demand equation in Grossman’s (1972) model. The evolution of health capital over time reflects the time profiles of the depreciation rate and any other time-varying variables, but also the size of any random ‘shocks’. The latter, which are captured by ε 1, could be rationalized in terms of the depreciation rate being stochastic rather than deterministic as in Grossman’s original formulation (cf. Grossman 2000). Correlations between estimates of ε 1 and the other residuals provides information on the extent to which health shocks get transmitted into unexpected changes in income, and medical and non-medical consumption.

# <u>Data</u>

The data are from the two-wave Vietnam Living Standards Survey (VLSS). A representative sample of 4800 households was interviewed in 1992/93, and then again in 1997/98.

The focus is on changes in adult health, measured by the body mass index (BMI). This is equal to the individual’s weight in kilograms divided by the square of the individual’s height in meters. BMI is first and foremost a measure of nutrition. A person with a BMI score below 18.5 is considered ‘underweight’, while someone with a BMI score in the range 18.5-24.9 is considered ‘normal’. An individual with a BMI score in the range 25-29.9 is considered to be ‘overweight’, and someone with a score higher than 30 is considered obese. In Vietnam in the survey period, less than 1% of the sample in either year was classified as overweight or obese, while roughly a quarter of the sample were classified as underweight. While primarily a measure of nutritional status, BMI has been found to be a good predictor of mortality, with mortality risk higher at both the bottom and top ends of the scale (Calle, Thun et al. 1999). Account is taken below of the non-monotonic relationship between health and BMI. Beyond BMI, the VLSS contains very little by way of useful information on adult health. Respondents were asked whether they had been sick in the four weeks prior to the interview on both occasions, but the question was posed differently in the two waves, so comparisons across the waves are not possible. In any case, evidence from the work of Gertler and Gruber (2002) suggests that changes in a short-term and self-reported health measure such as illness in the previous four weeks is unlikely to be associated with income and consumption changes. Indeed, a key conclusion of their work is that any failure to smooth consumption in response to health shocks is likely to be in relation to objective long-term health measures, not short-term subjective measures. Their measure—an index of people’s ability to perform activities of daily living—is not available in the VLSS. BMI seems, however, a good substitute. Indeed, it may be potentially a good complement.

Income is total per capita household income, broken down into earned income (wage income as well as income from agriculture and any family business) and unearned income (gifts, remittances, pensions, and the like). Medical spending is per capita household medical outlays, excluding health insurance contributions, based on a 12-month reference period. Non-medical consumption is broken down into food consumption and non-food consumption, the latter including the use value of durables.<sup>3</sup>

> 3  Full details are available in the VLSS basic information document available at <u>http://www.worldbank.org/lsms/country/vn98/vn98bif.pdf.</u>

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