Sperm donor anonymity and compensation: an experiment with American sperm donors

Abstract

Most sperm donation that occurs in the USA proceeds through anonymous donation. While some clinics make the identity of the sperm donor available to a donor-conceived child at age 18 as part of 'open identification' or 'identity release programs,' no US law requires clinics to do so, and the majority of individuals do not use these programs. By contrast, in many parts of the world, there have been significant legislative initiatives requiring that sperm donor identities be made available to children after a certain age (typically when the child turns 18). One major concern with prohibiting anonymous sperm donation has been that the number of willing sperm donors will decrease leading to shortages, as have been experienced in some of the countries that have prohibited sperm donor anonymity. One possible solution, suggested by prior work, would be to pay current anonymous sperm donors more per donation to continue to donate when their anonymity is removed. Using a unique sample of current anonymous and open identity sperm donors from a large sperm bank in the USA, we test that approach. As far as we know, this is the first attempt to examine what would happen if the USA adopted a prohibition on anonymous sperm donation that used the most ecologically valid population, current sperm donors. We find that 29% of current anonymous sperm donors in the sample would refuse to donate if the law changed such that they were required to put their names in a registry available to donor-conceived children at age 18. When we look at the remaining sperm donors who would be willing to participate, we find that they would demand an additional $60 per donation (using our preferred specification). We also discuss the ramifications for the industry.

Keywords: Reproductive technologies; anonymity; donor-conceived; egg banking; sperm banking; sperm donation.

Figure 1.

Assessing non-response among inactive donors. The gray ‘filled’ points represent the statistic of interest in the sampling frame, while ‘hollow’ points provide the same information for our inactive donor sample. Note that none of the observed differences are statistically different from zero.

Figure 2.

The effect of mandatory identification on refusal to donate. The estimates are based on the differences in the predicted probability of ‘refusal’ across the treatment and control conditions from a logistic regression. Each subfigure provides the full posterior distribution (n = 5000 draws), the posterior median (gray dot), and the 95 per cent highest density interval (gray line).

Figure 3.

The effect of mandatory identification on WTA. The estimates assume an exponential WTA function and are based on a log-normal regression. Each subfigure provides the full posterior distribution (n = 5000 draws), the posterior mode (gray dot), and the 95 per cent highest density interval. Note that the left column provides estimates when ‘censoring’ and the right column presents the same estimates when ‘trimming’ the WTA distribution at a given cut point (eg simply dropping all observations greater than a particular value).