Measurement of Inequality and Social Welfare

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January 16, 218

Ranking income distribution and Lorenz curves: Partial and complete orderings (i) Partial orderings: Stochastic and inverse stochastic dominance, Lorenz dominance (ii) Complete orderings: a. Social welfare criteria based on expected utility theory b. Rank-dependent social welfare criteria Important issue in both policy work, descriptive analysis and causal inference: 1 Statistical oces and gov agencies compare distribution functions and Lorenz curves across countries, subgroups and time 2 Research compares distributions of earnings, income, consumption and wealth to evaluate economic policies and social welfare

The cumulative distribution function and its inverse Let F be a member of the set F of cumulative distribution functions with mean µ F and left inverse dened by F 1 (t) = inf {x : F (x) t} Note that both discrete and continuous distribution functions are allowed in F, and though the former is what we actually observe, the latter often allows simpler derivation of theoretical results and is a valid large sample approximation. Thus, in most cases below F will be assumed to be a continuous distribution function, but the assumption of a discrete distribution function will be used where appropriate. To x ideas, we will refer to F as the income distribution, although our framework can be applied to any type of distribution functions. In order to rank distribution function we introduce the ordering Rolf relation Aaberge, Research Department,Statistics Norway

Ranking distribution functions: Examples Suppose we want to rank two distributions, F 1 and F Assume that the ordering relation satises rst-degree stochastic dominance, i.e. F 1 (x) F (x) for all x [, ) F 1 1 1 (t) F (t) for all t [,1]. Can be used as a ranking criterion when distribtion don't cross. But how do we deal with intersecting distribution functions (Figures 2 and 3)? Conventional approach in empirical work: Using summary measures like the mean, the median and the variance or weighted means.

Second-degree stochastic and inverse stochastic dominance Denition A distribution function F 1 is said to second-degree stochastic dominate a distribution function F if and only if y y F 1 (x)dx F (x)dx for all y [, ) and the inequality holds strictly for some y (, ). A distribution function F 1 is said to second-degree inverse stochastic dominate a distribution function F if and only if u u (t)dt 1 F 1 F 1 (t)dt for all u [,1] and the inequality holds strictly for some u (,1).

As was demonstrated by Atkinson (197), second-degree stochastic dominance is equivalent to second-degree inverse stochastic dominance, which is called generalized Lorenz dominance by Shorrocks (1983). Moreover, under the restriction of equal mean incomes second degree inverse stochastic dominance is equivalent to the criterion of non-intersecting Lorenz curves.

Third-degree stochastic dominance Since situations where second-degree dominance does not provide unambiguous ranking of distribution functions may arise, it will be useful to introduce weaker ranking criteria than second-degree dominance. To this end it appears attractive to consider third-degree stochastic and inverse stochastic dominance. Denition A distribution function F 1 is said to third-degree stochastic dominate a distribution function F if and only if z y F 1 (x)dxdy z y F (x)dxdy for all z [, ) z (z x)(f 1 (x) F (x))dx for all z [, )

Third-degree inverse stochastic dominance Denition A distribution function F 1 is said to third-degree inverse stochastic dominate a distribution function F if and only if v u v v F 1 (t)dtdu 1 u F 1 (t)dtdu for all v [,1] (v t) ( F 1 1 1 (t) F (t)) dt, for all v [,1] and the inequality holds strictly for some v (,1). Note that third-degree stochastic and inverse stochastic dominance do not coincide.

Transfer principles associated with second- and third-degree dominance Denition (The Pigou-Dalton principle of transfers). Consider a discrete income distribution F. A transfer δ > from a person with income x + h (or F 1 (t)) to a person with income x (or F 1 (s)) is said to reduce inequality in F when h > (s < t) and to raise inequality in F when h < (s > t). (i) If µ F1 = µ F, the condition of second-degree inverse stochastic dominance is identical to the Pigou-Dalton transfer principle. Denition (The principle of diminishing transfers, Kolm,1976). Consider a discrete income distribution F. A transfer δ > from a person with income x + h 1 to a person with income x is said to reduce inequality in F more than a transfer δ from a person with income x + h 1 + h 2 to a person with income x + h 2. (ii) If µ F1 = µ F, the condition of third-degree inverse stochastic dominance is identical to the principle of diminishing transfers.

Rank-preserving transfers Denition (The principle of positional transfer sensitivity, Mehran, 1976). Consider a discrete income distribution F. A rank-preserving transfer δ > from a person with income F 1 (s + h) to a person with income F 1 (s) is said to have a stronger equalizing eect on F than a transfer δ > from a person with income F 1 (t + h) to a person with income F 1 (t) when s < t. (iii) If µ F1 = µ F, the condition of third-degree inverse stochastic dominance is identical to the principle of rst-degree downside positional transfer sensitivity.

