We show that inequality-of-opportunity aversion and outcome-inequality aversion need not be inconsistent; the tension between them can be resolved, as long as one is given priority over the other. Our axioms allow us to characterize two classes of opportunity-sensitive poverty measures (OSPM) - one a strict subset of the other. Dominance conditions are established for each class. The first condition, based on the the broad class of OSPM, turns out to be a re-interpretation of an existing result in the literature on poverty dominance for heterogeneous populations (Atkinson and Bourguignon 1987, Jenkins and Lambert 1993). This condition involves a type-sequential comparison of the cumulative distribution functions truncated at the poverty line. The second condition, for the narrower class of OSPM, is a new sequential dominance procedure, which involves comparisons of the group speficic headcount ratios and of average incomes among the poor in each type. Moving from partial to complete orderings, we also propose a specific parametric family of OSPM which combines elements from the Sen and Foster et al. frameworks. We call it the opportunity-sensitive Foster, Greer and Thorbecke index, or OS-FGT.

We then apply both the partial-ordering analysis and the OS-FGT index to eighteen countries in the European Union, using the EU-SILC 2005 data. When aversion to inequality of opportunity is incorporated into the assessment of poverty, we are able to uncover aspects not captured when using standard income-poverty methods. The broad OSPM dominance condition yields a large number of unambiguous rankings: 128 of 153 possible pairwise comparisons. The more demanding sufficient conditions we establish for dominance in the narrow OSPM class are satisfied much more seldom. In addition, income poverty rankings and OS-FGT rankings, although positively correlated, frequently differ: whereas the Netherlands has less income poverty than Germany, for example, the reverse is true for opportunity-sensitive poverty. There are a number of such re-rankings, and we explore the extent to which they are caused by each of three key factors: country differences in overall income poverty; differences in population shares across types; and differences in type-specific income distributions among the poor.

The paper proceeds as follows: Section 2 describes the basic set up and notation. Section 3 lists the axioms that define the two classes of opportunity-sensitive poverty measures: the broad OSPM class, and the narrow OSPM class. Section 4 establishes dominance conditions for both classes. Section 5 defines the OS-FGT family of indices, and discusses some of its properties. Section 6 describes the empirical application to eighteen European countries. Section 7 concludes.

# **2 The basic set up**

Society consists of a large number of single-individual households. Each individual _h_ is completely described by a list of characteristics, which can be divided into two different classes: traits that lie beyond the individual’s responsibility, which are denoted by a vector of circumstances **c** , belonging to a finite set Ω= _{_ **c** 1 _, ...,_ **c** _n}_ ; and factors for which the individual is responsible, which can be summarized by a scalar variable denoted effort, _e ∈_ R+. There is no luck, nor random components in our model. The advantage variable of interest - which we will refer to as ”income” for short - is solely determined by circumstances and efforts, thus generated by a function _g_ : Ω _×_ R+ _→_ R+.

We partition the population into _n_ types, where a _type_ **Ti** _∈T_ is the set of individuals whose circumstance vector is **c** _i_ . The set of types, _T_ , is an exhaustive partition of the entire population. _T ∈I_ , where _I_ is the set of admissible 3