Neighbourhood effects, social capital and spatial mobility: evidence from the British Household Panel Survey Nick Buck ISER, University of Essex.

Slides:



Advertisements
Similar presentations
Experiences of Discrimination: The Impact of Metropolitan and Non- Metropolitan Location Brian Ray, University of Ottawa Valerie Preston, York University.
Advertisements

Place and Economic Activity: Key issues from the area effects debate Nick Buck ISER, University of Essex.
IFS Parental Income and Childrens Smoking Behaviour: Evidence from the British Household Panel Survey Andrew Leicester Laura Blow Frank Windmeijer.
Division of Domestic Labour and Women s Human Capital ESRC Gender Equality Network Project 4: Gender, Time Allocation and the Wage Gap Jonathan Gershuny.
Depression and work incapacity in Scotland: Evidence from the Scottish Health and British Household Panel Surveys Matt Sutton Will Whittaker Health Methodology.
Mixed methods in longitudinal research Nick Buck UK Longitudinal Studies Centre University of Essex.
Longitudinal LFS Catherine Barham and Paul Smith ONS.
The Marginal Utility of Income Richard Layard* Guy Mayraz* Steve Nickell** * CEP, London School of Economics ** Nuffield College, Oxford.
Employment transitions over the business cycle Mark Taylor (ISER)
How would you explain the smoking paradox. Smokers fair better after an infarction in hospital than non-smokers. This apparently disagrees with the view.
School District Consolidation William Duncombe and John Yinger The Maxwell School, Syracuse University February 2013.
Background Neighbourhood characteristics such as socio-economic status (SES) have been shown to correlate with poorer health outcomes, mortality rates,
Introduction and Aim Research indicates that socioeconomic status (SES) is an important predictor of mortality and morbidity. Low SES increases susceptibility.
Centre for Housing Research, University of St Andrews Occupational mobility and neighbourhood effects: a longitudinal study ESRC Seminar Series – 4 & 5.
Education and entitlement to household income. A gendered longitudinal analysis of British couples Jerome De Henau and Susan Himmelweit IAFFE annual conference,
LIST QUESTIONS – COMPARISONS BETWEEN MODES AND WAVES Making Connections is a study of ten disadvantaged US urban communities, funded by the Annie E. Casey.
Nonresponse bias in studies of residential mobility Elizabeth Washbrook, Paul Clarke and Fiona Steele University of Bristol Research Methods Festival,
METHODOLOGY PART 1PART 2 HOUSEHOLD STRUCTURE Relationship of adults (over age 18) to focal child. Includes parents (biological /foster), grandparents,
Wellbeing Watch: a monitor of health, wealth and happiness in the Hunter Shanthi Ramanathan.
Persistence of Social Exclusion Among Older People in Australia Riyana Miranti* and Peng Yu** * National Centre for Social and Economic Modelling (NATSEM),
Socio-economic Factors influencing the use of coping strategies among Conflict Actors (Farmers and Herders) in Giron Masa Village, Kebbi State, Nigeria.
Young People’s emotional well-being: The impact of parental employment patterns Dr Linda Cusworth Social Policy Research Unit, University of York International.
A model for spatially varying crime rates in English districts: the effects of social capital, fragmentation, deprivation and urbanicity Peter Congdon,
Understanding Population Trends and Processes: Links between internal migration, commuting and within household relationships Oliver Duke-Williams School.
Chapter 11 Contingency Table Analysis. Nonparametric Systems Another method of examining the relationship between independent (X) and dependant (Y) variables.
Carl E. Bentelspacher, Ph.D., Department of Social Work Lori Ann Campbell, Ph.D., Department of Sociology Michael Leber Department of Sociology Southern.
Chapter 6: Correlational Research Examine whether variables are related to one another (whether they vary together). Correlation coefficient: statistic.
Self perceived health in Ukraine: results of a cross sectional survey Dr Anna Gilmore EUROPEAN CENTRE ON HEALTH OF SOCIETIES IN TRANSITION London School.
LECTURE 3 Introduction to Linear Regression and Correlation Analysis
Can social capital buffer against feelings of marginalisation and its impact on subjective wellbeing? Empirical evidence from the 2003 Quality of Life.
Econ 140 Lecture 131 Multiple Regression Models Lecture 13.
1 WELL-BEING AND ADJUSTMENT OF SPONSORED AGING IMMIGRANTS Shireen Surood, PhD Supervisor, Research & Evaluation Information & Evaluation Services Addiction.
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
By Sanjay Kumar, Ph.D National Programme Officer (M&E), UNFPA – India
Quantitative Research
Leon-Guerrero and Frankfort-Nachmias,
SPSS Session 4: Association and Prediction Using Correlation and Regression.
Chapter 8: Bivariate Regression and Correlation
This Week: Testing relationships between two metric variables: Correlation Testing relationships between two nominal variables: Chi-Squared.
LEARNING PROGRAMME Hypothesis testing Intermediate Training in Quantitative Analysis Bangkok November 2007.
Factors that Influence Retention in Greek Therapeutic Communities Erianna Daliani MSc (Gerasimos Papanastasatos) KETHEA Research Dept. 11th European Conference.
Father Involvement and Child Well-Being: 2006 Survey of Income and Program Participation (SIPP) Child Well-Being Topical Module 1 By Jane Lawler Dye Fertility.
Employment, unemployment and economic activity Coventry working age population by disability status Source: Annual Population Survey, Office for National.
Does Formative Feedback Help or Hinder Students? An Empirical Investigation 2015 DEE Conference Carlos Cortinhas, University of Exeter.
Father involvement in family life: The many faces of 21st century British fathers Margaret O’Brien & Eloise Poole Svetlana Speight, Sara Connolly & Matthew.
Education, Training and Establishment Survival William Collier, Francis Green & Young-Bae Kim.
Widening Participation in Higher Education: A Quantitative Analysis Institute of Education Institute for Fiscal Studies Centre for Economic Performance.
Supervisor-Subordinate Friendships The Effects of Promotion on Peer Relationships Katie Nichols, Stefanie Ress, Jessica Rudd with Dr. Martha Fay Department.
Chapter 3 Section 3.1 Examining Relationships. Continue to ask the preliminary questions familiar from Chapter 1 and 2 What individuals do the data describe?
Longitudinal data analysis for social science researchers University of Stirling 5 th September 2006 Prof. John Field, Stirling University Longitudinal.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Correlation Analysis. Correlation Analysis: Introduction Management questions frequently revolve around the study of relationships between two or more.
Centre for Housing Research, University of St Andrews The Effect of Neighbourhood Housing Tenure Mix on Labour Market Outcomes: A Longitudinal Perspective.
Objectives 2.1Scatterplots  Scatterplots  Explanatory and response variables  Interpreting scatterplots  Outliers Adapted from authors’ slides © 2012.
University of Limerick Ollscoil Luimnigh 25 th September 2007Eileen Humphreys, HSyRC, Dept. Sociology, UL Social capital and community: Findings and conclusions.
Going from data to analysis Dr. Nancy Mayo. Getting it right Research is about getting the right answer, not just an answer An answer is easy The right.
Transition of NCV students from TVET colleges to the Labour Market Presentation to Bridge Post School Access Focus Group 22 October 2015.
Dr Veronique Siegler and Rachel O’Brien
CROSS-COUNTRY INCOME MOBILITY COMPARISONS UNDER PANEL ATTRITION: THE RELEVANCE OF WEIGHTING SCHEMES Luis Ayala (IEF, URJC) Carolina Navarro (UNED) Mercedes.
Poverty, ethnicity and social networks - how are they related? Dharmi Kapadia, Nissa Finney & Simon Peters The University of Manchester The State of Social.
Greek Affiliation and Success in College Ev A. Lynn Practicing Until Perfect University Introduction When students enter college, they have the choice.
Social Exclusion in the UK and Scotland
Assessing the Impact of Informality on Wages in Tanzania: Is There a Penalty for Women? Pablo Suárez Robles (University Paris-Est Créteil) 1.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Are Happy People Found in Connected Neighborhoods
APPROACHES TO QUANTITATIVE DATA ANALYSIS
POSC 202A: Lecture Lecture: Substantive Significance, Relationship between Variables 1.
The effects of rotational design and attrition
An Introduction to Correlational Research
in the Spanish Labour Market:
Presentation transcript:

