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Genuine savings as a test of New Zealand weak sustainability

Abstract

The key aims of this paper are to: (1) to extend the World Bank’s (WB) measure of genuine savings (GS) for New Zealand by using a longer time series of data, 1950–2015; (2) improve GS estimates for New Zealand by adding additional dimensions to GS, i.e. forestry; (3) investigate the relationship between several GS measures and the discounted values of GDP per capita and consumption per capita, used to proxy well-being; (4) test a series of hypotheses which relate GS to the change in future well-being using the framework proposed by Ferreira et al. (World Bank Econ Rev 22(2):233–248, 2008. https://doi.org/10.1093/wber/lhn008) and (5) investigate the effects of a growing population on the availability of future capital stocks by considering the consequences of “wealth-dilution” as defined by Ferreira et al. (2008). The paper makes a contribution to the literature on GS, particularly in the context of New Zealand, by considering patterns of GS and well-being over a longer time span of data than have been previously used and add to a relatively small, but growing literature on tests of GS using long or relatively long time-series data [see, e.g. Greasley et al. (J Environ Econ Manag 67(2):171–188, 2014. https://doi.org/10.1016/j.jeem.2013.12.001, Environ Dev Econ 22:674–98, 2017) and Hanley et al. (Enviro Resour Econ 63(2):313–338, (2016). https://doi.org/10.1007/s10640-015-9928-7]. We conclude, based on the data used here, that New Zealand’s GS has been positive (i.e. weakly sustainable), since the start of our data series, even without allowing for the contribution of technological advancement. However, we also conclude that the effects of a growing population and a savings gap have led to a “wealth-dilution” effect needed to maintain real wealth per capita, as we estimate that there was an average savings gap (GS as a percentage of gross national savings) over the period 1955–2015 of 0.5% per annum.

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Notes

  1. 1.

    For a “primer” and partial survey of this literature, see Oxley (2017).

  2. 2.

    See Fenichel and Abbott (2014) for recent developments of the Dasgupta/Maler approach.

  3. 3.

    Ferreira et al. (2008) present as their Eq. 1 (as above), the infinite horizon version of the genuine savings relationship. The fact that the theoretical version relates to an infinite horizon reinforces why, in empirical models, longer time series data are likely to generate results more closely aligned to the theoretical underpinnings than those from short time series or small T panels.

  4. 4.

    Estimates and testing based on Eq. (4) are presented in Sect. 2.

  5. 5.

    See “Appendix” for details on rent calculations.

  6. 6.

    The long-run discount rate is derived from the mean nominal discount rate minus the rate of inflation; see appendix for sources. 2.8% is our benchmark discount rate; this rates sits just below recent New Zealand Treasury discount rates projects over 10, 15, 20 and 30 years (3.06, 3.38, 3.57, 3.87%). Spot rates from: http://www.treasury.govt.nz/publications/guidance/reporting/accounting/discountrates

  7. 7.

    See “Appendix” for detailed results.

  8. 8.

    However, as the World Bank (2011), p. 43, concludes: “Even developed countries such as the United States and New Zealand have had positive ANS but a decline in per capita wealth because saving has not been sufficient to compensate for population growth”.

  9. 9.

    The World Bank (2011), p. 41, concludes that: “The adjusted net saving gap measures, as a percentage of GNI, the difference between actual ANS and the amount necessary to maintain per capita wealth. The savings gap for the United States and New Zealand is 2%”.

  10. 10.

    “For example, a detailed analysis of human capital accounts for Canada, New Zealand, Norway, Sweden, and the United States unambiguously shows that human capital is a leading source of economic growth”. World Bank (2011), p. 105. This conclusion, however, is based upon the exclusion of all forestry-related measures of capital from the World Bank estimates.

  11. 11.

    This assumes we are measuring brain-gain human capital from migration sufficiently accurately.

  12. 12.

    “For example, a detailed analysis of human capital accounts for Canada, New Zealand, Norway, Sweden, and the United States unambiguously shows that human capital is a leading source of economic growth”. World Bank (2011), p. 105.

  13. 13.

    “There are notable exceptions to this, such as fisheries in Iceland, New Zealand, and Namibia, where better management allows substantial rents to be generated” World Bank (2011), p. 21.

  14. 14.

    World Bank (2011).

  15. 15.

    “There are notable exceptions to this, such as fisheries in Iceland, New Zealand, and Namibia, where better management allows substantial rents to be generated” World Bank (2011), p. 21.

  16. 16.

    “New Zealand introduced a system of individually tradable quotas to manage its fisheries, resulting in a large competitive market for fish quota sales and rentals. This system has established a direct market price for the asset value of fisheries, which is used in the New Zealand fisheries accounts” World Bank (2011) p. 135.

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Funding

The funding was provided by Marsden Fund.

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Correspondence to Les Oxley.

Appendix

Appendix

See Table 8.

Table 8 Comparison of the World Bank and New Zealand national statistics office data sources

In addition to the data series mentioned in the above table, detailed description on the compilation of the other data series is as follows:


Consumption, GDP and GDP deflator


Total public and private consumption in real per capita terms is calculated as a residual from GDP. Similarly, all other data series to conduct hypothesis testing are constructed in real per capita terms.


Data source: The New Zealand Official Yearbooks, NZOYBs hereafter, (1950–1971) and Stats NZ (1972–2015).


