Copula-Based Orderings of Dependence between Dimensions of Well-being Koen Decancq Departement of Economics - KULeuven Canazei – January 2009 2 1. Introduction Individual well-being is multidimensional What about well-being of a society? Two approaches: Income Life Educ Anna 9000 77 61 Boris 13000 72 69 3500 73 81 Catharina WA WB WC Wsoc Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 3 1. Introduction Individual well-being is multidimensional What about well-being of a society? Alternative approach (Human Development Index): Income Life Educ Anna 9000 77 61 Boris 13000 72 69 3500 73 81 Catharina GDP Life Educ HDIsoc Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 4 1. Introduction Individual well-being is multidimensional What about well-being of a society? Alternative approach (Human Development Index): Income Life Educ Anna 9000 77 61 Boris 13000 72 69 3500 73 81 Catharina GDP Life Educ HDIsoc Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 5 1. Introduction Individual well-being is multidimensional What about well-being of a society? Alternative approach (Human Development Index): Income Life Educ Anna 13000 77 81 Boris 9000 73 69 Catharina 3500 72 61 GDP Life Educ HDIsoc Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 6 Outline Introduction Why is the measurement of Dependence relevant? Copula and Dependence A partial ordering of Dependence Dependence Increasing Rearrangements A complete ordering of Dependence Illustration based on Russian Data Conclusion Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 2. Why is Dependence between Dimensions of Well-being Relevant? 7 Dependence and Theories of Distributive Justice: The notion of Complex Inequality Walzer (1983) Miller and Walzer (1995) Dependence and Sociological Literature: The notion of Status Consistency Lenski (1954) Dependence and Multidimensional Inequality: Atkinson and Bourguignon (1982) Dardanoni (1995) Tsui (1999) Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 8 3. Copula and Dependence (1) xj: achievement on dim. j; Xj: Random variable Fj: Marginal distribution function of good j: for all goods xj in : F1(x1) 1 income 0.66 Anna 5000 0.33 Boris 13000 Catharina 0 3500 5000 3500 13000 x1 Probability integral transform: Pj=Fj(Xj) Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 3. Copula and Dependence (2) 9 x=(x1,…,xm): achievement vector; X=(X1,…,Xm): random vector of achievements. p=(p1,…,pm): position vector; P=(P1,…,Pm): random vector of positions. Joint distribution function: for all bundles x in m: A copula function is a joint distribution function whose support is [0,1]m and whose marginal distributions are standard uniform. For all p in [0,1]m: Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 10 3. Why is the copula so useful? (1) Theorem by Sklar (1959) Let F be a joint distribution function with margins F1, …, Fm. Then there exist a copula C such that for all x in m: The copula joins the marginal distributions to the joint distribution In other words: it allows to focus on the dependence alone Many applications in multidimensional risk and financial modeling Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 3. Why is the copula so useful? (3) 13 Fréchet-Hoeffding bounds If C is a copula, then for all p in [0,1]m : C-(p) ≤ C(p) ≤ C+(p). C+(p): comonotonic Walzer: Caste societies Dardanoni: after unfair rearrangement C-(p): countermonotonic Fair allocation literature: satisfies ‘No dominance’ equity criterion C ┴(p)=p1*…*pm: independence copula Walzer: perfect complex equal society Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 3. The survival copula 14 Joint survival function: for all bundles x in m A survival copula is a joint survival function whose support is [0,1]m and whose marginal distributions are standard uniform, so that for all p in [0,1]m : Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 15 Outline Introduction Why is the measurement of Dependence relevant? Copula and Dependence A partial ordering of Dependence Dependence Increasing Rearrangements A complete ordering of Dependence Illustration based on Russian Data Conclusion Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 16 4. A Partial dependence ordering Recall: dependence captures the alignment between the positions of the individuals Formal definition (Joe, 1990): For all distribution functions F and G, with copulas CF and CG and joint survival functions CF and CG, G is more dependent than F, if for all p in [0,1]m: CF(p) ≤ CG(p) and CF(p) ≤ CG(p) Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 4. Partial dependence ordering: 2 dimensions 17 Position in Dimension 2 1 p Position in Dimension 1 0 Canazei January 2009 1 Copula-based orderings of Dependence Koen Decancq 4 Partial dependence ordering: 3 dimensions 18 1 p 1 1 Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 4 Partial dependence ordering: 3 