Lorenz dominance The primal approach Denition A Lorenz curve L 1 is said to rst-degree dominate a Lorenz curve L if L 1 (u) L (u) for all u [,1] and the inequality holds strictly for some u [,1]. First-degree Lorenz dominance is identical to the Pigou-Dalton transfer principle. A social planner who prefers the dominating one of non-intersecting Lorenz curves favors transfers of incomes which reduce the dierences between the income shares of the donor and the recipient, and is therefore said to be inequality averse.

Second-degree Lorenz dominance To deal with situations where Lorenz curves intersect a weaker principle than rst-degree Lorenz dominance is called for. To this end it is normal to employ second-degree upward Lorenz dominance dened by Denition A Lorenz curve L 1 is said to second-degree upward dominate a Lorenz curve L if u L 1(t)dt u L (t)dt for all u [,1] and the inequality holds strictly for some u [,1]. Second-degree upward Lorenz dominance is identical to the principle of rst-degree downside positional transfer sensitivity. Under the restriction of equal mean incomes third-degree (upward) inverse stochastic dominance is equivalent to the criterion of seond-degree upward Lorenz dominance.

Higher degrees of inverse stochastic dominance and Lorenz dominance Since situations where second-degree (upward or downward) inverse stochastic and Lorenz dominance do not provide unambiguous ranking of distribution functions and Lorenz curves may arise, it is useful to introduce weaker dominance criteria than third-degree inverse stochastic dominance and second-degree Lorenz dominance. To this end two hierarchical sequences of nested inverse stochastic (Lorenz dominance) criteria might be introduced; one departs from third-degree upward inverse stochastic dominance (second-degree upward Lorenz dominance) and the other from third-degree downward inverse stochastic dominance (downward Lorenz dominance). More on this in Aaberge (29, SCW).

Complete orderings: Social welfare criteria based on expected utility theory The problem of ranking income distributions formally corresponds to the problem of choosing between uncertain prospects. This relationship has been utilized by e.g. Kolm (1969) and Atkinson (197) to characterize the criterion of second order (upward) stochastic dominance. Atkinson reinterpreted the standard theory of choice under uncertainty and demonstrated that inequality aversion can in fact be viewed as being equivalent to risk aversion. This was motivated by the fact that in cases of equal mean incomes the criterion of non-intersecting Lorenz curves is equivalent to second-degree stochastic dominance, which means that the Pigou-Dalton transfer principle is identical to the principle of mean preserving spread introduced by Rothschild and Stiglitz (197). To choose between F and F 1 we can then use the following criterion Rolf Aaberge, Research Department,Statistics Norway u(x)df 1(x) u(x)df (x)

Axiomatic justication of the primal approach Assume that the preference relation of the social planner satises the following axioms: (Order). is a transitive and complete ordering on F. (Continuity). For each F F the sets {F F : F F }and {F F : F F } are closed (w.r.t. L 1 -norm). (Dominance). Let F,F 1 F. If F 1 1 1 (t) F (y) for all t [,1] and the inequality holds strictly for some t (,1) then F 1 F. (Independence). Let F, F 1 and F 2 be members of F and let α [,1]. Then F 1 F implies (αf 1 (x) + (1 α)f 2 (x)) (αf (x) + (1 α)f 2 (x)). Von Neuman and Morgenstern (1936) proved that a preference relation that satises Axioms 1-4 can be represented by the following family of social welfare functions Eu(X ) = u(x)df (x)

Measures of inequality based on the primal approach Atkinson (197) proposed to use I u (F ) = 1 u 1 (Eu(X )) µ as a measure of inequality, where u 1 (Eu(X )) is denoted the equally distributed equivalent income and µi u (F ) is measure of the loss in social welfare due to inequality in the distribution F.

The relationship between dominance criteria and primal social welfare functions Theorem Let F 1 and F be members of F. Then the following statements are equivalent. (i) F 1 second-degree upward inverse stochastic dominates F (ii) E F1 u(x ) > E F u(x ) for all increasing concave u Theorem Let L 1 and L be members of L. equivalent. Then the following statements are (i) L 1 rst-degree dominates L (ii) I u (F 1 ) < I u (F ) for all increasing concave u

Complete orderings: The family of rank-dependent social welfare functions The general family of rank-dependent measures of social welfare introduced by Yaari (1987,1988) is dened by W P (F ) = 1 P (t)f 1 (t)dt, and can be interpreted as the equally distributed equivalent income. The weighting function P is the derivative of a preference function that is a member of the following the set of preference functions: P = {P : P (t) > and P (t) < for all t (,1), P() = P (1) =, P(1) = 1} W P preserves 1st-degree dom, since P (t) >, and W P preserves 2nd-degree dom (and Pigou-Dalton), since P (t) < W P µ F, and W P = µ F i F is the egalitarian distribution

Complete orderings: The family of rank-dependent social welfare functions The general family of rank-dependent measures of social welfare introduced by Yaari (1987,1988) is dened by W P (F ) = 1 P (t)f 1 (t)dt, and can be interpreted as the equally distributed equivalent income. The weighting function P is the derivative of a preference function that is a member of the following the set of preference functions: P = {P : P (t) > and P (t) < for all t (,1), P() = P (1) =, P(1) = 1} W P preserves 1st-degree dom, since P (t) >, and W P preserves 2nd-degree dom (and Pigou-Dalton), since P (t) < W P µ F, and W P = µ F i F is the egalitarian distribution

Dual measures of inequality Since W P (F ) can be interpreted as the equally distributed equivalent income the dual family of inequality measures is dened by J P (F ) = 1 W P(F ), µ where µ = EX = xdf (X ). Note that µj P (F ) is a measure of the loss in social welfare due to inequality in the distribution F.