Population


Estimated mean population of New Zealand for year ended 31 December.


Data source: NZOYBs (1950–1971) and Stats NZ (1972–2015).


Education expenditure


Human capital is used as a proxy of human capital. This is given by the total government expenditure on education (including primary, secondary, tertiary, etc.) and salaries excluding capital expenditure.


Data source: NZOYBs (1950–1971) and Stats NZ (1972–2015).


Discount rates


We derived discount rates from the mean of bonds long-term series from Homer and Sylla (2005). We subtracted the percentage of GDP deflator from the bond percentage to get the real discount factor, which is 1.4% per year. We also use an alternative discount rate of 2.8% for sensitivity analysis.


Gross national savings (GNS)


GNS is calculated by subtracting public and private consumption from gross national income plus net exports.


Data source: NZOYBs (1950–1971) and Stats NZ (1972–2015).


Depreciation of fixed capital


It is the replacement value of capital used in the process of production and consumption. Pre-calculated data series for depreciation of fixed capital are given Stats NZ.


Net national savings (NNS)


It is the difference between GNS and depreciation of fixed capita.


Rents from natural capital (excluding forestry)


Rents from the mining of natural resources are given by:

$${\text{Rents}} = {\text{Production}} \,{\text{volume}}\, \times \, {\text{unit}}\, {\text{resourcerent}}$$
$${\text{Unit}}\, {\text{resourcerent}}\, = \,{\text{unit}}\, {\text{price}} - {\text{cost }}\,{\text{of}}\,{\text{production}}$$
$${\text{Cost}}\, {\text{of}}\, {\text{production}} = {\text{labour}}\, {\text{emplpyed}}\, \times \, {\text{average}}\, {\text{salaries}} .$$

In our data set, the market value of all mineral resources is obtained from NZOYBs (1950–1993) and from the Mining Production Statistics annual publications by the Ministry of Business Innovation and Employment (2000–2015). Missing data between these periods are imputed from linear extrapolations.

Data for total labour employed in the mining sector and average annual wage in the mining industry are also compiled from NZOYBs and Stats NZ.


NNSNR


This is the difference between NNS and rents from natural capital (excluding forestry).


Rents from forestry


Rents from change in forestry are calculated as:

$${\text{Rents}} = {\text{Change}}\, {\text{in}}\, {\text{standing}}\, {\text{forest}}\, {\text{volume}}\, \times \, {\text{unit}}\, {\text{price}} - {\text{cost}}\, {\text{of}}\, {\text{production}}$$

\({\text{Standing}}\, {\text{forest}}\, {\text{volume}} = {\text{Standing}}\, {\text{stock}}\, {\text{of}}\, {\text{forest}}\, \times \, {\text{average}}\, {\text{volume}}\, {\text{per}}\, {\text{hectare}}.\)

$${\text{Cost}}\, {\text{of}}\, {\text{production}}\, = \, {\text{labour}}\, {\text{employed}}\, \times \, {\text{average}}\, {\text{salaries}} .$$

Forest volumes include the standing volume of both natural and planted forest in hectares. Standing volume in cubic meters is estimated by multiplying the standing stock of forest (in hectares) by average volume per hectare provided by the New Zealand Ministry of Primary Industries in the National Exotic Forest Description (NEFD) and Forest Owners Association (FOA) facts and figures reports. The cost of production is estimated from the product of a number of people employed in the forestry industry and real wage. Finally, market prices are determined by the average export price of all forest products from New Zealand.


Data source: Labour and wages data from NZOYBs Stats NZ, estimated round wood removals from New Zealand forests from Ministry of Primary Industries, forest volume and volume per hectare from NFED and FOA.


NNSF


It is given by the sum of Green series and rents from forestry.


Genuine savings (GS)


Finally, GS is obtained from the sum of Super Green series and investments human capital (i.e. education expenditures).


Total factor productivity (TFP)


The annual index of TFP is from Greasley and Madsen (2016, Eq. 1) using their preferred TFP (BDL) variant. Trend growth of these data for each year 1950–2015 is extracted using a Kalman filter and used to construct a measure of the value of technological progress. TFP series are compiled for GS, Green and Super Green series over 10, 15, 20 and 30 years horizons. For sensitivity analysis, we used the present value of future changes in TFP of aforementioned series with 1.4 and 2.8% per year discount rates to value technological progress, where the discount rates are matched with those for consumption and GDP per capita.


Net present values of consumption per capita, GDP per capita


Net present values for the future changes in real consumption per capita, real GDP per capita and TFP data series are estimated following Ferreira et al. (2008) over 10, 15, 20 and 30 years horizons with a 2.8% per year discount rate.


See Tables 9, 10 and 11.

Table 9 Summary statistics of key variables
Table 10 Summary of results with PV of change in GDP per capita at 2.8% discount rate
Table 11 Summary of results with PV of change in consumption per capita at 2.8% discount rate

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Qasim, M., Oxley, L. & McLaughlin, E. Genuine savings as a test of New Zealand weak sustainability. Environ Dev Sustain 22, 89–127 (2020). https://doi.org/10.1007/s10668-018-0185-0

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Keywords

  • Sustainability
  • Genuine savings
  • Natural capital
  • Hartwick rule
  • New Zealand