utilization that greater coverage permits is one of the factors that motivates health insurance, and is likely to account for a potentially large fraction of the welfare gain associated with it (cf. Nyman 1999). Insurance affords the prospect of receiving treatment that would have been beyond the feasible set in the absence of insurance. Further, linked to the other strand of literature discussed above, insurance reduces uncertainty and produces a wealth effect, which is likely to translate into higher levels of medical care use _irrespective of whether there is any moral hazard at work_ (cf. de Meza 1983).

If the risk-reduction attributable to health insurance is associated with wealth effects in medical care utilization, it is also likely to be associated with wealth effects in the consumption of _other_ commodities, some of which may be beneficial to health. If a household knows that by acquiring health insurance it has reduced its exposure to the risk of large out-of-pocket health expenses, it is likely to ‘spend’ some of this extra wealth on food, shelter, clothes, housing, education and other items of the household budget. In poor households, this extra spending may well be one of the channels by which health insurance leads to better health outcomes. Evidence from rural China, where health insurance coverage dropped dramatically following the decollectivization of agriculture, suggests that the risk associated with medical expenses does indeed influence a variety of household decisions, including the amount of wealth households hold, the share of wealth they hold in liquid form, the extent of temporary migration and school enrollment (Jalan and Ravallion 2001).

This paper estimates the impacts of health insurance on health outcomes, and on other variables some of which may conceivably impact on health outcomes, such as the use of medical care, food consumption, spending on water, and the use value associated with household durables. The setting is Vietnam in the 1990s. Vietnam’s social health insurance program, or Vietnam Health Insurance (VHI) as it was known at the time, was set up in 1993 in response to a growing concern over the scale of out-of-pocket payments for health. In 1993, over 70% of health spending in Vietnam was paid out-of-pocket, and out-of-pocket payments absorbed 6% of the average household’s total consumption (World Bank et al. 2001, Wagstaff 2002). As many as 18% of households spent more than 10% of their total consumption on health care, and as many as 47% of households spent more than 10% of their non-food consumption on health care (Wagstaff and van Doorslaer 2003). In 1993, a single visit to a public hospital by someone from the bottom quintile cost the equivalent of 41% of their _annual_ non-food consumption (World Bank et al. 2001). Unsurprisingly, health care payments were a major source of concern among Vietnamese participants in the global participatory poverty study _Voices of the Poor_ (Narayan et al. 2000).

Given this background, and given its very generous initial coverage (copayments were introduced only in late 1998), VHI can reasonably be expected to have had effects on both medical care use and on the consumption of other budget items, with likely consequences for health outcomes. We estimate insurance impacts through the use of propensity score matching (PSM) on longitudinal data collected just before the introduction of VHI in 1992/93 and five years later in 1997/98.<sup>3</sup> Two-thirds of those joining VHI in this period—and 95% of adults

> 3  The use of PSM and longitudinal data are two features that distinguish the present study from that of Trivedi (2003), who used regression analysis on the 1997/98 cross-section data.  The present study also looks beyond health care use and health care spending.  There are also differences in variable definitions that further make comparisons rather difficult.  For example, Trivedi defines annual health spending as the sum of spending in the last 4 weeks and spending in the last 12 months, whereas we treat them as two separate variables, assuming that one measures spending in the last month and the other spending in the last year.

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