The Economic and Health Status Of Households

Report by Brian Easton & Suzie Ballantyne, Wellington School of Medicine

Keywords: Distributional Economics ; Statistics;

This report contains the contents and executive summary only. Copies of the report (with its numerous tables) are available on request from Brian Easton. Some tables are in Validation and the Health and Household Economy Project

For an introduction to method see The Economic and Health Status Project

Executive Summary Below

Chapter 1: Introduction (page 8)
Chapter 2: Measures of Health Status (page 11)
Chapter 3: Adjusting Household Income for Housing Circumstances (page 24)
Chapter 4: The Utilisation of Health Care Services (page 35)
Chapter 5: The Determinants of Private Spending on Health Care (page 44)
Chapter 6:
Choosing Household Equivalence Indexes
(page 52)
Chapter 7: The Household Distribution of Income (page 76)
Chapter 8: The Household Distribution of Income Adjusted for Housing Circumstances (page 84)
Chapter 9: The Location of Health Status in the Income Distribution (page 92)
Chapter 10: Conclusion. (page 97)


Chapter 2: Measures of Health Status.

Chapter 2 examines two measures of health status. One is the reported self-categorisation from the Household Economic Survey, the other is an index based on the reported utilised health services (which is calibrated by using it to predict the self -categorisation status). Both measures are validated in later chapters.

The latter part of the chapter looks at the relationship between the two measures and household income for the elderly. It shows there is a tendency for those in poorer health to be in the lowest income households, but the effect is not strong, because the income distribution of the elderly is very compact.

Chapter 3: Adjusting Household Income for Housing Circumstances

Chapter 3 describes a rigorous procedure for assessing the impact of housing circumstances on income based on the difference between actual housing outlays and predicted housing outlays, where predicted outlays are derived from an econometric equation of the housing spending of households in the rental sector. (Thus those whose housing outlays are more expensive that the average rate in the rental sector for their particular circumstances have the difference deducted, those whose outlays are less have the difference added to their income.)

The econometric equation shows the following characteristics affect housing outlays of households which rent.
– Income (or aggregate expenditure).
– Type of tenancy (HNZ housing was being charged at much the same rate as private market rents, but employer and local authority rents were markedly cheaper, and a rental agency leasing the dearest).
– Region.
– Number of Bedrooms.
– Household composition (although as explained the coefficients are not intuitively correct).
– Age with older households (as measured by the age of the reference person) paying less than younger households (weakly).
– Ethnicity with Polynesians paying less Pakeha and Other (but the total effect is small).

However, whether the dwelling was furnished or unfurnished had little effect on rental outlays. (The text suggests that some of these may be quality of housing effects which are not measured.)

Chapter 4: The Utilisation of Health Care Services.

Chapter 4 pursues the practical problem of the determinants of health service utilisation, by estimating a logit function which determines the probability of utilisation of each service in terms of the household characteristics.

Most of the conclusions are not surprising. If all other characteristics are the same:
– income is not a major determinant of health care utilisation.
– holders of community services cards tend to use most services more than had they not one.
– holders of high use cards utilise all services more intensely.
– holders of medical insurance tend to use most services more intensely.
– those who describe themselves as not being in excellent health use health services more intensely. The exception is for dental care where greater use is associated with excellent health.
– the age and gender effect is much as expected. Young children are lower users of services, but boys more so than girls. In early adulthood women tend to use the services more than men, although this may partly reflect their child bearing and rearing duties. However, young men do use the accident and emergency and ambulance services more than women. In later adulthood there tends to be a diminution of use of health services (with some obvious exceptions such as for opticians), but with perhaps some rise for some services after retirement.
– ethnic minorities tend to use the health services less than the Pakeha majority, even after adjusting for other socioeconomic characteristics.

Chapter 5: The Determinants of Private Spending on Health Care.

Chapter 5 examines what determines the level of spending on private health care by private households. The equations of the individual spending groups are econometrically satisfactory, but they typically have little total explanatory power and the chapter focuses on total private spending.

Income is the single most important variable accounting for 39 percent of the total explained variation in spending. The income elasticity was .24 which means that while those on higher incomes spend more on health care, their health spending decreases as a proportion of their total spending.

Possession of medical insurance was second to income in explanatory power, accounting for 31 percent of the total explained variation in spending. The study also explored the characteristics of households which had medical insurance. Income is not an important determinant, while Maori households are less likely to be holders compared to others with similar socioeconomic characteristics. Household composition and age – but not gender – are factors, but the largest reason may be the health status of the members of the household, especially households with particularly sick members.

