Metrics Of Happiness

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  • 1. - Jeff Frank M.S. Candidate Community Development and Applied Economics University of Vermont The Metrics of Happiness: Assessing Subjective Well-Being using Anchoring Vignette Surveys
  • 2. Objective
    • To see if we can use an adapted version of the Anchoring Vignette survey technique to measure happiness in a way that will offer elasticity values for the contributing factors of happiness as well as a a workable social utility function.
    • Terminology: Happiness = Subjective Well-Being
  • 3. How it’s currently done
    • ESM – Experience Sampling Method
      • Edgeworth’s Hedonimeter device
    • DRM - Day Reconstruction Method
    • - Remembrance of things past, synthetic happiness
    • The U-Index
    • - Happiness through unhappiness, default state +
    • Brain Imaging
    • - Jevons, fMRI, neuro-parameters,
    • Self-Assessment Surveys
    • - (aka How yu doin?), ordinal categories
  • 4. Self-Assessment Surveys with Ordinal Categories
    • “ Taken all together, how would you say things are these days – would you say that you are very happy, pretty happy, or not too happy?”
      • General Social Survey (Davis, Smith and Marsden, 2001)
  • 5. What’s wrong with Self-Assessment?
    • Ordinal category response surveys aren’t very good at big self-assessment topics like Happiness.
      • People have bias embedded in their self-assessments.
    • Cross-population comparability
      • Respondents understand ordinal categories differently.
        • One person’s “Strongly Agree” may be another person’s “Agree”
      • OJ Trial - When asked, “Did he do it?”
        • Whites 90% Yes, Blacks 90% No
  • 6. Anchoring Vignettes
    • Taken all together, how would you say things are these days – would you say that you are very happy, pretty happy, or not too happy?
      • Research assumes a difference between Real and Reported values (How to measure real value?)
      • Difference is presence of DIF:
        • DIF ( response-category differential item functioning) ie. Survey conditions, temporary environmental influences (candy bars, sunny day)
    • Accounting for DIF you need to pivot reported value against real values.
  • 7. Anchoring for Happiness
    • Prevailing contributors to happiness
    Friends, Family, Marriage, Intelligence, Spirituality, Income, Extroversion, Aesthetics, Employment
    • Isolate variables with vignettes on continuum
    Positive : “Paul has a normal life and a very loving family. How happy is Paul?” 0___________________________________________________100 ||||||||||1|||||||||2||||||||||3||||||||||4|||||||||5|||||||||||6|||||||||||7|||||||||8||||||||||9|||||||||| Negative: “Kim has a normal life but has no family at all. How happy is Kim?” 0___________________________________________________100 ||||||||||1|||||||||2||||||||||3||||||||||4|||||||||5|||||||||||6|||||||||||7|||||||||8||||||||||9||||||||||
  • 8. Finding Variable Elasticities % Chg Q % Chg P = % Chg Happiness = (High-Low)/ Low % Chg Variable = 100% Def Elasticity: The measure of the percentage change in one variable brought about by a 1% change in another variable. 0____________|____________________|__________________100 ||||||||||1|||||||||2||||||||||3||||||||||4||||||||||5|||||||||||6|||||||||||7||||||||||8||||||||||9|||||||||| Low Family =25, High Family =65 %Chg F = 1.6 E(H,F) = 1.6 / 1 = 1.6 Means that a 1% increase in Family will result in a 1.6% increase in overall happiness.
  • 9. Happiness Function
    • Two-Input CES Function:
      • Q(x,y) = γ ∙[ β ∙x ρ + (1- β )∙y ρ ] 1/ ρ
    • Cobb-Douglas Utility Function:
    • Y = AL α K β
    • Need to understand substitutability of inputs
  • 10. Substitutability of Inputs
    • Priority Matrix:
    • Comparing each match, which makes you more happy?
    Marriage = M Intelligence = I Spirituality = S Family = F Wealth = W Volunteering = V Extroversion = X Aesthetics = A Job satisfaction = J J J A J X X J V X V J W X V W F F F F F F J A X V S F S J I X I I F S I M M M M M F M I M J A X V W F S I M
  • 11. Results of Priority Matrix
    • Family = 8
    • Marriage = 6
    • Job Satisfaction = 6
    • Extroversion = 5
    • Intelligence = 4
    • Volunteerism = 3
    • Spirituality = 2
    • Wealth = 1
    • Aesthetics = 1
    F = 1 M = 0.75 J = 0.75 X = 0.625 I = 0.5 V = 0.375 S = 0.25 W = 0.125 A = 0.125 Variable Priority 8 H f(M) = 0.75 M ^ 1.6
  • 12. Sample Survey
    • N = 21 Elasticities
    • Marriage = 0.404
    • Intelligence = -0.055
    • Spirituality = 0.182
    • Family = 0.483
    • Wealth = 0.241
    • Volunteering = 0.157
    • Extroversion = 0.328
    • Aesthetics = 0.243
  • 13.  
  • 14. Estimating Real Happiness
    • We can estimate Real Happiness to compare with Reported Happiness using census and biographic data to apply to our Happiness function.
    • Difference between Real an Reported is presence of DIF
  • 15. Uses and Policy Implications
    • Could help prioritize social programs by identifying what actions will cause best results.
    • Identifies negatives of threats to these variables.
    • Identify policy directives, inclusion of well-being.
    • Offers hard measures for well-being valuation.
    • Can help define: Development
    • Help identify community and international development goals.