Willingness to Pay to Prevent Water and Sanitation-Related Diseases Suffered by Slum Dwellers and Beneficiary Households: Evidence from Chittagong, Bangladesh

TL;DR

This study assesses the willingness of slum households in Chittagong, Bangladesh, to financially contribute to improving water and sanitation facilities, highlighting demographic factors influencing willingness to pay.

Contribution

It provides empirical evidence on households' willingness to pay for water and sanitation improvements using contingent valuation in a Bangladeshi slum context.

Findings

74% of households are willing to pay for improvements.

Women with college degrees are more willing to pay.

Household factors like housemaid working hours influence willingness.

Abstract

A significant proportion of slum residents offer vital services that are relied upon by wealthier urban residents. However, the lack of access to clean drinking water and adequate sanitation facilities causes considerable health risks for slum residents, leading to interruption in services and potential transmission of diseases to the beneficiaries. This study explores the willingness of the households benefitting from these services to contribute financially towards the measures that can mitigate the negative externalities of the diseases resulting from poor water and sanitation in slums. This study adopts the Contingent Valuation Method using face-to-face interviews with 260 service-receiving households in Chittagong City Corporation of Bangladesh. Estimating the logistic regression model, the findings indicate that 74 percent of respondents express their willingness to contribute financially towards an improvement of water and sanitation facilities in the slums. Within this group, 16 percent are willing to pay 1.88 USD/month, 18 percent prefer 3.86 USD/year, and 40 percent are willing to contribute a lump sum of 3.92 USD. The empirical findings suggest a significant influence of gender, college, and housemaids working hours in the households on respondents willingness to pay. For example, female respondents with a college degree and households with longer working hours of housemaids are more likely to contribute towards the improvement of the water and sanitation facilities in slums. Though the findings are statistically significant at a 5% level across different estimated models, the regression model exhibits a low goodness of fit.