3 Impact of the factors of demand
Compared to the factors of housing supply, the studies of the factors of housing demand in New Zealand have been limited.56 This is partly because the factors of housing demand have wider economic impacts, beyond the housing market. For example, a change in interest rate affects all other economic activities, as well as the housing market. Given the wide impact of the factors of demand, reaching causal inference about their impact is technically difficult.
Demand for housing depends on a range of factors, including affordability limit, location of jobs and preferences. The policy instruments that affect the factors of demand mostly affect a household’s serviceability limit, which has wider distributional effects on different income groups and different type of borrowers (first home buyers, owner-occupiers and investors). We review the factor of demand in different sections of this section.
The factors of demand, particularly income and population growth, are the drivers of both higher house prices and economic growth. A higher demand can be associated with a higher housing supply and lead to economic growth. If demand is not met by supply, then it is possible to either dampen the demand using macroprudential policy (to avoid higher HPG) or to allow the market to clear – i.e. let the house prices to increase until nobody can afford to pay a higher price. The latter solution is associated with increased inequality and negative economic and social outcomes.
In the short term, HPG can be controlled using monetary and macroprudential policies. This comes at a cost to some community groups and eventually a loss to the economy. Also, as discussed in the literature, and based on Macroeconomics theory, macroprudential policies take time to affect the market. In the case of multiple macroprudential policies, and with rapid changes in the economy, there is a risk that the lag associated with policies leads to unintended outcomes, such as dampening impacts on the construction sector and the economy.
3.1 Affordability
Description
Affordability is a complex notion. In many studies, housing affordability is considered as an output, driven by factors of demand and supply. Since the focus of our review is on HPG, we need to clarify the difference between HPG and affordability. A higher affordability level is usually associated with higher house prices, leading to HPG. Therefore, we consider affordability as an input to HPG.57
Summary of literature review
A wide range of studies use some indicators as measures of housing affordability. Most common measures of housing affordability are house prices as a ratio of income and rental yields. These indicators provide useful high-level description of the housing affordability issue that can be used for a general policy discussion. However, given their simplicity, these indicators are not useful for providing information about the drivers of housing affordability. Any use of these indicators simple trackable policy target needs to be with care – particularly because the distributional impacts of housing policies and their impacts on different income groups are not captured using these measures.
Uncertainty assessment: Households’ higher mortgage serviceability has led to increase in house prices.
Comparisons between house prices and household income has often been used as a measure of housing affordability. Figure 26 shows the growth in household income and house prices for the 1971-2021 period. Accordingly, house prices outpaced household income growth significantly after the 1991-1992 recession.
Figure 26 Real household income Period: 1971-2021; (1971=100)
Source: Bank for International Settlements, Statistics NZ, Principal Economics analysis.
Note: We source s.a. real property price index from The Bank of International Settlements. Real household income is sourced from Data 1850 up to 2017 with additional years sourced from the Statistics NZ Household Labour Force Survey adjusted for inflation using the CPI from Statistics NZ and indexed to match the historical series. We annualised real house prices based on the average quarterly index value to match our real income data. We rebase all figures to 1971 = 100. We highlight notable recessionary periods in New Zealand identified by Reddell et al., (2008). These include the First Oil Price Shock (1974 – 1977), The Second Oil Price Shock (1979 – 1982), The 91 – 92 Recession, (attributable to the 1987 share market crash, subsequent monetary responses and impacts of the first Gulf War - 1991 – 1992), The Asian Crisis and drought (1997 – 1999), we add COVID-19 as an additional recessionary period (2020-).
Robinson et al. (2006) discussed the concept of affordability and used descriptive statistics of a range of measures to examine trends in affordability over time. Their results suggest no long-term trend and the existence of a cycle. They refer to other studies’ use benchmarks for housing affordability, e.g., some studies consider any proportion over 30 percent of total income allocated to housing costs as unaffordable (Bull, 2003), while others consider a house price to household income ratio of over 5.1 as unaffordable (Urban Reform Institute, 2021). Robinson et al. conclude that “using some sort of normative basis for definition and measurement is inevitable for any analysis into housing affordability.”58 We suggest that for a robust discussion of housing affordability, it is important to have a better understanding of the information contained in housing affordability measures.
