Metrics Of Happiness

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Information about Metrics Of Happiness
Education

Published on December 12, 2008

Author: frankjef

Source: slideshare.net

- 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

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

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)

“ 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

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.

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||||||||||

Prevailing contributors to happiness

Isolate variables with vignettes on continuum

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

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

Priority Matrix:

Comparing each match, which makes you more happy?

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

Family = 8

Marriage = 6

Job Satisfaction = 6

Extroversion = 5

Intelligence = 4

Volunteerism = 3

Spirituality = 2

Wealth = 1

Aesthetics = 1

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

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

 

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

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

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.

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.

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