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Discounting Long-Term Job-Related Health Risks in the Context of Indian Workers

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Abstract

Discount rate plays a very important role in cost–benefit analysis of environmental, health and occupational safety policies. Since resources are limited, valuing the future benefits at present value using a discount rate becomes necessary for a government to decide on worthiness of any project. In this context, the choice of discount rate is a debated issue, especially for developing countries where such studies are scarce. The present study attempts to address this issue by estimating the discount rate for long-term job-related health risks of a sample of workers from an Indian city, Ahmedabad. These job risks pertain to environmental health risks and unhealthy work conditions. In this study, an extension of the standard hedonic wage method is used which captures the inter-temporal aspect of worker’s decision on choice of job risk and thereby reveals their implicit rate of time preference. The estimated discount rate for this study ranges between 2.6 and 18.6%. These estimates are consistent with the estimates of developed and developing countries. The corresponding value of statistical life ranges between INR 46.3 million ($0.69 million) and INR 81.28 million ($1.21 million). The discount rates calculated in this work will benefit policymakers in India and other developing countries in evaluating and designing various policies.

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Fig. 1

Source: Moore and Viscusi (1990a)

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Notes

  1. The social rate of time preference “s” is expressed as, \(s = \mu g + \tau\), where “\(\tau\)” is rate of pure time preference which indicates the myopic nature of individuals in society, “g” is the growth rate of per capita real consumption, and “\(\mu\)” is the elasticity of marginal utility of consumption (Markandya and Pearce 1988).

  2. For this study, the scale of fatality rate is taken per 0.1 million and the scale of injury rate is taken per 1000 workers. Using the number of deaths and injuries in factories of Gujarat and corresponding employment during 2010–2014, the fatality rate per 0.1 million worker and the injury rate per 1000 workers have been estimated. The following formula has been used to calculate the probability of death per 0.1 million worker for a particular year. Thus, the average probability of death (i.e. fatality rate) in this study is calculated using 5 years data\({\text{Probability}}\; {\text{of}}\; {\text{death}} = \frac{{{\text{Total}}\;{\text{ number}}\; {\text{of}}\;{\text{ fatal}}\; {\text{injuries}}\;{\text{ for}}\;{\text{ a}}\;{\text{ NIC}} }}{{{\text{Total}}\; {\text{number }}\;{\text{of }}\;{\text{blue }}\;{\text{collar}}\;{\text{ workers }}\;{\text{for}}\;{\text{ a}} \;{\text{NIC}} }} \times \left( {100,000} \right)\)

  3. The probability of injury per one thousand workers for a particular year has been calculated by the following formula. Similarly, the average probability of injury (i.e., injury rate) in this study is calculated using 5 years data\({\text{Probability}}\;{\text{ of}}\;{\text{ injury}} = \frac{{{\text{Total}}\;{\text{ number}}\;{\text{ of}}\;{\text{ non}}\;{\text{ fatal}}\;{\text{ injuries}}\;{\text{ for}}\;{\text{ a}}\;{\text{ NIC}} }}{{{\text{Total}}\;{\text{ number }}\;{\text{of}}\;{\text{ blue}}\;{\text{ collar}}\;{\text{ workers}}\;{\text{ for}}\;{\text{ a}}\;{\text{ NIC}}}} \times \left( {1000} \right)\)

  4. Value of Statistical Life from specification 1 = co-efficient of ELYL variable from specification 1 × mean wage × annual hours of work × 100,000 = 0.006 × 42.96 × 2160 × 100,000 = INR 55.6 million ($0.83 million).

    Value of Statistical Life from specification 2 = co-efficient of ELYL variable from specification 2 × mean wage × annual hours of work × 100,000 = 0.005 × 42.96 × 2160 × 100,000 = INR 46.3 million ($0.69 million).

  5. Value of Statistical Injury from specification 1 = [co-efficient of injury variable + (co-efficient of compensation variable × mean compensation benefit) × mean wage of the sample] × annual work hours × 1000 = [(0.051 − (0.040 × 0.46)) × 42.96 × 2160 × 1000] = INR 1.29 million ($0.019 million).

    Value of Statistical Injury from specification 2 = [co-efficient of injury variable + (co-efficient of compensation variable × mean compensation benefit) × mean wage of the sample] × annual work hours × 1000 = [(0.052 − (0.045 × 0.46)) × 42.96 × 2160 × 1000] = INR 2.90 million ($0.043 million).

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  1. Faculty of Economics, MIT-World Peace University, Pune, 411038, India

    Agamoni Majumder

  2. Centre for Economic Studies and Policy, Institute for Social and Economic Change, Dr. V. K. R. V. Rao Road, Nagarabhavi PO, Bangalore, 560072, India

    S. Madheswaran

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Majumder, A., Madheswaran, S. Discounting Long-Term Job-Related Health Risks in the Context of Indian Workers. Ind. J. Labour Econ. 65, 1099–1120 (2022). https://doi.org/10.1007/s41027-022-00415-4

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