Valuation of Avoiding Arsenic in Rural

Bangladesh: An Averting Behavior Analysis

Sonia AzizKevin J. Boyle

Thomas Crocker

Research Objectives

• Model household avoidance of exposure to arsenic in drinking water.

• Test whether safe drinking water intervention is successful.

• Estimate the relative value of improved child health from reduced arsenic exposure.

Previous Research

• Follows endogenous risk framework of Ehrlich and Becker (1972) and Quiggin (2002).

• Nastis and Crocker (2007) uses endogenous risk for averting behavior and include a child health component.

Previous Research cont.

• Relative value of child health about twice as large as value of parent’s own health – ratio of marginal willingness to pay estimates reveal parent’s value of child risk relative to parent risk.

– Obtain health services (Agee and Crocker, 2005)

– Second-hand smoke (Agee and Crocker, 2007)

– Sun protection (Dickie and Gerking, 2003)

Original Contributions

• Relax model assumption so that child health effects parent health and vice versa.

• First averting behavior study to consider the relative value of child health in a developing country.

Theoretical Framework

• People do not know if they or their children will be ill from arsenic.

• People can take an averting action.

• Averting choices reveal willingness to pay (WTP) for reduced risk.

Risk Framework

• Different States of Health.

• Expected utility function is the weighted average of utility in the different states.

• Subjective Probability :

– rc is level of perceived risk of arsenic hazard for child.

– rp is level of perceived risk of arsenic hazard for parent.

Value of Child Risk Relative to Parent Risk

Utility is function of gainsfrom mitigation and health. (under uncertainty). Parentsmaximize utility by choice

of level of averting.

Marginal cost = Marginal benefit(under uncertainty)

Effect of mitigating arsenic exposureon utility function.

p

c

r

Wr

W

Effect of child’srisk level on

utility function.

)(cr

W

Effect of parent’srisk level on

utility function.

)(pr

W

Data

• Survey data (n=2,800):– Respondent Characteristics – health, risk &

demographic– Arsenic Avoidance – Gains from Avoidance

• Secondary data (n=2,620):– Child health (Health and Demographic

Surveillance Data)– Arsenic levels for tube wells (GIS Data)

Empirical Setup

• Four discrete choice models are estimated simultaneously: – Perception of health state (ProbHealthState). – Overall gains from mitigating Arsenic

exposure (Gains).– Child’s level of health (Child Health). – Parent’s level of health (Parent Health).

Explanatory Variables

• Switching to green well (Avert).• Money spent (Price Avert).• Time spent walking (Time Avert).• Productivity (Work More, Work Ability).• Perceived arsenic risk (Child Risk, Parent

Risk).• Arsenic levels (AAS).• Demographic characteristics for parent –

Age & Male.

Coefficient Estimates

VARIABLE NAMES

Gains ProbHealthState

Child Health Parent Health

Avert -0.1361* 0.0215 -0.1673* -0.0280

Gains -0.1377* 0.0126 0.0589*

Price Avert 0.00005 0.00008*

Time Avert 0.0023* -0.0012* 0.0013* 0.0014*

Work More 0.3720*

Work Ability

0.3269*

Child Risk

0.0134* 0.0043 -0.0366* -0.0084

Parent Risk 0.0140* -0.0093 0.0070 0.0053

Arsenic Levels

0.00008 0.0004* 0.00018 -0.0003*

Age -0.0177*

Male -0.0080

Relative Value of Child Health

• Parents value child health 2.6 times more than their own health for a change from not healthy to healthy.

• Parents are willing to spend ~4% of their daily earnings to reduce the perceived risk to their child by one percent.

Policy Implications

• Intervention for safe drinking water programs successful, people choose green tube wells.

• Parents in a developing country value their child’s health 2.6 times their own.

• Policy focusing on well head mitigation will provide households with time to invest in other activities.