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New Zealand Households and the 2008/09 Recession

3 Household types split by hard dimension

3.1 The hard dimensions

The hard dimensions we use to split the data are age, household ownership status, household structure, highest qualification and income quartile. Age refers to the age of the member of the household who earns the most; household ownership refers to whether the household is a renter, a mortgage holder (or owned outright) or 'other' (typically a trust type arrangement). [11] Qualification is a categorical variable, defined as the whether the highest qualified person in the household has no tertiary qualification, a bachelors degree or a higher post graduate degree. Household structure is defined by looking at the living status of the adults in the household - whether they are a couple, single or other, as well as whether there are children in the house. [12]

Finally the household is also assigned to an income quartile, based on its household equivalised income. The equivalised disposable income is the total income of a household, after tax, subsidies and other deductions, that is available for spending or saving, divided by the number of adult equivalent members. Younger household members are made equivalent to adults by weighting each according to their age. Disposable income is equivalised to allow for the tendency for household expenses to grow with household size but allow for the fact that children need fewer resources than adults, ie the growth is not linear. There are various ways to calculate equivalised disposable income (see Table A.1 in Appendix A), we have chosen to use the Square Root Scale. Table A.1 shows this approach assumes there are more economies of scale in households than other scales, meaning expenses grow by less as household size increases compared to other measures.

Table 3.1 gives the sample counts and population weights of households for the categories within each household type for both the 2006/07 and 2009/10 editions of HES. The use of population weights, according to Statistics N.Z. (2001), takes account of under-coverage in the survey of specified population groups. All our analysis is done by weighting the sample value of a variable by its population weight.

Table 3.1: Dimensions (weights and sample)
2006/07 2009/10
Household Type Category weight
('000)		 n weight
('000)		n
Home
Renting 477 760 572 1,025
Mortgage holders 902 1,491 807 1,640
Other 191 299 244 461
Qualification[13]
School or none 1,144 1,896 1,190 2,267
Bachelor degree 222 333 237 446
Post-graduate 185 291 180 375
Age
< 25 95 144 92 160
25-34 254 406 264 484
35-44 363 562 336641
45-54 316 524 344 631
55-64 233 348 254525
65+ 308 566 334 685
Income quartile
1 393 670 406 789
2 392 630 406 762
3 393 627 406 791
4 391 623 405 784
Household structure
Single, no children 344 646 355 649
Single, children 134 243 147 301
Couple, no children 413 714 422 913
Couple, children 487 692 491 908
Other, no children 98 112 107 172
Other, with children 94 143 101 183

Notes

  • [11] We looked at the demographic characteristics of those in the "other" household ownership status; they were generally older and had a diverse set of income sources (from investment etc) perhaps indicating a degree of financial knowledge/expertise hence our deduction that these are trust situations.
  • [12] In explaining the more a typical household structures (see Table 3.1), the "other with no children" category is more likely to be a flatting/house sharing arrangements and"other, with children" may be a boarding arrangement or multiple families in one house.
  • [13] There are some households that are not in any of these qualification categories as some qualifications are post school but not bachelor degrees (for example trade qualifications). The number of households in this category was small (5% of the sample).
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