dimensions 19 1 up 1 1 Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 4 Partial dependence ordering: 3 dimensions 20 1 up 1 1 Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 21 Outline Introduction Why is the measurement of Dependence relevant? Copula and Dependence A partial ordering of Dependence Dependence Increasing Rearrangements A complete ordering of Dependence Illustration based on Russian Data Conclusion Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 22 5. Dependence Increasing Rearrangements (2 dimensions) A positive 2-rearrangement of a copula function C, adds strictly positive probability mass ε to position vectors (p1,p2) and (p1,p2) and subtracts probability mass ε from grade vectors (p1,p2) and (p1,p2) Position in Dimension 2 1 p2 p2 Position in Dimension 1 0 Canazei January 2009 p1 p1 1 Copula-based orderings of Dependence Koen Decancq 23 5. Dependence Increasing Rearrangements (generalization) A positive 2-rearrangement of a copula function C, adds strictly positive probability mass ε to position vectors (p1,p2) and (p1,p2) and subtracts probability mass ε from grade vectors (p1,p2) and (p1,p2) Multidimensional generalization: A positive k-rearrangement of a copula function C, adds strictly positive probability mass ε to all vertices of hyperbox Bm with an even number of grades pj = pj, and subtracts probability mass ε from all vertices of Bm with an odd number of grades pj = pj. Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 5. Dependence Increasing Rearrangements (generalization) 24 Position in 1 Dimension 2 Position in 0 Dimension 1 1 1 Position in Dimension 3 Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 5. Dependence Increasing Rearrangements (generalization) 25 G has been reached from F by a finite sequence of the following k-rearrangements, iff for all p in [0,1]m : Positive rearr. Negative rearr. Canazei January 2009 k = even k = odd CF(p) ≤ CG(p) CF(p) ≤ CG(p) CF(p) ≥ CG(p) CF(p) ≥ CG(p) CF(p) ≥ CG(p) CF(p) ≤ CG(p) CF(p) ≤ CG(p) CF(p) ≥ CG(p) Copula-based orderings of Dependence Koen Decancq 5. Dependence Increasing Rearrangements (generalization) 26 G has been reached from F by a finite sequence of the following k-rearrangements, iff for all p in [0,1]m : Positive rearr. Negative rearr. Canazei January 2009 k = even k = odd CF(p) ≤ CG(p) CF(p) ≤ CG(p) CF(p) ≥ CG(p) CF(p) ≥ CG(p) CF(p) ≥ CG(p) CF(p) ≤ CG(p) CF(p) ≤ CG(p) CF(p) ≥ CG(p) Copula-based orderings of Dependence Koen Decancq 27 Outline Introduction Why is the measurement of Dependence relevant? Copula and Dependence A partial ordering of Dependence Dependence Increasing Rearrangements A complete ordering of Dependence Illustration based on Russian Data Conclusion Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 6. Complete dependence ordering: measures of dependence 28 We look for a measure of dependence D(.) that is increasing in the partial dependence ordering Consider the following class: with for all even k ≤ m: Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 29 6. Complete dependence ordering: a measure of dependence An member of the class considered : Interpretation: Draw randomly two individuals: One from society with copula CX One from independent society (copula C┴ ) Then D┴(CX) is the probability of outranking between these individuals After normalization: Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 30 Outline Introduction Why is the measurement of Dependence relevant? Copula and Dependence A partial ordering of Dependence Dependence Increasing Rearrangements A complete ordering of Dependence Illustration based on Russian Data Conclusion Canazei January 2009 Copula-based orderings of Dependence Koen Decancq 7. Empirical illustration: russia between 1995-2003 Canazei January 2009 Copula-based orderings of Dependence 31 Koen Decancq 32 7. Empirical illustration: russia between 1995-2003 Question: What happens with the dependence between the dimensions of well-being in Russia during this period? Household data from RLMS (1995-2003) The same individuals (1577) are ordered according to: Dimension Primary Ordering Var. Secondary Ordering Var. Material wellbeing. Equivalized income Individual Income Health Obj. Health indicator Education Years of schooling Canazei January 2009 Number of additional Copula-based orderings of Dependence Koen Decancq 7. Empirical illustration: Complete dependence ordering Canazei January 2009 Copula-based orderings of Dependence 34 Koen Decancq 35 8. Conclusion The copula is a useful tool to describe and measure dependence between the dimensions. The obtained copula-based measures are applicable. Russian dependence is not stable during transition. Hence we should be careful in interpreting the HDI as well-being measure. Canazei January 2009 Copula-based orderings of Dependence Koen Decancq
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