1. What good is happiness?

2. Counting and Multidimensional

Poverty Measurement

Papers by: 1. Marc Fleurbaey, Erik Schokkaert, Koen Decancq

(FSD) Economics, KULeuven

2. Sabina Alkire & James Foster (AF) Oxford & Vanderbilt

Comments by: Lars OsbergEconomics, Dalhousie University

FSD: What good is happiness?

Q: How should welfare economics incorporate insights from happiness and satisfaction studies?

A: Focus on ordinal preferences reported by individuals over various dimensions of life calculate hypothetical equivalent incomes that would

put individuals at the same welfare level as if they were at well-defined reference levels for all other dimensions

Illustrate with data from the Russian Longitudinal Monitoring Survey (RLMS)

Are questions on subjective ‘happiness’ or ‘satisfaction’ admissible evidence?Of what? For what purpose?

Pre-1995 consensus: interpersonal comparisons of utility seen as deeply problematic

1- no sound empirical basis – only personal ordinal rankings of states possible

-FSD: mass of data – subjective utility now seems measurable & interpersonal comparisons feasible

2- not ethical metric for welfare evaluation- FSD: “argue against the welfarist use of such data on the ground that this is unlikely to respect individualpreferences on what makes a good life.”

- LO: “welfarism”/”welfarist” are key concepts for FSD – but not explicitly

defined

What do ‘Happiness’ studies measure?

FSD: contribution to “stress the importance of status and social relations, the harm done by unemployment or by competitive struggles among individuals, the benefits brought by good health and family ties, and so on”

BUT FSD: Valuing life – a ‘reflexive’ / cognitive activity,

but being ‘happy’ is affect / sensation LO: wording of question? ‘life satisfaction’ ??

Is it a problem that limited ‘time to respond’ may increase random measurement error?

FSD: If Happiness = fn(Aspirations – Realities) Adaptation of aspirations to unpleasant realities? Do expensive tastes imply ‘worse off’?

FSD issue is ethically relevant ‘normative’ evaluation – not ‘positive’ behavioral predictive power)

Ethical criticism of ‘Happiness’ literature (FSD ascribe to Sen but much, much older)

"Valuation neglect": valuing a life is a reflective activity; content of a life is a crucial determinant of its value

It is better to be a human being dissatisfied than a pig satisfied; better to be Socrates dissatisfied than a fool satisfied. And if the fool, or the pig, is of a different opinion, it is because they only know their own side of the question. The other party to the comparison knows both sides.

(John Stuart Mill)

LO: Note Mill’s willingness to make judgments & assert a moral ranking of knowledge states

FSD:“ what should matter for welfare evaluation is the judgment that individuals cast on their life, i.e., the cognitive part of their satisfaction”

FSD: “assume that each individual i has an ordering over the vectors of functionings, that reflects his judgment about what makes a life good or bad… the “valuation ordering Ri. ”

Ai vector = i’s frame of reference. σi satisfaction level of individual i

Paradox of ‘Happiness’

GDP per capita has increased, but average ‘happiness’ has not FSD object: Would equally ‘happy’ Icelanders

and Sierra Leoneans willingly trade places? LO: average happiness scores lower in LDCs

FSD: “Even when one forecasts that, by adapting one’s aspirations, one’s satisfaction will remain stable in the long run, one can still have definite preferences for a longer and more affluent life”. Hence – should not use reported happiness as

measure of well-being

Some notation

vector of functionings fi , describing the life of the individual in some a priori relevant dimensions (may contain affects)

"valuation ordering" – reflects judgments about what makes a good life

: i weakly prefers the life described by fi to the life described by fi' (NOT hedonic score)

"satisfaction" also depends on frame of reference (aspirations):

answers on satisfaction question:

Respect for individual sovereignty

if a rich life f** is preferred to a poor life f* by two individuals i and j having the same views about life (Ri = Rj = R), it can happen that σ(f**, R, Ai )=σ(f*, R, Aj ), when the rich suffers from high aspirations whereas the poor has adapted his aspirations

lives should be evaluated on the basis of Ri , not on the basis of satisfaction σi , nor a fortiori, on "measured" satisfaction Si

Si = S(σi, di) (i.e. measurement error = di)

LO: A missed opportunity:Human Rights Law as specifying Ri

Relevant ‘valuation orderings’: What is the empirical counterpart?– are they purely an individual researcher’s values?

