Abstract
This study examines the efficacy of Askeskin, a subsidized social health insurance targeted towards poor households and informal sector workers in Indonesia, in mitigating the impact of adverse health shocks on household consumption. To overcome selection bias from non-experimental nature of Askeskin enrolment, I use a robust estimation strategy, where outcome regressions are run on a propensity score-based matching sample. Using longitudinal data from the Indonesia Family Life Survey, this study finds that uninsured households facing extreme health health shocks experience a 1.3% point loss in growth in food and 2% point loss in non-food consumption growth. Importantly, households having Askeskin insurance, are fully insured in terms of food and medical consumption. But non-food spending, a discretionary component, is not insured fully resulting in a 1.2% point fall in consumption growth rate, despite Askeskin. This result is robust to a battery of sensitivity and robustness checks, including alternate definition of health shocks. Further, I investigate whether the Askeskin program simply displaced informal, community-based mechanisms of risk sharing. No crowd out effect is observed and informal risk-sharing coexists with Askeskin.
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Notes
Kabupaten (district)/Kota (city) level.
Susenas - Survei Sosial Ekonomi Nasional translated as the National socioeconomic survey.
Close to 90% of households from IFLS 1 were re-interviewed for IFLS 2. For subsequent rounds, on average, 70% of households of the immediate preceding round were re-contacted. New households (formed by split-offs from existing households or new households in the sample) formed 11% (IFLS 2) and 30% (IFLS 3–5) of sample size. This resulted in the doubling of the IFLS 1 sample to a total of 15,919 households by IFLS 5.
By multiplying weekly values with the factor 4.28 and by dividing annual values with 12.
\(ADL_{family}=\frac{\sum _{i=1}^{k}(Score)-k\left( Min.Score\right) }{\left( Max.Score-Min.Score\right) }\) and family health shock \(\Delta h_{ft}\) follows from Eq. 1.
Askeskin was rolled out in 2005, whereas IFLS 3rd round was in 2000 and IFLS 4 was in 2007. Thus IFLS 3 data serves as the baseline, which arguably, cannot be impacted by Askeskin rollout.
This indicator is not directly observed by someone targeting, but is rather used as it accurately describes the intended beneficiary group.
Frequency weights for a control observation correspond to number of times it is used as a match; for treated variables, the frequency weight is one.
Non-food spending includes spending on children’ education, entertainment, clothes, gifts and parties, among other things.
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Kolukuluri, K. Adverse health shocks, social insurance and household consumption: evidence from Indonesia’s Askeskin program. Int J Health Econ Manag. 23, 213–235 (2023). https://doi.org/10.1007/s10754-022-09329-6
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DOI: https://doi.org/10.1007/s10754-022-09329-6