TRACKING LIVING STANDARDS: IS IT DONE BETTER BY EDY OR HEDY?

• Author: Jensen, John
• Position: Unit of measurement used in this study of household incomes - Statistical Data Included

Abstract

There has been longstanding interest in the extent to which commonly available standard statistical information can provide a valid basis for monitoring hardship. The most common approach is based on applying income equivalisation to household income data. In this paper, a particular application of that approach is used to specify a metric called EDY. A second metric, called HEDY, is also specified. Its novel feature is that it incorporates an adjustment intended to take account of the variability in housing costs that occurs independently of income (reflected in previous findings that some with low incomes have relatively high housing costs and vice versa).

A series of analyses are made comparing the properties of EDY and HEDY with a view to assessing which on balance provides the better basis for monitoring living standards. The results show that both display similar trends over the decade 1988-98, although HEDY moves more smoothly, showing less year-to-year fluctuations. However, they present somewhat different pictures of the relative position of some sub-populations, with HEDY results implying that economic changes occurring over the decade have had a disproportionately severe impact on the living standards of children. The authors conclude by stating their provisional preference for the HEDY metric, but point to the need for further work -- which they intend to carry out -- to more clearly resolve the issue.

INTRODUCTION

There has been a long-standing interest in using statistical information to develop a picture of likely level of hardship in the population and whether it has been changing over time. Although household income has primarily been used for this purpose, its limitation is that it does not take into account differences in size. The most common way to deal with this is to equivalise.

Recent reports into poverty and income adequacy (see Stephens et al. 2000, Waldegrave and Sawrey 1994) and results from the Ministry of Social Policy's Living Standards Survey 2000 (2001) highlight the significance of housing cost as a factor that affects living standards. As a result of these studies, the authors have become interested in exploring an alternative approach for measuring living standards - one that incorporates housing cost into an equivalised income measure. The simplest way to do this is to subtract housing cost from income and equivalise the remaining net amount. In this paper, the remaining net amount is referred to as the Housing-adjusted Equivalised Disposable Income (HEDY) metric(2). This is in contrast to the commonly used Equivalised Disposable Income (EDY) metric.

This paper examines some of the issues that arise in such metrics for creating monitoring statistics (which most commonly are reported as the proportion of the population below a particular threshold). The central purpose of this paper is to begin a systematic examination of the relative merits of two metrics (EDY and HEDY) as the basis for living standards monitoring.

Using the metric to produce proportion-below-threshold statistics, the analysis will focus on three key questions:

* How sensitive is the broad trend to the choice of metric?

* Within the broad trend, how sensitive is the pattern of movement to choice of threshold?

* How sensitive is the relative position of sub-populations and the trend movements for sub-populations to the choice of metric?

It is worth noting that the creation of proportion-below-threshold statistics (for the population as a whole, or sub-populations, such as Maori, or children) is not the only way of using the metrics to create monitoring information. For example, they can be used to define index-type measures. However, consideration of the metrics for such wider purposes is not the topic of the present paper.

USING INCOME FOR THE PROXY MEASUREMENT OF LIVING STANDARDS

Income and housing costs have been referred to as factors that influence standard of living, but research has identified other factors that also are of major importance, implying that both the EDY and HEDY metrics are necessarily imperfect indicators of living standards. People with the same income level can have substantially different living standards as a result of their lifecycle stage (youth, middle age, older people), ownership of assets, the extent to which they receive assistance from others, and the extent to which they have atypical expenditure commitments (e.g. unusually high medical costs, debt repayments, transport costs, electricity costs, etc.).

Despite these disadvantages, such narrowly specified metrics as EDY and HEDY have some convenient features. Income is the single most accessible indicator of economic well-being for the residents of any given country at any given point in time. Income is concrete and measurable, and statistical information on income is widely collected and reported. Income can be compared across groups and within groups. Housing cost data are similarly quite widely collected and reported (although to a lesser extent than income data).

To address the three questions set out above, we have used the EDY and HEDY metrics to generate population-below-threshold statistics for a variety of thresholds (see Appendix Two).

The second of the questions required that the lowest threshold should be sufficiently low for the majority of income-tested beneficiaries and superannuitants to have EDY values above it throughout the period examined. (As discussed later, this was to minimise group-selection effects, whereby changes in real benefit rates for particular beneficiary groups can cause them to move en masse from a bit above the line to a bit below, or vice versa, causing the monitoring statistic to exhibit substantial lurches that do not reflect sudden substantial movements of living standards.) Similarly, it was necessary that the highest threshold should be sufficiently high for the majority of income-tested beneficiaries and superannuitants to have EDY values below it throughout the period. This resulted in a wide separation between the lowest and highest thresholds.

Two further thresholds were specified intermediate between the highest and lowest threshold. These are referred to as the second (highest) and third (highest) thresholds. For each EDY threshold value we identified a corresponding HEDY value that resulted in a proportion below threshold in 1988 that was the same as the 1988 EDY proportion below threshold.

This has resulted in four pairs of trend lines being generated with each pair being at the same value at the beginning period (1988), but being free to diverge from that year onwards according to the combined effects of various economic and demographic changes (i.e. changes in income, living costs, family size, etc.).

THINGS TO CONSIDER IN DEVELOPING INCOME-BASED MEASURES OF HARDSHIP

The most analytically satisfactory approach to an income-based living standards measure is to express income (by itself, or housing-adjusted on the basis of costs) in an equivalised form (thus taking account of the different relative needs of family units of different sizes), and relate the amount to a specified threshold value set in the lower part of the range. This results in each family being designated as being below or above the threshold (or "line").

There are several dimensions to this task. They relate to:

* the unit of analysis that should be used;

* how account should be taken of differences in the sizes of the units;

* how an income-based standard of living proxy measure should be defined for that unit (including whether it should include an adjustment for housing costs);

* whether the line should be defined in distributional or nominal terms;

* how the self-employed should be treated; and

* the form of the measure (head count of the number below threshold as a proportion of population, poverty index, etc.).

Each will be discussed briefly, in turn.

Unit of Analysis

Historically, households have been used as the base units for analysis. The rationale is that the members of a household can be assumed to have commingled their financial affairs to function as an economic unit whose members have a common standard of living. This may have been substantially true when the system of household statistics was first established, but has become increasingly doubtful as household composition has become increasingly heterogeneous.

An alternate approach is to use "economic family units" (also known as "family core economic units"). An economic family unit refers to a person who is financially independent or a group of people who usually reside together and are financially interdependent, This unit is essentially the unit of eligibility for core income-tested Social Security benefits (see Appendix One). A single household can be made up of several economic family units with different incomes (see Mowbray 1994).

For the present purpose, the economic family unit has been chosen as the unit of analysis. Given that economic families with different economic circumstances can be found within the same household, this can be expected to give a more valid measure than one based on the household as a whole(3).

Current data sources do not permit examination of the degree of resource pooling within economic families, nor the equity of resource use. Similarly, the sources do not permit examination of sharing of resources between units (whether they are within the same household or in different households). Use of the household as the unit would give rise to similar qualifications about inability to ascertain intra-unit and inter-unit sharing.

Accounting for Differences in Family Size (Equivalisation)

Families differ in size and composition. An income that provides one family with an adequate standard of living may be inadequate for another. It is necessary to allow for such differences in order to make meaningful analyses of the distribution of income and well-being among families. Equivalence scales...