Or can we collectively (e.g. democratically) decide a morally binding procedure of community choice of Ri?

Ri NOT an individual choice – but also not ‘paternalistic’ !

e.g. UN Universal Declaration of Human Rights or EU or national Human Rights codes- procedural legitimacy + case law specificity

Alternative: researchers generate idiosyncratic lists ?

FSD: Russia Longitudinal Monitoring Survey (RLMS)

13 waves since 1992 FSD analyse year 2000 5340 individuals in 2646 households "To what extent are you satisfied with your life in

general at the present time?“ 5 point scale – ‘fully’ to ‘not at all’

a. What are relevant functionings?

the estimated equation:

how to interpret X? "functionings" "conditioning variables" Z – preference

differences and aspiration levels

Fi Zi

How to distinguish between life dimensions and individual conditioning variables?

“We describe one promising approach to that problem, which consists in calculating equivalent incomes. These correspond to the hypothetical incomes that would put individuals at the same welfare level, i.e. on the same indifference curve, as in their actual situation, if they were at well-defined reference levels for all other dimensions. The reference levels are chosen in an ethically attractive way. Equivalent incomes fully respect individual preferences. To calculate them, we need knowledge about these preferences. While this knowledge can be obtained from different sources, one possibility is to start from the answers on the questions about happiness or life satisfaction.”

FSD:

“The main problem with our approach lies in the need to distinguish preference shifters and conditioning variables.”

LO: interpreting happiness scores as cardinal numbers and using OLS regressions is also a problem

a. What are relevant functionings?

the estimated equation:

how to interpret X? what are relevant "functionings"?

a. What are relevant functionings?

a. What are relevant functionings?

the estimated equation:

how to interpret X? "functionings" "conditioning variables" Z – preference

differences and aspiration levels

Fi Zi

Indifference curves 1

Indifference curves 2

b. Fixing reference values

health: perfect health employment: not being unemployed housing: median

calculation of "equivalent incomes" Yi*

c. Calculating "equivalent incomes“the level of equivalized expenditures that makes individual i indifferent between the bundle of functionings (Y∗

i , F ) and his actual bundle (Yi, Fi).

calculation of "equivalent incomes" Yi*

note that Z-variables, linked to aspiration levels, do not appear in this expression – but Z-variables linked to preference differences do

Does it make a difference?Spearman rank correlation between the welfare concepts

LO: What is the ‘optimal’ correlation – i.e. to establish the value of alternative measures? Correlation = 1 implies no information content to new

measure of welfare Correlation = 0 implies measuring something

completely different

Portrait of the "deprived“ – lowest quintile of satisfaction, equivalised expenditure or equivalent income

FSD conclusions

“the picture of well-being obtained with equivalent incomes is very different from the picture that is obtained by focusing either on material consumption or on subjective welfare.”

“The main problem with our approach lies in the need to distinguish preference shifters and conditioning variables.”

Counting and Multidimensional Poverty MeasurementSabina Alkire & James Foster (AF)

Proposes methodology for multidimensional poverty measures:

(i) an identification method ρk that extends the traditional intersection and union approaches

(ii) a class of poverty measures Mα that satisfies a range of desirable properties including decomposability.

Illustrative examples use data from US & Indonesia

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Review (2)Why did we measure income poverty?

Income is transferable - policy relevance DEBATE IS COMMUNICABLE OUTSIDE ACADEMIA !!

Income Data Availability & comparability over time & space Continuous, cardinally measurable variable

Unlike dichotomous or ordinal ‘capabilities’ E.g. paralysis, illegal status, social exclusion, human rights

Agency Voluntary Consumption Deprivation is not poverty

Income is potential command over resources Aggregation of dimensionality of functional deprivations is

a byproduct of agency Multi-dimensional “achievements” may be measurable but

“capabilities” are typically not observable

One dimension or many?Issues:

(i) which are the dimensions, and indicators, of interest?

(ii) where should cutoffs be set for each dimension? (iii) how should dimensions be weighted?

(iv) how can we identify the multidimensionally poor?(v) what multidimensional poverty measure(s) should

be used?(vi) which measures can accommodate ordinal data?

