The Treasury

Global Navigation

Personal tools

1  Introduction

Many government policies are designed to advance a redistributive objective. Many other policies may not have redistribution as their aim, but could have distributional consequences which need to be evaluated. Furthermore, a wide range of changes - including for example those affecting relative prices, or labour and asset markets, along with demographic change and the structure of households - can have substantial distributional effects. Understanding impacts on inequality and poverty is therefore likely to play a central role in evaluating policies and outcomes.

When attempting to compare distributions using measures of inequality and poverty, important decisions must first be made regarding three major elements, referred to as: ‘what, when and whose'. First, a choice must be made regarding precisely what is to be measured; this is often referred to as the ‘metric' or ‘welfare metric'. For example, this may be pre-tax incomes, wage rates, or a measure of expenditure or consumption. In some cases the welfare metric may even attempt to allow for the value of leisure.[1]

Second the accounting period, or time period over which the selected ‘welfare metric' is measured, must be chosen. This may be a week, year or even lifetime, depending on the context. A longer accounting period avoids difficulties arising from transitory changes, or variations arising from age differences which may not be regarded as relevant for inequality comparisons. For example, two individuals could have the same lifetime incomes but different time profiles of their annual incomes. However, data limitations often exist when attempting to extend the accounting period. The use of a longer period also introduces the role of systematic relative mobility.[2] Judgements about inequality may be closely related to judgements about mobility.

The third decision concerns the unit of analysis. This could be, for example, the family, the household, or the individual. Indeed, both the welfare metric and the income unit could be artificial measures, designed to allow for differences in the composition of households and involving the concept of an ‘equivalent adult'.[3] Assumptions about income sharing within households and families are also often used, and these need to be treated with care.

These choices are in some ways related. For example, if a longer accounting period is used, household and family structures change over time, so that it is more appropriate to consider individuals as the basic unit. The choice of a particular welfare metric may also suggest a particular unit of analysis. The choices depend on the precise nature of the basic question motivating the analysis. A crucial point to recognise is that ultimately these choices cannot avoid the use of value judgements. The view is taken here that the role of the professional economist is to examine the implications of adopting alternative value judgements, so it is very important to make these as explicit as possible.

Even a cursory examination of publications involving inequality and poverty comparisons shows that, in reporting results, decisions regarding the welfare metric, the unit of analysis and the time period are frequently given scant attention. Often the term ‘income' is used without being clearly defined. It is all too easy to make spurious comparisons between distributions. Many publications make only a limited number of comparisons, despite the fact, stressed above, that value judgements are involved at every stage.

The limited aim of this paper is therefore to provide an introductory review of the range of alternative possible distributions based on single-dimensional metrics which are variants of income and consumption concepts.[4] This paper attempts to clarify the various alternatives, both for users of data and those wishing to interpret results. Inequality comparisons nearly always give rise to technical and data difficulties, though these are outside the scope of the present paper.

Cross-sectional comparisons using a household economic survey are considered. Hence, the accounting period is necessarily a single period (typically a year or shorter). The contexts discussed here include analyses of the redistributive effects of direct taxes and transfers, along with the effects of indirect taxes. In addition, ‘fiscal incidence' studies attempt to allocate some items of government expenditure, such as health and education, to individuals as well as considering the effects of indirect taxes, direct taxes and transfers. In allocating such expenditure, the view is therefore taken that it relates to publicly provided (tax financed) private goods.[5] Simple hypothetical numerical examples are used to highlight the alternative approaches and distributions.

It should also be remembered that any measures of redistribution, measured in terms of a move from pre-tax to post-tax (and transfer) incomes, need to be interpreted with caution because the structure of taxes and benefits, and of government expenditures, itself influences the pre-tax distribution.

The structure of the paper is as follows. Section 2 introduces a hypothetical population consisting of just four households, chosen to illustrate the range of distributions which can be obtained. It describes the role of adult equivalence scales, designed to deal with the fact that individuals are not homogeneous, and of explicit sharing rules whereby total household income is allocated among all members of that household. Section 3 reports various measures of redistribution and progressivity for a range of comparisons. Section 4 examines the additional difficulties involved in making inequality comparisons over time. In particular, both the tax and transfer system and the population structure (for example the age distribution of the population) can change over time. It is therefore useful to be able to disentangle the separate effects of tax and demographic changes. Brief conclusions are in Section 5.


  • [1]The metric is usually a one-dimensional measure, although multi-dimensional approaches can also be taken. The present paper concentrates on comparisons of one-dimensional metrics.
  • [2]On longer accounting periods see, for example, Creedy (1997a, b).
  • [3]This is considered in more detail in Section 2 below.
  • [4]Hence, the use of a concept of ‘money metric utility', where incomes are affected by the tax structure via labour supply variations, is not considered here as this raises a different set of problems. These are considered by, for example, Donaldson (1992), Aaberge and Colombino (2008), Ericson and Flood (2009) and Decoster and Haan (2010) where there are heterogeneous preferences; see also Creedy and Hérault (2012).
  • [5]This is of course debatable. It may, for example, be thought that such expenditure gives rise to considerable externalities. Furthermore, some people may argue that health expenditure devoted to children could instead be added to the welfare metric of parents, who would otherwise need to pay for the care.
Page top