Neighbourhood effects, social capital and spatial mobility: evidence from the British Household Panel Survey Nick Buck ISER, University of Essex

Motivation Part of a research project examining how far where people live has effects on their life chances independent of personal characteristics … including how it relates to the longer term development of life chances and social mobility Longitudinal focus makes it essential to take account of migration and residential mobility: –not just a nuisance factor, but an important aspect of individual social and economic mobility, both as a consequence and with potentially causal effects Previous analysis shows limited and not very strong effects of area deprivation on individual deprivation and social exclusion Perhaps the effects are indirect, via social capital and other factors hypothesised to influence life chances

Motivation (2) Presentation investigates three way inter-relationships between neighbourhood deprivation, social capital and migration Social capital is hypothesised to have positive effects on both collective and individual outcomes – not something tested here Many potential dimensions of social capital, as well as significant measurement issues Hypothesised negative relationship between social capital and neighbourhood deprivation Hypothesised associations between social capital, especially local and residential mobility Methodological challenges in identifying area effects

Approach This research uses individual level survey data with local area census and other data attached It uses British Household Panel Survey data which has a rich array of social capital measures We exploit the longitudinal dimension provided by these data In this analysis main longitudinal focus is on residential mobility –For intrinsic reasons: how does mobility relate to the development and maintenance of social capital –Provides evidence on impact of change in area characteristics (but needs further evidence on degree of choice in migration)

Four questions Do we find cross-sectional associations between area deprivation and a range of social capital measures? Do social capital measures influence residential mobility probabilities? How does residential mobility affect social capital measures? Does change in area deprivation associated with mobility affect social capital measures?

