1. Simulating Geographies of Happiness Dimitris Ballas Social and Spatial Inequalities group Department of Geography, University of Sheffield http://sasi.group.shef.ac.uk/ RES-163-27-1013 UPTAP conference, University of Leeds, 17-19 March 2008

2. Outline Measuring happiness and well-being Individual-level and contextual factors that may be affecting subjective happiness Happiness and major life events Happy People or Happy Places? – a multilevel problem Spatial microsimulation of happiness Concluding comments

3. General Health Questionnaire (1) Have you recently: Been able to concentrate on whatever you are doing? Lost much sleep over worry? Felt that you are playing a useful part in things? Felt capable of making decisions about things? Felt constantly under strain? Felt you could not overcome your difficulties?

4. General Health Questionnaire (2) Have you recently: Been able to enjoy your normal day-to-day activities? Been able to face up to your problems? Been feeling unhappy or depressed? Been losing confidence in yourself? Been thinking of yourself as a worthless person? Been feeling reasonably happy all things considered?

5. Subjective happiness measure: HLGHQ1 This measure converts valid answers to questions wGHQA to wGHQL to a single scale by recoding so that the scale for individual variables runs from 0 to 3 instead of 1 to 4, and then summing, giving a scale running from 0 (the least distressed) to 36 (the most distressed). See Cox, B.D et al, The Health and Lifestyle Survey. (London: Health Promotion Research Trust, 1987).

6. Factors and variables linked to subjective happiness (individual level studies) Age Education Social Class Income Marital status/relationships Employment Leisure Religion Health Life events and activities

7. Can happiness be measured? Positive and negative feelings are inversely correlated Happiness can be thought of as a single variable (Layard, 2005; Frey and Stutzer, 2002)

8. "Event""Valuation” Employment to unemployment-£23,000.00 Single to married£6,000.00 Married to separated-£11,000.00 Married to widowed-£14,000.00 Health excellent to Health good-£12,000.00 Health excellent to Health fair-£41,000.00 After Clark, A, Oswald, A, (2002), A Simple Statistical Method for Measuring How Life Events affect Happiness, International Journal of Epidemiology, 2002, 31(6), 1139-1144.

9. Life-events and happiness BHPS: What has happened to you (or your family) which has stood out as important? 145,408 major life events recorded between 1992-1995 Ballas, D., Dorling, D. (2007) Measuring the impact of major life events upon happiness, International Journal of Epidemiology, 36, 1244-1252. doi:10.1093/ije/dym182doi:10.1093/ije/dym182

10. BHPS Major Life Events HEALTH MENTIONS 01 Ill Health / Concern about Health 02 Hospitalisation / Operation 03 Accident (Involving Injury) 04 Health Tests (Positive & Negative) 05 Loss of Mobility / House-Bound 06 Recovery / Continuing Good Health 09 Health (not elsewhere classified - nec)

11. BHPS Major Life Events CARING 10 Caring Responsibilities - Not Childcare (i.e. Who is Cared For?) 11 Babysitting (ie Who is the Sitter?)

12. BHPS Major Life Events EDUCATION 12 Starting / In School 13 Leaving School 14 Starting / In Further Education (inc. Sixth Form) 15 Leaving Further Education 16 Studying For / Passing Educational / Vocational Qualifications / Acquiring Skills / Training (nec) 17 Travel Related to Study 19 Education (nec)

13. BHPS Major Life Events EMPLOYMENT 20 Change of Job (inc. Hours, Status) / Starting Own Business 21 Planned / Possible Change of Job 22 Getting Job (Following Economic Inactivity) 23 Work-related Training (inc. Apprenticeship / HGV Licence / Work Experience) 24 Redundancy / Unemployment (Threat of or Actual) 25 Retirement 26 Travel Related to Work (Who Travels?) 27 Work-related Problems

14. BHPS Major Life Events LEISURE / POLITICAL 30 Vacation / Travel (nec) 31 Leisure Activities 32 Learning to Drive / Passing Test (not HGV) 33 Political Participation / Voluntary Work (inc Committee Work) 34 Reference to National / World Events (who is Concerned by Event?)