Grimes & Aitken (2006) studied the impact of demand factors on house prices. They use a multivariate panel structure to estimate the long-run and short-run impacts on house prices. Their results suggest that a 1 percent increase in real incomes raises real house prices by a minimum of 0.25 percent. This provides an understanding of the impact of household income on household affordability and how that affects HPG.
Torshizian & Meade (2020) estimated the price elasticity of housing, utility, food and petrol across New Zealand regions, using Almost Ideal Demand System (AIDS).59 Their results suggest that the expenditure elasticity of housing is 2.1, 1.9 and 1.8 for large, medium and small urban areas, respectively. This result suggests that housing is considered a luxury product that, with increases in its price, the share of extra consumption expenditure on it raises. The result of this study is consistent with the findings of Khaled (2005), who estimated the expenditure elasticity of housing being equal to 1.6.
The factors of affordability include mortgage rates, household income level, the required deposit ratio (loan to value ratio), the mortgage term, and their wealth levels. To understand the impact of each of these factors, a model of housing affordability needs to use them in conjunction with the number of households and the available stock of housing. In the following sections, we discuss the other factors of housing affordability.
3.2 Monetary policy and mortgage rates
Description
The Reserve Bank of New Zealand’s (RBNZ) tools with an impact on house prices consists of the Official Cash Rate (OCR) and macro-prudential policy.60 The OCR affects HPG through its impact on mortgage rates. The common macro-prudential policies include deposit ratio and debt to income ratio. In the short term, housing supply is fixed (because of the lag between the increase in demand and the response from developers) and the main policy instrument for affecting house prices is the monetary and macroprudential policies.
Summary of the literature review
A lower mortgage rate leads to higher serviceability limits. In the long-term61, if the number of supplied houses is limited, then an increase in the serviceability limit leads to an increase in house prices. It is also clear that the macro-prudential policies affect HPG, however, the distributional impacts of macro-prudential policies have not been discussed in the literature.
The record low mortgage rates post-GFC have led to increased house prices. The OCR, however, has a wide impact on different sectors of the economy, and is not considered as an appropriate tool for controlling house prices because of the wider impacts on other economic activities. The available literature does not provide a comprehensive framework for the assessment of the relative impact of factors of HPG, and often counts lower interest rate as the reason for HPG.
The literature on macro-prudential policies is limited. This is partly because of lack of data on household wealth in New Zealand. Another reason is that the link between macroeconomic models and the models of housing market has been weak.
Uncertainty assessment: a lower mortgage rate leads to HPG.
A range of studies suggest lower interest rates result in an increase in total housing demand through increased ability to service higher debt levels. Macroprudential policies control the (deposit) requirements for having the credit and lead to a reduction in the number of people who can enter the market (Denne et al., 2016; Parker, 2015; Torshizian, 2016).
Koveshnikova (2017) studied the impact of macroeconomic factors on house prices in New Zealand. She uses residential property price data covering the 2003Q4-2017Q1 period and an Error Correction Model (ECM). Her results suggest that mortgage rates have a positive impact on house prices pre-GFC. After the GFC, a lower mortgage rate is associated with a higher house price.62 Over the whole period, a 1 percent increase in mortgage interest rate is associated with 0.02 percent lower house prices. The study investigated the impacts at regional levels and concluded that macroeconomic factors have significant distributional effects. Also, her investigation of the spill-over effects suggests that higher house prices in Auckland have immediate spill-over effects on house prices in Wellington and Hamilton.
Grimes & Aitken (2004) used a macroeconomic model to estimate the impact of macroeconomic shocks on house prices. Their results suggest that a 1 percent increase in user cost of capital, through increased interest rates, leads to decreases in real house prices by 0.8 percent. An interesting result of their study is that a change in commodity prices in a region leads to lower house prices in that area. They use an example of a forestry-oriented area (e.g. South Waikato) and explain that a decrease in forestry prices is associated with lower house prices in that area. This is driven by the lower income of households in that area and therefore lower serviceability limit for buying houses.
