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The value of mortality risk reductions in Delhi, India

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Abstract

We interviewed commuters in Delhi, India, to estimate their willingness to pay (WTP) to reduce their risk of dying in road traffic accidents in three scenarios that mirror the circumstances under which traffic fatalities occur in Delhi. The WTP responses are internally valid: WTP increases with the size of the risk reduction, income, and exposure to road traffic risks, as measured by length of commute and whether the respondent drives a motorcycle. As a result, the value of a statistical life (VSL) varies across groups of beneficiaries. For the most highly-exposed individuals the VSL is about 150,000 Purchasing Power Parity (PPP) dollars.

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Notes

  1. Throughout the paper we use the term “two-wheeler” to refer to motorized two-wheelers, i.e., motorcycles and motor scooters.

  2. See also Schwab Christie and Soguel (1995).

  3. Vassanadumrongdee and Matsuoka (2005) elicit willingness to pay for an airbag, while Melhuish et al. (2005) use a scenario similar to Jones-Lee et al. (1985). Ortuzar et al. (2000) ask respondents what they would pay to travel on a safer road but do not associate this with a reduction in the respondent's personal risk reduction.

  4. The death rate for children is approximately 2 per 100,000.

  5. The city A v. city B choice question is modeled after Viscusi et al. (1991), who used a similar approach to elicit the additional cost of living at which respondents would be indifferent between a city with a specified risk of dying in a road traffic accident and another city with a lower death rate in a crash. City A v. City B questions were also used to elicit the rate at which people trade road safety for the risk of contracting chronic bronchitis.

  6. A corollary of this is that both the scenario dummies and baseline risk are highly correlated with the size of the risk change (delta risk) presented to the respondent.

  7. In cities in developing countries, work trips constitute a higher percent of kilometers traveled than in the U.S. Baker et al. (2005) report that in Mumbai work trips constitute 67.5% of all trips made by adults, weighted by distance traveled.

  8. In earlier versions of the questionnaire, we attempted to communicate risks of death by placing black grains of rice in a jar containing 100,000 white grains of rice. This device was useful in communicating the order of magnitude of fatal traffic risks, but difficult to use to represent specific risks changes in different scenarios.

  9. Because respondents are shown an array of possible payment amounts, rather than a single figure, the payment card approach is generally held to be free from anchoring effects or starting point biases associated with other elicitation approaches (Boyle, 2003) as long as the range of bids on the card is not arbitrarily cut off (Rowe et al., 1996; Roach et al., 2002). To avoid this problem, our payment card included Rs. 0 and explicitly allowed respondents to announce a willingness to pay amount greater than Rs. 3000. We also experimented with two variants of the payment card in our pretest, and found that changes in the bids on the payment card did not have a statistically significant effect on mean WTP.

  10. The 2001 Census reports that 28% of households in Delhi own a two-wheeler and 13% own a car.

  11. A possible explanation for these results is provided by Viscusi (1989) whose prospective reference theory describes how people may update the risk information we provide them in a Bayesian fashion. We return to this point below.

  12. This quadratic relationship is the mirror image of the quadratic relationship that earlier studies—including Jones-Lee et al. (1985) with contingent valuation and Viscusi and Aldy (forthcoming) with compensating wage studies—have observed between age and WTP for a reduction in mortality risks. Kniesner et al. (2006) condition their compensating wage equation on consumption expenditure.

  13. In the absence of life insurance, having more dependents should increase WTP to reduce mortality risk in order to provide for one's dependents in the future.

  14. The weight assigned to the prior depends on the precision of the prior itself. See Viscusi and O’Connor (1984).

  15. Our approach can be compared with that in Gayer et al. (2000), who do not observe the mortality risks residents associate with proximity to contaminated sites on the Superfund National Priorities List, and assume them to be equal to the average risks from Superfund sites. This prior belief is assumed to be updated with information disseminated by the U.S. Environmental Protection Agency at the end of site assessment. Gayer, Hamilton and Viscusi use the hedonic price approach.

  16. This may be interpreted as implying that prior risks are obtained as the product of risk per mile driven (which presumably depends on the mode of transportation used) times distance driven (which we proxy with commute time, and, as explained below, with whether the respondent travels as part of his job).

  17. In other words, in our empirical analysis we impose the restriction that δ1 is equal to zero.

  18. The cdf of the Weibull distribution is [1−exp(−WTP i /σ i ), where σ i is the exponential function of the right-hand side of Eq. (8), except for the error term. Mean WTP is computed as σ i ·Γ(1/θ+1), where θ is the shape parameter of the Weibull. The λ in Eqs. (9) and (10) is thus comprised of all βs, δs, and θ.

  19. Further analysis shows that 92% of the respondents reported WTP amounts for the largest risk reduction (city A v. city B questions) that were no less than those for the smallest risk reduction (the pedestrian crossing scenario), and that 74% held higher WTP values for the largest risk reduction than for the second largest risk reduction (the helmet question). This suggests that WTP exhibited good internal validity.

  20. We also fit models that assume that WTP is a lognormal variate, so that the error term in Eq. (8) is normally distributed. We found that the Weibull distribution fits the data much better than the lognormal. Moreover, the shape parameter of the Weibull distribution is less than one, and indeed rather low, implying that the shape of the density of the WTP observations is not compatible with that of a lognormal variate.

  21. We note that the VSLs reported in Table 6 are almost identical if they are computed using a model that drops answers to the pedestrian scenario—the least successful of our scenarios—which elicited a zero WTP response from 50% of respondents. The respective VSLs are: 121,000 (low income), 149,000 (middle income), 168,000 (high income).

  22. The Planning Commission of India currently uses a social discount rate of 12%.

  23. Assuming an income elasticity of one (i.e., multiplying by the ratio of Indian to U.S. per capita income in Purchasing Power Parity terms) would yield a VSL of $235,000 for India.

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Acknowledgments

We thank the World Bank Research Committee and Transport Anchor, and the Fondazione Eni Enrico Mattei for funding. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent.

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Authors and Affiliations

  1. University of Maryland, Maryland, USA

    Soma Bhattacharya

  2. University of Maryland and Fondazione Eni Enrico Mattei, Maryland, USA

    Anna Alberini

  3. Department of Economics, University of Maryland, College Park, MD, 20742, USA

    Maureen L. Cropper

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  1. Soma Bhattacharya
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  2. Anna Alberini
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  3. Maureen L. Cropper
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Correspondence to Maureen L. Cropper.

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JEL Classification R41 · I18

Appendix: Valuation questions from the survey

Appendix: Valuation questions from the survey

1.1 Part D: Behavioral Questions

In this section I am going to ask you a few questions about travel and travel safety. I will describe situations where you are a pedestrian or a two-wheeler driver and will ask you to tell me what you would do if you were in that situation. There is no right or wrong answer to any of the questions in this section. Please answer whatever you honestly feel you would do if you were actually in such a situation in real life.

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Bhattacharya, S., Alberini, A. & Cropper, M.L. The value of mortality risk reductions in Delhi, India. J Risk Uncertainty 34, 21–47 (2007). https://doi.org/10.1007/s11166-006-9002-5

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