15. BHPS Major Life Events NON-FAMILIAL RELATIONSHIPS 35 Began Friendship (including Girl / Boy Friend) 36 End Friendship (including Girl / Boy Friend) 37 Spending Time with / Visiting Friends (Coded as Holiday as Appropriate) 38 Problems with Neighbours (Who Has the Problem?) 39 Non-Family Relationship (nec)

16. BHPS Major Life Events FAMILY EVENTS 40 Pregnancy / Birth (Identity of Parent?) 41 Cohabitation 42 Engagements / Weddings 43 Separation / Divorce / End of Cohabitation 44 Leaving Parental Home 45 Death (Who Died?) 46 Wedding Anniversaries 47 Birthday Celebrations 48 Becoming Godparent 50 Spending Time / Visits with Relatives (Not Within Household) 51 Day-to-day Family Life 52 Family Problems (Person Causing Problems?) 53 Domestic Incident (eg Fire / Burst Pipes, etc) 54 Pets / Animals (Pet Coded) 59 Family Event / Family Reference (nec)

17. BHPS Major Life Events FINANCIAL MATTERS 60 Money Problems / Drop in Income / Debt 61 Forced Move (Repossession / Eviction) (Residential Move Not Included) 62 Improved Financial Situation 63 Received Money (Inheritance / Compensation / Pools) 69 Financial Other (nec)

18. BHPS Major Life Events CONSUMPTION 70 Bought / Buying Vehicle (Car, Caravan, etc) 71 Bought / Buying / Building House 72 Household Repairs / Improvements / Appliances 73 Won Prize (Not Cash) / Award 74 Received Present (from whom ?) 79 Other Purchases (nec)

19. BHPS Major Life Events RESIDENTIAL MOVE 80 Moved In Past Year 81 Future Intention to Move 82 Move into Residential Home (Nursing / Retirement, etc) 83 Move into Respondent’s Household (Who is Moving In?)

20. BHPS Major Life Events CRIME 90 Victim of Crime (Burglary,etc) 91 Committed Crime / In Trouble with Police

21. BHPS Major Life Events RELIGION 92 Joined / Changed Religion 93 Other Religious Reference (Not Confirmation / Baptism of Children) 94 Plan Not Fulfilled/ Something That Didn’t Happen (eg Didn’t Have a Holiday) 95 Civil Court Action / Battles with Bureaucracy 96 Other Occurrence (nec) given low priority 97 Nothing Happened -1 Don’t Know -9 Missing

22. Subject of event topic 00 Not Mentioned 01 ’We’/ Household 02 Self (Explicit or Inferred or No Pronoun) 03 Spouse /Partner 04 Daughter(s) 05 Son(s) 06 Child(ren) (nec) 07 Son / Daughter in-law 08 Mother 09 Father 10 Parents (both or not specified) 11 Parent(s) in-law 12 Siblings (sister / brother) 13 Sister-in-law / Brother-in- law 14 Grandparent(s) 15 Grandchild(ren) 16 Other Family Members / Family Members Unspecified 17 Friend / Colleague / Neighbour / Employer 18 Other 19 Pet 20 Not Specified

23. Combining “Event” and “Event Subject”  34 events 114.7%Nothing important happened (96-99) Health 27.6%health (other 1-9) 32.6%health (mine 1-9) 41.0%health (partner 1-9) 51.2%health (child 1-9) 61.2%health (parent 1-9)

24. Education 74.6%education (other 12-19) 81.4%education (mine 12-19) 92.5%education (child 12-19) Employment 103.0%employment (other 23,26-29) 114.0%employment (job change 20-21) 121.8%employment (job gain 22) 132.7%employment (job loss 24) Leisure 143.0%leisure (other 30-31) 155.3%leisure (our holiday 30) 162.7%leisure (my holiday 30)

25. Births and Deaths 171.4%pregnancy (other 40) 181.3%pregnancy (mine 40) 192.3%pregnancy (child's 40) 201.4%pregnancy (family 40) 211.0%death (other 45) 221.6%death (parent 45) 231.8%death (family 45) Relationships 242.0%relationships (family 35,41-42) 252.2%relationships (mine starting 35,42) 261.1%relationships (child's starting 35,42) 271.4%relationships (mine ending 36,43) 286.5%relationships (family, 46-53,55-59) 291.3%relationships (with pet 54 & subject)

26. Finance, etc 302.8%finance (other 60-69,73-79) 311.6%finance (car 70) 322.5%finance (house 71) 334.6%moving home (44,80-81) 343.8%other event (10-11,32-34,37-39,90-95)

27. So? What do you think most makes folk happy and unhappy? What are your top three ‘events’ most likely to be most strongly positively associated with being happy from the 34 above? What do you think are the events most commonly associated with folk being unhappy?

28. Life EventCoefficientP value RELATIONSHIPS (MINE ENDING 36,43)-0.1780.00 DEATH (PARENT, 45)-0.1660.00 HEALTHPARENT (1-9)-0.1390.00 DEATH (OTHER 45)-0.1370.00 EMPLOYMENT JOB LOSS 24-0.1290.00 HEALTH MINE (1-9)-0.1170.00 DEATH (FAMILY 45)-0.0980.00 HEALTH PARTNER (1-9)-0.0920.00 HEALTH CHILD (1-9)-0.0840.00 HEALTH OTHER (1-9)-0.0730.00 EDUCATION CHILD (12-19)-0.0290.12 EMPLOYMENT OTHER (23,26-29)-0.0280.13 OTHER EVENT (10-11;32-34;37-39;90-95)-0.0260.14 NOTHING IMPORTANT HAPPENED-0.0220.11 RELATIONSHIPS (WITH PET 54 AND SUBJECT)-0.0200.44 FINANCE (OTHER 60-69;73-79)-0.0190.27 RELATIONSHIPS FAMILY (46-53;55-59)-0.0140.39