Fraser & McAlevey (2015)use a macroeconomic (SVAR) model63 of the New Zealand economy to investigate the impact of the factors of demand. They found a 1 percent increase in interest rates leads to a maximum fall of 1.56 percent in national house prices. The study is using a stylised model, which is limited in the number of parameters included and may not capture some of the impacts from other related factors.
The Productivity Commission (2012)’s housing affordability inquiry discusses that the easier credit conditions for housing loans and particularly deregulation in early 1990 has had an inflationary effect on housing. This can be mitigated using macroprudential policies.
Shi (2009) studies the impact of mortgage rates on house prices during the period 1999-2009. His results suggest that real fixed interest rates are positively related to the real housing price, after controlling for other economic conditions such as the effect of real rental rates, unemployment rates, and housing credit. Therefore, increases in the interest rate did not lead to lower real housing price during the 1999-2009 period. This result is consistent with Koveshnikova (2017)’s results. Shi’s results suggest that when interest rates increase, people favour fixed rates against the floating rate, particularly as floating rates are likely to move more than fixed rates, which in New Zealand has often resulted in the yield curve becoming negative. Shi et al. (2013)’s study of the impact of interest rates suggest that a 1 percent increase in the real floating-rate will increase house prices by less than 1 percent. By contrast, the same change in the real 1-year fixed rate results in house price growth by 6 percent.
Thorns (2009) investigated the impact of housing booms and changes to the affordability levels of New Zealanders in 1991 and 2008. His results suggest that during the 2002-2005 house price boom, the OCR has had limited effectiveness in moderating housing prices, as many people were on 2- to 4-year fixed rate mortgages. The slackening of demand in the latter part of 2007 and into early 2008 was in part due to the refinancing of fixed rate mortgages; thus finally the Reserve Bank strategy had an impact. This suggests the existence of a time lag for the impact of monetary policy to be felt in the housing market.
Yang & Rehm (2021) studied the relationship between house prices and speculation behaviour in Auckland.64 Their results suggest that interest rates are an important determinant of speculative activities with the use of financing. Their results demonstrate a vicious cycle of leveraged investors’ speculative behaviour increasing Auckland house prices which in turn spurs property speculation.
Murphy (2011) investigates the response to the GFC by the Australian and New Zealand financial sectors and the impact of that on the housing market. He highlights that the New Zealand policy and regulatory responses to the GFC have centred on supporting the banks and moderating the adverse consequences of a housing downturn.
As discussed above, the impact of monetary policy highly depends on the other (supply) factors. Parker (2021) provides a comprehensive (theoretical) economic framework for the assessment of the impact of a competitive land market on house prices.65 The results of his investigation of the impact of an increase in interest rates on house rents, house prices, land prices and household wellbeing (utility) are illustrated in Table 6. An increase in interest rate is associated with no change in house prices in a competitive market, lower house prices in a moderately uncompetitive market, and significantly lower house prices in extremely uncompetitive land markets.
Table 6 Direction of impact of interest rates on key variables
| Urban land market | House rents | House prices | Land prices | Household utility |
|---|---|---|---|---|
| Competitive | + + | 0 | 0 | - - |
| Initially uncompetitive* | + + | - | - | - |
| Moderately uncompetitive | + | - | - | - |
| Extremely uncompetitive | 0 | - - | - - | 0 |
Source: (Parker, 2021)
Armstrong et al. (2019) used a DiD method to test the impacts of the Loan to Value Restrictions (LVR) based on newly built dwellings (that were exempt from the LVR restrictions). Their study used unit-record property sales data, with controls for regional effects, buyer type (investor or first home buyer), and whether the purchase was financed by a mortgage. Additional control variables such as interest rates, building consents and regional net migration were used for robustness tests. Given the changes in LVR policies the authors investigate how changes have impacted house prices in each iteration. Nationally the policy changes led to a fall in house price inflation of 4.4 percentage points, with the effects being less significant in Auckland. The authors suggest that, given past and expected house price growth, buyers can revalue their existing home equity and take out new loans counteracting the impact of the restrictions. Overall, the impacts of the policy appear to depend on house price inflation, if house prices increase quickly, the effect of the restrictions disappear faster.
3.3 Population and migration
Description
Population growth, driven by internal and external migration in addition to the birth and death rates, increases demand for housing and leads to HPG, when the housing supply is inelastic (and in the short term).