(vii) should multidimensional poverty measures reflect interactions between dimensions, and if so, how?

FS – assume (i)-(iii) already solvedfocus is (iv) – (vi)(vii) ignored – i.e. assumed to be zero

How to summarize?- Vector of Incomes- Matrix of Achievements

Income Poverty literature order individuals by income, if y<z individual is identified as

poor Multi-dimensional Poverty d > 2 ; Deprivation on

dimension j if achievement is less than Zj Poor if deprived on any dimension?

Intersection of sets Poverty increases as d increases

Poor only if deprived on all dimensions? Union of sets Poverty decreases as d increases

FS: Identify as ‘poor’ if deprived on k (< d) dimensions “Dual Cutoff” - Any poverty measure then depends on:

Vector of dimensional ‘poverty lines’ Zj

Critical number of dimensions k

Axioms of Income Poverty Measurement generalized to Multi-Dimensional Case

(1)    Focus: the poverty measure should

be independent of the nonpoor population.

(2)    Weak monotonicity: a reduction in a poor

person’s income, holding other incomes constant, must increase the value of the poverty measure.

(3)    Impartiality/Symmetry: A poverty measure should

be insensitive to the order of incomes.

(4)    Weak transfer: An increase in a poverty measure

should occur if the poorer of the two individuals involved in an upward transfer of income is poor and if the set of poor people does not change.

(5)    Strong upward transfer: An increase in a poverty measure

should occur if the poorer of the two individuals involved in an upward transfer of income is poor.

“Axioms” Continued – But should we think a little about implications?

(6)    Continuity : The poverty measure must

vary continuously with incomes.

(7)    Replication invariance : The value of a poverty

measure does not change if it is computed based on an income distribution that is generated by the k-fold replication of an original income distribution.

+ Desirable Property Decomposability into

population sub-groups

LO: - Transfer sensitivity axiom important BUT ….

Focus – relative poverty lines cannot qualify

Impartiality / Symmetry – group identities of poor are always irrelevant

Continuity – excludes all “threshold effects” – by assumption

Particularly dubious for disaggregated capabilities

Is “being poor” purely and always an individual characteristic?

Capabilities, Social Exclusion & Human Rights deprivation refer to relationships within a community

Capabilities – Do Cardinal measures make any sense?

Problem: Many dimensions of deprivation have sensible

ordinal rankings, but scale is often arbitrary FGT(α > 0) not invariant to monotonic

transformation FGT(α = 0): Zj implies dichotomisation

“count” of number of dimensions of deprivation Equal weights unless other information available

Compute average ‘count’ | “poor” (>k)

LO:FGT is transfer sensitive only if α > 1

US & Indonesia examples

USA - 2004 National Health Interview Survey 37 adults aged 19 + (n = 45,884 (1) income measured in poverty line increments &

grouped into 15 categories (2) self-reported health (3) health insurance (4) years of schooling

dimensional cutoffs: if a person(1) lives in a household falling below the standard

income poverty line, (2) reports ‘fair’ or ‘poor’ health(3) lacks health insurance(4) lacks a high school diploma

K=2Equal weights

.

% of ‘poor’ by ethnic group – differs if income or multi-dimensional criterion

Indonesia

Rand 2000 Indonesian Family Life Survey all adults 19+ (n = 19,752). d = 5

(1) expenditure measured in Rupiah(2) health measured as body mass index(3) years of schooling(4) drinking water(5) sanitation.

dimensional cutoffs : if a person (1) lives in household expenditures < 150,000 Rupiah(2) BMI of less than 18.5 kg/m2(3) has fewer than five years of schooling(4) lacks access to piped water or protected wells(5) lacks access to private latrine

If specify 3 cardinal dimensions:expenditure, health, and schooling

LO: when measures vary this much, in exactly what sense can we be measuring the “same” thing?

AF: Conclusions

New methodology for multidimensional poverty measurement consisting of: (i) an identification method ρk that extends the

traditional intersection and union approaches, - uses: 1] a cutoff within each

dimension to determine whether a person is deprived in that dimension; 2] a cutoff across dimensions that identifies the poor using a (weighted) count of the dimensions in which a person is deprived

(ii) a class of poverty measures Mα that satisfies a range of desirable properties including decomposability.