29. Life EventCoefficientP value RELATIONSHIPS (FAMILY 35. 41-42)0.0020.91 LEISURE (OUR HOLIDAY 30)0.0100.61 MOVING HOME (44;80-81)0.0130.46 EDUCATION OTHER (12-19)0.0240.27 FINANCE (CAR 70)0.0270.22 LEISURE (MY HOLIDAY 30)0.0290.07 PREGNANCY (OTHER 40)0.0310.56 PREGNANCY (FAMILY 40)0.0340.09 RELATIONSHIPS (CHILD'S STARTING 35, 42)0.0370.10 EMPLOYMENT JOB CHANGE (20-21)0.0400.02 LEISURE (OTHER 30-31)0.0430.02 EDUCATION MINE(12-19)0.0520.00 PREGNANCY (CHILD'S 40)0.0530.01 PREGNANCY (MINE 40)0.0840.00 FINANCE (HOUSE 71)0.0970.00 EMPLOYMENT JOB GAIN 220.0970.00 RELATIONSHIPS (MINE STARTING 35. 42)0.1600.00

31. Happiness and social comparisons “A house may be large or small; as long as the surrounding houses are equally small it satisfies all social demands for a dwelling. But if a palace arises beside the little house, the little house shrinks to a hovel… [and]… the dweller will feel more and more uncomfortable, dissatisfied and cramped within its four walls.” (Marx, 1847)

32. Happiness and inequality “When we are at home, most of us like to live in roughly the same style as our friends or neighbours, or better. If our friends start giving more elaborate parties, we feel we should do the same. Likewise if they have bigger houses or bigger cars.” (Layard, 2005: 43)

33. Geographies of happiness in Britain Source: The British Household Panel Survey, 2001

35. REGION BY SOCIAL CLASSCLASS 1CLASS 2CLASS 3CLASSES 1 - 3N Rest of Yorks & Humberside3.37.17.05.9328 Tyne & Wear10.07.13.47.2264 East Midlands5.38.111.27.9782 Inner London10.35.28.87.9418 Rest of North West4.99.212.38.5454 South West11.76.78.98.7930 Greater Manchester14.58.24.89.3416 West Midlands Conurbation10.58.98.89.3453 East Anglia10.76.513.39.5390 Merseyside17.69.20.09.5233 West Yorkshire14.57.79.610.2364 Rest of South East10.510.88.710.31,875 Outer London8.913.36.910.7668 Rest of West Midlands8.911.614.911.5506 Rest of North19.710.48.512.4400 Wales11.112.915.313.0533 South Yorkshire17.611.624.215.4293 Great Britain10.59.39.79.810,264 Geographies of unhappiness in Britain

37. Happiness by district - Wales Powys (Brecknock, Montgomeryshire & Radnorshire) Gwynedd Cardiff Ogwr Cynon Valley; Rhonda Blaenau Gwent; Islwyn Swansea

39. Research questions to be addressed: What are the factors that influence different types of individuals’ happiness? Is the source of happiness or unhappiness purely personal or do contextual factors matter? (and if they do, to what extent?) If social comparisons are important, what is the spatial scale at which people make their social comparisons? Happy People or Happy Places?

40. Research methods: Regression modelling single level analysis to investigate the association between “subjective happiness” and individual level explanatory variables Multi-level modelling Assesing variation in happiness at several levels simultaneously Spatial Microsimulation creating small area microdata

41. Multilevel Analysis World  Nation  Region  District  Electoral Wards  Neighbourhood  Household  Individual Multilevel modelling enables the analysis of data with complex patterns of variability – suitable to explore the variability of happiness at different levels

42. Multilevel Analysis World  Nation  Region  District  Electoral Wards  Neighbourhood  Household  Individual Multilevel modelling enables the analysis of data with complex patterns of variability – suitable to explore the variability of happiness at different levels

43. Combining Data 1991 & 2001 Census of UK population: 100% coverage fine geographical detail small area data available only in tabular format with limited variables to preserve confidentiality British Household Panel Survey: sample size: more than 5,000 households annual surveys since 1991 individual data more variables than census coarse geography household attrition

44. Modelling happiness and well- being: individual level models 1.Demography 2.Socio-economic 3.Health 4.Social context – interaction variables (e.g. “unemployed or not” dummy variable x “district unemployment rate” variable

