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Inclusive wealth of regions: the case of Japan

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  • Sustainability Science and Implementing the Sustainable Development Goals
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Abstract

The Inclusive Wealth Index (IWI) is a stock-based comprehensive indicator used to evaluate sustainability based on the wealth of nations, including a finer scale that considers the wealth of regions, in which these indicators are required for governance in the administrative regional hierarchies to achieve Sustainable Development Goals. However, few studies have applied the measure to finer-scale wealth relative to the national level. In this paper, we fill the gap by examining the IWI in all prefectures in Japan, where sustainability is increasingly being lost as a result of depopulation, an aging population, and the excessive burden of environmental regulations. We determined that all regions in Japan maintained sustainability from 1991 to 2000. Then, regional sustainability was lost in 8 prefectures from 2001 to 2005 and in 28 prefectures from 2006 to 2010. This trend is consistent with those found in previous studies, though more severe. The decreasing wealth growth is caused by the increasing damage to health capital, mainly in rural areas, whereas produced capital has had positive effects but has not mitigated the damage. Finally, we illustrate how this index can be applied to evaluate projects in response to the intense debate in regional public policy for rural sustainability through a case study of seawalls as a recovery project in the wake of the Great East Japan earthquake.

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Notes

  1. The prefecture level may not satisfy the limited distribution of capital assets and the mobility of capital assets, and optimal solutions for spatial units in Japan are not the main object of this study. Thus, we leave this question for future research.

  2. Kawagoe (1999) reexamined the results of Barro and Sala-i-martin (1992) by applying a panel unit root technique to nearly the same datasets and obtained evidence of no convergence. However, Shibamoto et al. (2016) reconcile the debate by classifying it as results for deviation from short-run and long-run growth equilibrium; short-run deviations from regional growth equilibrium (e.g., the bursting bubble economy) reduce the inequality of income, whereas the long-run growth equilibrium from 1955 to 1999 makes inequalities among prefectures converge. The results seem to be valid if the dataset extends to 2012, which is covering our dataset period.

  3. Wilkinson and Pickett (2006) review the relationship between health and income disparity. Refer to Oshio and Kobayashi (2009, 2010) for the case of Japan.

  4. We focus on the methods for estimating the stock amount of human capital and natural capital because of several complexities arising from the estimation framework for the shadow price of human capital and CO2 emissions, as well as the limited space for explaining these complexities here. See appendix 2 in Ikeda et al. (2016) for detailed assumptions and data.

  5. The data required for human capital are mainly obtained from the national census in Japan (1990, 1995, 2000, 2005, 2010) and life tables around the census years from the Japanese Mortality Database of the National Institute of Population and Social Security Research.

  6. The data were mainly available from statistical surveys of the Ministry of Agriculture, Forestry and Fisheries (MAFF).

  7. Ikeda et al. (2016) relied on the value of mineral capital in Japan, as estimated by Sato et al. (2015).

  8. Agency for Natural Resource and Energy, http://www.enecho.meti.go.jp/statistics/energy_consumption/ec002/results.html#headline5. Accessed Sep 2016.

  9. The global data on capital gains and consumption, in this case for Japan, are available from the BP Statistical Review of World Energy June 2015.

  10. IMF, http://www.imf.org/external/pubs/ft/weo/2015/01/weodata/weorept.aspx?sy=1980&ey=2020&scsm=1&ssd=1&sort=country&ds=.&br=1&pr1.x=28&pr1.y=18&c=158&s=NGDP_D&grp=0&a=. Accessed Dec 2015.

  11. Muñoz et al. (2014) reported that produced capital, human capital (only education capital), and natural capital accounted for 63 percent, 36 percent, and approximately 0 percent of the average annual growth rate of the IWI in Japan over a 20-year period.

  12. Nine prefectures are identified as rural areas (Aomori, Akita, Iwate, Yamagata, Kochi, Saga, Kumamoto, Miyazaki, and Kagoshima); ten as urban areas (Saitama, Tokyo, Kanagawa, Gifu, Aichi, Kyoto, Osaka, Hyogo, Hiroshima, and Fukuoka). We omit the other prefectures for simplicity. The calculation of the annual growth ratios for each component in IWI are based on aggregated values in above prefectures in each area (rural and urban). Thus, the aggregated values per capita are almost same as weighted average values among prefectures in an area by the population though we use the approximation for it.

  13. Higashikata (2013) suggests not only the same effect of public investment as that in Otuka and Goto (2016) but also the opposite effect of private investment on the disparity.

  14. We assume the shadow price of health capital in each area is a constant value during the evaluation period; thus, we avoid considering the effects of the gap of shadow prices in both areas.

  15. We update the IWI database by assuming constant shadow prices for each type of capital because shadow prices do not fluctuate under a stable economy with inclusive wealth accounting. We extrapolate only 3 years to compare with the 20-year database. Nonetheless, we update the data on capital stocks that have a major impact on the composition of IWI. Thus, health capital in 2013 is estimated using updated life tables and then interpolating missing data in 2011 and 2012 through linear interpolation. Produced capital, almost all natural capital and the adjustment factors are estimated from 2011 to 2013. However, we only extrapolate the stock of education capital, mineral capital and CO2 emissions due to limited data availability and the small impacts on the IWI.

  16. We have omitted some cases in which it is difficult to identify the fault of the hypocenter and the maximum Mw is less than 7.4.

  17. The data can be obtained from the authors upon request.

  18. We use the following two assumptions to make the spatial data tractable: The height of each mesh is the average height of the mesh; the run-up height is the same as the tsunami height.

  19. We should notice that the cost of the CBIW is not the construction cost (108.6 billion yen) used in the CBA but rather the depletion of natural capital as a result of the construction (0.2 billion yen). Although the construction costs indicate the increase in produced capital in terms of inclusive wealth, in this case, the national government of Japan invests in the seawalls. Thus, the cost should not be added to the produced capital in the CBIW, and it is convenient for analyzing the effect of the seawalls.

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Acknowledgements

We would like to express our thanks to Y. Fukutani who assisted us in making the hazard curve in Rikuzentakata. We also thank the Japanese Ministry of the Environment for providing financial support through the Environment Research and Technology Development Fund (S-14, S-15, S-16) and Policy Research of Environmental Economics FY2015–2017. In addition, this work was funded by Grant-in-Aid for Specially Promoted Research (26000001) by Japan Society for the Promotion of Science.

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Authors and Affiliations

  1. Department of Urban and Environmental Engineering, School of Engineering, Kyushu University, 744 Motooka, Nishiku, Fukuoka, 819-0395, Japan

    Shinya Ikeda, Tetsuya Tamaki & Shunsuke Managi

  2. Faculty of Commerce, Chuo University, 742-1 Higashinakano, Hachioji-shi, Tokyo, 192-0393, Japan

    Hiroki Nakamura

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  1. Shinya Ikeda
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  2. Tetsuya Tamaki
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  4. Shunsuke Managi
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Correspondence to Shinya Ikeda.

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Handled by Osamu Saito, United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), Japan.

Appendix

Appendix

See Fig. 9.

Fig. 9
figure 9

IWI per capita growth rate and GDP per capita growth. The IWI is composed of produced, human, and natural capital without any adjustment

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Ikeda, S., Tamaki, T., Nakamura, H. et al. Inclusive wealth of regions: the case of Japan. Sustain Sci 12, 991–1006 (2017). https://doi.org/10.1007/s11625-017-0450-4

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