Summary of the literature
The pull and push factors of migration include the attractiveness of the job market, the availability of amenities and facilities and the cost of living – which is highly interrelated with housing costs. This cycle in factors of migration and house price growth leads to complexities in causal inference about the impact of population growth on house prices. This has been reflected in our summary of the estimated impact of increases in population on house prices (ranging between 0.02 and 12 percent).
Uncertainty assessment: Strong migration has led to HPG.
Badcock (2004) discussed the impact of the deregulation of New Zealand’s finance sector in the mid-1980s, suggesting that the Government was taken a little by surprise at the size of the net migration ‘spike’ in the 12 months to August 2003 (caused by a combination of short-stay foreign students and fewer New Zealanders leaving for overseas). Because the supply response is always lagged in the property development and home building sector, pent up demand pushed up house prices.
PCE (2019) refers to different factors of demand and highlights that the (per capita) net migration to New Zealand during 2000 and 2019 was around 3 times higher than comparable developed countries. Koveshnikova (2017) studied the impact of macroeconomic factors on house prices in New Zealand. Her results suggest that, over the period of their study, a 1 percent increase in population is associated with 0.22 percent increase in house prices.
Johnson et al (2018) reviewed the factors of house prices in New Zealand. They discussed that an increase in net migration leads to a higher housing demand but if supply is responsive this will not affect house prices.
Coleman & Landon-Lane (2007) studied the link between migration and New Zealand housing market using structural vector autoregressive (VAR) models at the national level. Their results suggest that a 1 percent migration flow is associated with a price increase of between 8 and 12 percent.
Stillman & Maré (2008) assessed the impact of migration inflow on house prices between 1986 and 2006. After controlling for observable differences in the socio-demographic characteristics of areas, they found no evidence that a higher share of new (international) immigrants in an area is associated with higher house prices. Their results suggest that a 1 percent increase in an area’s population is associated with a 0.2 to 0.5 percent increase in local housing prices. Higher inflows of returning Kiwis associated with a 6 to 9 percent increase in house prices.
Maré et al (2009) studied the impact of increases in employment on house prices. They used a VAR model on a panel of regions across New Zealand. Their results suggest a significant 6 percent increase in prices in response to a 1 percent increase in employment. However, their result at the regional level is not significant.66 (Ge, 2009) investigated the determinants of house prices in New Zealand between 1980 and 2007. Her results suggest that a 1 percent increase in net migration is associated with approximated 10 percent increase in house prices.
Chanpiwat (2013) examined the response of New Zealand housing markets to immigration shocks. He used migration and census data between 1996 and 2011. His results suggest that a 1 percent increase in external migration raised house prices by 7.5 percent (at a national level).
McDonald (2013) assessed the impact of migration on house prices in New Zealand. His results suggest that a 1 percent population growth is associated with an 8 percent increase in house price over the following three years and an additional house is built for every 6 migrants. An interesting result is that a 1000-person increase in monthly arrivals raises real house prices by 4 percent, whereas a 1000-person fall in monthly departures increases real house prices by only 2 percent.
Hyslop et al. (2019) studied the impact of population on house prices. They used New Zealand data for the 1986-2019 period. Their results suggest that a 1 percent increase in population raises house prices by 4 to 6.5 percent. They result shows that an increase in arrival of international migrants in an area does not affect house prices significantly. Their results also suggest that the housing demand in long-term is inelastic (their estimated price elasticity of demand is equal to -0.3).
Nunns (2019) studied the socioeconomic impacts of the rising house prices in New Zealand.67 His results suggest that a 1 percent increase in regional population leads to an increase in local house prices by a factor of between 1.6 to 2.7 percent (and is associated with increases in local rents by a factor of between 1.5 and 2.1 percent). Nunns argues that in a perfectly mobile labour market, reducing land distortions to zero leads to an increase of the output per worker by 0.9 percent, which raises New Zealand GDP by up to 7.7 percent. His results for a scenario that excludes trans-Tasman migration and focuses on redistribution of labour across New Zealand regions, suggests that reducing land distortions to zero leads to an increase in the output per worker by 0.8 percent and leads to a similar size (0.8 percent) increase in GDP. Further investigation of the channels of impact and the potential reasons for the estimated significant effects on GDP will be required for improved understanding of the GDP impacts of lower land distortions through improved labour outputs resulted from migration policies.
