Metrics Of Happiness

- 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

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

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

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)

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

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.

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||||||||||

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.

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

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

Results of Priority Matrix