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Residential preferences for stable electricity supply and a reduction in air pollution risk: a benefit transfer study using choice modeling in China

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Abstract

This paper uses choice modeling surveys from the Chinese cities of Jiujiang, Jiangxi Province, and Changsha, Hunan Province, to identify residential preferences for simultaneously increasing the stability of the electricity supply and decreasing the health risks from air pollution. Air pollution in China is mainly attributable to externalities associated with the electricity supply. We employ a contingent ranking approach as our choice modeling method and test for the transfer of benefits for these preferences between the two sites. The original benefit estimates indicate that the implicit price for reducing the number of power breakdowns is about RMB 83 per times × year × household in Jiujiang and RMB 78 per times × year × household in Changsha, while the implicit price for reducing the duration of power breakdowns is statistically zero in Jiujiang and RMB 71 per times × year × household in Changsha. From the alternative perspective, we estimate that the annualized value of the statistical lifetime risk of cancer caused by air pollution over a 70-year period is RMB 50,844 per year in Jiujiang and RMB 67,146 per year in Changsha. This suggests that we do not reject benefit transferability based on the implicit price of the number of power breakdowns, but do reject it based on the number of deaths from cancer caused by air pollution.

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Notes

  1. Matsukawa and Fujii (1994) examined the choice of backup equipment by large-scale computer users. In terms of household preferences in China, it is reasonable to view this choice as unrealistic given the relatively small scale of household electricity usage.

  2. The Japanese Bank for International Cooperation has supported a number of official development assistance (ODA) loan projects in China, including the construction of the coal-fired thermal power plant in Jiujiang and a hydropower plant in the western region of Hunan Province. The former included funding for special equipment aimed at reducing the emissions of certain pollutants (including NOx, SOx, and PM10) associated with the power plant, and the latter funding was used to construct a cleaner alternative to a coal-fired power plant. Both projects thus aimed to provide more stable, cleaner, and more efficient energy to these areas, and to avert any health risks related to local air pollution.

  3. In 2007, the populations of Jiujiang and Changsha were 4.69 million and 6.28 million, respectively.

  4. Indeed, similar studies have frequently omitted a status quo option because of the difficulty in setting such an option. For example, Carlsson and Martinsson (2008) omitted a status quo option because “…both the historical levels of outages as well as future levels vary a lot, and in most cases are related to random events, it is difficult to include a realistic status-quo alternative in a postal questionnaire” (Carlsson and Martinsson 2008, p 1236).

  5. Other forms of local air pollution, such as NOx or SOx, remain outside the scope of the analysis. As we could not find any epidemiological data on their association with health risk, we decided in this study to concentrate on the mortality and cancer risk related to PM10. Elsewhere, Ito and Thurston (1996) examined the association between cancer risk and PM10 concentration, and Lee et al. (2002) examined the link between cancer risk and SO2 concentration.

  6. According to the World Development Indicators, life expectancy in China was about 72.835 years in 2008 (World Develop Indicator in World Bank website, URL: http://data.worldbank.org/data-catalog/world-development-indicators).

  7. Although we could have defined the annual cost of the electricity supply, we chose to define it on a monthly basis because we expected that respondents at each site typically perceive the cost of electricity on a monthly, not annual, basis.

  8. We also employed a linear form of the utility function with regard to attributes in the choice set.

  9. Assuming a strictly increasing, continuous, and strictly quasi-concave utility function.

  10. We appreciate comments from the editors and two anonymous referees that indicated that this assumption may have needed to be tested. We tested it with respect to four attributes in the choice set using the Hausman test, and obtained the following test statistics: 870.476 in Jiujiang, and 4.563 in Changsha, respectively. Thus, the homogeneity in ranking is rejected in Jiujiang, while it is not rejected in Changsha at the 5% significance level (\( {{\upchi}}_{0.05} \left( 4 \right) = 9.488 \)). For simplicity, and in order to fully utilize information from the ranking of responses, we assumed homogeneity in ranking with regard to the data in both sites. As it may be a rather strict assumption, there are certain limitations on the parameter estimates for Jiujiang.

  11. We removed tied values in the ranking prior to estimation. There were two respondents in Jiujiang, and four respondents in Changsha, whom we removed prior to the estimation.

