Social Capital and Conversion of Housing Tenure - The Case of Stockholm

1. Social Capital and Conversion of HousingTenure - The Case of Stockholm Inga- Britt Werner, Associate Professor, Urban Planning Kerstin Klingborg, PhD, Real Estate Economics

2. Social Capital and Conversion of Housing Tenure- The Case of Stockholm • The presence of social capital in selected houses owned by municipal housing companies in Stockholm • What happens with the social capital in connection with the conversion process to cooperative ownership? • Are the rental and cooperative housing institutions effective institutions – do they contribute to the creation of trust and collective action among residents? A comparison with the design principles of effective institutions (Ostrom 1990) • Commissioned research work for Stockholms Stadshus AB, owner of the municipal housing companies in Stockholm. ERES 27 June 2009 KK , IBW

3. Method and Selection of Sample • Two step interview study • Step 1: Before conversion to cooperative ownershipStep 2: After conversion • Structured telephone interviews with residents and complementary face to face deep interviews • Face to face interviews with key informants at managing institutions • Two houses in five housing neighborhoods are selected for pairwise comparisons: both rental housing during the first round of interviews, during the second round one house has converted converted to cooperative ownership • Studied cases chosen along criteria of similar number and size of dwelling units - respondents randomised ERES 27 June 2009 KK , IBW

4. Present Status of the Project • The first step of data collection complete; 304 telephone interviews with residents in the five neighborhoods and 16 interviews with managers • Interviews with residents were purchased from Statistics Sweden. Problem: A lot of residents have mobil phones with cash card, ie phone numbers not available ERES 27 June 2009 KK , IBW

5. Design principles for sustainable institutions (Ostrom 1990) • Clearly defined boundaries. • Rules for appropriation and provision adjusted to local conditions. • Collective-choice arrangements. Can residents participate in changing the rules. • Monitoring. • Graduated sanctions. • Conflict-resolution mechanisms. • Rights to organize. ERES 27 June 2009 KK , IBW

6. ResultsDesign principle 1. Clearly defined boundaries • Unauthorized subletting • Moving rates • Other persons than tenants use common facilities Clearly defined boundaries is a major problem for the housing companies in the study in terms of who has the right to use the common resources. Can cause hesitation or reluctance to contribute to the common resources among residents. ERES 27 June 2009 KK , IBW

7. ResultsComprehensive analysis • The design of the rental housing institution differs a great deal from the ideal design principles found in long-enduring common pool resources. ERES 27 June 2009 KK , IBW

8. Response alternatives: Very good, rather good, some, not so much, not at all ERES 27 June 2009 KK , IBW

9. Aspects of Social Capital- Measurements and Indicators • Norms, sanctions and incentives • Collective action and cooperation • Trust and solidarity • Networks and social inclusion • Information and communication • Social cohesion and integration • Democracy and political action Measuresments and indicators of Social capital are adapted from other studies, f ex World Bank SC Group CoreQuestionnaire for Measuring SC (2002), the SOM-institute’s studies (2006) and the European Social Survey (2006) ERES 27 June 2009 KK , IBW

10. Analysis of the Telephone Interviews • Comparisons; categories still renting – converting to coop ownership, total • Factor analysis, reduction of data, comparison to the aspects of SC presumed in the questionnaire • Regression analyses, testing relationships SC—conversion to coop ownership, together with socioeconomic conditions and housing area • Comparisons; amount and type of SC/housing area • Comparisons; categories still renting – converting to coop ownership / housing area ERES 27 June 2009 KK , IBW

11. Converting – Still Renting, Total • No significant differences regarding education, age, type of household or foreign background • Converting had less trust in housing companies’ staff and in local police (!) • Converting had more trust in neighbours and more often find that neighbours adhere to rules and regulations ERES 27 June 2009 KK , IBW

12. Factor Analysis • Six factor solution, 65 % of variance explained • F1 Quality of network of neighbours; respect, politeness and trust (α= 0,78; 18 % of variance) • F2 Trust in the political system (α=0,85; 11% of var.) • F3 Extension of network of neighbours; recognise and know by name (α=0,69; 10.4 % of variance) • F4 Trust in local institutions ( 9.4 % of variance) • F5 Trust in and access to a close circle of friends / relatives (9,3 % of variance) • F6 general political interest (7.0 % of variance) ERES 27 June 2009 KK , IBW

13. Factors Versus SC Dimensions • Factors illustrate the individual residents’ perspective • Thus the grouping of variables concerning relations with family and friends, neighbours, local and political institutions • SC dimensions in the questionnaires constructed from an analytical perspective ERES 27 June 2009 KK , IBW

14. Linear Regression 1 • Dependent variables; each factor, factor scores by sums of values of included variables. Independent variables are socioeconomic data: age, gender etc. • F3, size of network, sign. positive correlation to higher age and having children- female gender barely sign. Born abroad sign. negative correlation to F3 • F5, near relations, sign. positive correlation to higher education and male gender. Higher age sign. negative correlation to F5 • F6, general political interest, sign. positive correlation to higher education ERES 27 June 2009 KK , IBW

15. Social Capital and Socio -economic Groups ERES 27 June 2009 KK , IBW

16. Linear Regression 2 • Dependent variables; each factor, factor scores by sums of values of included variables, independent variables are housing neighborhood dummies • F2, In areas 1 and 5 levels of trust in political institutions are sign. lower than in other areas • F3, in area 5 there is sign. less common to know your neighbours • F6, in areas 1 and 5 levels of general political interest are sign. lower than in other areas ERES 27 June 2009 KK , IBW

17. Socialt Capital / Housing Area ERES 27 June 2009 KK , IBW

18. Logit Regression / Converting- Still Renting • Variables in the equation from start were socio- economic data, housing area (dummies, one constant) and factor scores • Dependent variable Converting =1, else =0 • Only three factors were significant predictors for Converting =1 • F1 Trust in neighbours • F2 Trust in the political system • F4 Trust in local institutions (negatively!) ERES 27 June 2009 KK , IBW

19. Questions, Comments, Contact Kerstin Klingborg: kerstin.klingborg@infra.kth.se Inga Britt Werner: ingabritt@infra.kth.se ERES 27 June 2009 KK , IBW