Axiomatic justication of the dual approach Assume that the preference relation of the social planner satises the following axioms: (Order). is a transitive and complete ordering on F. (Continuity). For each F F the sets {F F : F F }and {F F : F F } are closed (w.r.t. L 1 -norm). (Dominance). Let F,F 1 F. If F 1 1 1 (t) F (y) for all t [,1] and the inequality holds strictly for some t (,1) then F 1 F. (Independence). Let F, F 1 and F 2 be members of F and let α [,1]. Then F 1 F implies ( ) 1 ( ) αf 1 1 1 (t) + (1 α)f2 (t) αf 1 1 1. (t) + (1 α)f2 (t) Yaari (1936) proved that a preference relation that satises Axioms 1-4 can be represented by the following family of social welfare functions 1 W P (F ) = P (t)f 1 (t)dt,

Normative justication of the general family The normative justication of W P can be made in terms of a (a) Theory for ranking distribution functions: With basic ordering and continuity assumptions, the dual independence axiom characterizes W P (Yaari, 1988) (b) Value judgement of the trade-o between the mean and (in)equality in the distributions (Ebert, 1987; Aaberge, 21) W P = µ F [1 J P (F )] where µ F is the mean of F and J P (F ) is the family of rank-dependent measures of inequality aggregating the P -weighted Lorenz curve of F

The Gini subfamily The primal approach If we choose P 1k (t) = 1 (1 t) k 1, k > 2 then W P is equal to the extended Gini family of social welfare functions (Donaldson and Weymark, 198) where W Gk = µ [1 G k (F )] =, k > 2 G k (F ) is the extended Gini family of inequality measures G 3 (F ) is the Gini coecient and W G2 = µ Note that {µ,w Gi (F ) : i = 3,4,...} uniquely determines the distribution function F (Aaberge, 2)

The Lorenz subfamily The primal approach If we instead choose P 2k (t) = (k 1)t tk 1, k > 2 k 2 then W P is the Lorenz family of social welfare functions (Aaberge, 2) where W Dk = µ [1 D k (F )], k > 2 D k (F ) is the Lorenz family of inequality measures D 3 (F ) is the Gini coecient Note that {µ,w Di (F ) : i = 3,4,...} uniquely determines the distribution function F (Aaberge, 2)

The relationship between dominance criteria and dual criteria of social welfare and inequality Theorem Let F 1 and F be members of F. Then the following statements are equivalent. (i) F 1 second-degree upward inverse stochastic dominates F 1 (ii) P (t)f 1 (t)dt > 1 1 P (t)f 1 P (P (t) < ) (t)dt for all increasing concave Theorem Let L 1 and L be members of L. equivalent. Then the following statements are (i) L 1 rst-degree dominates L (ii) J P (F 1 ) < J(F ) for all increasing concave P

Partial dual ordering - Third degree upward dominance Note that second degree inverse stochastic dominance is dened by u Λ 2 F (u) F 1 (t)dt, u [,1] To dene third degree upward inverse stochastic dominance, we use the notation u u Λ 3 F (u) Λ 2 F (t)dt = (u t)f 1 (t)dt, u [,1] Denition A distribution F 1 is said to third degree upward inverse stochastic dominate a distribution F if and only if Λ 3 F 1 (u) Λ 3 F (u) for all u [,1] and the inequality holds strictly for some u (,1).

Transfer principle The primal approach s W P (δ,h): change in W P of a fixed progressive transfer δ from an individual with rank s + h to an individual with rank s. 1 stw P (δ,h) s W P (δ,h) t W P (δ,h). Denition (Zoli, 1999; Aaberge, 2, 29) W P satises the principle of rst degree downside positional transfer sensitivity (DPTS) if and only if 1 stw P (δ,h) >, when s < t.

Equivalence result The primal approach Let P 3 be the family of preference functions dened by { } P 3 = P P : P (t) >, Theorem Let F 1 and F be members of F. Then the following statements are equivalent. (i) F 1 third-degree upward inverse stochastic dominates F (ii) W P (F 1 ) > W P (F ) for all P P 3 (iii) W P (F 1 ) > W P (F ) for all P P where W P satises rst-degree DPTS (i) and (ii): least-restrictive set of social welfare functions that unambiguously rank in accordance with 3-UID (i) and (iii): normative justication for 3-UID