  12. For any two alternatives \( i \) and \( k \), the IIA property of CL in Eq. 2 is equivalent to the ratio of the probabilities being not dependent on any alternatives other than \( i \) and \( k \) \( P_{i} /P_{k} = \exp \left( {V_{i} } \right)/\exp \left( {V_{k} } \right). \)

    (see e.g. Train (2009): p. 45). With respect to RPL, the ratio of the probabilities becomes: \( P_{nit} /P_{nkt} = {\int \nolimits \mathop \smallint \nolimits \mathop \prod \nolimits_{t} \exp \left( {V_{nit} } \right)}/\mathop \sum \nolimits_{j} \exp \left( {V_{njt} } \right)f\left( {\beta |\Upomega } \right)d\beta /{\int \nolimits \mathop \smallint \nolimits \mathop \prod \nolimits_{t} \exp \left( {V_{nkt} } \right)}/\mathop \sum \nolimits_{j} \exp \left( {V_{njt} } \right)f\left( {\beta |\Upomega } \right)d\beta \). Then, the ratio depends on all alternatives other than \( i \) and \( k \), and IIA is totally relaxed by RPL.

  13. We could have employed the two one-sided convolutions test in Johnston and Duke (2008), but chose not to given the restrictions placed on the preference heterogeneities (see also Baskaran et al. 2010, p 1020).

  14. With regard to Changsha data, we obtain only one cross-term model.

  15. Although we could compare our results with those in Hammitt and Zhou (2006), their results concerning fatality risk suffer from scope insensitivity concerning the magnitude of the risk reduction. We thus omit the comparison.

  16. According to the Statistical Bureau of Jiangxi Province (2007), Jiujiang had a population of around 4.69 million and about 1.46 million households in 2006. The Statistical Bureau of Hunan Province (2007) reported that in 2006 Changsha had a population of about 6.28 million and some 1.87 million households.

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Acknowledgments

This paper is part of an ex post evaluation of the 2007 ODA yen loan projects granted by the Japanese Bank for International Cooperation. This research was supported by a Ministry of Education, Culture, Sports, Science, and Technology Grant-in-Aid for Scientific Research (No. 22310030 and 23710057). The authors gratefully acknowledge the comments of Dr. Yohei Mitani as a discussant at the 2008 meeting of the Society for Environmental Economics and Policy Studies, along with those of a number of other participants, including Dr. Kenji Takeuchi of the Graduate School of Economics at Kobe University and Dr. Takahiro Tsuge of the Faculty of Economics at Konan University. The authors also greatly appreciate the comments of two anonymous reviewers and the cooperation of the survey respondents in Jiujiang and Changsha.

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Authors and Affiliations

  1. Faculty of Economics, Department of Economics on Sustainability, Dokkyo University, 1-1 Gakuen-cho, Soka, Saitama, 340-0042, Japan

    Taro Ohdoko

  2. Graduate School for International Development and Cooperation, Hiroshima University, 1-5-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8529, Japan

    Satoru Komatsu & Shinji Kaneko

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  1. Taro Ohdoko
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  2. Satoru Komatsu
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  3. Shinji Kaneko
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Correspondence to Taro Ohdoko.

Appendices

Appendix 1: Description of the status quo in the questionnaire

Suppose you select the location of your residence by considering the electricity conditions in each location.

This questionnaire provides three alternative scenarios: Plan 1, Plan 2, and Plan 3. Each plan offers a different combination of the number of power breakdowns (frequency, times/year), duration of power breakdowns (the aggregate duration of power breakdowns, including regular maintenance, minutes/year), the number of deaths from cancer caused by air pollution (number of people per 10,000 citizens over a 70-year period who die from cancer caused by air pollution), and the cost of electricity supply (RMB/month).

Currently air pollution is severe in Jiujiang/Changsha, and causes cancer deaths at a rate of ____ (220.8 for Jiujiang and 292.2 for Changsha) people per 10,000 citizens over a 70-year period. This means that, out of 1,000 people who live in Jiujiang/Changsha for 70 years, about ____ (22 for Jiujiang and 29 for Changsha) will die from cancer caused by air pollution. Power stations also have a harmful influence on air quality.

Appendix 2: Example of a choice set

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Ohdoko, T., Komatsu, S. & Kaneko, S. Residential preferences for stable electricity supply and a reduction in air pollution risk: a benefit transfer study using choice modeling in China. Environ Econ Policy Stud 15, 309–328 (2013). https://doi.org/10.1007/s10018-013-0061-y

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