The third largest determinant (12 percent) of explained variation is household composition and gender.

Another 8 percent of variation is explained by health status. However the effect is strong one for those who are in poor health. A household which is has a zero probability of excellent health spends over four times as much on health care as one all of whose members are in perfect health.

Additionally, those with community service cards spend 25 percent less than those without (despite, as we saw in Chapter 4, their being higher utilisers of the services), while those with High Use Cards spend on average 15 percent more (but they do spend less on prescriptions).

Chapter 6: Choosing Household Equivalence Indexes

Chapter 6 explains why household income often has to be adjusted for household composition. A means of doing this is a household equivalence scale which divides the income by an index which reflects the relative housing expenditure needs.

There are a number of ways of constructing household equivalence scales.
– Perhaps the least satisfactory method is the delphic where the scale is chosen by judgement with little empirical input.
– Using overseas constructed scales involves the assumption of international comparability.
– Scales have also been constructed on the basis of household budgets consisting of quantities of consumption items (or just food) but these have a judgmental element to them.
– The most rigorous way to construct a household equivalence scale is to use an econometric method, the more sophisticated of which pursued in New Zealand being Claudio Michelini’s explicitly based on utility theory. However Michelini’s work is not complete.

The choice of equivalence scale matters. It is simply not true that they are all broadly the same in terms of actual effects and outcomes.

How then to choose a scale? Until there is a validated one the use of an equivalence scale should be avoided unless it is absolutely necessary.
– One option where scale use cannot be avoided is to use a plausible set of them, and report only results which are robust to the choice of scale.
– Another procedure which avoids the arbitrary use of a scale is to use dummy variables in regression equations, but that is not always possible.
– Where it is not, the generalised Michelini scale seems the best available. The only other with merit might be the Jensen 1978 scale. All others seem unsatisfactory, including the Jensen 1988 and the Square Root scales which are most used for official statistical purposes.

While the generalised Michelini Scale may be the best available, given the importance of an equivalence scale in research and policy, there is a strong case for more effort to improve its estimation, possibly along the lines that Michelini contemplated before his premature death. There is also a desperate need to validate any chosen scale, that is to use evidence external to their construction to demonstrate they are doing what the claim to do.

Chapter 7: The Household Distribution of Income.

Chapter 7 describes how the household (equivalised) distribution is constructed, and some of the difficulties with current applications of the method. It also reports the rankings by socioeconomic characteristics. It suggests they are largely uninfluenced by choice of scale, although precise locations are much less stable. These results must be tentative, because they do not allow for housing circumstance, the subject of Chapter 8.

Chapter 8: The Household Distribution of Income Adjusted for Housing Circumstances

Chapter 8 looks at the location of socioeconomic groups in the household distribution if allowance is made for differing housing circumstances. It finds
– households with children tend to be at the bottom of the distribution, even lower than retired households. Households with working adults tend to be at the top of the distribution.
– men tend to be higher in the household distribution than women (although there is little difference between male and female children).
– the average ranking by age from bottom to top is children, the retired, young adults, middle working age adults, older working age adults.
– European/Pakeha are on average the highest ranked ethnic group, with Maori and then Pacific Island ones below. Other ethnicities at the top of the income distribution rank just above Maori, but at the bottom they rank below Pacific Islanders (presumably reflecting the heterogeneity of this group).
– rent free and owned without mortgage are the high ranked housing tenures, with renting below and owned with mortgage between.

The effect of the housing adjustment is to increase the dispersion in the household income distribution – that is those on higher incomes also tend to have more favourable housing circumstances, so the gap between their adjusted incomes and those at the bottom are even greater than the gap where there is no adjustment. Adjustment also raised the relative ranking of the elderly, because they are more likely to own their housing without a mortgage.

Adjusting for housing also reduces the proportion below the poverty line. This is because average housing circumstances are superior to those who rent. However, the poverty incidence is higher for those who lived in housing which is owned with a mortgage. If the case of the Royal Commission on Social Security’s Benefit Datum line the proportion of the population below the poverty line reduces from 17.3 percent to 14.2 percent.

Chapter 9: The Location of Health Status in the Income Distribution

Chapter 9 confirms that poor health is associated with low incomes, but shows that for the population as a whole the story is complicated by the interaction between age and income. Age is a much stronger predictor of poor health, and because the age groups are not spread evenly through the income distribution, the pattern of low incomes being associated with poor health gets distorted.

Sick children, in particular, are more concentrated in households with incomes below the poverty line (however defined).