Economic valuation of air quality improvement using contingent valuation: Evidence from San Juan de Lurigancho, Lima, Peru

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Type of the article: Research Article

Abstract
Air pollution causes an alarming number of deaths worldwide. Metropolitan Lima is one of the megacities with the worst air quality in the world; San Juan de Lurigancho, one of the most polluted districts in Peru, recorded an annual average concentration of 41.2 µg/m3 of PM2.5 in 2023, which significantly exceeds the annual reference limit of 15 µg/m3 established by the World Health Organization. Therefore, this study aimed to estimate the economic benefit of improving air quality in San Juan de Lurigancho using the contingent valuation method in both simple and double dichotomous formats. A total of 400 face-to-face interviews were conducted to assess households’ willingness to pay for this environmental improvement, based on a price vector of 4, 6, 8, and 10 PEN as a monthly contribution over one year. The results indicate that 60% of respondents are willing to make a financial contribution. The average willingness to pay values, taking into account the variables household income and age of the head of household – the only statistically significant variables in the econometric models – are 8.77 PEN/month and 7.99 PEN/month, for the simple dichotomous and double dichotomous formats, respectively. Using this latter estimate, the associated social benefit amounts to 28,994,112 PEN/year (approximately 8,076,354 USD/year), which provides a useful benchmark for evaluating public policies aimed at mitigating air pollution in large urban centers.

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    • Figure 1. Method of application of the double dichotomous choice
    • Figure 2. Location map of San Juan Lurigancho in Metropolitan Lima
    • Figure 3. Willingness to pay histogram – Double dichotomous including all responses
    • Figure 4. Willingness to pay histogram – Double dichotomous excluding negative responses
    • Table 1. Main descriptive survey data statistics
    • Table 2. Relationship between initial price plan and willingness to pay in simple and double dichotomous formats
    • Table 3. Logit regression between willingness to pay and initial price plan under the simple dichotomous format
    • Table 4. Logit regression estimation with socioeconomic variables
    • Table 5. Average willingness to pay derived from simple and double dichotomous formats
    • Table 6. Results of t-test
    • Table A1. Probit regression estimate without socioeconomic variables
    • Table A2. Probit regression estimate with socioeconomic variables
    • Table B1. Part 4 of the survey: Socioeconomic variables
    • Conceptualization
      Carlos Minaya, Milagros Estrada, Duber Chinguel
    • Funding acquisition
      Carlos Minaya, Milagros Estrada
    • Investigation
      Carlos Minaya, Carolay Vasquez, Karla Vega
    • Project administration
      Carlos Minaya, Duber Chinguel
    • Supervision
      Carlos Minaya, Milagros Estrada
    • Writing – original draft
      Carlos Minaya, Carolay Vasquez, Duber Chinguel, Karla Vega
    • Data curation
      Milagros Estrada, Karla Vega
    • Resources
      Milagros Estrada
    • Writing – review & editing
      Milagros Estrada, Carolay Vasquez
    • Formal Analysis
      Carolay Vasquez
    • Methodology
      Carolay Vasquez
    • Software
      Carolay Vasquez
    • Visualization
      Duber Chinguel, Karla Vega
    • Validation
      Karla Vega