Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Estimation of demand for health care with samples of only the ill may bias estimates. Additionally, the lack of exogenous information, especially distance, about the alternative care providers causes omitted variable problems. This paper alleviates both problems through geographic mapping of facility information to individuals, combined with joint estimation of illness (health production) and health care demand. The joint estimation full sample demand results are compared to those from one equation estimation for only the ill sample. The results indicate that the selectivity problem is significant, but that for this sample the magnitude of the bias on the price coefficient is small. © 1998 John Wiley & Sons, Ltd.