This rental bond data provides information about the activity level in the housing rental market since January 1993. By comparison, the market rent online tool provides rental information for the previous six months.
This data was previously published to the Ministry of Business, Innovation and Employment website.
About the data
The files below are for private bonds, starting from January 1993. 'Private' means private sector landlords.
This data comes from our tenancy bond database, which records all new rental bonds that are lodged with us each month.
Make sure you always use the latest file available. This is because slight delays between a bond being lodged and the details being recorded in the database can cause figures for the latest month to change the next month.
Rental bond data, January 1993 - December 2020
Last updated 13 January 2021.
We update the data in these files every month:
- By territorial authority, January 1993 - December 2020 [CSV, 1.5 MB]
- By region, January 1993 - December 2020 [CSV, 552 KB]
We update the data in this file every quarter:
The historical rental bond data uses the SA2-2019 area definitions from Stats NZ:
Analytical note: medians and quartiles for rent data
Median and quartile data for rents are often requested in order to get an understanding of the distribution of rents in a region. This is especially important for social housing, as social housing is not typically targeted at average households.
However, rents tend to cluster at round numbers – a weekly rent of $300 is much more common than a rent of $297.50. This has an unfortunate effect on median and quartile measures (which are based on actual values from the data), as they tend to plateau for months at a time, before jumping up by $10 or $20. This can make analysing time series of medians and quartiles difficult.
For this reason, we have developed alternative measures for use with rent data:
- Geometric mean (replacing median): The geometric mean is calculated by multiplying n values together and taking the nth root of the result. When a variable is log-normally distributed (a common distribution for variables than must be greater than 0) the geometric mean will closely approximate the median.
- Synthetic Quartiles (replacing quartiles): The synthetic quartiles are designed to find the 25th percentile (for the lower quartile) and 75th percentile (for the upper quartile) of a set of data, assuming the data is lognormally distributed. The mean and variance of the data are not assumed, but instead are calculated. This approach is consistent with using the geometric mean to approximate the median.
Using data under Creative Commons
We're making this raw data available under a Creative Commons licence. This means you can use the data free of charge to perform your own analysis, as long as you credit us ('The Ministry of Business, Innovation and Employment') as the source of the data.
If you have any questions, comments or requests, please contact us.
This work is licensed under a Creative Commons Attribution 3.0 New Zealand License.(external link)