Table 7 Price response to a 1 percent increase in population
| Study | Price elasticity (%) | Data coverage |
|---|---|---|
| Coleman and Landon-Lane 2007 | 8-12 | 1962-1982; 1991-2006 |
| Stillman and Maré 2008 | 0.2-0.5 | Census and Quotable Value New Zealand and rent data 1986-2006 |
| Maré, Grimes, and Morten 2009 | 6 | Household Labour Force Survey (HLFS) 1989-2006 |
| Chanpiwat, 2013 | 7.5 | Migration and census data 1996-2011 |
| McDonald 2013 | 10 | 1990-2013 |
| Koveshnikova, 2017 | 0.022 (short term – 3 months) | 2003-2017 |
| Hyslop et al., 2019 | 4-6.5 | Census 1986-2013 |
| Nunns 2019 | 1.6-2.7 | regional wages, employment, and house prices 2000-2016 |
Source: Principal Economics, 2021
Figure 27 shows the net Permanent and Long Term (PLT) arrivals over the 1983 - 2018 period. Accordingly, the number of arrivals increased during the boom periods with average quarterly permanent long-term migration averaging 10,395 over the 2011-2018 period, compared to an average of 1,500 people over the earlier period of 1983 - 2010.
Figure 27 Net migration and HPG
Source: Bank for International Settlements, Statistics NZ, Principal Economics analysis.
Note: We source s.a. real property price index from The Bank of International Settlements and Net permanent and long-term arrivals from Statistics NZ. We calculate year-on-year annual percentage growth for the real property price index to determine house price inflation. Permanent and long-term’ departures and net migration are unavailable from November 2018, because of the removal of the departure card. We have omitted estimates for migration post November 2018 given the significant differences in measurement. We highlight notable recessionary periods in New Zealand identified by Reddell et al., (2008). These include the First Oil Price Shock (1974 – 1977), The Second Oil Price Shock (1979 – 1982), The 91 – 92 Recession, (attributable to the 1987 share market crash, subsequent monetary responses and impacts of the first Gulf War - 1991 – 1992), The Asian Crisis and drought (1997 – 1999), we add COVID-19 as an additional recessionary period (2020-).
3.4 Household size
Description
The number of dwellings required for accommodating the population depends on the size of households and the acceptable level of household crowding.68 This has been reflected in the price of houses. Some preferences for size (and other features) of housing may not be captured in prices. A policy targeting the wellbeing of New Zealand population, needs to account for the potential unrevealed preferences of population for the housing outcomes.
Summary of literature review
The literature refers to the decrease in the size of households and the move towards smaller dwellings. It is not clear if the zoning regulations have accounted for the changes in preferences and composition of households over time and allow for the right size of the new dwellings in the plans. A mismatch between demand and supply may lead to higher house prices.
Uncertainty assessment: A decrease in the size of households leads to higher house prices when the supply is inelastic.
The Productivity Commission’s (2012) housing affordability inquiry suggests that changes to demographic and family structures have led to changes in household formation and changes in housing affordability. Denne et al. (2016) refer to the impact of household formation on the demand side of housing, and highlight the importance of the changing demographic on house prices.
Gaynor (1999, cited in Badcock, 2004) highlighted the role of household size in the number of dwellings required for accommodating households. Badcock (2004) suggested that, with a drop in the average size of New Zealand households from 3 in 1981 to 2.7 in 2001, there is a need for 150,000 additional dwellings (this is probably based on an assumption of a population of 4 million).
Stats NZ (2020) described the changes in households and housing in New Zealand using Stats NZ data. Based on Stats NZ projections, the household size is expected to decrease from 2.6 in 2013 to 2.5 in 2038. This reflects the increases in the number of one-person households. In addition to the changes in households’ size, the composition and features of households are changing too. The size of houses in New Zealand has increase from 135 sqm in 1991 to 200 sqm in 2010. Stats NZ suggest that, with the decreases in the size of households, the demand for larger properties, with more bedrooms, may decrease in the future.
