_Table 4: Distributions of propensity scores before and after matching_

|||# cases|Mean|Std. Dev.|Min|Max|
|---|---|---|---|---|---|---|
|Before matching|Uninsured|14795|0.135738|0.124385|0.000453|0.988689|
||Insured|3014|0.332719|0.233047|0.004923|0.996576|
|After nearest neighbor matching|Uninsured|3011|0.331963|0.231969|0.004934|0.988689|
||Insured|3011|0.332058|0.232220|0.004923|0.988621|
|After matching on common support|Uninsured|2797|0.295473|0.194748|0.004934|0.988689|
|and with 0.001 caliper|Insured|2797|0.295474|0.194748|0.004923|0.988621|

# V. **HEALTH OUTCOMES**

We measure health outcomes through anthropometry, there being no data in the VLSS on activities of daily living or self-assessed health. The VLSS is unusual among living standards measurement surveys in recording the height and weight for _everyone_ in the sample, not just children under the age of five (Alderman 2000). Furthermore, anthropometric measurements were taken for the full sample in _both_ waves of the VLSS.

For children, we use z-scores for both height-for-age (HAZ) and weight-for age (WAZ).<sup>10</sup> Higher z-scores indicate improved nutritional status, and children with values below –2 (i.e. less than two standard deviations below the mean of the reference group) are by convention classified as “underweight” (WAZ) or “stunted” (HAZ). We present results for three age groups: children aged between zero and 4 inclusive in 1992/93 and therefore between 5 and 9 at the time of the second wave; children aged between 5 and 23 in 1992/93; and all children between the ages of zero and 23 in 1992/93. In the second and third cases, in addition to matching on the propensity score, we match on the child’s age bracket (the brackets being in five-yearly intervals).<sup>11</sup> Table 5 shows the results.<sup>12</sup> VHI produces a significant effect on the height and weight of young children (children aged between 0 and 4 in 1992/93) but not of older children. In the case of weight-for-age but not height-for-age, the effect rises with per capita household consumption; indeed, there is no evidence of any beneficial effect of VHI on weight-for-age among the poorest quintile.

> 10  We standardize the anthropometric data using the 1990 British growth reference data (Cole, Freeman and Preece 1998) which - - are available for newborns up to the age of 23.  A convenient Stata routine <u>http://www.stata journal.com/software/sj4</u>

> <u>1/dm0004/zanthro.hlp: is available to undertake these and the more familiar US reference standardizations (Kuczmarski et al.</u> 2000).  The latter are available for young people only up to the age of 20.

> 11  Similar results were obtained when we matched on the propensity score and restricted matches to the same age group. 12 The treatment effects reported throughout are the average treatment on the treated.  The standard errors underlying the z- statistics were computed treating propensity score as fixed using the Stata add-in ‘nnmatch’, and requesting the standard error relevant to the population rather than the sample.  The reported z-statistics tend to be marginally larger than those obtained via bootstrapping with the Stata add-in ‘psmatch2’.  This allows for the fact that the propensity score is itself subject to sampling variability but adds substantially to computation time.  The F-tests for the constancy of treatment effects across per capita consumption quintiles are obtained from regressions of estimated treatment effects on consumption quintile dummies.  The regressions are estimated on a sample comprising insured individuals and matched uninsured individuals.  The latter weighted by the number of times they are used as a match for an insured individual.  Quintile-specific treatment effects and their standard errors are obtained from this regression.

11