Poverty and illness in low-income rural areas
利用亚洲农村的纵向数据，考察疾病对低收入农户生产率的影响，发现疾病与财富关系不显著，而营养与财富相关，这为政策干预提供了依据。
One of the oldest and most studied questions in development is whether the resource and environmental conditions faced by households in low-income rural areas significantly affect productivity.' The reason for this interest is clear: if productivity is significantly constrained by these factors, then the returns to investment in the form of human capital are likely to be high, and under certain conditions there may be scope for efficiency-improving policies and programs. Given this motivation it may at first seem surprising that most of the existing literature focusing on the health-productivity relationship concentrates on the effects of nutrition. While nutrition is an important contributor to good health, other components of health, especially illness, may also influence worker productivity. Moreover, in contrast to the case of nutrition, over which households have direct control, illness is affected by exposure to pathogens, something over which individual households may have little control. This public aspect of illness makes an examination of the effects of illness on productivity particularly important from a policy perspective. This distinction between the private nature of nutrition and the public nature of illness may at least in part be evident in Tables 1 and 2. These tables present the distribution of illness and calories, respectively, by wealth quartiles in three Asian countries. What is most striking about these tables is the fact that despite clear evidence that calories are importantly associated with wealth in at least two of the countries (Bangladesh and Pakistan) there is little systematic relationship between illness and wealth in any of the countries. For example, in Bangladesh, the top quartile (in terms of wealth) of the population of men and women consumes 6 percent and 8 percent more calories, respectively, than the lowest quartile. By contrast, Bangladeshi males in the upper quartile experience 19-percent more days ill over the same period than do those in the lower quartile; the figures for the women are identical. There are several possible reasons for this pattern. As suggested earlier, one possibility is that households have little control over their exposure to illness. If this is the case, then one might well conclude that the distributional effects of illness are quite limited. A second plausible explanation is that illness is measured or reported differently for better-off households. For example, a better-off individual who is generally healthy may be more readily able to identify when he or she is ill than a poor individual with low caloric intake. Moreover, to the extent that illness is measured as an alternative to work (as is the case for the Pakistani data set), a wealthier individual may be more willing to skip work on a day that he or she is ill. If this latter point is true, then the distributional consequences of illness could be quite important despite what is evident in Table 1.2 In this paper I address these and other related issues using two of the longitudinal data sets from rural Asia from which these tables were derived. In the first section of