Morrison & Torshizian (2017) discussed the role of demographics, and the way housing space consumption responds to local housing market characteristics. Using Census data from 1991 to 2013, they show that the number of people per dwelling has increased in dense areas of Auckland. Anecdotally, they discuss that with the rising housing costs a lot of parents are now providing housing within their own home to their own adult children. Their study is a descriptive study and does not account for the impact of other relevant factors.
Torshizian (2017) studied the impact of household crowding and population density on residential satisfaction. After accounting for a wide range of factors, his results suggest that household crowding’s impact on residents’ satisfaction is affected by their social norms. Torshizian discusses that house prices do not hold information about unrevealed preferences. Therefore, a policy that aims to improve wellbeing of New Zealand population, needs to investigate the housing features that New Zealand residents will value most, including the level of crowding, and plan for providing houses with those features.
3.5 Availability of finance
The availability of capital in the market and its impact on housing prices has been discussed in a very few studies. The availability of finance is associated with speculative purchases and house price bubbles. Our review of the available literature does not provide us with robust understanding of the impact of availability of finance in New Zealand.
Uncertainty assessment: high access to finances has led to increases in house prices due to lack of supply responsiveness.
Badcock (2004) discussed the impact of the deregulation of New Zealand’s finance sector in the mid-1980s. Accordingly, with better access of New Zealand banks to overseas credit, residential mortgage lending jumped from 13.6 to 42.8 percent of total bank lending between 1984 and 1999. In the year ending 30 September 2003, 99.2 percent of total new lending was on housing loans – and only 0.8 percent for all other areas, such as transport, tourism and agriculture.
Greenaway-Mcgrevy & Phillips (2016) investigated the existence of a house price bubble in Auckland using house price data for 72 territorial authorities across New Zealand between 1993 and 2014. To identify the periods of house price bubble, they used measures of price to rent and price to income ratios.69 Their results suggest that there was a housing bubble in Auckland between 2003 and 2008 and the latest bubble has started since 2013 and had not collapsed until the end of their data in December 2014.
Murphy (2011) discusses the impact of the GFC on the Australian and New Zealand housing markets. He mentioned banks’ lack of access to international funds as one of the challenges that altered the New Zealand mortgage market.
Bassett et al. (2013) discussed the housing affordability problem in New Zealand looking at descriptive statistics since early 1990s. They highlighted that the investment in housing has risen at the expense of investment in other sectors of the economy. This is consistent with Badcock (2014). NZIER (2014a) discusses that increased household indebtedness has at least partly contributed to increasing price of houses.
3.6 Tax policy, housing subsidies and other interventions
Description
Taxes are considered as a solution to decrease speculative behaviour and to raise funds for infrastructure investments. There is a range of tax policies, including development contributions, financial contributions, and betterment taxes. Both taxes and subsidies (depending on their type) are associated with distributional effects across different income groups, types of buyers, and regions.
Summary of the literature
The available literature does not provide enough evidence-based analysis of the likely impact of the tax and subsidy policies. This is partly due to confidentiality of data and partly because of political complexities involved in a tax policy. Generally, there is high agreement that a tax policy leads to lower speculation incentives and therefore lower HPG. The size of the impact of a tax policy on HPG is unclear.
Uncertainty assessment: A betterment tax leads to lower house prices.
Yang & Rehm (2021) studied the relationship between house prices and speculation behaviour in Auckland.70 Their results demonstrate a vicious cycle of leveraged investors’ speculative behaviour increasing Auckland house prices which in turn spurs property speculation.
Grimes & Coleman (2009) discuss that a betterment tax can be used for funding public infrastructure under certain circumstances. They use a theoretical framework and show that the full costs of a new infrastructure investment can be funded using an incremental land tax that only taxes the uplift in the values caused by the infrastructure investment. That study does not provide data analysis in support of the theory. In practice, using any type of land tax for funding infrastructure is difficult due to political sensitivities.
Bassett et al. (2013) reviewed New Zealand’s housing affordability problem and the development of housing in New Zealand since the early 1900s. They note that in June 2003 nearly 252,000 people receive some form of housing supplement. However, the effects of this subsidy are noted as having little effect to the adding to the housing stock with its impacts being absorbed into rental prices.
