The Demand for Outpatient Medical Care in Rural Kenya
This paper develops a new specification of the demand for outpatient medical care and then estimates the model using data from a household survey conducted in rural Kenya in 1989. A four-stage nested logit model is used with a variable number of choices at several nodes. The first stage modeled is the choice of whether or not to report an illness, while the second is the probability of seeking treatment conditional on a positive report of illness. In contrast with the previous literature, the first two stages are modeled separately rather than as a single decision to seek treatment. The third stage, the individual's choice of a particular provider, is modeled as depending upon individual and household characteristics, as well as characteristics of specific health facilities from which choices are made. The fourth stage modeled is the choice of a mode of transport to the health facility (walking or taking the bus), an endogenous choice variable that greatly affects the total cost of seeking treatment. The previous empirical literature has not attempted to separate out the probability of reporting an illness from the probability of seeking treatment, and hence has estimated only the combined effect of variables such as income on the illness and the decision to seek treatment. This study finds that income and wealth variables are negatively related to reporting an illness, but positively related to deciding to seek treatment. Most of the demographic variables seem to influence the probability of reporting an illness rather than the decision to seek treatment. This finding is significant because if the results from one setting are applied to others, it is important to know whether demand for health care depends upon the underlying illness patterns or the demographics of the population. This study would suggest that the former are more important. The choice of mode of transportation is found to be is clearly endogenous, and affected by travel time, travel costs, and the
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NBER Working Papers
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