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Residential water demand and water waste in Taiwan

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Abstract

Residential water demand has long been an important topic of empirical research. How to estimate water waste, however, has rarely been touched. Using the stochastic frontier approach, this article jointly estimates the residential demand for water and water waste in Taiwan, where water resources are scarce and unevenly distributed throughout the island and across seasons. The empirical results confirm that residential water demand is closely related to household characteristics and the overuse of water is affected by environmental variables. The estimated price and income elasticities are below 0.1 in absolute value. The estimated amount of wasted water is around 83 L per capita per day, which is roughly 1/3 of the actual water consumption. It is also shown that overlooking the waste of water use results in an over-estimation of the subsistence water requirement.

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Notes

  1. Taiwan is mountainous, and its rivers are short and steep, which makes the storage of precipitation for subsequent use difficult. According to the United Nations World Water Development Report 2 (WWDR2 (2006), Table 4.3), the annual available water per capita in Taiwan is only 2930 m3/year, which is in the 71st position among 179 countries if we rank the availability of water from low to high.

  2. In fact, in terms of water charges, Taipei and Kaohsiung, the two biggest cities in Taiwan, rank 5th and 6th, respectively, among 133 cities surveyed by IWA (2010) (the higher the ranking, the lower the charge). On the other hand, in terms of quantity of water consumed per capita per day, Taipei and Kaohsiung rank 9th and 20th, respectively, among 112 cities surveyed by IWA (2010) (the higher the ranking, the higher the consumption).

  3. For example, their estimation shows that there is a significantly positive effect of the average water price on water demand. In addition, their estimate of household bimonthly necessary water consumption is as low as 165.75 L (that is, 0.69 L per capita per day for an average household with four members). Moreover, their estimate of household bimonthly reasonable water consumption is equal to 18,406 L which can be re-expressed as 76.7 L per capita per day. Because the authors have treated the data of households with per capita daily water consumption exceeding 310 L or less than 80 L as outliers and eliminated these data from their raw data set, the figure of 76.7 is obviously an unreasonable estimate.

  4. The Stone-Geary specification is rarely applied in the earlier studies related to water demand. However, it is more often applied in the recent literature [see e.g., Gaudin et al. (2001), Martínez-Espiñeira and Nauges (2004), Madhoo (2009), García-Valiñas et al. (2010), Dharmaratna and Harris (2012), and Hung and Chie (2013)].

  5. The main issues covered include: (i) whether the average or the marginal price combined with the difference variable should be used as the price variable in the demand equation [see e.g., Taylor (1975), Nordin (1976), Foster and Beattie (1979, 1981a, b), Billings and Agthe (1980), Billings (1982), Nieswiadomy and Molina (1989), Nieswiadomy (1992), Renwick and Archibald (1998), Shin (1985), Opaluch (1982, 1984), and Taylor et al. (2004)]; (ii) model specification and functional forms of the demand equation (linear, logarithmic, Stone-Geary, or discrete/continuous choice models among others) [see e.g., Gaudin et al. (2001), Martínez-Espiñeira and Nauges (2004), Hewitt and Hanemann (1995), Olmstead et al. (2007), and Olmstead (2009)]; (iii) meta-analysis of various research estimates [see e.g., Espey et al. (1997) and Dalhuisen et al. (2003)]; and (iv) country case studies [see e.g., Martínez-Espiñeira (2003), Reynaud et al. (2005), Schleich and Hillenbrand (2009), Miyawaki et al. (2011), Dharmaratna and Harris (2012), Rinaudo et al. (2012), and Polycarpou and Zachariadis (2013)].

  6. According to behavioral economics, wasted water might be due to biases in perception and behavior of households. An expanding empirical literature has demonstrated that “judgement bias” on the part of some market participants can lead to an inefficient allocation of resources (Hurley and McDonough 1995). People may make systematic mistakes when making decisions. For example, households might count on the experience or the use of heuristics to consume water which however causes a waste; facing a leaking faucet, households might be reluctant to fix it up because they have a problem of myopic loss aversion—they evaluate the present repair cost higher than the persistent loss of wasted water. If they could have a long-run perspective and repair the faucet, they would have in fact saved more money; households might also overconsume water because of the immediate benefits and the negligible immediate marginal cost of leaving water on, such as when brushing teeth. This is related to the so-called self-control problem (see e.g., Kahneman et al. 1991; Benartzi and Thaler 1995; Genesove and Mayer 2001; Stutzer and Frey 2007; Ameriks et al. 2007).

  7. Readers are suggested to refer to, for instance, Gaudin et al. (2001) and Martínez-Espiñeira and Nauges (2004), for details.

  8. The choice of these variables will be discussed in detail in Sect. 3.

  9. Appendix” gives the probability density functions of ω and ɛ.

  10. The question is: “On average, how much do you pay for tap water every 2 months?”

  11. There are two public water utilities in Taiwan, the Taipei Water Department (TWD) and the Taiwan Water Corporation (TWC). The former mainly serves the Taipei metropolis, and the latter serves the remaining area in Taiwan. Table 2 shows the rate structures for TWD and TWC that are increasing block rates. The rate structures of both TWD and TWC have remained constant since March 1994 and May 1997, respectively.

