At a given health cost, if health status rises wages, then the shadow price of health care declines, inducing a greater demand for health. It has been argued that there are nonlinearities in this link as the shadow price decreases more for people in worse health (Strauss and Thomas 1998). This entails important distributional consequences if the poor are most likely to be below the health threshold level.

By inverting the last equation we obtain a reduced form demand function for health care: which implies that the demand for health will depend on its cost, but also on non-health consumption, individual and household characteristics (such as schooling and family background), and unobserved characteristics. The presence of α in both the wage function and the health demand function captures the simultaneity problem that is central to the difficulty in disentangling the causal effects of health on productivity<sup>5</sup> . Therefore, a reduced form estimation cannot provide an unambiguous determination of whether health does influence economic wellbeing. However, it does provide an indication of the (total) effect of health prices and the health environment on household wellbeing.

Our purpose in this paper is not to tackle the causality issue, but rather to shed some light on the link between health and poverty in the Western Balkans. We do this by taking into account the main socio-demographic variables that affect health care demand. It should be noted that variables like age and education enter the theoretical model through their impact on either the cost of health capital or its marginal productivity. Thus, there are important implications to be tested concerning the effects of socio-demographic characteristics, along with economic ones, on health status and the utilization of health care<sup>6</sup> .

# **3. Data, measurement and methodology**

# _3.1 Data_

Data are drawn from recent household surveys, either official Living Standards and Measurement Surveys (LSMS) or surveys that are considered LSMS equivalents. The LSMS surveys are multitopic household surveys that include data on a wide range of demographic and socio-economic characteristics. The typical health module provides information on (i) health status, (ii) the utilization of health services, (iii) health expenditures, and (iv) insurance status. The depth of the health section varies somewhat across the surveys considered, with the most detailed information available for Albania and the least detailed for Montenegro, but an effort has been made to recode data so that variables are as homogenous as possible across data sets.

> 5 On the other hand, the extent to which households are able to insure consumption against illness depends on the ability to reduce the incidence and severity of illness shocks. For example, as argued by Gertler and Gruber (2002), households may be more able to effectively insure against frequently-occurring, small health shocks than large rare illnesses.

> 6 Indeed, one prediction of Grossman’s (1972) model is that if the rate of depreciation of health increases with age, at least after some point in the life cycle, then the quantity of health capital demanded will decline over the life cycle. At the same time, provided the elasticity of the marginal efficiency of health capital is less than unity, expenditure on health care will rise with age.

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