Do Local Property Taxes Affect New Building Development? Results from a Quasi-Natural Experiment in New Zealand

Abstract

We utilise a quasi-natural experiment in local property tax reform arising from a compulsory amalgamation of several local councils in 2010 in Auckland, New Zealand, to form a unitary local authority. The reform involved changes in property taxes (known as ‘Rates’ in New Zealand) including a shift in the local tax base from land-value to capital-value in some of the former councils; changes in relative levels of Rates across former councils; and changes in levels of a separate tax (Development Contributions) levied on new building. These exogenously imposed reforms enable us to test several hypotheses related to the effects on property development of these tax switches using a difference-in-difference approach, controlling for other influences. We find support for tax effects on building alterations but no evidence of effects on new building development after amalgamation. Our dataset covers only two post-amalgamation years, and we speculate that this apparent difference may arise from greater flexibility of building alterations to respond quickly compared with new developments.

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Notes

  1. 1.

    Prior to an earlier local government reorganization in 1989, the region comprised 44 local authorities (Grimes 2011).

  2. 2.

    Whenever Rates is referred to with an upper case ‘R’ the meaning is the property tax; when a lower case ‘r’ is used (e.g. tax rate) the standard meaning of the word is intended.

  3. 3.

    Development contributions are generally levied on alterations that could increase the number of households in a dwelling (e.g. if a new kitchen is added) but not for other forms of alterations.

  4. 4.

    Some councils levied infrastructure fees as well as DCs; we have no data on these contributions.

  5. 5.

    TLAs are not, however, simple sub-divisions of regional councils; for example, one TLA may form part of more than one region.

  6. 6.

    The smallest geographic disaggregation in administrative data is the ‘meshblock’. There are around 11,700 meshblocks in the Auckland region with around 30 meshblocks per AU on average. However, data at this disaggregation are not available (or do not differ across meshblocks within an AU) for most of the variables required for our analysis.

  7. 7.

    Some TLAs used properties’ so-called ‘annual value’ as the tax base, but since this was set at 5% of the capital-value it can be treated identically to a capital-value tax base.

  8. 8.

    Gemmell et al. (2016) also presents more detailed descriptive statistics for some of our variables.

  9. 9.

    Papakura is omitted from Fig. 2 owing to unavailability of water rates data. Data on Papakura in Fig. 3 should be treated with caution given limited available information for this Council, and the much lower value of the sum of the components shown in Figs. 2 and 3. Papakura appears to have no ‘Reserves’ contributions.

  10. 10.

    The Figure amalgamates some small Rates components, such as the ‘Regional Biosecurity Rate’ (average value across TLAs: $6.70) and the ‘Rugby World Cup Levy’ ($4.00) payable only in Waitakere.

  11. 11.

    With the exception of Franklin (which has a longer post-amalgamation transition period), DCs in the remaining 5 TLAs with full data, were all within $1000 of the TLA-6 average.

  12. 12.

    DC is missing for a small number of AUs; we include a DC09_missing binary variable to account for DCs in these AUs.

  13. 13.

    Lagged variables use data either from the 2006 census, with suffix 06, or from 2008 to 09 (2009 Rates data), with suffix ‘09’. Rates (and DCs) are set annually on a July (q3) – June (q2) basis. Hence the Rates year 2009 is equal to the Rates set for q3 2008 – q2 2009. Building consent applications happen throughout the year; in allocating BC data to years for regressions we adopt the same ‘Rating years’.

  14. 14.

    Since this is a cross section (difference) regression, there are no time fixed effects, while Area Unit fixed effects are effectively differenced out.

  15. 15.

    We do not include separate regressions for housing types (houses, apartments etc.) again because there are insufficient building consents within most AUs for apartments in most years of our data.

  16. 16.

    Another statistical reason is that by examining differences in building consent variables and differences in independent variables, we remove common fixed effects that affect building consents similarly across all AUs, so reducing goodness of fit.

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Acknowledgements

We are grateful to the Lincoln Institute of Land Policy, especially Joan Youngman and Semida Munteanu, for their support of the project on which this paper is based: “Auckland Agglomeration: An Inquiry into the Impacts of Agglomeration, Development Contributions and Land Taxation on Rate and Density of Development”. Arthur Grimes also acknowledges support from the Building Better Homes, Towns and Cities National Science Challenge. We are grateful to a referee who provided several insightful suggestions, and to our research assistants – Marc Reinhardt, Yen Le and Loc Nguyen – for their inputs to the project.

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Appendices

Appendix 1: Calculation of Regression Analysis Variables

Population Density

AU land area is measured as square kilometres, obtained by adding Statistics New Zealand data on Meshblock land areas within each 2013 AU. Population estimates are from Statistics New Zealand, estimated 2009 population using 2015 boundaries and the 2013 Area Unit codes (all 2015 Meshblocks are in the same Area Units as the 2013 Area Units). Population Density PopDensit is then obtained as Area Unit i’s population divided by its respective land area:

$$ PopDen{s}_{it}=\frac{Po{p}_{it}}{LandAre{a}_i} $$

Dwellings per Area Unit

Dwellings data are obtained from the 2013 (Stats NZ) Census meshblock dataset for the Auckland Region, giving the 2013 Census number of occupied Dwellings, as well as mean number of bedrooms as reported in the 2013 census. We then calculate:

$$ \mathrm{Dwellings}=\mathrm{number}\ \mathrm{of}\ \mathrm{occupied}\ \mathrm{dwellings}\ \mathrm{per}\ \mathrm{Area}\ \mathrm{Unit}\ \mathrm{in}\ \mathrm{the}\ 2013\ \mathrm{census}\ \left(\mathrm{in}\ \mathrm{thousands}\right). $$

Population Weighted Average Rate

AKavRatet is the population-weighted average Rate across all (i = 1, …, N) Auckland Area Units.

$$ {AKavRate}_t=\sum \limits_{i=1}^N{w}_i{ATR}_{it} $$

where ATRit is Area Unit i average Rate in period t and wi is the population weight of Area Unit i which does not change over time. That is, \( {w}_i=\frac{1}{P} po{p}_i \), where P is the total population (sum of all populations of Area Units in the sample), popi is Area Unit i‘s population in 2009, and \( {\sum}_{i=1}^N{w}_i=1 \).

The average total Rate for each Area Unit is therefore the same for each Area Unit within a given TLA. Only the Area Units in our sample have been used to construct this population-weighted average Rate.

Definitions of all variables are given in Table 2.

Appendix 2

Table 4 Regression results for BC-NEW (for sample: AUs with BC-NEW > 5)

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Gemmell, N., Grimes, A. & Skidmore, M. Do Local Property Taxes Affect New Building Development? Results from a Quasi-Natural Experiment in New Zealand. J Real Estate Finan Econ 58, 310–333 (2019). https://doi.org/10.1007/s11146-017-9651-y

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Keywords

  • Property taxes
  • Land tax
  • Development contributions
  • Impact fees
  • Property development