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Did the post-1986 decline in the homeownership rate benefit the New Zealand labour market? A spatial-econometric exploration

  • Spatial Analysis and Modeling
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Abstract

The proportion of New Zealand households living in owner-occupied dwellings has declined steadily since the early 1990s. The unemployment rate declined steadily as well, except for upward shifts due to the late 1990s Asian Financial Crisis and the Global Financial Crisis a decade later. Research initiated by Andrew Oswald in the 1990s posits that declining homeownership and declining unemployment are linked and that the causality runs from high homeownership leading to high unemployment. The international empirical evidence for this hypothesis is rather mixed. In this paper, we revisit the issue with New Zealand census data for commuting-defined labour market areas from 1986 until 2013. Allowing for spatial spillovers in our data, we apply a general nesting spatial-econometric model. We also consider the potentially different impacts of freehold and mortgaged homeownership. Generally, the evidence that a declining homeownership rate contributes to a lower unemployment rate is statistically fragile. When statistically significant, an increase of 1% in freehold ownership appears to increase a labour market area’s unemployment rate by between 0.07 and 0.2% points. The effect is relatively stronger in those labour market areas where freehold ownership is still relatively low.

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Notes

  1. Homeownership rates are only observed in the NZ Census of Population and Dwellings. The rates have been linearly interpolated for the intercensal periods. It should also be noted that there have been changes in the census questions on homeownership that may affect the intercensal comparison.

  2. A left-of-centre coalition government elected in October 2017 has implemented a range of policies to improve the supply, quality and affordability of housing.

  3. See e.g. https://www.statschat.org.nz/2016/02/24/home-ownership-comparisons/ on the relatively faster declining homeownership rates in Auckland. Morton et al. (2014) reports the growing mobility of young families there.

  4. Prior to the restructuring period many manufacturing products received effective rates of protection in excess of 100%. In addition, subsidization of manufacturing exports was also common. Following 1984, tariffs were removed so that the effective assistance rate for manufacturing fell from 30 to around 7% in 1996. Contemporaneously with the substantive removal of tariff protection, import licensing was removed from all but a few products (Chatterjee 1996, p 29).

  5. It should be noted than even the 2–3% unemployment prevailing at the start of the 1980s was a marked departure from the unemployment rates that had been experienced in the period of the so-called long boom (Marglin and Schor 1990) during which New Zealand’s unemployment rate is estimated to have remained below 1 percent until the final quarter of 1967 (Chappell 1994).

  6. A panel model with regional and time fixed effects was used for the “State-level US Unemployment Regressions with Housing Owner-Occupation as an Independent Variable, 1986–1995” and the “Region-level UK Unemployment Regressions with Proportion of Housing Privately Rented as an Independent Variable, 1973–1994”, Tables 4 and 5 respectively in Oswald (1996, pp 27–28).

  7. New Zealand is divided into 2020 area units. In urban areas these generally coincide with suburbs that contain a population of 3000–5000. In rural areas, area units cover larger areas but have much smaller populations.

  8. Some housing stock may be vacant. However, housing tenure (ownership or renting) is in our data only defined for all private dwellings that were occupied on census night. Hence the vacancy rate is by definition zero. It is in theory possible for renters to own a home that they did not occupy on census night (e.g. because it is an unoccupied vacation home or a home rented out to someone else) but the ownership rate in this paper is based on the tenure of the dwelling the person lives in during the night of the census. This is arguably the best measure of housing tenure in terms of a potential relationship with labour mobility.

  9. The range of variables that can be considered for our modelling is limited by the information included in the census and the extent to which this information is collected consistently across censuses. Except for the ownership variables, other variables included in this paper have been selected based on their robustness in our previous work (Cochrane and Poot 2007). Additionally we also considered household type (% single person households); ethnicity and the net migration rate. The latter variable is problematic due to its endogeneity and the use of the others did not improve the fit. These alternative results are available upon request from the authors. See also Cochrane and Poot (2007) for including these variables in non-spatial estimation. By adopting panel estimation with fixed area and period effect, we reduce the potential impact of omitted variable bias.

  10. The New Zealand Census is normally held every five years. However, a devastating earthquake in 2011 in the city of Christchurch, from where the census is administered, led to this census being delayed until 2013.

  11. The classic illustration of a local spatial spillover is the case of an increase in the sales tax on cigarettes in one state causing sales of cigarettes in neighbouring states with lower taxes to increase, as smokers cross state borders in search of cheaper cigarettes. However, if there is a nationwide commercial smuggling network, cigarettes are bought in states where prices are relatively low and sold in states where they are high-leading to global spillovers in which sales of cigarettes in any state are related to sales in all other states. See, e.g., LeSage (2014).

  12. Beenstock and Felsenstein (2007, p 178) cited in Elhorst (2014, p 56).

  13. We thank an anonymous reviewer for suggesting to check for interaction effects and nonlinearity effects.

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Authors and Affiliations

  1. School of Social Sciences, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand

    William Cochrane

  2. Department of Spatial Economics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands

    Jacques Poot

  3. National Institute of Demographic and Economic Analysis, University of Waikato, Private Bag 3105, Hamilton, New Zealand

    Jacques Poot

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  2. Jacques Poot
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Correspondence to William Cochrane.

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Cochrane, W., Poot, J. Did the post-1986 decline in the homeownership rate benefit the New Zealand labour market? A spatial-econometric exploration. Asia-Pac J Reg Sci 4, 261–284 (2020). https://doi.org/10.1007/s41685-020-00148-6

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