Household spendingSales, trade-ins and refunds

Clothing Resales: what NZ households spend per week

Quick answer Stats NZ publishes clothing resales as a category of household spending, but too few surveyed households recorded any for the national figure to be reported at a sampling error under 30 per cent. The history below shows the direction, which is reliable even where the level is not.

Stats NZ publishes this category as Sales of clothing and footwear, within Sales, trade-ins and refunds. It is called Clothing Resales here because that is what it is, but every figure on this page is the official category.

What this category covers

Money coming into the household from selling clothing and footwear it already owned. Sales through an online marketplace, a social media selling group, a garage sale or a market stall, consignment through a second-hand or designer resale shop, and sales to a dealer. Refunds received on returned clothing are recorded here where they are not netted against the original purchase.

What it does not cover

Buying clothing, new or second-hand, is clothing. A refund on a returned item bought in the same period may be netted against the purchase rather than recorded here.

Those boundaries are set by the survey's own classification, not by us. They matter because a figure read against the wrong definition is worse than no figure: it looks precise and it answers a different question. If you are comparing your own spending against this page, check the exclusions above first.

How to read the figure

The survey records this as negative expenditure, because it is money received rather than spent, and the chart on this page shows the amount received. Under one household in a hundred records anything, so the level is not reliable, but the direction is: resale receipts have grown steadily across the six surveys, which is consistent with the growth of online resale.

Every survey year

The Household Economic Survey runs every three years. This is sales of clothing and footwear in each survey since 2007, for all New Zealand households. Amounts are money received by the household, which the survey records as negative expenditure.

The figures are in the money of each survey year itself, so comparing 2007 with 2023 compares two different dollars. There is no column restating them in current dollars, because the Consumers Price Index has no series matching sales, trade-ins and refunds: the CPI measures the prices of things bought, and this category is not a purchase of goods or services. Part of any rise below is inflation, and nothing here can tell you how much.

The reporting column is the share of surveyed households that recorded any spending in this category at all: the lower it is, the further the average sits from what a household that does spend here actually pays.

SurveyPublished per weekSampling errorHouseholds reportingChange
2007$0.10±83%0.3%
2010$0.10±90%0.4%0%
2013$0.10±76%0.6%0%
2016$0.20±87%0.6%+100%
2019$0.30±57%0.7%+50%
2023$0.50±55.9%0.7%+67%

Clothing Resales over time

Each bar is one survey, in the money of its own year. There is no CPI series that matches this category for every survey year, so the bars are not restated in today's dollars and part of any rise you see is inflation rather than a change in what households buy.

Clothing Resales per week by survey year (amounts received by the household)

The survey records this category as negative expenditure, because it is money coming into the household rather than going out. Bars show the amount received.

2007$0.10
2010$0.10
2013$0.10
2016$0.20
2019$0.30
2023$0.50

$0$0.81

The dark line with a cap at each end shows the sampling error Stats NZ publishes with that figure: the survey is confident the true value lies within it. A long line means a less certain number. Bars in a pale fill are survey years whose sampling error is above the level at which this site normally withholds a figure. They are drawn here because the direction of a series is worth seeing even where the level is not reliable enough to quote, and the table above gives the error on each one.

By household size

Household size explains more of the variation in most categories than anything else on this page.

Every figure in this breakdown has a sampling error too large to report reliably, so nothing is shown. That usually means few surveyed households reported spending in this category.

By region

The survey groups the country into five broad regions rather than cities, so Auckland is a region and Hamilton is part of the rest of the North Island.

Every figure in this breakdown has a sampling error too large to report reliably, so nothing is shown. That usually means few surveyed households reported spending in this category.

By tenure

Whether a household owns or rents correlates with age, income and household composition, so a difference here is not caused by tenure alone.

Every figure in this breakdown has a sampling error too large to report reliably, so nothing is shown. That usually means few surveyed households reported spending in this category.

By household income

Deciles split households into ten equal groups from lowest income to highest. A category that barely changes from decile 1 to decile 10 is close to a necessity.

Every figure in this breakdown has a sampling error too large to report reliably, so nothing is shown. That usually means few surveyed households reported spending in this category.

The rest of sales, trade-ins and refunds

These are the other components of the same top-level category. They add up, with this one, to the total on the Sales, trade-ins and refunds page.

Related calculators

Where these numbers come from

Every figure on this page is from the Stats NZ Household Economic Survey, retrieved through the Aotearoa Data Explorer, for survey years 2007 to 2023. Inflation adjustments use the Stats NZ Consumers Price Index to the 2026.06 quarter. Stats NZ data is used with attribution; the survey figures are theirs and the adjustments are ours.

Household Economic Survey figures are averages of weekly household expenditure and carry the sampling errors shown. They are averages rather than medians, so they are pulled upward by the highest spenders. Figures are rounded as published.