  12. Three data adjustments should be noted. First, in practice, a sewer fee of NT$5 is charged for each cubic meter of water consumed in addition to the unit price of water for the area served by the TWD. For this area, the sewer fee is therefore included in the unit price when calculating the quantity of water consumption. Second, for the area served by the TWC, the trash collection-and-treatment fee is based on the quantity of tap water used. This unit trash fee varies across counties and must be included in the unit price of water to calculate the quantity of water consumption. Third, the fixed cost is related to the diameter of the water meter. Because the information on the diameter is not made available for each household, we assume that all households have a 20 mm diameter meter, which is the most popular type for households in Taiwan (its shares are 46 and 61 % for areas served by TWD and TWC, respectively).

  13. For those interested in this model’s specification and estimation, see Appendix 1 in Dharmaratna and Harris (2012).

  14. First, the ratio of water expenditure to final consumption expenditure per household per year is only about 0.5–0.6 % in Taiwan (Water Resources Agency: http://www.wcis.itri.org.tw/life/charge-3.asp). It could be expected that the ratio for water expenditure to income per household should be even lower. Second, Martínez-Espiñeira (2003) states that “Conventional consumer theory assumes that users have perfect information about their preferences and constraints. They are assumed to react to changes in marginal prices and not to changes in intramarginal prices, because the former give rise to a substitution effect while the latter are assumed to create only an income effect. However, under high relative costs of information on the tariff, water users might respond more to average price changes than to marginal price changes (Foster and Beattie 1981a, b; Nieswiadomy 1992) by obtaining information on the total bill and the total amount consumed and roughly calculating an average price. Extra effort would be needed to learn about the marginal price. Calculating the marginal price from a bill in the presence of pricing blocks is not easy, and calculating which block consumers are consuming in (and therefore which marginal price they are facing) is even more difficult. This might not be considered worthwhile, especially since the relative cost of water is low compared to income”.

  15. The information regarding the number of younger household members is not available for the sample.

  16. This figure is obtained from dividing water consumption by average household size and converting the unit of cubic meters to liters.

  17. The southern region is the second most economically developed region, in which various industries and factories are located. Because the quality of tap water in this area is commonly thought to be inferior to that in other regions, residents usually buy water from other sources (mineral water for example) for cooking and drinking. Although it is the hottest region in Taiwan, the water consumption in the southern region is insignificantly less than that in the northern region.

  18. As mentioned in Sect. 2.1, this figure is calculated at the mean values of the exogenous variables. In addition, the time span is rescaled from bimonthly to per day and the average household size is around 3.4 persons. There are different suggestions for the basic water requirement in the literature. For example, WELL (1998) and WHO and UNICEF (2000) suggest a reasonable minimum as being 20 L per capita per day; Gleick (1996, 1998) recommends an overall basic water requirement of 50 L per capita per day. In Howard and Bartram (2003), 100 liters per capita per day and above is the optimal access.

  19. Based on a review of 24 journal articles published between 1967 and 1993, Espey et al. (1997) indicate that the price elasticity estimates range from −0.02 to −3.33, with an average of −0.51. About 90 % of the estimates are between 0 and −0.75. Dalhuisen et al. (2003) review 64 studies appearing between 1963 and 2001. The average price elasticity is equal to −0.41 with a standard deviation of 0.86. The minimum and maximum values are equal to −7.47 and 7.90, respectively, with a median of −0.35. The mean and median values of income elasticities are equal to 0.43 and 0.24, respectively, with a standard deviation of 0.79. Approximately 10 % of the estimates are greater than 1. More recent survey papers, such as Worthington and Hoffman (2008), note that price elasticity estimates are generally found in the range from 0 to 0.5 in the short run and from 0.5 to unity in the long run; income elasticity estimates are of a much smaller magnitude (usually) and are positive.

  20. This figure is obtained by calculating (β 0 + β 1 X 1 + ··· + β k X k  + αI/p w ) with the coefficient estimates of Eq. (3) and the means of variables. The unit is also transferred to be per capita per day.

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Appendix

Appendix

The probability density functions

The probability density function (pdf) of ω is equal to:

$$f\left( \omega \right) = \frac{{\frac{1}{{\sigma_{\omega } }}\phi \left( {\frac{\omega }{{\sigma_{\omega } }}} \right)}}{{1 - \varPhi \left( {\frac{{ - \delta^{\prime}Z}}{{\sigma_{\omega } }}} \right)}}$$
(6)

where ϕ(·) and Φ(·) are the pdf and cumulative distribution function of the standard normal random variable, respectively. The pdf of the composed error ɛ can be expressed as:

$$f\left( \varepsilon \right) = \frac{{\varPhi \left( { - B} \right)}}{{\sigma \varPhi \left( {\frac{{\delta^{\prime}Z}}{{\sigma_{\omega } }}} \right)}}\phi \left( {\frac{\varepsilon }{\sigma }} \right)$$
(7)

where \(- B = \frac{{\delta^{\prime}Z\sigma^{2} + \sigma_{\omega } \varepsilon }}{{\sigma_{v} \sigma_{\omega } \sigma }}\) and σ 2 = σ 2 v  + σ 2 ω . On the basis of Eq. (7), the corresponding log-likelihood function is readily derived and can be applied to estimate the parameters in Eqs. (3) and (4).

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Hung, MF., Chie, BT. & Huang, TH. Residential water demand and water waste in Taiwan. Environ Econ Policy Stud 19, 249–268 (2017). https://doi.org/10.1007/s10018-016-0154-5

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