joining the scheme—were compulsorily enrolled by virtue of their employment with the government or a state-owned enterprise, or being a pensioner or a ‘person of merit’ (such as a war veteran). The bulk (95%) of those voluntarily enrolled were school children, whose schools are encouraged to enroll their pupils by the local Communist party. While there appears to have been very little _self_ -selection into the scheme during this period, there is the possibility that those selected into the scheme share unobservable attributes that make them healthier (or heavier users of health care) than those not selected. The pre-post longitudinal data allow us to replace the standard PSM assumption—that outcomes are independent of participation given the values of the relevant pre-intervention control variables—by a weaker assumption, namely that _changes_ in outcomes are independent of participation given the pre-intervention controls (cf. Blundell and Costa Dias 2000). We are thus able to eliminate any bias due to time-invariant unobservable heterogeneity, in addition to bias due to observable heterogeneity which PSM on cross-section data already eliminates (cf. Heckman, Ichimura and Todd 1997, Heckman et al. 1998, Jalan and Ravallion 2003a). We are, however, forced to assume that any unobserved time trend in our outcomes is the same for the insured and uninsured. Only randomization can completely rule out such a possibility, which in principle is a concern even in studies that exploit differences in speed of adoption across geographic units. The attraction of PSM over a regression analysis is that we do not need to specify any model for our outcomes and hence reduce the risk of biases due to inappropriate model specification, whether in the functional form or the covariates included. We do have to do some modeling, namely in the prediction of propensity scores—the probability of being enrolled in VHI.

Section II outlines the salient features of Vietnam’s health insurance program. Section III sets out our estimation method, based on a combination of propensity score matching and double differencing on pre-intervention and post-intervention data. Section IV outlines the model used to generate our propensity scores, and compares the distributions of the propensity scores of the insured and uninsured pre- and post-matching. Sections V-VIII contain our results for health outcomes, health utilization, out-of-pocket expenditures and nonmedical consumption, respectively. Section IX contains our conclusions.

# II. **VIETNAM’S HEALTH INSURANCE PROGRAM**

Prior to the _Doi Moi_ (or ‘renovation’) reforms of the late 1980s, health services in Vietnam were provided at the taxpayer’s expense, with patients paying only the cost of drugs (Bloom 1998). The decollectivization of agriculture and the liberalization of the economy led to a swift erosion of the government’s role in financing health care in Vietnam. Following changes in 1989 government facilities were allowed to charge fees, and in 1991 legislation was passed that paved the way for a private health sector (Bloom 1998, Glewwe 2003). The share of the cost of health care borne directly by households is likely to have increased considerably following these reforms. This prompted concerns about the affordability of health care, especially among the poor, which in 1993 still accounted for 58% of the population (Glewwe 2003). Subsequent analysis of data from the 1993 Vietnam Living Standards Survey (VLSS) bore these concerns out: a single visit in 1993 to a public hospital by someone from the bottom quintile would have cost the equivalent of 41% of their _annual_ non-food consumption (World Bank et al. 2001). Even for the population as a whole, the figure was close to 20%.

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