personal endorsement of norms – only difference: binds every citizen Symbolically identified

6. Context 1: SocialOrder – Typical Level Higher aggregation level: Validity “top down” Hierarchy, disaggregation not possible Global quality Higher level more consequential for action: e.g. parental leave legislation

7. Context 2: Opportunity Structure - Definition Range of options for every citizen, beyond personal resources, indirectly affects actions. Results from actions of all citizens and all organizations of country. E.g.: Social inequality, reduces trust. Democracy since long, facilitates associations Facilitates actions in same way as opportunity profile of person (combination of resources) - only difference: for every citizen alike Need not be symbolically identified

8. Context 2: Opportunity Structure – Typical Level Lower aggregation level: Availability In most cases: disaggregation possible. GDP in nation, region, community Analytical Property Lower level more consequential for action: e.g. Kindergarten places per parents in neighborhood, not in city

9. Cross-Classification of contexts with societal life domains

10. 2 Hypotheses for country effects on persons 2.1 Mean hypotheses 2.2 Effect hypotheses

11. Country Context b a Ressources Actions a = effect on mean, b = effect on relation (also effects on parameter of a regression equation) Mean Hypotheses (a) and Effect hypotheses (b)

12. 2.1 Mean hypotheses Justified by process/mechanism at country level. - Obvious when context = global quality - Yet also when context = aggregation of person variable Three examples from social capital research

13. Example 1: „Rich“ Rich people more often engage in voluntary associations than poor people. “People” persons or countries? - Persons: high income = resource, facilitating engagement - Countries: higher GDPpc = higher mean engagement Richness of “average citizen” no explanation. Country level mechanism: GDPpc = economic progress • societal and occupational differentiation • requires more organization of interests • enlarges supply and, consequently, demand of associations Opportunity structure

14. Example 2: „TV kills social capital“ TV detrimental for social capital. - Persons: passive, motivation to socialize reduced; occupies time, opportunity reduced. - Countries: many heavy TV users = no opportunity to socialize. Opportunity structure unfavorable “Average citizen” argument: greater mean TV time is greater mean passivity and less mean time to socialize, and therefore less mean social capital? Country level mechanism: Mean TV time = negative interdependencies, vicious circle Opportunity structure

15. Example 3: „Catholics less engaged than Protestants“ C and P: no differences of teachings, but of organization • C = “top down” in hierarchical, centralized, authoritarian bureaucracy • P = “bottom up” in egalitarian communities Country level mechanism: organization > tradition confessional tradition of engagement: P > C % membership in country Person level: no corresponding explanatory argument. Hypotheses cannot be founded on “average citizen” arguments, but on country-specific traditions. Social order

16. Two general mechanisms to justify country effects on means 1 Social differentiation 2 Choices of collective actors

17. 1 Social differentiation (SD) SD Basic > further processes. Not under control of politics. 1 > social subsystems, functionally specified to serve needs formerly served unnoticed. E.g.: Social security system substitutes informal networks, 2 > pluralization of social cleavages. More social positions = more diversity of interests > more supply of associations > more participation 3 > social inequality, reduces social trust. SD driving force of opportunity structure. gravity, path dependency Generalization: SD affects opportunity structure rather than social order

18. 2 Choices of collective actors (CCA) at historical branching points, critical events. Examples: 1 D “corporatist” social-political regime, Bismarck 1870s GB from “corporatist” to “liberal”, Thatcher 1980s. 2 European countries “Catholic”, “Protestant”, “Mixed” since 30YsWar WestD “Catholic” to “Mixed” through refugees after WW II 3 East Europe from state socialist to capitalist social order CCA changed social order almost overnight. Re-set normative frame within which SD proceed Generalization: CCA affect social order, not opportunity structure

19. SD and CCA: opportunity structure and social order SD Opportunity Structure CCA Social Order

20. 2.2 Effect hypotheses Example - Social capital = person’s social relations • Reinforcement hypothesis. Relations more consequences, the more densely knit the network Same friend more Social Capital for me once he has more friends

21. Reinforcement hypothesis System Social Capital (Network) + Personal Social Capital (Relations) Actions + a = effect on mean, b = effect on relation (also effects on parameter of a regression equation)

22. Cross-level interaction System and personal social capital, context and person. Yet: Interaction effect presupposes main effects. When interaction, two consequences for analysis of main effect 1 Interaction without main effects conceivable, but examine main before interaction effect 2 Interaction both ways logically, but only one in cross country comparison. Both in the following

23. 1 Interaction without main effect conceivable Example: • social capital more fruitful for personal prestige, when in line with social order • Communist party fruitful in GDR, harmful in FRG. GDR: party members prestige 70, non-members 30 FRG: party members prestige 30, non-members 70 Membership 1, non-membership -1. GDR 1, FRG -1 • zero main effects, general mean 50 • cross-level interaction: ((70-30) – (30-70))/4 = 20 Artificial example. Therefore in general: - main AND interaction effect - Independent justification for each