45. Dependent variable: "unhappiness"B Std. ErrorSig. Constant-0.8860.1230.000 Age0.0330.0060.000 Agesq0.000 Female0.1950.0240.000 Individual level LLTI0.5250.0500.000 University degree0.0240.0400.549 Unemployed (reference group = "employed or self employed")0.8910.2340.000 Retired (reference group = "employed or self employed")0.0190.3450.957 Family care (reference group = "employed or self employed")0.2730.2230.220 Student (reference group = "employed or self employed")-0.0540.0810.505 Sick/disabled (reference group = "employed or self employed")-0.6570.5890.265 On maternity leave (reference group = "employed or self employed")-0.4740.3120.129 On a government scheme (reference group = "employed or self employed")-0.3070.1850.098 Other job status (reference group = "employed or self employed")0.2420.4480.590 Household income-0.0460.0130.001 Couple no child (reference = "single")-0.0890.0500.078 Couple with dependent children (reference = "single")-0.0250.0500.619 Couple with no dependent children (reference = "single")-0.0630.0560.262 Lone parent (reference = "single")0.1570.0820.054 Lone parent non dependent children (reference = "single")0.0770.0730.295 Other household type (reference = "single")-0.0250.0740.732 Renting (reference = "owner occupier")0.0150.0470.753 Local authority housing (reference = "owner occupier")0.0580.0400.150 One car (reference = "no car")0.0490.0400.218 Two cars (reference = "no car")0.0620.0440.161 Three or more cars (reference = "no car")0.0380.0560.497

46. Dependent variable: "unhappiness" BStd. ErrorSig. Constant-0.8860.1230.000 District rates Unemployment rate0.0160.0390.692 Lone parent0.0100.0280.710 Social housing0.0350.0340.296 Sick/disabled0.0140.0210.500 % "affluent"0.0600.0400.132 % "poor"0.0130.0260.630 % "households with one car"0.0020.0260.926 % "households with two cars"0.0120.0750.874 % "households with three cars"-0.0070.0670.914 Interaction variables unemployment-0.8460.2350.000 no car-0.0310.0330.353 students-0.0560.0730.440 social housing-0.0700.0420.093 private renting-0.0320.0290.275 owner occupier0.0280.0320.381 age 20-240.0650.0360.068 aged over 75-0.1270.2510.612 "affluent"-0.0070.0330.841 "middle"-0.0070.0270.785 "poor"0.0010.0260.963 sick/disabled0.1630.2950.580

47. Modelling happiness and well-being: multilevel (Ballas and Tranmer, 2007) 1.“Null model” – extent of variation 2.Demographic variables – random intercepts 3.Socio-economic variables and health – random intercepts 4.Social context – interaction variables

48. model 1: null

49. LevelVarianceVariance (%)SE Region0.0020.210.002 District0.0070.730.003 Household0.14114.630.014 Individual0.81484.440.017 Model 1 variance component estimates

50. Model 3 – socio economic & health controls

51. Model 3 significant main effects Age + Female + Health less than very good + Unemployed + Family Carer + Sick disabled + Couple no child – Lone parent + Rent +

52. All variables – random intercepts

53. Model 3 vs model 1 district level residuals

56. All variables and interaction variables – random intercepts

57. Spatial Microsimulation Reweight the first wave of the BHPS microdata to fit small area “constraints” Dynamically simulate this population for the years 1991, 2001, 2011, 2021 (“groundhog day” scenario) What-if dynamic simulations After Ballas, D., Clarke, G.P., Dorling, D., Eyre, H. and Rossiter, D., Thomas, B. (2005) SimBritain: a spatial microsimulation approach to population dynamics. Population, Space and Place, 11, 13 – 34. doi: 10.1002/psp.351

58. Modelling approach 1.Establish a set of constraints 2.Choose a spatially defined source population 3.Repeatedly sample from source 4.Adjust weightings to match first constraint 5.Adjust weightings to match second constraint 6.… 7.Adjust weightings to match final constraint 8.Go back to step 4 and repeat loop until results converge 9.Save weightings which define membership of SimBritain

59. MODEL CONSTRAINTS 1971, 1981 and 1991 Census Small Area Statistics (SAS) 6 constraint tables with 3 categories projected forward for 2001, 2011 and 2021 ward level projections

60. CONSTRAINT TABLES

61. Estimated geography of happiness in Wales (%) happy more than usual, 1991

63. Estimated geography of happiness in Wales (%) happy more than usual, 2001

65. Estimated geography of happiness in Wales (%) happy more than usual, 2011

67. Estimated geography of happiness in Wales (%) happy more than usual, 2021

69. Conclusions There are individual variations in happiness Social context matters Can explore additional geographical variations using multilevel and spatial microsimulation modelling techniques Some district level variation in happiness does exist, even after accounting for individual and social context Next steps and future possibilities: –Detailed longitudinal analysis –Further analysis for finer geographical scales (spatial microsimulation and agent-based modelling)