Data sources BHPS waves 8 (1998) and 13 (2003) carry additional neighbourhood and social capital questions Approximately 8,500 cases at wave 8, 6,000 at wave 13, movers. Matched to Townsend area deprivation score, calculated from 2001 Census data at Lower Super Output Area (average population 1,400 people)

Social Capital measures Trust: generally people can be trusted Activity in voluntary organisations Whether meet with friends at least once per week Whether talk to neighbours at least once per week Whether three best friends all live within 5 miles (8 kilometres) Whether none three best friends in employment Neighbourhood affiliation score

Neighbourhood affiliation score number of positive responses to: I feel like I belong to this neighbourhood The friendships and associations I have with other people in my neighbourhood mean a lot to me If I needed advice about something I could go to someone in my neighbourhood I borrow things and exchange favours with my neighbours I would be willing to work together with others on something to improve my neighbourhood I plan to remain a resident of this neighbourhood for a number of years I like to think of myself as similar to the people who live in this neighbourhood I regularly stop and talk to people in my neighbourhood

Cross-sectional models Fit regressions (logistic or OLS) to each social capital measure – Townsend score alone, and then include a range of personal characteristics (next slide) Explore non-linear effects of area deprivation (Are effects especially strong in most deprived areas?) Present graphs showing differences in dependent variable (values in OLS, relative odds in logistic) at deciles of Townsend scoere. NB: more deprived have higher scores.

Individual characteristics included in models Age, age squared Sex Equivalised household income Education qualifications (6 categories) Social class (7 categories) Housing tenure (4 categories) Activity status (5 categories) Effects of personal characteristics not shown here – generally positive associations with age, income, higher education and higher social class, negative effects of being in rented accommodation

Trust: generally people can be trusted

Number of organisations in which respondent is active

Whether all three best friends live within 8 Kilometres Increasing with area deprivation

Whether none of three best friends are employed NB: differences are not significant with individual factors

Meets with people at least once per week NB: generally increasing with area deprivation, but non-linear effects

Talks with neighbours at least once per week NB: clear non linear effects; area differences stronger after controlling for individual factors

Mean value of neighbourhood affiliation score No difference in area effects after controlling for individual factors

Summary on cross-sectional area effects Generally negative associations between social capital measures and area deprivation, except for measures related to close friendship networks (bonding social capital) Effects are mainly weaker, but still significant after introducing individual characteristics, But effect disappears for economically salient friendship networks

Residential mobility A range of reasons for being interested: Migration can be related to positive career returns, and can be an expression of positive choice over housing and neighbourhood Migration may disrupt social networks, and thus harm social capital; conversely strong social capital may be disincentive to migration Models of the probability of migration suggest it is positively associated with income, social class, and negatively associated with age Relationship with area deprivation different for all moves and longer distance only – these associations are attenuated with other individual controls.

Migration between 1998 and 2003: association with initial area deprivation Clear non-linear effect: some increase in migration risks from most deprived areas

Influence of social capital measures on residential mobility Non-significant for: organisation membership, trust (weakly significant on its own, disappears with controls) Simple positive association with meeting regularly, which disappears with individual controls Measures related to area embeddedness have strong negative association Association also negative with whether no employed people amongst close friends

All movesMoves over 20 km variable alone + area deprivation + individual factors variable alone + area deprivation + individual factors Neighbourhood affiliation score (effect of 1SD change) Talks regularly with neighbours best friends live within 8 KM None of 3 best friends employed (0.8920) Influence of Social Capital measures on relative odds of residential mobility

Influence of residential mobility on change in social capital measures Meeting people regularly – substantial negative distance effect Talking to neighbours - no mover effect, negative distance effect Trust – no mover or distance effect Organisation activity – no mover or distance effect Neighbourhood affiliation – weak mover effect and small negative distance effect

Association of change in area deprivation with change in social capital, for movers only No effects for: –Meeting people –talking to neighbours –organization membership –trust Strong effect for neighbourhood affiliation score, similar in scale to cross-sectional association Asymetric effect - those who move to worse areas are especially unlikely to experience substantial reduction in neighbourhood affiliation: need to investigate whether this relates to degree of choice over neighbourhood

Summary on mobility analysis Area embeddedness significantly reduces mobility prospects Evidence on the disruption of social networks and sociability Neighbourhood affiliation is sensitive to neighbourhood characteristics – how far does it also measure social capital Some social capital measures (trust, organisation activity), people appear to carry with them