24. 2Interaction both ways logically, only one in cross country comparison - A conditions the impact of B on Y - B conditions the impact of A on Y However, persons “nested” in countries: Countries condition person level effect. Not the other way round GDR-FRG example: countries condition effect of membership on prestige How could membership condition effect of countries on prestige? Tax refugees

25. Two forms how country conditions impact of A on B on person level • Reinforcement • Compensation

26. (a) Reinforcement: main and interaction effect same direction Climate of trust = system capital of country, measured by mean attitudes. Opportunity structure, conditions person level effect of trust on political involvement. • If mean trust high, trustful people can participate in decisions. Trust > political involvement, strong • If mean trust low, no motivation to get involved politically. Trust > political involvement, weak Positive cross-level interaction: Main and interaction effect in same direction

27. But: Main effect of climate of trust on political involvement? SD or CCA? - SD = more social interaction > decrease or increase trust, and involvement • CCA: tax rates, public health insurances etc., not mean social trust. No main effect However, SD > mean trust, through other paths: • politicization, requires capacities of state to govern society. Politics gain relevance among sub-sectors and in life of people, people more involved in politics. Government consumption and state intervention >+ mean political involvement. • economic growth, facilitates political involvement. GNPpc >+ mean political involvement. In sum - Mean trust: effects, but not mean - Government consumption, state intervention, GNPpc: mean, but not effects

28. Country context on the person level relation trust-political involvement: Mean and effect hypotheses Government consumption, state intervention Climate (Mean) of Social Trust + ? + Social Trust Political Involvement

29. (b) Compensation: main and interaction effect opposite direction Example: Empowerment at the work place, improved by • Workers: union membership, personally • Trade union: strength, collectively. Main effect of strength: The more co-determination granted to unions (social order) and the more bargaining power they have (opportunity structure), the more they can improve empowerment Yet: The stronger unions, the less worker needs personal strategy Country effect compensates for effect on person level. Negative cross-level interaction effect

30. Compensation hypothesis + Legal Means and Bargaining Power of Unions + - Empowerment at the Work place Union Membership + a = effect on mean, b = effect on relation (also effects on parameter of a regression equation)

31. 3 Systematic comparison <> comparison of cases 3.1 explanation by variables of country context <> description using proper names 3.2 control of explanatory person characteristics <> level of countries only 3.3 examination of two series of general questions <> ad hoc questions 3.4 multi-level analyses <> simple regression analyses.

32. 3.1 Explanation by variables of country context Proper names substituted by explanatory variables. Trust in ESS: DK,N,FI,SW > UK,AU,D,LUX,B,E,F > PT,I,SV,H,P,G partly overlaps with rankings of other data sets. Without context variable: description of selected countries. With variable: different analyses comparable in spite of different country samples Social inequality explains trust in ESS and EB. From singular descriptions to general laws • Miller more friends than Smith, trust higher in D than in G • Why? more than two persons/countries needed. But: Difference D-G may be due to difference in population composition

33. 3.2 Control of explanatory person characteristics If country composition according to independent person variables not controlled for, wrongly attributed to country context. Example trust: depends on subjective well-being. If mean well-being higher in countries where mean trust is high (Northern Europe), part of country differences in trust due to population composition according to well-being rather than to differences of social order. Control person level, before effects of social order!

34. Compositional effects: case of spurious correlation EU countries North - South + + Social Trust: High-Low Well being: high-low +

35. 3.3 Two series of general questions: on means and slopes of countries Mean (= Intercept, grand mean centering) • Differences large enough? • If so, differences large enough if person characteristics controlled? • If so, can differences be explained by country variable? Slope of some explanatory person characteristics (4) Differences large enough? (5) If so, can differences be explained by country variable? (1) raw mean = (2) net mean (1) and (2) correspond to (4), (3) corresponds to (5) (1), (2), and (4): countries = proper names, “treatments” (3) and (5): explanation by context variables.

36. 3.4 Multi-level analysis (MLA) Analysis of variance, analysis of covariance, and multilevel analysis: Questions and equations; one individual and one aggregate level predictor

37. Advantages of MLA overcountry specific OLS: theoretical Each coefficient only once, rather than for each country Cross-level interactions in advance, rather than inductive search However: coefficients increase in MLA also, once intercept and slopes are examined simultaneously Covariance between their estimates

38. Advantages of MLA overOLS with country dummies: statistical (1) OLS wrongly assumes that each case drawn independently > underestimation of SE > non-effects becomes significant OLS adequate only if countries do no not differ, not interesting HLM: appropriate conservative tests (2) OLS does not estimate explained variances for the two levels, HLM does