1. Health effects of indoor and outdoor air pollution Jie-Sheng Tan-Soo Subhrendu K. Pattanayak Duke University Camp Resources 2012

2. Research questions What are the joint impacts of indoor and outdoor air pollution on children’s health? – Are impacts different for self-reported and objective health measurements? 2

3. Introduction Respiratory illnesses is top disease burden for developing countries (WHO, 2008) Environmental causes: indoor and outdoor air pollution Indoor air pollution from ‘dirty’ household fuel (PM 2.5 air particulates, carbon monoxide) Outdoor air pollution from emissions and forest fires (PM 10 air particulates, SO 2, NOX, CO, O 3 ) Climate change to result in worsening outdoor air pollution (IPCC, 2007) Need better understanding on the concurrent effects of indoor and outdoor air pollution Need to consider endogenous exposure to indoor air pollution 3

4. Why conduct another study? Epidemiological reason: – Most existing studies are conducted in places where exposure is low compared to developing countries Econometric reason / omitted variable bias: – 1 st : Indoor air pollution highly correlated with outdoor air pollution (see review by Yocom, 1982) – 2 nd : Exposure to air pollution may be endogenous (e.g. Mullahy and Portney, 1990) 4

5. Study Approach Panel individual-level dataset from Indonesia Include measurements for both indoor air pollution (IAP) and outdoor air pollution (OAP) Use household fixed effects to control time- invariant heterogeneity Use a wide range of self-reported and objective health measures 5

6. Literature Review Use 1997 Indonesian forest fires as exogenous shock to OAP (Frankenberg et al., 2005 ; Jayachandran, 2008) Use fuel price as instrument for stove usage (Hanley, 2006) Include both IAP & OAP in India (Ghosh & Mukherji, 2011) 6

7. Model 7

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9. Empirical strategy 9

10. Data Indonesia Family and Life Survey – Main type of stove used & individual health measurements – Four waves (1993, 1997, 2000, 2007) – Panel individual and household survey – High re-contact rate/ Low attrition – ~20,000 children (under age of 12) over three waves NASA Total Ozone Mapping Spectrometer – Aerosol index – From 1993 onwards – Satellite data at district level 10

11. Source: http://www.rand.org/labor/FLS/IFLS.html 11

12. 12 Sep 24, 1997 Sep 18, 2000 Sep 21, 2005

13. Data Self-reported health measurements – Cough in last 4 weeks? – Breathing difficulties in last 4 weeks? – Number of days ill in last 4 weeks? – Number of days in bed due to poor health in last weeks? – Assessment of overall health (1-4 with 1 being very unhealthy) Objective health measures: – Lung capacity – Body-mass index – Height-for-age z-score – Weight for age z-score 13

14. Results – self-reported health (1)(2)(3)(4)(5) VARIABLES CoughBreathing difficultyDays illDays miss activity Negative health self-assessment Aerosol index (AI)-0.00140**0.000144-0.00473***-0.00603*2.26e-06 (p-value) (0.0168)(0.510)(0.00442)(0.0695)(0.997) Dirty stove indicator0.00559-0.00559-0.0149-0.0117-0.0421** (0.757)(0.375)(0.796)(0.907)(0.0129) Observations20,86320,84220,85220,85120,866 R-squared0.0210.0030.0060.0220.013 Number of hh_id7,0097,0087,0097,0107,011 Controls: Age, Gender, Household assets, Year FE Expected signs: +ve for column (1) to (5) 14

15. Results – objective health (1)(2)(3)(4) VARIABLESBody-mass indexLung capacityHeight-for-ageWeight-for-age Aerosol index (AI)-0.00467-0.293**-0.00396-0.00681** (p-value) (0.147)(0.0181)(0.398)(0.0411) Dirty stove indicator0.0348-6.2960.0861-0.0759 (0.705)(0.105)(0.527)(0.378) Observations20,9166,6857,797 R-squared0.0040.2130.0320.049 Number of hh_id7,0233,9744,933 Controls: Age, Gender, Household assets, Year FEs Expected signs: -ve for column (1) to (4) 15

16. Robustness checks VARIABLES(p-value)VARIABLES(p-value) Cough (0.00) Body-mass index (0.0395) Breathing difficulty (0.453) Lung capacity (0.0001) Days ill NA Height-for-age (0.0051) Days miss activity (0.1140) Weight-for-age (0.0207) Health self-assessment(0.0036) 16

17. Robustness checks Hausman-Taylor method (1981) to estimate the impact of time-invariant regressors VARIABLES Cough Breathing difficulty Days ill Days miss activity Health self- assessment Body-mass index Lung capacity Height-for- age Weight-for- age Dirty stove indicator -0.208***-0.01-0.015-0.380.0003-0.46*-46.7***-1.21***-1.02*** Aerosol index-0.00070.0004***-0.004***-0.0046*0.0008*-0.0074***-0.36***-0.002-0.005** 17

18. Robustness checks Hausman-Taylor method (1981) to estimate the impact of time-invariant regressors VARIABLES Cough Breathing difficulty Days ill Days miss activity Health self- assessment Body-mass index Lung capacity Height-for- age Weight-for- age Dirty stove indicator -0.208***-0.01-0.015-0.380.0003-0.46*-46.7***-1.21***-1.02*** Dirty stove indicator 0.0056-0.006-0.015-0.0120.04**0.035-6.30.09-0.076 Aerosol index-0.00070.0004***-0.004***-0.0046*0.0008*-0.0074***-0.36***-0.002-0.005** Aerosol index-0.001**0.0001-0.005***-0.006*-2.26e-06-0.0047-0.29**-0.004-0.007** 18

19. Summary Self-reported health likely unreliable Only OAP has adverse impact on health – Results are driven by HHs that switch stove Hausman-Taylor estimator however shows that both OAP & IAP are damaging to health – But results are driven by non-switcher HHs In all, results suggest differences between switchers & non-switchers – Long term exposure vs. short term? – Switchers and non-switchers fundamentally different? 19

20. Key points Effects of air pollution on health is a very important and complex problem – Respiratory illnesses is a major burden – Close relationship between indoor and outdoor pollution – Endogenous exposure to pollution Indoor and outdoor air pollution harm health – Switchers vs. non-switchers – Self-reported vs. objective health measures Need structural modeling 20