Price (2014) finds that house price inflation is 3.3 percent lower than it could have been following the introduction of LVR restrictions as at March 2014. The author uses seasonally adjusted monthly data from January 1992 to April 2013 to construct a model of the counterfactual to determine these results. Variables used include net migration (disaggregated by New Zealand and non-New Zealand citizens), net experienced domestic trading activity, two-year fixed mortgage rates, number of house sales, median days to sell a house, residential consent issuance, REINZ stratified house price index and household credit. The counterfactual is constructed as a forecast starting in September 2013.
Armstrong et al. (2019) used a DiD71 method to test the impacts of the Loan to Value Restrictions (LVR) based on newly built dwellings (that were exempt from the LVR restrictions). They assessed the impact of the “Bright-Line” tax72 and residential property investment loans being given a separate asset class with higher capital requirements, which were introduced in November 2015. Their results suggest that the impact of the “Bright-Line” Tax was not significant in Auckland. They suggest that the reason for no impact from the “Bright-Line” Tax was that Auckland investors have enough housing equity, which allows them to obtain leverage on their existing houses to finance new purchases.
The New Zealand Tax Working Group recommended a broad extension of taxation of capital gains. This included all types of land and improvements (excluding the family home), shares, intangible property, and business assets New Zealand Tax Working Group (2019). Specific to housing, the group recommended that consideration for tax on vacant residential land best levied as local taxes. The Tax Working Group report does not provide evidence on the impact of the capital gain tax on the housing market and the rest of the economy. The proposed capital gain tax was rejected by the Government and New Zealand remains without a comprehensive capital gains tax, and with no prospect of one in the near future.
This is also noted by Simon (2019)↩︎
The factors of house price growth are so closely related that any robust distinction between them needs extensive theoretical discussions, supported with evidence. This is out of the scope of our report, but is an important topic for a future study↩︎
Normative definition of housing features is further discussed by (Torshizian, 2017)↩︎
AIDS is a consumer demand model used primarily by economists to study consumer behaviour↩︎
For definition, see Macro-prudential policy FAQs - Reserve Bank of New Zealand (rbnz.govt.nz)↩︎
Long term is defined as the period that the housing supply needs to adjust and respond to the changes in demand↩︎
In the short run before the crisis, mortgage rates were positively related to property indices. After the crisis most regions 2-year fixed mortgage rate coefficients had the expected negative sign and were statistically negative. Indicating that lowering real interest rates is associated with a rising house price↩︎
The study uses a structural auto-regressive method. The core model does not include construction costs employment and income↩︎
They used a VECM model. Their data covers the 2003-2016 period and includes Auckland house price index, metric of leveraged speculation, metric of unleveraged speculation, effective mortgage interest rate, the number of building consent issued in Auckland and net permanent and long-term immigrants entered into New Zealand↩︎
His framework is based on a well-known economic modelling framework – AMM (Alonso-Muth-Mills model), which was widely used by a range of previous studies in New Zealand↩︎
One explanation that the authors suggested for their regional results is that the house prices and employment may be cointegrated↩︎
The author developed a spatial equilibrium model of household location choice based on the Rosen-Roback framework. The model consists of a productions sector, workers and the housing developers. This modelling approach has been widely used before in the urban economics literature↩︎
There are a range of household crowding measures. An objective measure of crowding is the people per bedroom measure (PPBR), which is the number of people living in each bedroom. The Canadian National Occupation Standard (CNOS) is a measure of crowding that accounts for cultural aspects and the characteristics of the household. (Torshizian & Grimes, 2020) discuss the importance of using correct measures of household crowding↩︎
There are different measures of affordability and price distortion available. For more information see (Murphy, 2014), for example↩︎
They used a VECM model. Their data covers the 2003-2016 period and includes Auckland house price index, metric of leveraged speculation, metric of unleveraged speculation, effective mortgage interest rate, the number of building consent issued in Auckland and net permanent and long-term immigrants entered into New Zealand↩︎
Difference in Difference method↩︎
The bright-line test is the rule that determines whether a person who sells a residential property has to pay tax on the money they make in the deal↩︎